Current Regulating and Supporting Services: Nutrient Cycles

The study forest regulates nutrient cycles as a supporting ecosystem service mainly via retention in the biosphere and the soil organic layer. How tight the nutrient cycles are depends on environmental conditions. In this chapter, we focus on the roles of (1) deposition from the atmosphere, (2) soil moisture regime, and (3) conversion to pasture in the nutrient cycle. Between 1998 and 2010, there were a seasonal deposition of salpetric acid, an episodic deposition of Ca and Mg from Sahara dusts, and a continuous increase in reactive N inputs related to Amazonian forest fires, the El Niño Southern Oscillation cycle, and the economic development, respectively. Simultaneously, soils became increasingly drier enhancing nutrient release by mineralization. An increasing number of rain storms could considerably increase the export of N and base metals (K, Ca, Mg) via fast surface-near lateral transport in soil. Land-use change from forest to pasture introduces alkaline ashes and grass-derived organic matter. The resulting increases in soil pH and nutrient and substrate supply increase nutrient cycling rates because of enhanced microbial activity.

Protecting Tropical Forests through Public Procurement of Emission Reductions

The rate of destruction of tropical forests continues to accelerate at an alarming rate contributing to an important fraction of overall greenhouse gas emissions. In recent years, much hope has been vested in the emerging REDD+ framework under the UN Framework Convention on Climate Change (UNFCCC), which aims at creating an international incentive system to reduce emissions from deforestation and forest degradation. This paper argues that in the absence of an international consensus on the design of results-based payments, “bottom-up” initiatives should take the lead and explore new avenues. It suggests that a call for tender for REDD+ credits might both assist in leveraging private investments and spending scarce public funds in a cost-efficient manner. The paper discusses the pros and cons of results-based approaches, provides an overview of the goals and principles that govern public procurement and discusses their relevance for the purchase of REDD+ credits, in particular within the ambit of the European Union.

Do relocated villages experience more forest cover change? Resettlements, shifting cultivation and forests in the Lao PDR

This study explores the relationships between forest cover change and the village resettlement and land planning policies implemented in Laos, which have led to the relocation of remote and dispersed populations into clustered villages with easier access to state services and market facilities. We used the Global Forest Cover Change (2000–2012) and the most recent Lao Agricultural Census (2011) datasets to assess forest cover change in resettled and non-resettled villages throughout the country. We also reviewed a set of six case studies and performed an original case study in two villages of Luang Prabang province with 55 households, inquiring about relocation, land losses and intensification options. Our results show that resettled villages have greater baseline forest cover and total forest loss than most villages in Laos but not significant forest loss relative to that baseline. Resettled villages are consistently associated with forested areas, minority groups, and intermediate accessibility. The case studies highlight that resettlement coupled with land use planning does not necessarily lead to the abandonment of shifting cultivation or affect forest loss but lead to a re-spatialization of land use. This includes clustering of forest clearings, which might lead to fallow shortening and land degradation while limited intensification options exist in the resettled villages. This study provides a contribution to studying relationships between migration, forest cover change, livelihood strategies, land governance and agricultural practices in tropical forest environments.

Detection of convergent genome-wide signals of adaptation to tropical forests in humans

Tropical forests are believed to be very harsh environments for human life. It is unclear whether human beings would have ever subsisted in those environments without external resources. It is therefore possible that humans have developed recent biological adaptations in response to specific selective pressures to cope with this challenge. To understand such biological adaptations we analyzed genome-wide SNP data under a Bayesian statistics framework, looking for outlier markers with an overly large extent of differentiation between populations living in a tropical forest, as compared to genetically related populations living outside the forest in Africa and the Americas. The most significant positive selection signals were found in genes related to lipid metabolism, the immune system, body development, and RNA Polymerase III transcription initiation. The results are discussed in the light of putative tropical forest selective pressures, namely food scarcity, high prevalence of pathogens, difficulty to move, and inefficient thermoregulation. Agreement between our results and previous studies on the pygmy phenotype, a putative prototype of forest adaptation, were found, suggesting that a few genetic regions previously described as associated with short stature may be evolving under similar positive selection in Africa and the Americas. In general, convergent evolution was less pervasive than local adaptation in one single continent, suggesting that Africans and Amerindians may have followed different routes to adapt to similar environmental selective pressures.

