A new method for the identification of old-growth trees in National Forest Inventories: Application to Pinus halepensis Mill. stands in Spain

Old-growth trees play a very important role in the maintenance of biodiversity in forests. However, no clear definition is yet available to help identify them since tree age is usually not recorded in National Forest Inventories. To develop and test a new method to identify old-growth trees using a species-specific threshold for tree diameter in National Forest Inventories. Different nonlinear mixed models for diameter ? age were generated using data from the Spanish Forest Inventory in order to identify the most appropriate one for Aleppo pine in its South-western distribution area. The asymptote of the optimal model indicates the threshold diameter for defining an old-growth tree. Additionally, five site index curves were examined to analyze the influence of site quality on these models.

Impacts of global change on iberian forest ecosystems inferred from the spanish national forest inventory = Impactos del cambio global en ecosistemas forestales ibéricos a partir del inventario forestal nacional

Los efectos del cambio global sobre los bosques son una de las grandes preocupaciones de la sociedad del siglo XXI. Algunas de sus posibles consecuencias como son los efectos en la producción, la sostenibilidad, la pérdida de biodiversidad o cambios en la distribución y ensamblaje de especies forestales pueden tener grandes repercusiones sociales, ecológicas y económicas. La detección y seguimiento de estos efectos constituyen uno de los retos a los que se enfrentan en la actualidad científicos y gestores forestales. En base a la comparación de series históricas del Inventario Forestal Nacional Español (IFN), esta tesis trata de arrojar luz sobre algunos de los impactos que los cambios socioeconómicos y ambientales de las últimas décadas han generado sobre nuestros bosques. En primer lugar, esta tesis presenta una innovadora metodología con base geoestadística que permite la comparación de diferentes ciclos de inventario sin importar los diferentes métodos de muestreo empleados en cada uno de ellos (Capítulo 3). Esta metodología permite analizar cambios en la dinámica y distribución espacial de especies forestales en diferentes gradientes geográficos. Mediante su aplicación, se constatarán y cuantificarán algunas de las primeras evidencias de cambio en la distribución altitudinal y latitudinal de diferentes especies forestales ibéricas, que junto al estudio de su dinámica poblacional y tasas demográficas, ayudarán a testar algunas hipótesis biogeográficas en un escenario de cambio global en zonas de especial vulnerabilidad (Capítulos 3, 4 y 5). Por último, mediante la comparación de ciclos de parcelas permanentes del IFN se ahondará en el conocimiento de la evolución en las últimas décadas de especies invasoras en los ecosistemas forestales del cuadrante noroccidental ibérico, uno de los más afectados por la invasión de esta flora (Capítulo 6). ABSTRACT The effects of global change on forests are one of the major concerns of the XXI century. Some of the potential impacts of global change on forest growth, productivity, biodiversity or changes in species assembly and spatial distribution may have great ecological and economic consequences. The detection and monitoring of these effects are some of the major challenges that scientists and forest managers face nowadays. Based on the comparison of historical series of the Spanish National Forest Inventory (NFI), this thesis tries to shed some light on some of the impacts driven by recent socio-economic and environmental changes on our forest ecosystems. Firstly, this thesis presents an innovative methodology based on geostatistical techniques that allows the comparison of different NFI cycles regardless of the different sampling methods used in each of them (Chapter 3). This methodology, in conjunction with other statistical techniques, allows to analyze changes in the spatial distribution and population dynamics of forest species along different geographic gradients. By its application, this thesis presents some of the first evidences of changes in species distribution along different geographical gradients in the Iberian Peninsula. The analysis of these findings, of species population dynamics and demographic rates will help to test some biogeographical hypothesis on forests under climate change scenarios in areas of particular vulnerability (Chapters 3, 4 and 5). Finally, by comparing NFI cycles with permanent plots, this thesis increases our knowledge about the patterns and processes associated with the recent evolution of invasive species in the forest ecosystems of North-western Iberia, one of the areas most affected by the invasion of allien species at national scale (Chapter 6).

