Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+M-bM-^@M-^SN and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics. Twelve samples were collected from four elevations (3200, 3400, 3600 and 3800 m) along a Tibetan grassland; Three replicates in every elevation
Project description:Global warming substantially changes precipitation patterns in the Tibetan plateau, with projection of increased precipitation in southern and northern Tibet but decreased precipitation in the center. Understanding mechanisms of such changes in greenhouse gas emissions is of vital importance in predicting ecosystem feedbacks to climate changes. Nonetheless, it has been hampered by limited knowledge in soil microbial communities, one of the major drivers of greenhouse gas emission. Here, we report a field experiment simulating drying and wetting conditions in the Tibetan grassland. Our field site is located at the Haibei Alpine Grassland Ecosystem Research Station in the northeast of Tibet Plateau, China, and we employed GeoChip 5.0 180K to analyze microbial responses. 18 samples were collected from 3 plots in Haibei Station, with 6 replicates in each plot
Project description:Global warming substantially changes precipitation patterns in the Tibetan plateau, with projection of increased precipitation in southern and northern Tibet but decreased precipitation in the center. Understanding mechanisms of such changes in greenhouse gas emissions is of vital importance in predicting ecosystem feedbacks to climate changes. Nonetheless, it has been hampered by limited knowledge in soil microbial communities, one of the major drivers of greenhouse gas emission. Here, we report a field experiment simulating drying and wetting conditions in the Tibetan grassland. Our field site is located at the Haibei Alpine Grassland Ecosystem Research Station in the northeast of Tibet Plateau, China, and we employed GeoChip 5.0 180K to analyze microbial responses.
Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+–N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics.
Project description:Understanding and quantifying the effects of environmental factors influencing the variation of abundance and diversity of microbial communities was a key theme of ecology. For microbial communities, there were two factors proposed in explaining the variation in current theory, which were contemporary environmental heterogeneity and historical events. Here, we report a study to profile soil microbial structure, which infers functional roles of microbial communities, along the latitudinal gradient from the north to the south in China mainland, aiming to explore potential microbial responses to external condition, especially for global climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 5.0, we showed that microbial communities were distinct for most but not all of the sites. Using substantial statistical analyses, exploring the dominant factor in influencing the soil microbial communities along the latitudinal gradient. Substantial variations were apparent in nutrient cycling genes, but they were in line with the functional roles of these genes. 300 samples were collected from 30 sites along the latitudinal gradient, with 10 replicates in every site