Bamboo overabundance alters forest structure and dynamics in the Atlantic Forest hotspot

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Reproductive modes in frogs and their unexpected diversity in the Atlantic forest of Brazil

Amphibians, and especially the anurans (frogs and toads), exhibit a greater diversity of reproductive modes than other tetrapod vertebrates. Twenty-nine reproductive modes have been recognized for the anurans; we propose 10 more, elevating by more than 34% the number of reproductive modes known for anurans worldwide. These newly recognized reproductive modes for the frogs elevate by almost 48% the number of anuran reproductive modes known for the Neotropics. The highly complex topography of the Atlantic forest, breaking up the biome into many small microhabitats, and the high humidity, which reduces desiccation risks, have enabled the evolution of reproductive specializations such as eggs or tadpoles that develop out of water. Nearly 90% of the Atlantic forest has been cleared, and because several anurans are endemic to this region or have specialized reproductive modes dependent on the forest, this partly explains the generalized population declines and large numbers of species that have disappeared in the last few decades. © 2005 American Institute of Biological Sciences.

New karyologycal data and cytotaxonomic considerations on small mammals from Santa Virginia (Parque Estadual da Serra do Mar, Atlantic Forest, Brazil)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The contribution of multiple use forest management to small farmers' annual incomes in the Eastern Amazon

Small-scale farmers in the Brazilian Amazon collectively hold tenure over more than 12 million ha of permanent forest reserves, as required by the Forest Code. The trade-off between forest conservation and other land uses entails opportunity costs for them and for the country, which have not been sufficiently studied. We assessed the potential income generated by multiple use forest management for farmers and compared it to the income potentially derived from six other agricultural land uses. Income from the forest was from (i) logging, carried out by a logging company in partnership with farmers' associations; and (ii) harvesting the seeds of Carapa guianensis (local name andiroba) for the production of oil. We then compared the income generated by multiple-use forest management with the income from different types of agrarian systems. According to our calculations in this study, the mean annual economic benefits from multiple forest use are the same as the least productive agrarian system, but only 25% of the annual income generated by the most productive system. Although the income generated by logging may be considered low when calculated on an annual basis and compared to incomes generated by agriculture, the one-time payment after logging is significant (US$5,800 to US$33,508) and could be used to implement more intensive and productive cropping systems such as planting black pepper. The income from forest management could also be used to establish permanent fields in deforested areas for highly productive annual crops using conservation agriculture techniques. These techniques are alternatives to the traditional land use based on periodic clearing of the forest. Nevertheless, the shift in current practices towards adoption of more sustainable conservation agriculture techniques will also require the technical and legal support of the State to help small farmers apply these alternatives, which aim to integrate forest management in sustainable agricultural production systems.

Bamboo overabundance alters forest structure and dynamics in the Atlantic Forest hotspot

With fast growth rates and clonal reproduction, bamboos can rapidly invade forest areas, drastically changing their original structure. In the Brazilian Atlantic Forest, where recent mapping efforts have shown that woody bamboos dominate large areas, the present study assessed the differences in soil and vegetation between plots dominated (>90% of bamboo coverage) and not dominated (<10% of coverage) by the native Guadua tagoara. Surface soil was physically and chemically analyzed, and trees at three size classes (seedling, sapling, and adult) were counted, identified and measured. New inventories were conducted to assess recruitment, mortality, and damage rates. Bamboo plots had more fertile soils (higher bases saturation and lower potential acidity) due to the preferential occurrence of G. tagoara on more clayey soils. Bamboo-dominated plots had lower density of adult trees (diameter >5 cm) and lower species density. In addition, overall tree diameter distribution was very different between environments, with bamboo plots having greater concentration of small-sized trees. Such differences are probably related to the general tendency of higher mortality, recruitment, and damage rates in bamboo plots. Greater physical (wind and bamboo-induced damages) and physiological stress (heat and light) in bamboo plots are probable causes of bamboo-dominated plots being more dynamic. Finally, we discuss the differences between Atlantic and Amazonian Guadua-dominated forests, causes, and possible consequences of bamboo overabundance to the Atlantic Forest conservation. (C) 2012 Elsevier Ltd. All rights reserved.

Impacts of Trade in Non-timber Forest Products on Cooperation among Caboclo Households of the Brazilian Amazon

Trade in non-timber forest products (NTFPs) has been touted as promoting forest conservation and enhancing the well-being of local residents through increased cash income, which is considered a positive outcome. However, research on cooperation has demonstrated that increased market access and income may strengthen or weaken cooperation. Because cooperation is essential for community resilience in small-scale societies, negative effects on people's well-being can be expected if increased NTFP trade reduces cooperation. To evaluate whether NTFP trade affected cooperation, we used household data (survey and systematic observations) to compare the frequency of cooperation in two communities of Brazilian Amazon Caboclos, one of which engaged in NTFP trade, while the other did not. Cooperation was less frequent in the community trading NTFPs, but neither household cash income nor household participation in NTFP exploitation was associated with cooperative behavior. Decreased frequency most likely derived from indirect effects of NTFP trade, such as less time to fish or socialize, or other outcomes observable only at the community level, such as income inequality, the influx of new residents and consequent population growth. Our results indicate that conservation and development projects based on NTFP trade may negatively impact social and economic well-being of local communities.

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.

Natural old-growth forest stands in Maine and its relevance to the Critical Areas Program : a report /

"October 1983."

An assessment of need for the Illinois Forest Legacy Program.

Cover title.

Preparing for the future : Forest Service research natural areas.

"FS-503."

Forest Service video library catalog.

Includes index.

Pathogens and microbial control of North American forest insect pests /

"August 1998" -- Cover.

Forest Legacy Program national report for 2001.

"January 2002."

10 things you never knew about the USDA Forest Service /

"April 2003"--P. [23].

The Division of Forestry in the California conservation camp program.

Mode of access: Internet.