Herbivores limit the population size of big-leaf mahogany trees in an Amazonian forest

The Janzen–Connell hypothesis proposes that specialized herbivores maintain high numbers of tree species in tropical forests by restricting adult recruitment so that host populations remain at low densities. We tested this prediction for the large timber tree species, Swietenia macrophylla, whose seeds and seedlings are preyed upon by small mammals and a host-specific moth caterpillar Steniscadia poliophaea, respectively. At a primary forest site, experimental seed additions to gaps – canopy-disturbed areas that enhance seedling growth into saplings – over three years revealed lower survival and seedling recruitment closer to conspecific trees and in higher basal area neighborhoods, as well as reduced subsequent seedling survival and height growth. When we included these Janzen–Connell effects in a spatially explicit individual-based population model, the caterpillar's impact was critical to limiting Swietenia's adult tree density, with a > 10-fold reduction estimated at 300 years. Our research demonstrates the crucial but oft-ignored linkage between Janzen–Connell effects on offspring and population-level consequences for a long-lived, potentially dominant tree species.

Avian species identity and predation success in tropical cacao agroforestry of the Napu Valley in Central Sulawesi, Indonesia

Avian ecosystem services such as the suppression of pests are considered being of high ecological and economic importance in a range of ecosystems, especially in tropical agroforestry. But how bird predation success is related to the diversity and composition of the bird community, as well as local and landscape factors, is poorly understood. The author quantified arthropod predation in relation to the identity and diversity of insectivorous birds, using experimental exposure of artificial, caterpillar-like prey on smallholder cacao agroforestry systems, differing in local shade management and distance to primary forest. The bird community was assessed using both mist netting (targeting on active understory insectivores) and point count (higher completeness of species inventories) sampling. The study was conducted in a land use dominated area in Central Sulawesi, Indonesia, adjacent to the Lore Lindu National Park. We selected 15 smallholder cacao plantations as sites for bird and bat exclosure experiments in March 2010. Until July 2011, we recorded several data in this study area, including the bird community data, cacao tree data and bird predation experiments that are presented here. We found that avian predation success can be driven by single and abundant insectivorous species, rather than by overall bird species richness. Forest proximity was important for enhancing the density of this key species, but did also promote bird species richness. The availability of local shade trees had no effects on the local bird community or avian predation success. Our findings are both of economical as well as ecological interest because the conservation of nearby forest remnants will likely benefit human needs and biodiversity conservation alike.

Bird observation and sampling in tropical agroforestry landscapes of the Napu Valley in Central Sulawesi, Indonesia

We investigated the local bird community in Central Sulawesi (Indonesia), with focus on insectivorous species in the agroforestry landscapes adjacent to the Lore Lindu National Park. All study sites were situated at the northern tip of Napu Valley in Central Sulawesi, Indonesia. After an initial mapping of the study area, we selected 15 smallholder cacao plantations as sites for our study in March 2010. These sides were mainly used for bird and bat exclosure experiments. All sited were situated along a local gradient (shade availability on each plantation) and a landscape gradient (distance to primary forest), which were independent from each other. In September 2010 and from February until June 2011, we assessed the bird community on our 15 study sites using monthly point count and mist netting sampling. Point count (20 minutes between 07 am and 10 am and in between the net checking hours) and mist netting surveys (12 hours, between 05:30 am and 17:30 pm) were conducted simultaneously but only once per month on each study site, to avoid habituation of the local bird community to our surveys. Further, point counts were conducted at least 100 m apart from the mist netting sites, to avoid potential disturbance between the two methods. We discarded all observations beyond 50 m (including those individuals that flew over the canopy) from the statistical analysis, as well as recaptures of individuals within identical mist netting rounds.

Major ion concentrations in rain water and atmospheric moisture above the Atlantic Ocean

Concentratios of Cl-, Mg2+, Ca2+, and HCO3- ions were studied in rain waters and condensed atmospheric moisture above the Atlantic Ocean. Maximal number of samples was collected in the eastern tropical North Atlantic. Concentration of chloride ions ranged from 1 to 28 mg/l in rain waters (average 4.3 mg/l) and ranged from 0.3 to 2 mg/l in condensed atmospheric moisture with the average about one order of magnitude less than that for rain waters. Chloride normalized concentrations of magnesium and calcium are greater in rain waters and condensed atmospheric moisture than in ocean water due to more intensive subtraction of these ions as compared to chloride ions. Chloride normalized HCO3- concentration is one order of magnitude greater in atmospheric moisture than in seawater, possibly because of volatile component CO2 taking part in exchange between the ocean and the atmosphere.

