Assessment of microbial diversity associated with CH4 emission from sugarcane vinasse storage and transportation systems.

Sugarcane bioethanol has favorable energy and greenhouse gas balance, although the production process generates several residues including vinasse, which deserves attention because of its significant methane (CH4) emission during storage and transportation stages. Considering that CH4 emissions are dependent on the structure and abundance of microbial communities, we hypothesized that different vinasse transportation systems would harbor different microbial community composition, resulting in distinct CH4 patterns. To test this hypothesis, we used high-throughput 16S rRNA sequencing with real-time PCR to evaluate the composition and abundance of microorganisms in the two main systems of vinasse storage and transportation (i.e. open channels and tanks systems) in Brazil. Our results showed higher microbial diversity and CH4 emissions in channel system, especially in the uncoated section. Significant differences in microbial community structure, diversity, and abundance between the uncoated/coated open channel and tanks indicated a clear selection at taxonomic and functional levels, especially in relation to CH4 production. These responses included higher methanogens diversity in the uncoated section of the channel and are in agreement with the methanogen abundance determined by mcrA and mba genes copy number (1.5 × 107 and 4.3 × 1010) and subsequent positive correlation with CH4 emissions (R2 = 0.8). The most representative methanogen genus across the samples was Methanobrevibacter. The results observed herein shows that the use of the coating in the bottom of channels and tanks prevent the growth and development of a methanogen-related community. We concluded that the improvements in vinasse storage and transportation systems would significantly change the microbial community and reduce CH4 emissions, thereby making bioethanol a greener biofuel.

Loss of soil (macro)fauna due to the expansion of Brazilian sugarcane acreage.

Land use changes (LUC) from pasture to sugarcane (Saccharum spp.) crop are expected to add 6.4Mha of new sugarcane land by 2021 in the Brazilian Cerrado and Atlantic Forest biomes. We assessed the effects of these LUC on the abundance and community structure of animals that inhabit soils belowground through a field survey using chronosequences of land uses comprising native vegetation, pasture, and sugarcane along a 1000-km-long transect across these two major tropical biomes in Brazil. Macrofauna community composition differed among land uses. While most groups were associated with samples taken in native vegetation, high abundance of termites and earthworms appeared associated with pasture soils. Linear mixed effects analysis showed that LUC affected total abundance (X(2)(1)=6.79, p=0.03) and taxa richness (X(2)(1)=6.08, p=0.04) of soil macrofauna. Abundance increased from 411±70individualsm(-2) in native vegetation to 1111±202individualsm(-2) in pasture, but decreased sharply to 106±24individualsm(-2) in sugarcane soils. Diversity decreased 24% from native vegetation to pasture, and 39% from pasture to sugarcane. Thus, a reduction of ~90% in soil macrofauna abundance, besides a loss of ~40% in the diversity of macrofauna groups, can be expected when sugarcane crops replace pasture in Brazilian tropical soils. In general, higher abundances of major macrofauna groups (ants, coleopterans, earthworms, and termites) were associated with higher acidity and low contents of macronutrients and organic matter in soil. This study draws attention for a significant biodiversity loss belowground due to tropical LUC in sugarcane expansion areas. Given that many groups of soil macrofauna are recognized as key mediators of ecosystem processes such as soil aggregation, nutrients cycling and soil carbon storage, our results warrant further efforts to understand the impacts of altering belowground biodiversity and composition on soil functioning and agriculture performance across LUC in the tropics.

Specific microbial gene abundances and soil parameters contribute to C, N, and greenhouse gas process rates after land use change in Southern Amazonian Soils.

Ecological processes regulating soil carbon (C) and nitrogen (N) cycles are still poorly understood, especially in the world's largest agricultural frontier in Southern Amazonia. We analyzed soil parameters in samples from pristine rainforest and after land use change to pasture and crop fields, and correlated them with abundance of functional and phylogenetic marker genes (amoA, nirK, nirS, norB, nosZ, nifH, mcrA, pmoA, and 16S/18S rRNA). Additionally, we integrated these parameters using path analysis and multiple regressions. Following forest removal, concentrations of soil C and N declined, and pH and nutrient levels increased, which influenced microbial abundances and biogeochemical processes. A seasonal trend was observed, suggesting that abundances of microbial groups were restored to near native levels after the dry winter fallow. Integration of the marker gene abundances with soil parameters using path analysis and multiple regressions provided good predictions of biogeochemical processes, such as the fluxes of NO3, N2O, CO2, and CH4. In the wet season, agricultural soil showed the highest abundance of nitrifiers (amoA) and Archaea, however, forest soils showed the highest abundances of denitrifiers (nirK, nosZ) and high N, which correlated with increased N2O emissions. Methanogens (mcrA) and methanotrophs (pmoA) were more abundant in forest soil, but methane flux was highest in pasture sites, which was related to soil compaction. Rather than analyzing direct correlations, the data integration using multivariate tools provided a better overview of biogeochemical processes. Overall, in the wet season, land use change from forest to agriculture reduced the abundance of different functional microbial groups related to the soil C and N cycles; integrating the gene abundance data and soil parameters provided a comprehensive overview of these interactions. Path analysis and multiple regressions addressed the need for more comprehensive approaches to improve our mechanistic understanding of biogeochemical cycles.