Assessing forest response-type diversity to natural disturbances in Peninsular Spain and the Balearic Islands = Evaluación de la diversidad de tipos de respuesta a perturbaciones naturales en la España peninsular e Islas Baleares

Disturbances shape forest ecosystems by influencing their composition, structure, and processes. In the Mediterranean Basin, changes in the disturbance regimes have been predicted to occur in the next future with a higher occurrence of extreme events of drought, wildfire, and – to a lesser extent – windstorm. Woody species are the main elements defining the structure and functioning of forest ecosystems. Recently, response-type diversity has been pointed out as an appropriate indicator of ecosystems resilience. For this, we have elaborated a complete response-trait database for the tree and shrubby species considered in the Third Spanish National Forest Inventory (3SNFI). In the database, the presence or absence of nine response traits associated to drought, fire, and wind were assigned to each species. The database reflected the lack of information about some important traits (in particular for shrubby species) and allowed to determine those traits most widely distributed. The information contained in the database was then used to assess a relative index of forest resilience to these disturbances calculated from the abundance of response traits and the species redundancy for each plot of the 3SNFI; considering both tree and shrubby species. In general, few plots showed high values of the resilience index, probably because some traits were scarcely presented in the species and also because most plots presented very few species. The cartographic representation of the index showed low values for the stands located in mountainous ranges, which are mostly composed by species typical from central Europe. In the other side, Eucalyptus plantations in Galicia appeared as one thee the most resilient ecosystems, due to its higher adaptive capacity to persist after the occurrence of drought, fire, and windstorm events. We conclude that the response traits database can constitute a useful tool for forest management and planning and for future research to enhance the forest resilience.

An empirical mixed model to quantify climate influence on the growth of Pinus halepensis Mill. stands in South-Eastern Spain

The influence of climate on forest stand composition, development and growth is undeniable. Many studies have tried to quantify the effect of climatic variables on forest growth and yield. These works become especially important because there is a need to predict the effects of climate change on the development of forest ecosystems. One of the ways of facing this problem is the inclusion of climatic variables into the classic empirical growth models. The work has a double objective: (i) to identify the indicators which best describe the effect of climate on Pinus halepensis growth and (ii) to quantify such effect in several scenarios of rainfall decrease which are likely to occur in the Mediterranean area. A growth mixed model for P. halepensis including climatic variables is presented in this work. Growth estimates are based on data from the Spanish National Forest Inventory (SNFI). The best results are obtained for the indices including rainfall, or rainfall and temperature together, with annual precipitation, precipitation effectiveness, Emberger?s index or free bioclimatic intensity standing out among them. The final model includes Emberger?s index, free bioclimatic intensity and interactions between competition and climate indices. The results obtained show that a rainfall decrease about 5% leads to a decrease in volume growth of 5.5?7.5% depending on site quality.

Mixing effect on volume growth of Fagus sylvatica and Pinus sylvestris is modulated by stand density

Despite the increasing relevance of mixed stands due to their potential benefits; little information is available with regard to the effect of mixtures on yield in forest systems. Hence, it is necessary to study inter-specific relationships, and the resulting yield in mixed stands, which may vary with stand development, site or stand density, etc. In Spain, the province of Navarra is considered one of the biodiversity reservoirs; however, mixed forests occupy only a small area, probably as a consequence of management plans, in which there is an excessive focus on the productivity aspect, favoring the presence of pure stands of the most marketable species. The aim of this paper is to study how growth efficiencies of beech (Fagus sylvatica) and pine (Pinus sylvestris) are modified by the admixture of the other species and to determine whether stand density modifies interspecific relationships and to what extent. Two models were fitted from Spanish National Forest Inventory data, for P. sylvestris and F. sylvatica respectively, which relate the growth efficiency of the species, i.e. the volume increment of the species divided by the species proportion by area, with dominant height, quadratic mean diameter, stocking degree, and the species proportions by area of each species. Growth efficiency of pine increased with the admixture of beech, decreasing this positive effect when stocking degree increased. However, the positive effect of pine admixture on beech growth was greater at higher stocking degrees. Growth efficiency of beech was also dependent on stand dominant height, resulting in a net negative mixing effect when stand dominant heights and stocking degrees were simultaneously low. There is a relatively large range of species proportions and stocking degrees which results in transgressive overyielding: higher volume increments in mixed stands than that of the most productive pure pine stands. We concluded that stocking degree is a key factor in between-species interactions, being the effects of mixing not always greater at higher stand densities, but it depends on species composition.

