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Este libro trata de la parte de la ciencia forestal dedicada a la medición de las dimensiones y edad de los árboles individuales, al estudio de su forma, y a la determinación de su volumen y crecimiento. Para ello se divide en ocho capítulos en los que, tras uno primero introductorio en el que se describen principalmente los sistemas de medición, los errores que se pueden cometer y la simbología utilizada en el campo forestal, se desarrolla sucesivamente el estudio de diámetros, alturas, forma, volumen, crecimiento, copa, espesor de corteza, edad y biomasa del árbol individual, profundizando tanto en conceptos teóricos como en los aparatos diseñados específicamente para medir dichas variables. Finalmente, se dedica un capítulo entero al estudio y manejo del relascopio de Bitterlich. Por tanto, este libro trata de cubrir una parte de la Dasometría que es la base imprescindible para el Inventario, la Selvicultura, la Ordenación de Montes y la Valoración Forestal. En definitiva, este libro, que pretende completar la escasa bibliografía en castellano existente sobre Dendrometría, y Dasometría en general, es un útil texto para los estudiantes de la ciencia forestal, una práctica guía sobre el manejo de los principales aparatos de medición dasométricos y, en general, un sencillo libro de consulta y referencia para todas aquellas personas relacionadas profesionalmente o interesadas en el sector forestal

In this study we present several multi-objective models for forest harvest scheduling in forest with single-species, even-aged stands using a continuous formulation. We seek to maximize economic profitability and even-flow of timber harvest volume, both for the first rotation and for the regulated forest. For that, we design new metrics that allow working with continuous decision variables, namely, the harvest time of each stand. Unlike traditional combinatorial formulations, this avoids dividing the planning horizon into periods and simulating alternative management prescriptions before the optimization process. We propose to combine a scalarization technique (weighting method) with a gradient-type algorithm (L-BFGS-B) to obtain the Pareto frontier of the problem, which graphically shows the relationships (trade-offs) between objectives, and helps the decision makers to choose a suitable weighting for each objective. We compare this approach with the widely used in forestry multi-objective evolutionary algorithm NSGA-II. We analyze the model in a Eucalyptus globulus Labill. forest of Galicia (NW Spain). The continuous formulation proves robust in forests with different structures and provides better results than the traditional combinatorial approach. For problem solving, our proposal shows a clear advantage over the evolutionary algorithm in terms of computational time (efficiency), being of the order of 65 times faster for both continuous and discrete formulations

En esta tesis se presentan varios modelos multiobjetivo para la planificación de cortas en montes constituidos por rodales regulares monoespecíficos (los más habituales en Galicia), utilizando una formulación temporal continua que busca maximizar la rentabilidad económica y la renta constante en volumen en el primer turno y/o en el monte regulado. Para ello, se han diseñado nuevas métricas para medir esa constancia de rentas que permiten trabajar con variables de decisión continuas. Para la resolución de los problemas, se propone una estrategia que combina una técnica de escalarización (método de pesos) con un algoritmo de tipo gradiente (L-BFGS-B) que permite obtener el frente Pareto. Esto posibilita que el tomador de decisiones especifique sus preferencias con posterioridad al proceso de optimización, ya que dispone de toda la información sobre los costes de oportunidad que asume cuando elige una solución satisfactoria entre el conjunto de soluciones no dominadas del frente. Con el fin de analizar el rendimiento de la estrategia planteada, se comparan los resultados que proporciona con los obtenidos mediante el algoritmo evolutivo para optimización multiobjetivo NSGA-II. Para evaluar los modelos propuestos se usan varios montes de Eucalyptus globulus Labill. La formulación continua ha demostrado ser robusta en montes con distinto número de rodales y diferente estructura de edades, y ha proporcionado resultados mejores que los obtenidos con el enfoque combinatorio tradicional. Con respecto a la resolución de los problemas, la estrategia propuesta ha resultado claramente más eficiente que el algoritmo evolutivo, y tanto más eficaz cuanto mayor ha sido la dimensión del problema.

