A Whole-Stand Model for Estimating the Productivity of Uneven-Aged Temperate Pine-Oak Forests in Mexico

María Guadalupe Nava-Miranda (), Juan Gabriel Álvarez-González, José Javier Corral-Rivas, Daniel José Vega-Nieva, Jaime Briseño-Reyes, Jesús Aguirre-Gutiérrez and Klaus von Gadow
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María Guadalupe Nava-Miranda: Escuela Politécnica Superior de Ingeniería, Campus Terra, Universidad de Santiago de Compostela, 27002 Lugo, Spain
Juan Gabriel Álvarez-González: Escuela Politécnica Superior de Ingeniería, Campus Terra, Universidad de Santiago de Compostela, 27002 Lugo, Spain
José Javier Corral-Rivas: Facultad de Ciencias Forestales y Ambientales, Universidad Juárez del Estado de Durango, Durango 34120, Mexico
Daniel José Vega-Nieva: Facultad de Ciencias Forestales y Ambientales, Universidad Juárez del Estado de Durango, Durango 34120, Mexico
Jaime Briseño-Reyes: Facultad de Ciencias Forestales y Ambientales, Universidad Juárez del Estado de Durango, Durango 34120, Mexico
Jesús Aguirre-Gutiérrez: Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK
Klaus von Gadow: Faculty of Forestry and Forest Ecology, University of Göttingen, 37077 Göttingen, Germany

Sustainability, 2025, vol. 17, issue 8, 1-23

Abstract: This study presents a model for estimating forest productivity based on a sample of 2048 permanent field plots covering a wide range of growing sites in Mexico. Our state-space approach assumes that the growth behavior of any stand over time can be estimated on the basis of its current state, defined by the dominant height ( H ), number of trees per hectare ( N ), and stand basal area ( BA ). We used transition functions to estimate the change in states as a function of the current state. We also present transition functions for the change in stand volume ( V ) and total above-ground biomass ( AGB ). The first transition function relates dominant height to dominant diameter by using the guide-curve method to estimate site form. The transition function for N consists of two models, one for estimating natural mortality and the other for estimating recruitment. These models were developed in two steps: in the first step, the logistic regression and maximum likelihood approach were used to estimate the probability of the occurrence of mortality or recruitment, and in the second step, the rate of change associated with each event was modeled when mortality or recruitment was assumed to have occurred as a result of the first step. The remaining three transition functions ( BA , V, and AGB ) were fitted simultaneously to account for possible correlations between errors. The model estimating total above-ground biomass ( AGB ), which can be considered a state variable that summarizes the performance of the whole model, explained more than 97% of the observed variability, with a root mean square error value of 10.57 Mg/ha.

Keywords: site quality; mortality; recruitment; logistic models; transition functions; simultaneous fitting (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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