Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.

Soil carbon sequestration in grass and grass-legume pastures in the western Brazilian Amazon.

Land use change from native forests to pastures in the tropics have impact on global carbon (C) cycle through increased rates of C emissions to the atmosphere and the loss of above- and belowground C accumulation and storage capacity (SILVER et al., 2000). This study was conducted to determine the carbon stock in a Ultisol under a pure Brachiaria humidicola (Rendle) Scheick pasture and a mixed pasture of B. humidicola and Arachis pintoi Krapov. & W. C. Greg cv. BRS Mandobi, both without fertilization.

Carbon sequestration associated to the land-use and land-cover changes in the forestry sector in Southern Brazil.

We studied the Paraíba do Sul river watershed , São Paulo state (PSWSP), Southeastern Brazil, in order to assess the land use and cover (LULC) and their implication s to the amount of carbon (C) stored in the forest cover between the years 1985 and 2015. Th e region covers a n area of 1,395,975 ha . We used images made by the Operational Land Imager (OLI) sensor (OLI/Landsat - 8) to produce mappings , and image segmentation techniques to produce vectors with homogeneous characteristics. The training samples and the samples used for classification and validation were collected from the segmented image. To quantify the C stocked in aboveground live biomass (AGLB) , we used an indirect method and applied literature - based reference values. The recovery of 205,690 ha of a secondary Native Forest (NF) after 1985 sequestered 9.7 Tg (Teragram) of C . Considering the whole NF area (455,232 ha), the amount of C accumulated al ong the whole watershed was 3 5 .5 Tg , and the whole Eucalyptus crop (EU) area (113,600 ha) sequester ed 4. 4 Tg of C. Thus, the total amount of C sequestered in the whole watershed (NF + EU) was 3 9 . 9 Tg of C or 1 45 . 6 Tg of CO 2 , and the NF areas were responsible for the large st C stock at the watershed (8 9 %). Therefore , the increase of the NF cover contribut es positively to the reduction of CO 2 concentration in the atmosphere, and Reducing Emissions from Deforestation and Forest Degradation (REDD + ) may become one of the most promising compensation mechanisms for the farmers who increased forest cover at their farms.