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.

Molecular survey and genetic characterization of tick-borne pathogens in dogs in metropolitan Recife (north-eastern Brazil).

To identify DNA of the main tick-borne pathogens in dogs from Recife (Brazil), polymerase chain reactions were carried out on blood samples of dogs treated at the Veterinary Hospital of the Universidade Federal Rural de Pernambuco from March 2007 to June 2008. The detection of DNA was performed using specific primers. Amplicons were analyzed through electrophoresis and sequencing. A phylogenetic tree was constructed using the UPGMA method, revealing that the sequences were closely related to those of strains from other geographic regions. Among the 205 blood samples analyzed, 48.78% was positive for Anaplasma platys; 38.04% was positive for Ehrlichia canis; 7.31% was positive for Babesia canis vogeli; and 0.49% was positive for Hepatozoon canis and Mycoplasma haemocanis. Coinfection of two or three pathogens was found in 23.9% (49/205) of the dogs. The subspecies B. canis vogeli was identified. Infection by H. canis and M. haemocanis is reported for the first time in dogs in the state of Pernambuco (Brazil). The data indicate that the main tick-borne pathogens in dogs in this region are E. canis and/or A. platys, followed by B. canis vogeli.

Searching for novel targets to control wheat Head Blight Disease-I-Protein identification, 3D modeling and virtual screening.

2016