Analyzing size-symmetric vs. size-asymmetric and intra-vs. inter-specific competition in beech (Fagus sylvatica L.) mixed stands

In mixed stands, inter-specific competition can be lower than intra-specific competition when niche complementarity and/or facilitation between species prevail. These positive interactions can take place at belowground and/or aboveground levels. Belowground competition tends to be size symmetric while the aboveground competition is usually for light and almost always size-asymmetric. Interactions between forest tree species can be explored analyzing growth at tree level by comparing intra and inter-specific competition. At the same time, possible causes of niche complementarity can be inferred relating intra and inter-specific competition with the mode of competition, i.e. size-symmetric or sizeasymmetric. The aim of this paper is to further our understanding of the interactions between species and to detect possible causes of competition reduction in mixed stands of beech (Fagus sylvatica L.) with other species: pine?beech, oak?beech and fir?beech. To test whether species growth is better explained by size-symmetric and/or size-asymmetric competition, five different competition structures where included in basal area growth models fitted using data from the Spanish National Forest Inventory for the Pyrenees. These models considered either size-symmetry only (Reineke?s stand density index, SDI), size-asymmetry only (SDI of large trees or SDI of small trees), or both combined. In order to assess the influence of the admixture, these indices were introduced in two different ways, one of which was to consider that trees of all species compete in a similar way, and the other was to split the stand density indices into intra- and inter-specific competition components. The results showed that in pine?beech mixtures, there is a slightly negative effect of beech on pine basal area growth while beech benefitted from the admixture of Scots pine; this positive effect being greater as the proportion of pine trees in larger size classes increases. In oak?beech mixtures, beech growth was also positively influenced by the presence of oaks that were larger than the beech trees. The growth of oak, however, decreased when the proportion of beech in SDI increased, although the presence of beech in larger size classes promoted oak growth. Finally, in fir?beech mixtures, neither fir nor beech basal area growth were influenced by the presence of the other species. The results indicate that size-asymmetric is stronger than size-symmetric competition in these mixtures, highlighting the importance of light in competition. Positive species interactions in size-asymmetric competition involved a reduction of asymmetry in tree size-growth relationships.

Metodología para la estimación de indicadores armonizados a partir de los inventarios forestales nacionales europeos con especial énfasis en la biodiversidad forestal

