Esteban Gómez-García

Aboveground stand-level biomass estimation: a comparison of two methods for major forest species in northwest Spain

ContextThe scaling-up approach (which requires the use of individual tree biomass equations and data) is one of the most commonly used methods for estimating stand biomass at a local scale. However, biomass prediction over large management areas requires more efficient methods.AimsTwo methods of estimating aboveground stand biomass were developed and compared: stand biomass equations (SBE) including observed stand variables, and SBE including biomass expansion factors (BEF) and stand volume.MethodsTwo types of systems of additive equations were fitted simultaneously for components and total aboveground stand biomass, to ensure additivity. Inherent correlations among biomass components were also taken into account in the fitting process.ResultsThe systems explained a high percentage of the observed variability. The SBE systems that included observed stand variables provided more accurate estimates than those that included BEF and stand volume. However, the latter were found to be more precise for stem wood and total aboveground biomass prediction.ConclusionsBoth approaches provide a direct link between forest inventory data, outputs from whole-stand growth models, and biomass estimates at stand level. Taking into account that the inventory effort is similar for both alternatives, the choice of which to use will depend on the data available and on the relative importance of the biomass components for the end-users.

Selection of mixed-effects parameters in a variable–exponent taper equation for birch trees in northwestern Spain

ContextTaper equations predict the variation in diameter along the stem, therefore characterizing stem form. Several recent studies have tested mixed models for developing taper equations. Mixed-effects modeling allow the interindividual variation to be explained by considering both fixed-effects parameters (common to the population) and random-effects parameters (specific to each individual).AimsThe objective of this study is to develop a mixed-effect variable exponent taper equation for birch trees in northwestern Spain by determining which fixed-effects parameters should be expanded with random-effects parameters.MethodsAll possible combinations of linear expansions with random effects in one and in two of the fixed-effects model parameters were tested. Upper stem diameter measurements were used to estimate random-effects parameters by the use of an approximate Bayesian estimator, which calibrated stem profile curves for individual trees.ResultsParameter estimates for more than half of the mixed models investigated were nonsignificant. A first order autoregressive error structure was used to completely remove the autocorrelation between residuals, as mixed-effects modeling were not sufficient for this purpose.ConclusionThe mixed model with the best fitting statistics did not provide the best calibration statistics for all upper stem diameter measurements. From a practical point of view, model calibration should be considered an essential criterion in mixed model selection.

Tarifas de biomasa aérea para abedul (Betula pubescens Ehrh.) y roble (Quercus robur L.) en el noroeste de España

El objetivo de este trabajo fue el desarrollo de modelos de estimacion de biomasa aerea para abedul (Betula pubescens Ehrh.) y roble (Quercus robur L.) en Galicia (noroeste de Espana). Para ello se emplearon datos obtenidos mediante el muestreo destructivo de 50 abedules y 50 robles, en los que se obtuvo el peso seco de biomasa total y por fracciones: madera del fuste, corteza del fuste, ramas mayores de 2 cm, ramas de 0,5 cm a 2 cm, ramas menores de 0,5 cm, y hojas. En un primer paso se seleccionaron los modelos que presentaban el mejor ajuste para cada fraccion de biomasa arborea considerada. Posteriormente, y para asegurar la aditividad, se realizo un ajuste simultaneo de las ecuaciones de estimacion de biomasa por fracciones junto con la de biomasa total, empleando el procedimiento estadistico denominado NSUR (Nonlinear Seemingly Unrelated Regressions). Tambien fue necesario un ajuste ponderado para corregir la existencia de heterocedasticidad. El numero de condicion verifico que no existian problemas graves de multicolinealidad. Al final se obtuvo, para cada especie, un sistema de siete ecuaciones de estimacion de biomasa aerea para las distintas fracciones y para la biomasa total. Estas ecuaciones explicaron como minimo 79% de la variabilidad observada, y en el caso de las ecuaciones de biomasa total 98% para abedul y 97% para roble. Se recomienda la utilizacion de las ecuaciones desarrolladas en este estudio en sustitucion de las ecuaciones de biomasa existentes para la region.