Project description:Land cover change has long been recognized that marked effect the amount of soil organic carbon. However, little is known about microbial-mediated effect processes and mechanism on soil organic carbon. In this study, the soil samples in a degenerated succession from alpine meadow to alpine steppe meadow in Qinghai-Tibetan Plateau degenerated, were analyzed by using GeoChip functional gene arrays.
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, 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. sixty-three samples were collected from four elevations (3200,3400,3600 and 3800 m) along a Tibetan alpine meadow; Three replicates in each treatment
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: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:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.
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:To study long-term elevated CO2 and enriched N deposition interactive effects on microbial community and soil ecoprocess, here we investigated soil microbial community in a grassland ecosystem subjected to ambient CO2 (aCO2, 368 ppm), elevated CO2 (eCO2, 560 ppm), ambient nitrogen deposition (aN) or elevated nitrogen deposition (eN) treatments for a decade. There exist antagonistic CO2×N interactions on microbial functional genes associated with C, N, P S cycling processes. More strong antagonistic CO2×N interactions are observed on C degradation genes than other genes. Remarkably antagonistic CO2×N interactions on soil microbial communities could enhance soil C accumulation.
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