992 resultados para forest degradation


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Reducing emissions from deforestation and forest degradation plus (REDD+) encourages economic support for reducing deforestation and conserving or increasing existing forest carbon stocks. The way in which incentives are structured affects trade-offs between local livelihoods, carbon emission reduction, and the cost-effectiveness of a REDD + programme. Looking at first-hand empirical data from 208 farming households in the Bolivian Amazon froma household economy perspective, our study explores two policy options: 1) compensated reduction of emissions fromold-growth forest clearing for agriculture, and 2) direct payments for labour input into sustainable forest anagement combined with a commitment not to clear old-growth forest. Our results indicate that direct payments for sustainable forest management – an approach that focuses on valuing farmers' labour input – can be more cost-effective than compensated reduction and in some cases is themost appropriate choice for achieving improved household incomes, permanence of changes, avoidance of leakages, and community-based institutional enforcement for sustainable forest management.

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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.

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This paper assesses the complex interplay between global Renewable Energy Directives (RED) and the United Nations programme to Reduce Emissions from Deforestation and forest Degradation (REDD). We examine the interaction of the two policies using a scenario approach with a recursive-dynamic global Computable General Equilibrium model. The consequences of a global biofuel directive on worldwide land use, agricultural production, international trade flows, food prices and food security out to 2030 are evaluated with and without a strict global REDD policy. We address a key methodological challenge of how to model the supply of land in the face of restrictions over its availability, as arises under the REDD policy. The paper introduces a flexible land supply function, which allows for large changes in the total potential land availability for agriculture. Our results show that whilst both RED and REDD are designed to reduce emissions, they have opposing impacts on land use. RED policies are found to extend land use whereas the REDD policy leads to an overall reduction in land use and intensification of agriculture. Strict REDD policies to protect forest and woodland lead to higher land prices in all regions. World food prices are slightly higher overall with some significant regional increases, notably in Southern Africa and Indonesia, leading to reductions in food security in these countries. This said, real food prices in 2030 are still lower than the 2010 level, even with the RED and REDD policies in place. Overall this suggests that RED and REDD are feasible from a worldwide perspective, although the results show that there are some regional problems that need to be resolved. The results show that countries directly affected by forest and woodland protection would be the most economically vulnerable when the REDD policy is implemented. The introduction of REDD policies reduces global trade in agricultural products and moves some developing countries to a net importing position for agricultural products. This suggests that the protection of forests and woodlands in these regions reverses their comparative advantage as they move from being land-abundant to land-scarce regions. The full REDD policy setting, however, foresees providing compensation to these countries to cover their economic losses.

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The current scale of deforestation in tropical regions and the large areas of degraded lands now present underscore the urgent need,for interventions to restore biodiversity, ecological functioning, and the supply of goods and ecological services previously used by poor rural communities. Traditional timber plantations have supplied some goods but have made only minor contributions to fulfilling most of these other objectives. New approaches to reforestation are now emerging, with potential for both overcoming forest degradation and addressing rural poverty.

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Through a forest inventory in parts of the Amudarya river delta, Central Asia, we assessed the impact of ongoing forest degradation on the emissions of greenhouse gases (GHG) from soils. Interpretation of aerial photographs from 2001, combined with data on forest inventory in 1990 and field survey in 2003 provided comprehensive information about the extent and changes of the natural tugai riparian forests and tree plantations in the delta. The findings show an average annual deforestation rate of almost 1.3% and an even higher rate of land use change from tugai forests to land with only sparse tree cover. These annual rates of deforestation and forest degradation are higher than the global annual forest loss. By 2003, the tugai forest area had drastically decreased to about 60% compared to an inventory in 1990. Significant differences in soil GHG emissions between forest and agricultural land use underscore the impact of the ongoing land use change on the emission of soil-borne GHGs. The conversion of tugai forests into irrigated croplands will release 2.5 t CO2 equivalents per hectare per year due to elevated emissions of N2O and CH4. This demonstrates that the ongoing transformation of tugai forests into agricultural land-use systems did not only lead to a loss of biodiversity and of a unique ecosystem, but substantially impacts the biosphere-atmosphere exchange of GHG and soil C and N turnover processes.

