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

Lammel DR, Feigl BJ, Cerri CC, Nüsslein K - Front Microbiol (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Centro de Energia Nuclear na Agricultura, University of São Paulo Piracicaba, Brazil ; Department of Microbiology, University of Massachusetts Amherst, MA, USA.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Principal Components Analysis of land uses (symbols) and soil parameters (vectors) in Southern Amazonia in the middle of the wet season. Data are shown for four different land use types, forest (), pasture (▲), soybean 25 years (), soybean 2 years (, and adjacent forest in a gray circle); and vectors for the soil chemical parameters, microbial genes, and GHG fluxes.
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Figure 4: Principal Components Analysis of land uses (symbols) and soil parameters (vectors) in Southern Amazonia in the middle of the wet season. Data are shown for four different land use types, forest (), pasture (▲), soybean 25 years (), soybean 2 years (, and adjacent forest in a gray circle); and vectors for the soil chemical parameters, microbial genes, and GHG fluxes.

Mentions: The abundance of N-fixers, based on nifH genes, was highest in forest soils, followed by pasture soils. Archaeal ammonium oxidizers (AOAs) were numerically dominant at all sites, and overall abundance (amoA Archaea) was highest in the old soybean fields, and lowest in forest soils. Bacterial ammonium oxidizers (AOB) were more abundant in the forest sites (Table 1). The abundance of denitrification genes was highest in forest soils, intermediate in pasture, and lowest in soybean fields (Table 1). Significant correlations and relationships between related genes (nirK and nosZ) were found, and also between them and N, NO3-, NH4+, and N2O (Supplementary Table S4). Interestingly, abundances of nifH, amoA Bacteria, nirK, and nosZ genes were correlated between each other (in fact, they are all present in some bacteria, such as Rhizobium sp.). Interactions among the variables were further characterized by 3D plots and multivariate techniques (Figures 3 and 4).


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

Lammel DR, Feigl BJ, Cerri CC, Nüsslein K - Front Microbiol (2015)

Principal Components Analysis of land uses (symbols) and soil parameters (vectors) in Southern Amazonia in the middle of the wet season. Data are shown for four different land use types, forest (), pasture (▲), soybean 25 years (), soybean 2 years (, and adjacent forest in a gray circle); and vectors for the soil chemical parameters, microbial genes, and GHG fluxes.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4594008&req=5

Figure 4: Principal Components Analysis of land uses (symbols) and soil parameters (vectors) in Southern Amazonia in the middle of the wet season. Data are shown for four different land use types, forest (), pasture (▲), soybean 25 years (), soybean 2 years (, and adjacent forest in a gray circle); and vectors for the soil chemical parameters, microbial genes, and GHG fluxes.
Mentions: The abundance of N-fixers, based on nifH genes, was highest in forest soils, followed by pasture soils. Archaeal ammonium oxidizers (AOAs) were numerically dominant at all sites, and overall abundance (amoA Archaea) was highest in the old soybean fields, and lowest in forest soils. Bacterial ammonium oxidizers (AOB) were more abundant in the forest sites (Table 1). The abundance of denitrification genes was highest in forest soils, intermediate in pasture, and lowest in soybean fields (Table 1). Significant correlations and relationships between related genes (nirK and nosZ) were found, and also between them and N, NO3-, NH4+, and N2O (Supplementary Table S4). Interestingly, abundances of nifH, amoA Bacteria, nirK, and nosZ genes were correlated between each other (in fact, they are all present in some bacteria, such as Rhizobium sp.). Interactions among the variables were further characterized by 3D plots and multivariate techniques (Figures 3 and 4).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Centro de Energia Nuclear na Agricultura, University of São Paulo Piracicaba, Brazil ; Department of Microbiology, University of Massachusetts Amherst, MA, USA.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus