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The theory of microbial stoichiometry can predict the proportional coupling of microbial assimilation of carbon (C), nitrogen (N), and phosphorus (P). The proportional coupling is quantified by the homeostasis value (H). Covariation of H values for C, N, and P indicates that microbial C, N, and P assimilation are coupled. Here, we used a global dataset to investigate the spatiotemporal dynamics of H values of microbial C, N, and P across biomes. We found that land use and management led to the decoupling of P from C and N metabolism over time and across space. Results from structural equation modeling revealed that edaphic factors dominate the microbial homeostasis of P, while soil elemental concentrations dominate the homeostasis of C and N. This result was further confirmed using the contrasting factors on microbial P vs. microbial C and N derived from a machine-learning algorithm. Overall, our study highlights the impacts of management on shifting microbial roles in nutrient cycling.

 

Restoring ecosystems requires the re-establishment of diverse soil microbial communities that drive critical ecosystem functions. In grasslands, restoration and management require the application of disturbances like fire and grazing. Disturbances can shape microbial taxonomic composition and potentially functional composition as well. We characterized taxonomic and functional gene composition of soil communities using whole genome shotgun metagenomic sequencing to determine how restored soil communities differed from pre-restoration agricultural soils and original remnant soils, how management affects soil microbes, and whether restoration and management affect the number of microbial genes associated with carbohydrate degradation. We found distinct differences in both taxonomic and functional diversity and composition among restored, remnant, and agricultural soils. Remnant soils had low taxonomic and functional richness and diversity, as well as distinct composition, indicating that restoration of agricultural soils does not re-create soil microbial communities that match remnants. Prescribed fire management increased functional diversity, which also was higher in more recently planted restorations. Finally, restored and post-fire soils included high abundances of genes encoding cellulose-degrading enzymes, so restorations and their ongoing management can potentially support functions important in carbon cycling.

 

We applied a microbial-explicit model – the CLM-Microbe – to investigate the dynamics of C in vegetation, litter, soil, and microbes during 1901-2016. The CLM-Microbe model was able to reproduce global averages and latitudinal trends of gross (GPP) and net (NPP) primary productivity, heterotrophic (HR) and soil (SR) respiration, biomass C in fungi (FBC) and bacteria (BBC) in the top 30 cm and 1 m, dissolved (DOC) and soil organic C (SOC) in the top 30 cm and 1 m. In addition, the CLM-Microbe model captured the grid-level variation in GPP (R2=0.78), NPP (R2=0.63), SR (R2=0.26), HR (R2=0.23), DOC in 0-30 cm (R2=0.2) and 0-1 m (R2=0.22), SOC in 0-30 cm (R2=0.36) and 0-1 m (R2=0.26), FBC (R2=0.22) and BBC (R2=0.32) in 0-30 cm, and MBC in 0-1 m (R2=0.21). From the 1900s to 2007-2016, simulated C variables increased by approximately 30 PgC yr-1 for GPP, 15 PgC yr-1 for NPP, 12 PgC yr-1 for HR, 25 PgC yr-1 for SR, 1.0 PgC for FBC and 0.4 PgC for BBC in 0-30 cm, 1.5 PgC for FBC, 0.8 PgC for BBC, 2.5 PgC for DOC, 40 PgC for SOC, and 5 PgC for litter C in 0-1 m, and 40 PgC for vegetation C. The relative increases in C fluxes and pools varied across the globe. Increases in vegetation C were closely related to warming and increased precipitation, while C accumulation in microbes and soils was jointly governed by vegetation C input and soil temperature and moisture. 

Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower domains (200 m × 200 m) in the Alaska North Slope, for three sites in Utqiaġvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo), for a period of 2013–2015. Three footprint algorithms were the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. Simulated annual CH 4 flux was highly consistent with the EC measurements at US-Beo and US-Bes. In contrast, flux was overestimated at US-Brw, US-Atq, and US-Ivo due to the higher simulated CH 4 flux in early growing seasons. The simulated monthly CH 4 flux was consistent with EC measurements but with different accuracies among footprint algorithms. At US-Bes in September 2013, RMSE and NNSE were 0.002 μmol m −2  s −1 and 0.782 using the DF algorithm, but 0.007 μmol m −2  s −1 and 0.758 using HF and 0.007 μmol m −2  s −1 and 0.765 using GF, respectively. DF algorithm performed better than the HF and GF algorithms in capturing the temporal variation in daily CH 4 flux each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH 4 flux during 2013–2015 were predominately explained by air temperature (67–74%), followed by precipitation (22–36%). Spatial heterogeneities in vegetation fraction and elevation dominated the spatial variations in CH 4 flux for all five tower domains despite relatively weak differences in simulated CH 4 flux among three footprint algorithms. The CLM-Microbe model can simulate CH 4 flux at both plot and landscape scales at a high temporal resolution, which should be applied to other landscapes. Integrating land surface models with an appropriate algorithm provides a powerful tool for upscaling CH 4 flux in terrestrial ecosystems. 

An isotopic labeling experiment was conducted in an Arctic coastal wet tundra ecosystem to determine how quickly acetate is transformed into methane and transported from the soil to the atmosphere. Carbon-13 (13C) labelled acetate was injected into soil chambers installed across a 131 meter (m) transect. Gas samples were periodically collected from the headspace in chambers, and analyzed for methane concentration and enrichment in 13C. Methane flux was roughly estimated from the final concentration in the chambers accumulated over a one-hour sampling period. This dataset includes methane fluxes, concentrations and 13C enrichment values from this experiment. In addition, water samples were collected from 15 centimeters (cm) depth after the final time point for measurements of residual dissolved 13C-methane in the soil after 9 days. 

When wet Arctic tundra soils begin to freeze in the fall, an unfrozen layer remains between the frozen surface and deeper permafrost layers. This period is known as the zero curtain, as liquid water keeps the temperature of this soil layer near 0 Celsius (C) while latent heat is gradually dissipated. This experiment compares the temperature response of the methanogenic community in the zero curtain period with that of the summer community to test whether the zero curtain methanogenic community is especially cold adapted. This dataset includes methane production rates measured in anaerobic laboratory incubations of soils collected from two dates (July and Nov 2018) at temperatures around 0, 4 and 10C. 

When wet Arctic tundra soils begin to freeze in the fall, an unfrozen layer remains between the frozen surface and deeper permafrost layers. This period is known as the zero curtain, as liquid water keeps the temperature of this soil layer near 0 Celsius (C) while latent heat is gradually dissipated. This project investigates the microbes that are metabolically active in the unfrozen layer during the fall zero curtain period and compares this community to that which is active in the late summer at the same depth (10-20 centimeters (cm)). This dataset contains the abundance and taxonomic designation of distinct 16S ribosomal ribonucleic acid (16S rRNA) sequences (operational taxonomic units, OTU's) associated with samples in this study. These data complement the sequences and metadata deposited in GenBank Bioproject PRJNA780202. 

When wet Arctic tundra soils begin to freeze in the fall, an unfrozen layer remains between the frozen surface and deeper permafrost layers. This period is known as the zero curtain, as liquid water keeps the temperature of this soil layer near 0 Celsius (C) while latent heat is gradually dissipated. This project investigates the methanogenic Archaea that are metabolically active in the unfrozen layer during the fall zero curtain period and compares this community to that which is active in the late summer at the same depth (10-20 centimeters (cm)). This dataset contains the abundance of distinct partial mcrA (Methyl-coenzyme M reductase alpha subunit) gene sequences (operational taxonomic units, OTU's defined at 16% similarity) amplified from messenger ribonucleic acid (mRNA) extracted from soil samples in this study. These data complement the sequences deposited in GenBank (accession numbers OL505703-OL505708). 

When wet Arctic tundra soils begin to freeze in the fall, an unfrozen layer remains between the frozen surface and deeper permafrost layers. This period is known as the zero curtain, as liquid water keeps the temperature of this soil layer near 0 Celsius (C) while latent heat is gradually dissipated. Significant methane emissions have been observed during this period but the role of concurrent biological production vs escape of stored methane requires more study. This dataset includes dissolved methane concentrations from the active layer (upper 35 centimeters (cm)) of Arctic tundra soils during the fall zero curtain period and in the spring, at the beginning of the thaw period. These data help address the question of biological methane production and storage during the fall.