Estimating tree volume components is an essential element in sustainable forest management. Compatible taper and merchantable outside-bark volume systems based on volume ratio models were globally fitted to four pine species (reduced models) with the aim to select the best reduced model and to fit it with dummy variables and additive effects using Pinus pseudostrobus Lindl as a base species. The study was carried out in the northern mountains of Oaxaca, Mexico. To fit the taper, merchantable volume, stem volume, branch volume, and total tree volume (stem volume and branch volume) equations, a taper dataset of 222, 230, 245, and 333 trees of Pinus douglasiana Martínez (Pd), Pinus oaxacana Mirov (Po), Pinus patula Schltd (Pp), and Pinus pseudostrobus Lindl (Pps), respectively, was used. In general, the compatible systems explained more than 97% in the observed variability for the four studied components: outside-bark diameter (d), merchantable outside-bark volume (Vm), stem outside-bark volume (Vs), and total tree volume (Vt). Alternatively, more than 52% of the observed variability for branch volume (Vb) was also explained. The developed compatible systems based on volume ratio models are a simple and consistent alternative for estimating the outside-bark diameter and variable outside-bark volume, as well as the components of commercial species for uneven-age and mixed-species forests in Oaxaca, Mexico

Background: Forest management planning involves deciding which silvicultural treatment should be applied to each stand and at what time to best meet the objectives established for the forest. For this, many mathematical formulations have been proposed, both within the linear and non-linear programming frameworks, in the latter case generally considering integer variables in a combinatorial manner. We present a novel approach for planning the management of forests comprising single-species, even-aged stands, using a continuous, multi-objective formulation (considering economic and even flow) which can be solved with gradient-type methods. Results: The continuous formulation has proved robust in forest with different structures and different number of stands. The results obtained show a clear advantage of the gradient-type methods over heuristics to solve the problems, both in terms of computational time (efficiency) and in the solution obtained (effectiveness). Their improvement increases drastically with the dimension of the problem (number of stands). Conclusions: It is advisable to rigorously analyze the mathematical properties of the objective functions involved in forest management planning models. The continuous bi-objective model proposed in this paper works with smooth enough functions and can be efficiently solved by using gradient-type techniques. The advantages of the new methodology are summarized as: it does not require to set management prescriptions in advance, it avoids the division of the planning horizon into periods, and it provides better solutions than the traditional combinatorial formulations. Additionally, the graphical display of trade-off information allows an a posteriori articulation of preferences in an intuitive way, therefore being a very interesting tool for the decision-making process in forest planning

Climate change might entail significant alterations in future forest productivity, profitability and management. In this work, we estimated the financial profitability (Soil Expectation Value, SEV) of a set of radiata pine plantations in the northwest of Spain under climate change. We optimized silvicultural interventions using a differentiable approach and projected future productivity using a machine learning model basing on the climatic predictions of 11 Global Climate Models (GCMs) and two Representative Concentration Pathways (RCPs). The forecasted mean SEV for future climate was lower than current SEV (∼22% lower for RCP 4.5 and ∼29% for RCP 6.0, with interest rate = 3%). The dispersion of the future SEV distribution was very high, alternatively forecasting increases and decreases in profitability under climate change depending on the chosen GCM. Silvicultural optimization considering future productivity projections effectively mitigated the potential economic losses due to climate change; however, its ability to perform this mitigation was strongly dependent on interest rates. We conclude that the financial profitability of radiata pine plantations in this region might be significantly reduced under climate change, though further research is necessary for clearing the uncertainties regarding the high dispersion of profitability projections

As climate change makes many traditional empirical growth approaches not functional for forest dynamics modelling, new climate-sensitive models are needed. However, using these newly developed models for extrapolation, such as predicting forest productivity for new areas or future scenarios is still a difficult task. In this study, we proposed a method for delimiting the uncertainty of climate-sensitive extrapolations of forest productivity (site index, ) using the regularisation approach implicit in distance-based Support Vector Regression. As a case study, we predicted forest productivity with a dataset of 165 permanent research plots of radiata pine forests in Galicia (NW of Spain) as a function of bioclimatic variables from the Worldclim 2 raster datasets. The developed model was based on the radial basis kernel and, after calibrating it using cross-validation, produced adequate performance metrics, explaining up to 56% of the site index’ variability. Then, we predicted forest productivity for the Galician territory basing on climate raster maps for current conditions and six future scenarios (using different Global Climate Models) and evaluated the resulting maps by delimiting the surfaces with predictions strongly regressed to the mean. This analysis revealed that the extrapolations for unseen climatic conditions were extremely regularised, even for current climate, being 60–99% of the territory regressed to the observational site index mean. In other words, the validity area delimited for the fitted model was narrow in comparison with the prediction extent. These results imply that the climatic conditions in these areas/scenarios were too different from the training datastet for making reliable predictions, at least under the optimum model setup defined by cross-validation. However, when we reduced the parameter, responsible for controlling distance-based regularisation, we observed a noticeable increase in validity area of the model, together with a drop in