Forest Hydrology, Soil Conservation and Green Barriers in Canary Islands

In volcanic islands, the rainfall regime and its torrential nature, together with the steep slopes and the soil types present are considered to be some of the main factors affecting forest hydrology and soil conservation. In such environments, rain regime is generally irregular and characterized by short and intense rainfalls, which could cause destructive flows at times, followed by long periods of rain absence. The volcanic nature of these islands have as a direct resultant steep slopes which influences the runoff volume and speed, as well as the amount of topsoil susceptible to be detached and transported downstream. The soil type also affects the susceptibility to erosion processes. Andisols are the most typical soil on volcanic islands. Their particularities derive their mineral constituents, called short-range-order products, which provide these soils with an increased structural stability, which in turn reduces their susceptibility to erosion. However, the land use changes and the environmental factors such as rain regime and steep slopes may be determinant factor in destabilizing these soils and ultimately a cause for soil erosion and runoffs, which become a threat to the population downstream. Green barriers have been traditionally used to prevent or reduce these processes, also to enhance the dew effect and the fog water collection, and as a firebreak which acts as a barrier to slow or stop the progress of a wildfire. Wooded species present and subsequently their performance have a major influence on their effectiveness. The use of this natural erosion and fire control methods on volcanic islands is discussed in this paper.

Forest Biodiversity Assessment in Peruvian Andean Montane Cloud Forest

Cloud forests are unusual and fragile habitats, being one of the least studied and least understood ecosystems. The tropical Andean dominion is considered one of the most significant places in the world as rega rds biological diversity, with a very high level of endemism. The biodiversity was analysed in an isolated remnant area of a tropical montane cloud forest known as the ?Bosque de Neblina de Cuyas?, in the North of the Peruvian Andean range. Composition, structure and dead wood were measured or estimated. The values obtained were compared with other cloud forests. The study revealed a high level of forest biodiversity, although the level of biodiversity differs from one area to another: in the inner areas, where human pressure is almost inexistent, the biodiversity values increase. The high species richness and the low dominance among species bear testimony to this montane cloud forest as a real enclave of biodiversity.

Tree height integrated into pantropical forest biomass estimates

Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- andWeibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (?40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8Mgha?1 (range 6.6 to 112.4) to 8.0Mgha?1 (?2.5 to 23.0). For all plots, aboveground live biomass was ?52.2 Mgha?1 (?82.0 to ?20.3 bootstrapped 95%CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in eastcentral Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 PgC (31?39 bootstrapped 95%CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

Amazonian white-sand forest: a black future?

Los bosques sobre arena blanca amazónicos son un tipo singular y frágil de bosque tropical húmedo de selva de zonas bajas, que aparecen dispersos sobre teselas de suelo muy oligotrófico y albergan un alto porcentaje de endemismos. No son susceptibles de aprovechamiento maderero ni de uso agrícola, pero su madera redonda de pequeño diámetro (5-15 cm) posee gran durabilidad y es un recurso extraído tradicionalmente por los pobladores locales para construir sus viviendas. A pesar de ello, este aprovechamiento local permanece invisible para la reglamentación forestal, lo que puede perjudicar el futuro de estos bosques sobre arena blanca. Este trabajo tiene por objetivo aportar conocimientos básicos sobre la estructura forestal y la composición florística de estos bosques, lo que es esencial para poder planificar un gestión sustentable. Los resultados muestran que, a pesar de su fragilidad, los bosques sobre arena blanca también presentan ciertas ventajas en vista de sus posibilidades de gestión sustentable en comparación con otro tipo de bosques tropicales húmedos: debido a un alto porcentaje de especies comerciales (26 %), a la clara dominancia de un pequeño grupo de especies, la mayoría de ellas (67%) con interés comercial y al hecho de que los fustes potencialmente aprovechables sólo suponen el 17% del área basimétrica total, resulta que en la situación actual, no es necesario aplicar técnicas de aprovechamiento de impacto reducido, puesto que los pies aprovechados son de pequeño diámetro, que no se utiliza maquinaria y que el transporte se realiza únicamente a hombros y/o por flotación

Analysing trade-offs between food production and ecosystem services in tropical forests of lowland Bolivia

The expansion of agricultural land is responsible for most tropical deforestation. Historically, smallholder farming and shifting cultivation has been reported as the main agent of deforestation. However, the increasing global demand for food in recent years has greatly boosted the development of medium and large-scale commercial agriculture which is nowadays causing the majority of tropical forest cover loss, particularly in Latin America.

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.