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.

Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Height-diameter relationships of tropical Atlantic moist forest trees in southeastern Brazil

Site-specific height-diameter models may be used to improve biomass estimates for forest inventories where only diameter at breast height (DBH) measurements are available. In this study, we fit height-diameter models for vegetation types of a tropical Atlantic forest using field measurements of height across plots along an altitudinal gradient. To fit height-diameter models, we sampled trees by DBH class and measured tree height within 13 one-hectare permanent plots established at four altitude classes. To select the best model we tested the performance of 11 height-diameter models using the Akaike Information Criterion (AIC). The Weibull and Chapman-Richards height-diameter models performed better than other models, and regional site-specific models performed better than the general model. In addition, there is a slight variation of height-diameter relationships across the altitudinal gradient and an extensive difference in the stature between the Atlantic and Amazon forests. The results showed the effect of altitude on tree height estimates and emphasize the need for altitude-specific models that produce more accurate results than a general model that encompasses all altitudes. To improve biomass estimation, the development of regional height-diameter models that estimate tree height using a subset of randomly sampled trees presents an approach to supplement surveys where only diameter has been measured.

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.

Applications of Radial Basis Neural Networks for Area Forest

This paper proposes a new method using radial basis neural networks in order to find the classification and the recognition of trees species for forest inventories. This method computes the wood volume using a set of data easily obtained. The results that are obtained improve the used classic and statistical models.

Cultural valuation and biodiversity conservation in the Upper Guinea forest, West Africa

The cultural valuation of biodiversity has taken on renewed importance over the last two decades as the ecosystem services framework has become widely adopted. Conservation initiatives increasingly use ecosystem service frameworks to render tropical forest landscapes and their peoples legible to market-oriented initiatives such as REDD+ and biodiversity offsetting schemes. Ecosystem service approaches have been widely criticized by scholars in the social sciences and humanities for their narrow focus on a small number of easily quantifiable and marketable services and a reductionist and sometimes simplistic approach to culture. We address the need to combine methods from each of the “three cultures” of natural science, quantitative social science, and qualitative social science/humanities in conceptualizing the relationship between cultural valuation and biodiversity conservation. We combine qualitative data with forest inventories and a quantitative index of cultural value to evaluate the relationship between cultural valuation and biodiversity conservation in Upper Guinea forest in Liberia, West Africa. Our study focuses on “sacred agroforests,” spaces that are associated with Mande macro-language speaking groups such as the Loma. We demonstrate that sacred agroforests are associated with different cultural values compared with secondary forests. Although biodiversity and biomass are similar, sacred agroforests exhibit a different species composition, especially of culturally salient species, increasing overall landscape agro-biodiversity. Sacred agroforests are also shaped and conserved by local cultural institutions revolving around ancestor worship, ritual, and the metaphysical conceptual category “salɛ.” We conclude that to understand the relationship between cultural valuation and biodiversity conservation, interpretivist approaches such as phenomenology should be employed alongside positivist ecosystem service frameworks.

An estimate of biometric parameters in eucalyptus clone plantations in Southern Bahia: an application of the airborne laser scanning (ALS) technology

The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.

Non-volant tetrapods from Reserva Biológica de Duas Bocas, State of Espírito Santo, Southeastern Brazil

A Reserva Biológica de Duas Bocas (2.190 ha) é um dos maiores remanescentes de Mata Atlântica do Estado do Espírito Santo, Sudeste do Brasil. Nós amostramos tetrápodes não voadores nessa área entre maio de 2007 e abril de 2008, utilizando armadilhas de queda, armadilhas de isca, armadilhas fotográficas e buscas oportunísticas diurnas e noturnas. Além disso, nós compilamos registros de vertebrados não voadores ocorrentes nesta área disponíveis na literatura e através de espécimes em museus. Nós documentamos 52 espécies de anfíbios, 24 espécies de répteis não voadores e 39 espécies de mamíferos não voadores. Do total de 115 espécies, 47 configuram novos registros para a área e seis outras espécies tiveram sua distribuição geográfica ampliada com os resultados do presente estudo. Além disso, apresentamos o registro de predação da perereca Hypsiboas faber pela serpente Chironius bicarinatus. Cinco das espécies registradas são listadas como ameaçadas no Estado do Espírito Santo e muitas outras possuem estado de conservação incerto. A Reserva Biológica de Duas Bocas é um importante refúgio de vida selvagem, principalmente quando consideramos a expansão de áreas urbanas no seu entorno.