Durante las últimas décadas el objetivo principal de la silvicultura y la gestión forestal en Europa ha pasado de ser la producción de madera a ser la gestión sostenible de los ecosistemas, por lo que se deben considerar todos los bienes y servicios que proporcionan los bosques. En consecuencia, es necesario contar con información forestal periódica de diversos indicadores forestales a nivel europeo para apoyar el desarrollo y la implementación de políticas medioambientales y que se realice una gestión adecuada. Para ello, se requiere un seguimiento intensivo sobre el estado de los bosques, por lo que los Inventarios Forestales Nacionales (IFN), (principal fuente de información forestal a gran escala), han aumentado el número de variables muestreadas para cumplir con los crecientes requerimientos de información. Sin embargo, las estimaciones proporcionadas por los diferentes países no son fácilmente comparables debido a las diferencias en las definiciones, los diseños de muestreo, las variables medidas y los protocolos de medición. Por esto, la armonización de los datos que proporcionan los diferentes países es fundamental para la contar con una información forestal sólida y fiable en la Unión europea (UE). La presente tesis tiene dos objetivos principales: (i) establecer el diseño de una metodología para evaluar la biodiversidad forestal en el marco del Inventario forestal nacional de España teniendo en cuenta las diferentes iniciativas nacionales e internacionales, con el objetivo de producir estimaciones comparables con las de otros países de la UE y (ii) armonizar los indicadores más relevantes para satisfacer los requerimientos nacionales e internacionales. Como consecuencia del estudio realizado para alcanzar el primer objetivo, la metodología diseñada para estimar la biodiversidad fue adoptada por el Tercer Inventario forestal nacional. Ésta se componía de indicadores agrupados en: cobertura del suelo, composición de árboles y especies de arbustos, riqueza de especies herbáceas y helechos, especies amenazadas, estructura, madera muerta, y líquenes epífitos. Tras el análisis del diseño metodológico y de los datos proporcionados, se observó la conveniencia de modificarla con el fin de optimizar los costes, viabilidad, calidad y cantidad de los datos registrados. En consecuencia, en el Cuarto Inventario Forestal Nacional se aplica una metodología modificada, puesto que se eliminó el muestreo de especies herbáceas y helechos, de líquenes epífitos y de especies amenazadas, se modificaron los protocolos de la toma de datos de estructura y madera muerta y se añadió el muestreo de especies invasoras, edad, ramoneo y grado de naturalidad de la masa. En lo que se refiere al segundo objetivo, se ha avanzado en la armonización de tres grupos de variables considerados como relevantes en el marco de los IFN: los indicadores de vegetación no arbórea (que juegan un papel relevante en los ecosistemas, es donde existe la mayor diversidad de plantas y hasta ahora no se conocían los datos muestreados en los IFN), la determinación de los árboles añosos (que tienen un importante papel como nicho ecológico y su identificación es especialmente relevante para la evaluación de la biodiversidad forestal) y el bosque disponible para el suministro de madera (indicador básico de los requerimientos internacionales de información forestal). Se llevó a cabo un estudio completo de la posible armonización de los indicadores de la vegetación no arbórea en los IFN. Para ello, se identificaron y analizaron las diferentes definiciones y diseños de muestreo empleados por los IFN, se establecieron definiciones de referencia y se propusieron y analizaron dos indicadores que pudiesen ser armonizados: MSC (mean species cover) que corresponde a la media de la fracción de cabida cubierta de cada especie por tipo de bosque y MTC (mean total cover). Se estableció una nueva metodología que permite identificar los árboles añosos con los datos proporcionados por los inventarios forestales nacionales con el objetivo de proporcionar una herramienta eficaz para facilitar la gestión forestal considerando la diversidad de los sistemas forestales. Se analizó el concepto de "bosque disponible para el suministro de madera" (FAWS) estudiando la consistencia de la información internacional disponible con el fin de armonizar su estimación y de proporcionar recomendaciones para satisfacer los requerimientos europeos. Como resultado, se elaboró una nueva definición de referencia de FAWS (que será adoptada por el proceso paneuropeo) y se analiza el impacto de la adopción de esta nueva definición en siete países europeos. El trabajo realizado en esta tesis, puede facilitar el suministrar y/o armonizar parcial o totalmente casi la mitad de los indicadores de información forestal solicitados por los requerimientos internacionales (47%). De éstos, prácticamente un 85% tienen relación con los datos inventariados empleando la metodología propuesta para la estimación de la biodiversidad forestal, y el resto, con el establecimiento de la definición de bosque disponible para el suministro de madera. No obstante, y pese a que esta tesis supone un avance importante, queda patente que las necesidades de información forestal son cambiantes y es imprescindible continuar el proceso de armonización de los IFN europeos. ABSTRACT Over the last few decades, the objectives on forestry and forest management in Europe have shifted from being primarily focused on wood production to sustainable ecosystem management, which should consider all the goods and services provided by the forest. Therefore, there is a continued need for forest indicators and assessments at EU level to support the development and implementation of a number of European environmental policies and to conduct a proper forest management. To address these questions, intensive monitoring on the status of forests is required. Therefore, the scope of National Forest Inventories (NFIs), (primary source of data for national and large-area assessments), has been broadened to include new variables to meet these increasing information requirements. However, estimates produced by different countries are not easily comparable because of differences in NFI definitions, plot configurations, measured variables, and measurement protocols. As consequence, harmonizing data produced at national level is essential for the production of sound EU forest information. The present thesis has two main aims: (i) to establish a methodology design to assess forest biodiversity in the frame of the Spanish National Forest Inventory taking into account the different national and international initiatives with the intention to produce comparable estimates with other EU countries and (ii) to harmonize relevant indicators for national and international requirements. In consequence of the work done related to the first objective, the established methodology to estimate forest biodiversity was adopted and launched under the Third National Forest Inventory. It was composed of indicators grouped into: cover, woody species composition, richness of herbaceous species and ferns, endangered species, stand structure, dead wood, and epiphytic lichens. This methodology was analyzed considering the provided data, time costs, feasibility, and requirements. Consequently, in the ongoing Fourth National Forest Inventory a modified methodology is applied: sampling of herbaceous species and ferns, epiphytic lichens and endangered species were removed, protocols regarding structure and deadwood were modified, and sampling of invasive species, age, browsing impact and naturalness were added. As regards the second objective, progress has been made in harmonizing three groups of variables considered relevant in the context of IFN: Indicators of non-tree vegetation (which play an important role in forest ecosystems, it is where the highest diversity of plants occur and so far the related sampled data in NFIs were not known), the identification of old-growth trees (which have an important role as ecological niche and its identification is especially relevant for the assessment of forest biodiversity) and the available forest for wood supply (basic indicator of international forestry information requirements). A complete analysis of ground vegetation harmonization possibilities within NFIs frame was carried on by identifying and analyzing the different definitions and sampling techniques used by NFIs, providing reference definitions related to ground vegetation and proposing and analyzing two ground vegetation harmonized indicators: “Mean species cover” (MSC) and “Mean total cover” (MTC) for shrubs by European forest categories. A new methodology based on NFI data was established with the aim to provide an efficient tool for policy makers to estimate the number of old-growth trees and thus to be able to perform the analysis of the effect of forest management on the diversity associated to forest systems. The concept of “forest available for wood supply” (FAWS) was discussed and clarified, analyzing the consistency of the available international information on FAWS in order to provide recommendations for data harmonization at European level regarding National Forest Inventories (NFIs). As a result, a new reference definition of FAWS was provided (which will be adopted in the pan-European process) and the consequences of the use of this new definition in seven European countries are analyzed. The studies carried on in this thesis, can facilitate the supply and/or harmonization partially or fully of almost half of the forest indicators (47%) needed for international requirements. Of these, nearly 85% are related to inventoried data using the proposed methodology for the estimation of forest biodiversity, and the rest, with the establishment of the definition of forest available for wood supply. However, despite this thesis imply an important development, forest information needs are changing and it is imperative to continue the process of harmonization of European NFIs.

Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Negative density dependence and environmental heterogeneity effects on tree ferns across succession in a tropical montane forest.

Although tree ferns are an important component of temperate and tropical forests, very little is known about their ecology. Their peculiar biology (e.g., dispersal by spores and two-phase life cycle) makes it difficult to extrapolate current knowledge on the ecology of other tree species to tree ferns. In this paper, we studied the effects of negative density dependence (NDD) and environmental heterogeneity on populations of two abundant tree fern species, Cyathea caracasana and Alsophila engelii, and how these effects change across a successional gradient. Species patterns harbor information on processes such as competition that can be easily revealed using point pattern analysis techniques. However, its detection may be difficult due to the confounded effects of habitat heterogeneity. Here, we mapped three forest plots along a successional gradient in the montane forests of Southern Ecuador. We employed homogeneous and inhomogeneous K and pair correlation functions to quantify the change in the spatial pattern of different size classes and a case-control design to study associations between juvenile and adult tree ferns. Using spatial estimates of the biomass of four functional tree types (short- and long-lived pioneer, shade- and partial shade-tolerant) as covariates, we fitted heterogeneous Poisson models to the point pattern of juvenile and adult tree ferns and explored the existence of habitat dependencies on these patterns. Our study revealed NDD effects for C. caracasana and strong environmental filtering underlying the pattern of A. engelii. We found that adult and juvenile populations of both species responded differently to habitat heterogeneity and in most cases this heterogeneity was associated with the spatial distribution of biomass of the four functional tree types. These findings show the effectiveness of factoring out environmental heterogeneity to avoid confounding factors when studying NDD and demonstrate the usefulness of covariate maps derived from mapped communities.

