Adriano José Nogueira Lima

Projeção da dinâmica da floresta natural de Terra-firme, região de Manaus-AM, com o uso da cadeia de transição probabilística de Markov

Os fatores que envolvem os processos da dinâmica da floresta influenciam a sua biodiversidade e, portanto, a qualidade da floresta. A definicao de estrategias que envolve a protecao e o uso adequado da floresta manejada e a recuperacao de areas ja degradadas tornam-se possivel com o estudo da estrutura e dinâmica da floresta primaria por meio de informacoes como a mortalidade, o recrutamento e a permanencia das arvores no sistema florestal. Este trabalho teve como objetivo avaliar a dinâmica de uma floresta nao perturbada e fazer projecoes da dinâmica florestal usando a matriz de transicao probabilistica (Cadeia de Markov). As taxas de recrutamento, mortalidade e incremento foram determinadas a partir de inventarios florestais realizados em dois transectos, nos sentidos Norte-Sul e Leste-Oeste (20 x 2500 m cada, totalizando 10 ha), localizados no km 50 da BR 174, na estrada vicinal ZF-2, Manaus/AM, nos anos de 2000 e 2004. A floresta acumulou 8,34 t.ha-1.ano-1 de biomassa fresca acima do solo. De acordo com projecao para 2008, o numero total de arvores diminuira em 2,67% (de 5987 individuos (2004) para 5827 (2008)) e a mortalidade sera 15% maior (de 264 (2004) para 311 (2008)). O teste Qui-quadrado mostrou que nao ha diferenca significativa (1% de probabilidade) entre as informacoes coletadas e projetadas. Esses resultados permitem concluir que a Cadeia de Markov e um eficiente instrumento para projetar a dinâmica da floresta natural, contribuindo para o planejamento em curto prazo das atividades que utilizam os recursos florestais.

Overview of Forest Carbon Stocks Study in Amazonas State, Brazil

Tropical forests, specially the Amazon, are important ecosystems in research on the effects of climate change on biological systems and their functioning. The main relationship between the forest and the climate is the carbon fluxes and stock. Although carbon stock estimates of tropical forests are an issue and still raise many uncertainties. This study aims to present the main literature references and the huge effort to sample the forests of Central Amazon. Many attempts to estimate the carbon stock of the Amazon rainforest resulted in high uncertainties due to sampling and allometric constrains. After developing an allometric equation, based on destructive method and adapted to each different site based on dominant height, sampling over 1800 plots in primary and selectively logged non-flooded forests, across the State of Amazonas, the estimated average of total (tree’s above- and below-ground) carbon stock is 159.8 ± 9.2 Mg C ha−1.

Relating Amazon forest biomass to PolInSAR extracted features

The combination of polarimetric SAR (PolSAR) with the interferometry capability (InSAR) enables the extraction of new features that enhances the development of biomass estimation models. This work aims in demonstrating the importance of the simultaneous use of several types of SAR features for estimating forest biomass. The study site is São Gabriel da Cachoeira, located in the Brazilian Amazon. Forest inventory was conducted by INPA and a sample of 29 plots have been used to compute above and below-ground biomass. Polarimetric interferometric X and P band SAR data (PolInSAR) were acquired by the DSGs Amazon Radiography Project. After the initial analysis of the data and feature extraction, analyses on the relationship between biomass and SAR features have been done. Only 4 out of the 122 features extracted presented a significant correlation with biomass and each of them were related to a structural characteristic of the forest.