Climate change is intended to impact forest dynamics significantly inthe following decades. To proactively adapt forest management to these expected alterations, new methodologies for handling the uncertain-ties regarding forest growth under varying environmental conditions become necessary. The purpose of this thesis was to forecast the impact of climate change on radiata pine plantations in the northwest of Spain in terms of productivity, profitability, and silvicultural treatments. In Study I, several statistical techniques were used for predicting thesite index (SI) of radiata pine stands using environmental predictors extracted from available raster maps. A non-linear technique, Multivariate Adaptive Regression Splines (MARS), was suggested as the best modelling alternative, explaining up to 52% of the SI variability. In Study II, the Support Vector Regression technique was used to predict SI and delimit the validity area of predictions based on the radial basis kernel. The resulting model had high predictive performance, provided robust predictions under varied climatic conditions, and included a relatively small number of predictors. Moreover, the model was able to identify areas where climatic conditions were very different from the observed and consequently regularised predictions for those areas. In Study III, silviculture under climate change was optimised for maximising the soil expectation value of a set of radiata pine plantations. The future forest productivity projections, produced by the model developed in Study II, forecasted an overall reduction in SI under climate change, mainly driven by increased temperatures and continentality. Consequently, the economic simulations forecasted a drop in profitability under climate change that was more intense for more pessimistic scenarios (RCP 6.0). However, the climatic projections were very varied over the set of used climate models, which led to a great dispersion in productivity and profitability predicti

Lack of knowledge of individual tree growth in species-rich, mixed forest ecosystems impedes their sustainable management. In this study, species-specific models for predicting individual diameter at breast height (dbh) and total tree height (h) growth were developed for 30 tree species growing in mixed and uneven-aged forest stands in Durango, Mexico. Growth models were also developed for all pine, all oaks, and all other species of the genus Arbutus (strawberry trees). A database of 55,158 trees with remeasurements of dbh and h of a 5-year growth period was used to develop the models. The data were collected from 217 stem-mapped plots located in the Sierra Madre Occidental (Mexico). Weighted regression was used to remove heteroscedasticity from the species-specific dbh and h growth models using a power function of the tree size independent variables. The final models developed in the present study to predict dbh and total tree height growth included size variables, site factors, and competition variables in their formulation. The developed models fitted the data well and explained between 98 and 99% and of the observed variation of dbh, and between 77 and 98% of the observed variation of total tree height for the studied species and groups of species. The developed models can be used for estimating the individual dbh and h growth for the analyzed species and can be integrated in decision support tools for management planning in these mixed forest ecosystems

Key message: Site form and site index have shown similar precision for estimating site quality in even-aged Pinus radiata D. Don stands in north-western Spain. Additionally, SF presents the advantage that it does not require stand age information and can therefore be used in a wider set of situations in the forestry practice. Context: Estimation of site quality is essential for characterizing, monitoring and predicting forest resources. Site index (i.e. the dominant height of the stand at a reference age) is ordinarily used to estimate site quality; however, this index is only useful for even-aged stands of known age. By contrast, SF is age-independent as it uses the dominant height of the stand at a reference dominant diameter. Aims: The aim of this study was to compare the performance of SF and SI for site quality estimation in even-aged P. radiata stands. Methods: Dynamic equations derived with the Generalized Algebraic Difference Approach (GADA) from the Hossfeld IV base model were fitted to predict site quality with both SI and SF. SF predictions were compared with SI regarding variability within the same plot and consistency in site quality predictions, using the observed maximum mean annual volume increment (MAI) as a direct measure of site quality. Results: Both approaches showed good performance in model fitting and provided similar goodness-of-fit statistics and variability in the predictions. However, SI performed slightly stronger when related to MAI. Conclusion: SF performed adequately in estimating site quality for even-aged P. radiata stands, with results comparable to those obtained using traditional SI