Spatially-Explicit Testing of a General Aboveground Carbon Density Estimation Model in aWestern Amazonian Forest Using Airborne LiDAR

Mapping aboveground carbon density in tropical forests can support CO2 emissionmonitoring and provide benefits for national resource management. Although LiDAR technology has been shown to be useful for assessing carbon density patterns, the accuracy and generality of calibrations of LiDAR-based aboveground carbon density (ACD) predictions with those obtained from field inventory techniques should be intensified in order to advance tropical forest carbon mapping. Here we present results from the application of a general ACD estimation model applied with small-footprint LiDAR data and field-based estimates of a 50-ha forest plot in Ecuador?s Yasuní National Park. Subplots used for calibration and validation of the general LiDAR equation were selected based on analysis of topographic position and spatial distribution of aboveground carbon stocks. The results showed that stratification of plot locations based on topography can improve the calibration and application of ACD estimation using airborne LiDAR (R2 = 0.94, RMSE = 5.81 Mg?C? ha?1, BIAS = 0.59). These results strongly suggest that a general LiDAR-based approach can be used for mapping aboveground carbon stocks in western lowland Amazonian forests.

LiDAR remote sensing applied to forest resources assessment

Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el número de pies, el volumen de madera, la altura dominante, el diámetro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicación de los denominados métodos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y características de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (información proveniente de vuelo nacionales e información capturada de forma específica). Como consecuencia de lo anterior, se profundiza en la generación de inventarios forestales continuos con LiDAR en grandes áreas. Los métodos de masa se basan en la búsqueda de relaciones estadísticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartografía continua de inventario forestal. El rápido desarrollo de esta tecnología en los últimos años ha llevado a muchos países a implantar programas nacionales de captura de información LiDAR aerotransportada. Estos vuelos nacionales no están pensados ni diseñados para fines forestales por lo que es necesaria la evaluación de la validez de esta información LiDAR para la descripción de la estructura del bosque y la medición de variables forestales. Esta información podría suponer una drástica reducción de costes en la generación de información continua de alta resolución de inventario forestal. En el capítulo 2 se evalúa la estimación de variables forestales a partir de la información LiDAR capturada en el marco del Plan Nacional de Ortofotografía Aérea (PNOA-LiDAR) en España. Para ello se compara un vuelo específico diseñado para inventario forestal con la información de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra cómo el ángulo de escaneo, la pendiente y orientación del terreno afectan de forma estadísticamente significativa, aunque con pequeñas diferencias, a la estimación de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas resultó más afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimación de la biomasa con ambas bases de datos no presentó diferencias estadísticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimación de biomasa entre un vuelo específico y el vuelo nacional podrán superar el 4% en áreas abruptas, con ángulos de escaneo altos y cuando la pendiente de la ladera no esté orientada hacia la línea de escaneo. En el capítulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la información disponible (vuelos LiDAR nacionales de baja densidad de puntos, imágenes satelitales Landsat y parcelas permanentes del inventario forestal nacional español). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resolución en grandes superficies. Los errores obtenidos en la fase de ajuste y de validación de los modelos de área basimétrica y volumen son similares a los registrados por otros autores (usando un vuelo específico y parcelas de campo específicas). Se observan errores mayores en la variable número de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodología de parcelas de radio variable en esta variable. En los capítulos 4 y 5 se evalúan los métodos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volcán Poás (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del área de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es técnica o económicamente posible y se combina una cobertura incompleta de LiDAR con imágenes Landsat e información auxiliar para la estimación de biomasa y carbono (capitulo 5). En el capítulo 4 se valida un modelo LiDAR general de estimación de biomasa aérea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma específica para el área de estudio. Ambos modelos están basados en la variable altura media de copas (TCH por sus siglas en inglés) derivada del modelo digital LiDAR de altura de la vegetación. Los resultados en el área de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos específicos y que la biomasa aérea puede ser estimada en una nueva zona midiendo en campo únicamente la variable área basimétrica (BA). Para mejorar la aplicación de esta metodología es necesario definir en futuros trabajos procedimientos adecuados de medición de la variable área basimétrica en campo (localización, tamaño y forma de las parcelas de campo). La relación entre la altura media de copas del LiDAR y el área basimétrica (Coeficiente de Stock) obtenida en el área de estudio varía localmente. Por tanto es necesario contar con más información de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificación pueden reducir los errores en la estimación de biomasa y carbono en bosques tropicales. En el capítulo 5 se concluye que la combinación de una muestra sistemática de información LiDAR con una cobertura completa de imagen satelital de moderada resolución (e información auxiliar) es una alternativa efectiva para la realización de inventarios continuos en bosques tropicales. Esta metodología permite estimar altura de la vegetación, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realización de un gran volumen de trabajo de campo es económica o/y técnicamente inviable. Las alternativas examinadas para la predicción de biomasa a partir de imágenes Landsat muestran una ligera disminución del coeficiente de determinación y un pequeño aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetación, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del área de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15º. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.