Inventario das espécies arbóreas da caatinga em Petrolina-PE.

O presente trabalho objetivou-se inventariar as espécies arbóreas mais frequentes da caatinga, visando oferecer subsídios para eventuais programas de manejo e uso sustentável desse tipo de vegetação.

Comparação de métodos para determinar biomassa na região amazônica

The aboveground biomass content of a region can be estimated by either direct or indirect methods. Direct methods correspond to the biomass content determination with scales and extrapolation of results to larger areas. It is a destructive and very laborious procedure. Indirect methods utilize formulas whose entrance parameters are obtained from forest inventories. Forest inventories are made with the purpose to plan exploration and land use and the inventory data are frequently not suitable for biomass estimation. Problems with both methods increase in the Amazon region, where little information is available on forest biomass. The objective of this paper is to establish, by comparing the application of the indirect and direct methods in the determination of the biomass, the more appropriate indirect formulation to represent the characteristic vegetation of a region in the amazonian forest. A 0.2 hectare area was chosen, which was part of a major forest clearing experiment conducted in Tomé Açu, a town located 250 km south of Belém, the capital of the Brazilian state of Pará. The entire biomass in the area was weighted with scales during the three weeks that followed the cut of the forest in July 1994. A detailed inventory was carried out in the area and then the indirect method was applied in the data. Seven different formulas for determining biomass were used. Comparison of the data of real mass and the mass obtained through the application of the seven formulas indicated that the more suitable for the region is given by FW = α · φβ · Hγ, where FW is total fresh weight (kg), φ is the diameter at breast height (cm), H is the total height of the tree and α, β and γ are regression coefficients (equal to 0.026, 1.529 and 1.747, respectively).

Anthropogenic perturbation of the carbon fluxes from land to ocean

A substantial amount of the atmospheric carbon taken up on land through photosynthesis and chemical weathering is transported laterally along the aquatic continuum from upland terrestrial ecosystems to the ocean. So far, global carbon budget estimates have implicitly assumed that the transformation and lateral transport of carbon along this aquatic continuum has remained unchanged since pre-industrial times. A synthesis of published work reveals the magnitude of present-day lateral carbon fluxes from land to ocean, and the extent to which human activities have altered these fluxes. We show that anthropogenic perturbation may have increased the flux of carbon to inland waters by as much as 1.0 Pg C yr(-1) since pre-industrial times, mainly owing to enhanced carbon export from soils. Most of this additional carbon input to upstream rivers is either emitted back to the atmosphere as carbon dioxide (similar to 0.4 Pg C yr(-1)) or sequestered in sediments (similar to 0.5 Pg C yr(-1)) along the continuum of freshwater bodies, estuaries and coastal waters, leaving only a perturbation carbon input of similar to 0.1 Pg C yr(-1) to the open ocean. According to our analysis, terrestrial ecosystems store similar to 0.9 Pg C yr(-1) at present, which is in agreement with results from forest inventories but significantly differs from the figure of 1.5 Pg C yr(-1) previously estimated when ignoring changes in lateral carbon fluxes. We suggest that carbon fluxes along the land-ocean aquatic continuum need to be included in global carbon dioxide budgets.

Estimación de variables dasométricas a partir de datos LiDAR y obtención de modelos de referencia para las distribuciones de alturas y diámetros del arbolado