We evaluated the use of low-density airborne laser scanning data to estimate diameter distributions in radiata pine plantations. The moment-based parameter recovery method was used to estimate the diameter distributions, considering LiDAR metrics as explanatory variables. The fitted models explained more than 77% of the observed variability. This approach can be replicated every 6 years (temporal cover planned for countrywide LiDAR flights in Spain). Context: The estimation of stand diameter distribution is informative for forest managers in terms of stand structure, forest growth model inputs, and economic timber value. In this sense, airborne LiDAR may represent an adequate source of information. Aims: The objective was to evaluate the use of low-density Spanish countrywide LiDAR data for estimating diameter distributions in Pinus radiata D. Don stands in NW Spain. Methods: The empirical distributions were obtained from 25 sample plots. We applied the moment-based parameter recovery method in combination with the Weibull function to estimate the diameter distributions, considering LiDAR metrics as explanatory variables. We evaluated the results by using the Kolmogorov–Smirnov (KS) test and a classification tree and random forest (RF) to relate the KS test result for each plot to stand-level variables. Results: The models used to estimate average (dm) and quadratic (dg) mean diameters from LiDAR metrics, required for recovery of the Weibull parameters, explained a high percentage of the observed variance (77 and 80%, respectively), with RMSE values of 3.626 and 3.422 cm for the same variables. However, the proportion of plots accepted by the KS was low. This poor performance may be due to the strictness of the KS test and/or by the characteristics of the LiDAR flight. Conclusion: The results justify the assessment of this approach over different species and forest types in regional or countrywide surveys.

Los modelos dinámicos a nivel de rodal son ampliamente usados en el ámbito forestal. Para su ajuste se emplean datos empíricos que se integran en un conjunto de ecuaciones que describen las relaciones entre diferentes variables. Las metodologías clásicas para desarrollar ecuaciones de transición invariantes con respecto al intervalo de simulación (path invariance) e invariantes respecto a la edad de referencia empleadas son algebraic difference approach (ADA) y generalized algebraic difference approach (GADA). El objetivo de este trabajo fue desarrollar un modelo dinámico de rodal para Eucalyptus globulus, empleando ecuaciones de transición para área basal, altura media dominante y mortalidad, utilizando enfoque de variables dummy. Los datos utilizados provienen de 168 parcelas permanentes. Las ecuaciones evaluadas individualmente fueron luego ajustadas simultáneamente mediante seemingly unrelated regression (SUR). En base al análisis de bondad de ajuste y de la capacidad predictiva, se seleccionó el modelo propuesto por Korf, modificado por Cieszewski (2004), para la altura media dominante; el modelo de Levakovic (Zeide, 1993), para el área basal y el modelo de Pienaar y Shiver (1981) para la mortalidad. El modelo de simulación desarrollado es más flexible y permite levantar algunas de las limitantes del modelo utilizado anteriormente. Su integración a sistemas de apoyo a la toma de decisiones constituirá una herramienta de gran utilidad para la planificación y toma de decisiones en el sector forestal., Stand level dynamic models are widely used in forestry. Fitting empirical data that is integrated into a set of equations is used to describe the relationships between different variables The classic methodologies to develop equations invariant with respect to transition simulation interval (path invariance) and invariant respect to the reference age are employed algebraic difference approach (ADA) and generalized algebraic difference approach (GADA). The aim of this study was to develop a dynamic model for Eucalyptus globulus stand using transition equations for basal area, dominant average height and mortality, using tle dummy variables approach. The data used are from 168 permanent plots. The equations evaluated individually were then adjusted simultaneously by seemingly unrelated regression (SUR). Based on the analysis of goodness of fit and predictive ability, the model proposed by Korf, as amended by Cieszewski (2004), for the dominant average height was selected; Levakovic model (Zeide, 1993) for the basal area and the model Pienaar and Shiver (1981) for mortality. The simulation model developed is more flexible and can lift some of the limitations of the model used previously. Its integration into a decision support system (DSS), constitute a useful tool for planning and decision making in the forestry sector.