ABSTRACT Research that aims to quantify the carbon stock in riparian forests underscores the environmental services of these forests to minimize the effects of climate change. The objective of this work was to i) quantify the carbon stock present in the above-ground biomass of the species present in areas of riparian forest and ii) rank species by the expanded importance value index (IVIA) in relation to a standard phytosociological analysis by the importance value index (IVI). The data used in the study were taken from an inventory conducted in areas of riparian vegetation in the southwestern region of the state of Goiás. The wood biomass of each tree was estimated for all species, with a later estimate of carbon stock (Mg.ha-1) per hectare in the phytophysiognomy. The riparian forest has a high capacity to store carbon. Incorporation of this variable and ranking of species by the expanded importance index can be a reason to conserve and preserve riparian forests, as well as a criterion in the choice of species with greater potential to stock carbon for the recovery of degraded areas.

RESUMO Pesquisas que quantificam o estoque de carbono em matas ciliares destacam-se pela apresentação de serviços ambientais que essas florestas oferecem e assim minimizam os efeitos das mudanças climáticas. Objetivou-se com a realização deste trabalho: i) quantificar o estoque de carbono presente na biomassa acima do solo das espécies presentes em áreas de mata ciliar; ii) ranquear as espécies pelo índice de valor de importância ampliado (IVIA) em relação à análise fitossociológica padrão, pelo índice de valor de importância (IVI). Os dados utilizados no estudo foram obtidos a partir de um inventário realizado em áreas de vegetação ripária, região sudoeste do estado de Goiás. Estimou-se a biomassa da madeira de cada árvore para todas as espécies e posteriormente a estimativa de estoque de carbono (Mg.ha-1) por hectare na fitofisionomia. A mata ciliar possui alta capacidade de estocar carbono e a incorporação dessa variável e o ranqueamento das espécies pelo índice de importância ampliado pode ser utilizado como razão para conservação e preservação das matas ciliares, bem como um critério na escolha de espécies com maior potencial de estoque de carbono para recuperação de áreas degradadas.

ABSTRACT In eucalyptus plantations, the presence of understory increases the risk of fires, acts as an obstacle to forest operations, and leads to yield losses due to competition. The objective of this study was to develop an approach to discriminate the presence or absence of understory in eucalyptus plantations based on airborne laser scanning surveys. The bimodal canopy height profile was modeled by two Weibull density functions: one to model the canopy, and other to model the understory. The parameters used as predictor in the logistic model successfully discriminated the presence or absence of understory. The logistic model composed by ℽ canopy, ℽ understory, and ℽ understory showed higher values of accuracy (0.96) and kappa (0.92), which means an adequate classification of presence of understory and absence of understory. Weibull parameters could be used as input in the logistic regression to effectively identify the presence and absence of understory in eucalyptus plantation.

ABSTRACT The objective of this study was to model the potential effect of future climate change on the distribution of a tree species indicator of Cerrado. For the modeling, we used 488 occurrence points of the species and also bioclimatic variables corresponding to 2050 and 2070, for the more optimistic and pessimistic scenarios. All generated models were classified as consistent, getting an area under curve higher than 0.90. The current modeling of Connarus suberosus showed that 88% of the area with a high probability of species occurrence is inside the Cerrado domain. Future projections suggest losses in the environmental suitability area around 40.8% and 44.8% in the optimistic scenario, 61.6% and 81.6% in the pessimistic scenario considering 2050 and 2070, respectively. Furthermore, we found a tendency of the C. suberosus to move in the Atlantic Forest direction. This modeling is an alert that the C. suberosus will suffer from future climate change.

RESUMO São poucos os estudos dedicados a entender a criação de modelo digital de terreno (MDT) para florestas amazônicas. O MDT tem uma importante função quando o escaneamento laser aerotransportado é usado para estimar a biomassa da vegetação. Examinamos a relação da densidade de pulsos, resolução espacial, algoritmos de filtragem, densidade da vegetação e inclinação do terreno com a qualidade do MDT. Três áreas de floresta amazônica foram sobrevoadas usando LiDAR aerotransportado. Cada nuvem de dados original teve sua densidade reduzida objetivando 20; 15; 10; 8; 6; 4; 2; 1; 0,75; 0,5 e 0,25 pulsos por metro quadrado, utilizando um processo de reamostragem aleatória. Os MDTs das nuvens reamostradas foram comparados com o MDT de referência, produzido a partir da nuvem original, calculando o desvio pixel a pixel e resumindo-o por meio do erro padrão da estimativa (RMSE). Os MDTs das nuvens reamostradas também foram avaliados quanto ao nível de correspondência com o MDT de referência. Houve uma clara compensação entre densidade de pontos e resolução horizontal. Dosséis mais densos exigem uma maior densidade de retornos, ou MDT com menor resolução.

ABSTRACT Very few studies have been devoted to understanding the digital terrain model (DTM) creation for Amazon forests. DTM has a special and important role when airborne laser scanning is used to estimate vegetation biomass. We examined the influence of pulse density, spatial resolution, filter algorithms, vegetation density and slope on the DTM quality. Three Amazonian forested areas were surveyed with airborne laser scanning, and each original point cloud was reduced targeting to 20, 15, 10, 8, 6, 4, 2, 1, 0.75, 0.5 and 0.25 pulses per square meter based on a random resampling process. The DTM from resampled clouds was compared with the reference DTM produced from the original LiDAR data by calculating the deviation pixel by pixel and summarizing it through the root mean square error (RMSE). The DTM from resampled clouds were also evaluated considering the level of agreement with the reference DTM. Our study showed a clear trade-off between the return density and the horizontal resolution. Higher forest canopy density demanded higher return density or lower DTM resolution.