Monthly Archives: December 2018

Can an Exponential Function Be Applied to the Asymptotic Density–Size Relationship? Two New Stand-Density Indices in Mixed-Species Forests

Abstract: This study presents two stand-density indices (SDIs) based on exponential density decline as a function of quadratic mean diameter for all species combined in mixed-species forests with 22 species mix grouped in four species groups. The exponential-based density–diameter relationship, as well the density index corresponding to the slope or instantaneous mortality rate parameters, was compared with those based on power-law density–diameter relationship. A dataset of 202 fully stocked circular plots at maximum density was used for fitting the models, and a dataset of 122 circular plots was used for validation stand density index for all species combined of mixed-species stands. The dataset for validation was independent of dataset for model development. The first stand-density index showed a density management graphic (DMG) with a variable intercept and common instantaneous mortality rate, and the second index showed a DMG with common intercept and variable mortality rate. Additionally, the value of the initial density of the fitted line was more realistic than those generated by the potential model for all species combined. Moreover, the density management diagrams showed a curvilinear trend based on the maximum stand density index in graphical log–log scale. The DMGs could be interpreted as forest scenarios based on variable initial density and common management objectives or the same density and different management objectives for forest-rotation periods involving all species combined in mixed-species stands. The fitting of exponential and potential equations for species or species groups showed that the density–size relationships in mixed-species forests should be modeled for all species combined because the disaggregation of mixture species represented a weak tendency for each species or species group and the resultant fitted equations were unrealistic.

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Compatible taper, volume, green weight, biomass and carbon concentration system for Quercus sideroxyla Bonpl./Sistema compatible de ahusamiento, volumen, peso verde, biomasa y concentración de carbono para Quercus sideroxyla Bonpl.

Abstract
Introduction: Estimation of total and merchantable tree volume, as well as of biomass and carbon, implies the generation of biometric tools essential in forest management and planning.
Objectives: To fit a compatible taper, volume, green weight, dry biomass and carbon concentration system for Quercus sideroxyla Bonpl. species using wood density.
Materials and methods: A database of 522 diameter-height measurements, obtained from 37 trees, was used in the fitting equations. The compatible system (CS) was integrated by 34 equations, which were simultaneously fitted by generalized nonlinear least squares. Taper and volume were the base variables for estimating green weight, dry biomass and carbon concentration.
Results and discussion: All equations were compatible with the stem volume equation, and the merchantable equations with the taper and merchantable volume equations. The fit statistics showed the efficiency of the equations in global terms and by relative height classes.
Conclusions: The CS has the property of estimating taper, merchantable volume, green weight, dry biomass and carbon concentration at upper-height and by components (stem, total tree and branches).
Resumen
Introducción: La estimación de volumen total y comercial de árboles, así como la de biomasa y carbono, implica la generación de herramientas biométricas esenciales en el manejo y planeación forestal.
Objetivos: Ajustar un sistema compatible (SC) de ahusamiento, volumen, peso verde, biomasa seca y concentración de carbono para la especie Quercus sideroxyla Bonpl., con el uso de la densidad de la madera.
Materiales y métodos: Una base de datos de 522 pares de diámetro-altura, obtenida de 37 árboles, se utilizó en el ajuste. El SC se conformó de 34 ecuaciones ajustadas simultáneamente por mínimos cuadrados generalizados no lineales. El ahusamiento y volumen fueron las variables base para la estimación del peso verde, biomasa seca y concentración de carbono.
Resultados y discusión: Todas las ecuaciones fueron compatibles con la ecuación de volumen de fuste, y las ecuaciones comerciales, con los parámetros del ahusamiento y volumen comercial. Los estadísticos de ajuste mostraron la eficiencia de las ecuaciones en términos globales y por clases de altura relativa.
Conclusiones: El SC posee la cualidad de estimar el ahusamiento, volumen comercial, peso verde, biomasa seca y concentración de carbono a una altura comercial y por componentes (fuste, total árbol y ramas).

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