Cercozoa soil depth
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB30791 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:GCMS datasets for the soil depth manuscript
Abstract
Two factors that are well-known to influence soil microbiomes include the depth of the soil as well as the level of moisture. Previous works have demonstrated that climate change will increase the incidence of drought in soils, but it is unknown how fluctuations in moisture availability affect soil microbiome composition and functioning down the depth profile. Here, we investigated soil and wheatgrass rhizosphere microbiomes in a common field setting under four different irrigation regimes and three depths. We demonstrated that there is a significant interactive effect, where fluctuations in soil moisture more strongly influence soil microbiomes at the surface layer than in deeper layers, including for soil community composition, diversity, and for functional profiles. Meanwhile, in rhizosphere communities the influence of irrigation was similar across the different depths, although there were slight discrepancies between the two cultivars of wheatgrass used. The lessened response of deeper soil microbiomes to changes in irrigation may be due to higher incidence of slow-growing, stress-resistant microbes.
2022-11-07 | MSV000090655 | MassIVE
Project description:The experiment at three long-term agricultural experimental stations (namely the N, M and S sites) across northeast to southeast China was setup and operated by the Institute of Soil Science, Chinese Academy of Sciences. This experiment belongs to an integrated project (The Soil Reciprocal Transplant Experiment, SRTE) which serves as a platform for a number of studies evaluating climate and cropping effects on soil microbial diversity and its agro-ecosystem functioning. Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of soil type, soil transplant and landuse changes on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles.
2016-02-04 | GSE77546 | GEO
Project description:Cercozoa from agricultural samples Metagenome
| PRJNA298969 | ENA
Project description:Investigation of LC-MS/MS approaches to improve soil metaproteome depth of coverage for a Kansas prairie native soil
2018-11-21 | PXD008895 | Pride
Project description:We carried out an in-depth analysis of the monthly variations of a temperate grassland ecosystem to examine a range of biotic and abiotic factors that underpin soil respiration changes in response to warming.
2022-02-10 | GSE195490 | GEO
Project description:Because of severe abiotic limitations, Antarctic soils represent simplified ecosystems, where microorganisms are the principle drivers of nutrient cycling. This relative simplicity makes these ecosystems particularly vulnerable to perturbations, like global warming, and the Antarctic Peninsula is among the most rapidly warming regions on the planet. However, the consequences of the ongoing warming of Antarctica on microorganisms and the processes they mediate are unknown. Here, using 16S rRNA gene pyrosequencing and qPCR, we report a number of highly consistent changes in microbial community structure and abundance across very disparate sub-Antarctic and Antarctic environments following three years of experimental field warming (+ 0.5-2°C). Specifically, we found significant increases in the abundance of fungi and bacteria and in the Alphaproteobacteria-to-Acidobacteria ratio. These alterations were linked to a significant increase in soil respiration. Furthermore, the shifts toward generalist or opportunistic bacterial communities following warming weakened the linkage between bacterial diversity and functional diversity. Warming also increased the abundance of some organisms related to the N-cycle, detected as an increase in the relative abundance of nitrogenase genes via GeoChip microarray analyses. Our results demonstrate that soil microorganisms across a range of sub-Antarctic and Antarctic environments can respond consistently and rapidly to increasing temperatures, thereby potentially disrupting soil functioning. We conducted in situ warming experiments for three years using open-top chambers (OTCs) at one sub-Antarctic (Falkland Islands, 52ºS) and two Antarctic locations (Signy and Anchorage Islands, 60ºS and 67ºS respectively) (see Supplementary Fig. 1 for a map). OTCs increased annual soil temperature by an average of 0.8°C (at a depth of 5 cm), resulting in 8-43% increase in positive-degree days annually and a decrease in freeze-thaw cycle frequency by an average of 15 cycles per year (8). At each location, we included densely vegetated and bare fell-field soils in the experimental design for a total of six environments. Densely vegetated and bare environments represent two contrasting environments for Antarctic soil microorganisms, with large differences in terms of C and N inputs to soils. Massively parallel pyrosequencing (Roche 454 GS FLX Titanium) of 16S rRNA gene amplicons was used to follow bacterial diversity and community composition [GenBank Accession Numbers: HM641909-HM744649], and functional gene microarrays (GeoChip 2.0)(11) were used to assess changes in functional gene distribution. Bacterial and fungal communities were also quantified using real-time PCR.
2010-12-30 | E-GEOD-22825 | biostudies-arrayexpress
Project description:Copper has long been applied for agricultural practices. Like other metals, copper is highly persistent in the environment and biologically active long after its use has ceased. Here we present a unique study on the long-term effects (27 years) of copper and pH on soil microbial communities and on Folsomia candida, an important representative of the soil macrofauna, in an experiment with a full factorial, random block design. Bacterial communities were mostly affected by pH. These effects were prominent in Acidobacteria, while Actinobacteria and Gammaroteobacteria communities were affected by original and bioavailable copper. Reproduction and survival of the collembolan F. candida was not affected by the studied copper concentrations. However, the transcriptomic responses to copper reflected a mechanism of copper transport and detoxification, while pH exerted effects on nucleotide and protein metabolism and (acute) inflammatory response. We conclude that microbial community structure explained the history of copper contamination, while gene expression analysis of F. candida is associated with the current level of bioavailable copper. Combined analysis at various trophic levels is highly relevant in the context of assessing long-term soil pollution. A single channel, interwoven loop design was used to test animals exposed to the copper-spiked field soil samples. The field soil was spiked with 4 copper and 4 pH treatments yielding 16 combinations. Combinations are displayed in the Sample descriptions, with 1 M-bM-^@M-^S 4 representing the copper concentrations from low to high, and A-D representing the soil pH from low to high. 4 biological replicates per copper/pH combination were used. Each replicate contained 25 grams of soil and thirty 23-day-old animals.
2012-04-03 | E-GEOD-29644 | biostudies-arrayexpress
Project description:Organic agricultural field soil Raw sequence reads
| PRJNA283223 | ENA
Project description:Environmental pollution is a worldwide problem, and metals are the largest group of contaminants in soil. Microarray toxicogenomic studies with ecologically relevant organisms such as springtails, supplement traditional ecotoxicological research, but are presently rather descriptive. Classifier analysis, a more analytical application of the microarray technique, is able to predict biological classes of unknown samples. We used the uncorrelated shrunken centroid (USC) method to classify gene expression profiles of the springtail Folsomia candida exposed to soil spiked with six different metals (barium, cadmium, cobalt, chromium, lead, and zinc). We identified a gene set (classifier) of 188 genes that can discriminate between six different metals present in soil, which allowed us to predict the correct classes for samples of an independent test set with an accuracy of 83% (error rate = 0.17). This study shows further that in order to apply classifier analysis to actual contaminated field soil samples, more insight and information is needed on the transcriptional responses of soil organisms to different soil types (properties) and mixtures of contaminants.
2010-02-05 | GSE19353 | GEO