La Gestión Forestal Sostenible se define como “la administración y uso de los bosques y tierras forestales de forma e intensidad tales que mantengan su biodiversidad, productividad, capacidad de regeneración, vitalidad y su potencial para atender, ahora y en el futuro, las funciones ecológicas, económicas y sociales relevantes a escala local, nacional y global, y que no causan daño a otros ecosistemas” (MCPFE Conference, 1993). Dentro del proceso los procesos de planificación, en cualquier escala, es necesario establecer cuál será la situación a la que se quiere llegar mediante la gestión. Igualmente, será necesario conocer la situación actual, pues marcará la situación de partida y condicionará el tipo de actuaciones a realizar para alcanzar los objetivos fijados. Dado que, los Proyectos de Ordenación de Montes y sus respectivas revisiones son herramientas de planificación, durante la redacción de los mismos, será necesario establecer una serie de objetivos cuya consecución pueda verificarse de forma objetiva y disponer de una caracterización de la masa forestal que permita conocer la situación de partida. Esta tesis se centra en problemas prácticos, propios de una escala de planificación local o de Proyecto de Ordenación de Montes. El primer objetivo de la tesis es determinar distribuciones diamétricas y de alturas de referencia para masas regulares por bosquetes, empleando para ello el modelo conceptual propuesto por García-Abril et al., (1999) y datos procedentes de las Tablas de producción de Rojo y Montero (1996). Las distribuciones de referencia obtenidas permitirán guiar la gestión de masas irregulares y regulares por bosquetes. Ambos tipos de masas aparecen como una alternativa deseable en aquellos casos en los que se quiere potenciar la biodiversidad, la estabilidad, la multifuncionalidad del bosque y/o como alternativa productiva, especialmente indicada para la producción de madera de calidad. El segundo objetivo de la Tesis está relacionado con la necesidad de disponer de una caracterización adecuada de la masa forestal durante la redacción de los Proyectos de Ordenación de Montes y de sus respectivas revisiones. Con el fin de obtener estimaciones de variables forestales en distintas unidades territoriales de potencial interés para la Ordenación de Montes, así como medidas de la incertidumbre en asociada dichas estimaciones, se extienden ciertos resultados de la literatura de Estimación en Áreas Pequeñas. Mediante un caso de estudio, se demuestra el potencial de aplicación de estas técnicas en inventario forestales asistidos con información auxiliar procedente de sensores láser aerotransportados (ALS). Los casos de estudio se realizan empleando datos ALS similares a los recopilados en el marco del Plan Nacional de Ortofotografía Aérea (PNOA). Los resultados obtenidos muestran que es posible aumentar la eficiencia de los inventarios forestales tradicionales a escala de proyecto de Ordenación de Montes, mediante la aplicación de estimadores EBLUP (Empirical Best Linear Unbiased Predictor) con modelos a nivel de elemento poblacional e información auxiliar ALS similar a la recopilada por el PNOA. ABSTRACT According to MCPFE (1993) Sustainable Forest Management is “the stewardship and use of forests and forest lands in a way, and at a rate, that maintains their biodiversity, productivity, regeneration capacity, vitality and their potential to fulfill, now and in the future, relevant ecological, economic and social functions, at local, national, and global levels, and that does not cause damage to other ecosystems”. For forest management planning, at any scale, we must determine what situation is hoped to be achieved through management. It is also necessary to know the current situation, as this will mark the starting point and condition the type of actions to be performed in order to meet the desired objectives. Forest management at a local scale is no exception. This Thesis focuses on typical problems of forest management planning at a local scale. The first objective of this Thesis is to determine management objectives for group shelterwood management systems in terms of tree height and tree diameter reference distributions. For this purpose, the conceptual model proposed by García-Abril et al., (1999) is applied to the yield tables for Pinus sylvestris in Sierra de Guadrrama (Rojo y Montero, 1996). The resulting reference distributions will act as a guide in the management of forests treated under the group shelterwood management systems or as an approximated reference for the management of uneven aged forests. Both types of management systems are desirable in those cases where forest biodiversity, stability and multifunctionality are pursued goals. These management systems are also recommended as alternatives for the production of high quality wood. The second objective focuses on the need to adequately characterize the forest during the decision process that leads to local management. In order to obtain estimates of forest variables for different management units of potential interest for forest planning, as well as the associated measures of uncertainty in these estimates, certain results from Small Area Estimation Literature are extended to accommodate for the need of estimates and reliability measures in very small subpopulations containing a reduced number of pixels. A case study shows the potential of Small Area Estimation (SAE) techniques in forest inventories assisted with remotely sensed auxiliary information. The influence of the laser pulse density in the quality of estimates in different aggregation levels is analyzed. This study considers low laser pulse densities (0.5 returns/m2) similar to, those provided by large-scale Airborne Laser Scanner (ALS) surveys, such as the one conducted by the Spanish National Geographic Institute for about 80% of the Spanish territory. The results obtained show that it is possible to improve the efficiency of traditional forest inventories at local scale using EBLUP (Empirical Best Linear Unbiased Predictor) estimators based on unit level models and low density ALS auxiliary information.

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.