Geografía del carbono en alta resolución en bosque tropical amazónico del Ecuador mediante sensores aerotransportados

La estimación de la biomasa de la vegetación terrestre en bosque tropical no sólo es un área de investigación en rápida expansión, sino también es un tema de gran interés para reducir las emisiones de carbono asociadas a la deforestación y la degradación forestal (REDD+). Las estimaciones de densidad de carbono sobre el suelo (ACD) en base a inventarios de campo y datos provenientes de sensores aerotransportados, en especial con sensores LiDAR, han conducido a un progreso sustancial en el cartografiado a gran escala de las reservas de carbono forestal. Sin embargo, estos mapas de carbono tienen incertidumbres considerables, asociadas generalmente al proceso de calibración del modelo de regresión utilizado para producir los mapas. En esta tesis se establece una metodología para la calibración y validación de un modelo general de estimación de ACD usando LiDAR en un sector del Parque Nacional Yasuní en Ecuador. En el proceso de calibración del modelo se considera el tamaño y la ubicación de las parcelas, la influencia de la topografía y la distribución espacial de la biomasa. Para el análisis de los datos se utilizan técnicas geoestadísticas en combinación con variables geomorfométricas derivadas de datos LiDAR, y se propone un esquema de muestreo estratificado por posiciones topográficas (valle, ladera y cima). La validación del modelo general para toda la zona de estudio presentó valores de RMSE = 5.81 Mg C ha-1, R2 = 0.94 y sesgo = 0.59, mientras que, al considerar las posiciones topográficas, el modelo presentó valores de RMSE = 1.67 Mg C ha-1, R2 = 0.98 y sesgo = 0.23 para el valle; RMSE = 3.13 Mg C ha-1, R2 = 0.98 y sesgo = - 0.34 para la ladera; y RMSE = 2.33 Mg C ha-1, R2 = 0.97 y sesgo = 0.74 para la cima. Los resultados obtenidos demuestran que la metodología de muestreo estratificado por posiciones topográficas propuesto, permite calibrar de manera efectiva el modelo general con las estimaciones de ACD en campo, logrando reducir el RMSE y el sesgo. Los resultados muestran el potencial de los datos LiDAR para caracterizar la estructura vertical de la vegetación en un bosque altamente diverso, permitiendo realizar estimaciones precisas de ACD, y conocer patrones espaciales continuos de la distribución de la biomasa aérea y del contenido de carbono en la zona de estudio. ABSTRACT Estimating biomass of terrestrial vegetation in tropical forest is not only a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD+). The aboveground carbon density estimates (ACD) based on field inventories and airborne sensors, especially LiDAR sensors have led to a substantial progress in large-scale mapping of forest carbon stocks. However, these carbon maps have considerable uncertainties generally associated with the calibration of the regression model used to produce these maps. This thesis establishes a methodology for calibrating and validating a general ACD estimation model using LiDAR in Ecuador´s Yasuní National Park. The size and location of the plots are considered in the model calibration phase as well as the influence of topography and spatial distribution of biomass. Geostatistical analysis techniques are used in combination with geomorphometrics variables derived from LiDAR data, and then a stratified sampling scheme considering topographic positions (valley, slope and ridge) is proposed. The validation of the general model for the study area showed values of RMSE = 5.81 Mg C ha-1, R2 = 0.94 and bias = 0.59, while considering the topographical positions, the model showed values of RMSE = 1.67 Mg C ha-1, R2 = 0.98 and bias = 0.23 for the valley; RMSE = 3.13 Mg C ha-1, R2 = 0.98 and bias = - 0.34 for the slope; and RMSE = 2.33 Mg C ha-1, R2 = 0.97 and bias = 0.74 for the ridge. The results show that the stratified sampling methodology taking into account topographic positions, effectively calibrates the general model with field estimates of ACD, reducing RMSE and bias. The results show the potential of LiDAR data to characterize the vertical structure of vegetation in a highly diverse forest, allowing accurate estimates of ACD, and knowing continuous spatial patterns of biomass distribution and carbon stocks in the study area.