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Regrowing forests on cleared land is a key strategy to achieve both biodiversity conservation and climate change mitigation globally. Maximizing these co-benefits, however, remains theoretically and technically challenging because of the complex relationship between carbon sequestration and biodiversity in forests, the strong influence of climate variability and landscape position on forest development, the large number of restoration strategies possible, and long time-frames needed to declare success. Through the synthesis of three decades of knowledge on forest dynamics and plant functional traits combined with decision science, we demonstrate that we cannot always maximize carbon sequestration by simply increasing the functional trait diversity of trees planted. The relationships between plant functional diversity, carbon sequestration rates above-ground and in the soil are dependent on climate and landscape positions. We show how to manage ‘identities’ and ‘complementarities’ between plant functional traits in order to achieve systematically maximal co-benefits in various climate and landscape contexts. We provide examples of optimal planting and thinning rules that satisfy this ecological strategy and guide the restoration of forests that are rich in both carbon and plant functional diversity. Our framework provides the first mechanistic approach for generating decision-making rules that can be used to manage forests for multiple objectives, and supports joined carbon credit and biodiversity conservation initiatives, such as Reducing Emissions from Deforestation and forest Degradation REDD+. The decision framework can also be linked to species distribution models and socio-economic models in order to find restoration solutions that maximize simultaneously biodiversity, carbon stocks and other ecosystem services across landscapes. Our study provides the foundation for developing and testing cost-effective and adaptable forest management rules to achieve biodiversity, carbon sequestration and other socio-economic co-benefits under global change.

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Reducing Emissions from Deforestation and Forest Degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) has emerged out of the United Nations Framework Convention on Climate Change (UNFCCC)/Kyoto Protocol negotiations. It is intended to be a mechanism to channel funding (from both public and private sources) for reducing emissions from the forest sector. It is an international climate change policy that relies on national implementation. In order to attract and manage REDD+ investments (both public and private), countries need to decide on their approach to REDD+ implementation through a series of policy choices, and then implement those policy choices through strong legal frameworks. An important question for REDD+ host countries to consider, therefore, is how to develop robust legal structures to facilitate REDD+ implementation. These legal frameworks could be based on existing laws, and/or require new law making.

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Forest certification has been put forward as a means to improve the sustainability of forest management in the tropical countries, where traditional environmental regulation has been inefficient in controlling forest degradation and deforestation. In these countries, the role of communities as managers of the forest resources is rapidly increasing. However, only a fraction of tropical community forests have been certified and little is known about the impacts of certification in these systems. Two areas in Honduras where community-managed forest operations had received FSC certifications were studied. Río Cangrejal represents an area with a longer history of use, whereas Copén is a more recent forest operation. Ecological sustainability was assessed through comparing timber tree regeneration and floristic composition between certified, conventionally managed and natural forests. Data on woody vegetation and environmental conditions was collected within logging gaps and natural treefall gaps. The regeneration success of shade-tolerant timber tree species was lower in certified than in conventionally managed forests in Río Cangrejal. Furthermore, the floristic composition was more natural-like in the conventionally managed than the certified forests. However, the environmental conditions indicated reduced logging disturbance in the certified forests. Data from Copén demonstrated that the regeneration success of light-demanding timber species was higher in the certified than the unlogged forests. In spite of this, the most valuable timber species Swietenia macrophylla was not regenerating successfully in the certified forests, due to rapid gap closure. The results indicate that pre-certification loggings and forest fragmentation may have a stronger impact on forest regeneration than current, certified management practices. The focus in community forests under low-intensive logging should be directed toward landscape connectivity and the restoration of degraded timber species, instead of reducing mechanical logging damage. Such actions are dependent on better recognition of resource rights, and improving the status of small Southern producers in the markets of certified wood products.

