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Forests contribute substantially to maintaining the global greenhouse gas balance, primarily because among the five economic sectors identified by the United Nations Framework Convention on Climate Change, only the forestry sector has the potential to remove greenhouse gas emissions from the atmosphere. In this context, development of national forest carbon accounting systems, particularly in countries with tropical forests, has emerged as an international priority. Because these systems are often developed as components of or in parallel with national forest inventories, a brief review of statistical issues related to the development of forest ground sampling designs is provided. This overview addresses not only the primary issues of plot configurations and sampling designs, but also to a lesser extent the emerging roles of remote sensing and uncertainty assessment. Basic inventory principles are illustrated for two case studies, the national forest inventory of Brazil with special emphasis on the state of Santa Catarina, and an inventory for Tanzania

The strategic importance of forest resources, both at the national and global level, as well as the scarcity of reliable qualitative and quantitative information about Brazilian forests are among the motivations that led to the implementation of a new national forest inventory in Brazil (IFN-BR). Beyond traditional field survey through clustered sampling, the IFN-BR incorporates Landscape Sample Units (LSU) as a geospatial component of the inventory. Landscape indicators and indices are generated through the analysis of land use/land cover in the LSUs, which provide information about composition, morphology, mosaic patterns, adjacent habitat similarity, connectivity, fragmentation, and state of riparian zones. In the current study, we describe the indicators selected to assess landscape using pilot LSUs established in Paraná State, as well as the calculation and composition of indices and scores.

Allometric models embedding independent variables such as diameter at breast height (d) and total height (h) are useful tools to predict the biomass of individual trees. Models for tropical forests are often constructed based on datasets composed of species with different morphological features and architectural models. It is reasonable to expect, however, that species-specific models may reduce uncertainties in biomass predictions, especially for palms, tree ferns, and trees with peculiar morphological features, such as stilt roots and hollow trunks. In this sense, three species with wide geographical distribution in the Brazilian Atlantic Forest were sampled, namely Euterpe edulis Mart., Cyathea delgadii Sternb., and Cecropia glaziovii Snethl., with the aim to (i) quantify their aboveground biomass (AGB), (ii) evaluate the AGB distribution in different plant compartments, (iii) fit species-specific models for predicting AGB at the individual level, and (iv) assess the performance of specific and generic models available in the literature to predict the AGB of individuals of these species. The compartment stem represented, on average, ∼74% of the total AGB of E. edulis individuals; in turn, the caudex compartment of C. delgadii represented, on average, ∼87% of the total AGB, while the trunk compartment of C. glaziovii represented, on average, ∼74%. Among the fitted models, the power model [Formula: see text] showed the best performance for E. edulis and C. delgadii. In turn, the asymptotic logistic model [Formula: see text], where dc is the diameter above the upper stilt root, presented the best performance for C. glaziovii. The variable h appeared as the most important predictor of AGB of E. edulis and C. delgadii; in contrast, the stem and caudex mean basic specific gravities were not suitable predictors. The fitted species-specific models outperformed the specific and generic models selected from the literature. They may, therefore, contribute to the reduction of uncertainties in AGB estimates. In addition, the results support evidence that specific models may be necessary for species with different growth forms and (or) peculiar morphological features, especially those with great abundance and wide geographic distribution.

Neste estudo foram utilizados dados de 42 planos de manejo florestal (PMF), protocolados no Instituto Estadual de Florestas no período de 1992 a 1998, com o objetivo de realizar a análise documental através de indicadores e verificadores de sustentabilidade de fácil aplicação, pertencentes à estrutura básica de um plano de manejo, conforme normas legais vigentes no Estado de Minas Gerais. Portanto, inicialmente fez-se a padronização de procedimentos referentes a todas as etapas de um PMF, tendo como base as exigências legais do Estado, de onde se originou a lista de checagem (check list) e, conseqüentemente, os indicadores e verificadores utilizados na análise documental dos PMF. Constatou-se que a ausência de um roteiro básico para elaboração dos PMF compromete a análise documental prévia para protocolo institucional e que houve deficiência institucional na análise documental e técnica dos planos de manejo. Os itens constantes dos PMF que apresentaram menor porcentagem de atendimento foram os que exigiram mais conhecimentos técnicos (análise de impacto ambiental, sistema silvicultural e bibliografia), enquanto os descritivos foram os que apresentaram maior porcentagem de atendimento e os que exigiram menos conhecimentos técnicos (objetivos e justificativas, informações gerais e discriminação de áreas da propriedade). Os indicadores e verificadores mostraram-se eficientes e de fácil aplicação nas análises documental e técnica dos planos de manejo estudados. A análise prévia documental, fundamentada em um roteiro básico elaborado neste estudo, reprovou todos os planos de manejo. É necessário padronizar e informatizar os procedimentos de análises documental e técnica para aprovação dos planos de manejo. O nível de exploração florestal, em área basal, de todos os planos de manejo analisados ultrapassou o limite máximo de intervenção permitido por lei.