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We studied the altitudinal ranging of one habituated group of black-crested gibbons (Nomascus concolor) at Dazhaizi, Mt. Wuliang, Yunnan, China, between March 2005 and April 2006. The group ranged from 1,900 to 2,680 m above sea level. Food distribution was the driving force behind the altitudinal ranging patterns of the study group. They spent 83.2% of their time ranging between 2,100 and 2,400 m, where 75.8% of important food patches occurred. They avoided using the area above 2,500 m despite a lack of human disturbance there, apparently because there were few food resources. Temperature had a limited effect on seasonal altitudinal ranging but probably explained the diel altitudinal ranging of the group, which tended to use the lower zone in the cold morning and the higher zone in the warm afternoon. Grazing goats, the main disturbance, were limited to below 2,100 m, which was defined as the high-disturbance area (HDA). Gibbons spent less time in the HDA and, when ranging there, spent more time feeding and travelling and less time resting and singing. Human activities directly influenced gibbon behaviour, might cause forest degradation and create dispersal barriers between populations. Copyright (C) 2010 S. Karger AG, Basel

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We examined the cost of conserving species as climate changes using Madagascar as an example. We used a Maxent species distribution model to predict the ranges of 74 plant species endemic to the forests of Madagascar from 2000-2080 in three climate scenarios. We set a conservation target of achieving 10,000 hectares of forest cover for each species, and calculated the cost of achieving this target under each climate scenario. We interviewed natural forest restoration project managers and conducted a literature review to obtain the net present cost per hectare of management actions to maintain or establish forest cover. For each species we added hectares of land from lowest to highest cost per additional year of forest cover until the conservation target was achieved throughout the time period. Climate change was predicted to reduce the size of species’ ranges, the overlap between species’ ranges and existing or planned protected areas, and the overlap between species’ ranges and existing forest. As a result, climate change increased the cost of achieving the conservation target by necessitating successively more costly management actions: additional management within existing protected areas (US$0-60/ha), avoidance of forest degradation (loss of biomass) in community-managed areas ($160-576/ha), avoidance of deforestation in unprotected areas ($252-1069/ha), and establishment of forest on non-forested land within protected areas ($802-2710/ha), in community-managed areas ($962-3226/ha), and in unprotected areas ($1054-3719/ha). Our results suggest that though forest restoration may be required for the conservation of some species as climate changes, it is more cost-effective to maintain existing forest wherever possible.

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Ce travail s’inscrit dans le cadre d’un programme de recherches appuyé par le Conseil de recherches en sciences humaines du Canada.

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La situation de la forêt tropicale dans les pays en développement en général, et en République Démocratique du Congo (RDC) en particulier, est inquiétante. Les émissions de dioxyde de carbone dues au déboisement sont de l’ordre de 1,6 GtCO2e/an, soit 17% des émissions mondiales de « gaz à effet de serre ». Sous l’égide de la Convention-cadre des Nations Unies sur les changements climatiques, le REDD+ a été institué pour lutter contre cette déforestation et la dégradation des forêts. Cette étude examine les différentes opportunités qu’offre ce programme pour l’aménagement écosystémique du couvert forestier de la RDC et les obstacles contextuels à sa mise en oeuvre. Pour la RDC, le REDD+ présente un certain nombre d’opportunités : réduction des émissions liées au déboisement et à la dégradation des forêts; amorce des travaux d’afforestation et de reforestation par une gestion durable des ressources conduisant à la création des emplois et favorisant la croissance des PIB et des exports; accroissement du rendement et maintien d’une plus grande couverture des besoins alimentaires. Le REDD+ peut favoriser la croissance du Produit intérieur brut agricole. Il peut contribuer à l’électrification des ménages et réduire de moitié les dépenses des ménages dépendant de l’exploitation minière et des hydrocarbures et, ainsi, générer des milliers d’emplois en infrastructures. Pour les populations locales et autochtones, il peut contribuer aussi à protéger et à valoriser les cultures liées à la forêt. Mais, face aux pesanteurs d’ordre juridique, politique, social, économique, technologique et culturel caractéristiques de ce pays, ces opportunités risquent d’être amenuisées, sinon annihilées. Étant donné que l’essentiel du déploiement du dispositif du REDD+ se réalisera dans les zones rurales congolaises, l’obstacle majeur reste le droit coutumier. La solution serait d’harmoniser les exigences et finalités du REDD+ non seulement avec le Code forestier de 2002 et ses mesures d’exécution mais aussi avec le droit coutumier auquel les communautés locales et autochtones s’identifient.