Dataset Information

Seasonal change is a major driver of soil resistomes at a watershed scale.

ABSTRACT: Soils harbor the most diverse naturally evolved antibiotic resistomes on Earth that threaten human health, ecosystem processes, and food security. Yet the importance of spatial and temporal variability in shaping the distribution of soil resistomes is not well explored. Here, a total of 319 topsoil samples were collected at a watershed scale during four seasons (spring to winter) and high-throughput quantitative PCR (HT-qPCR) was used to characterize the profiles of soil antibiotic resistance genes (ARGs). A significant and negative correlation was observed between soil ARG profiles and seasonal dissimilarity, which along with seasonally dependent distance-decay relationships highlight the importance of seasonal variability in shaping soil antibiotic resistomes. Significant, though weak, distance-decay relationships were identified in spring, summer and winter, for ARG similarities with geographic distances. There were also strong interactions between specific soil ARGs and Actinobacteria, Firmicutes and Proteobacteria. Moreover, we found that the relative abundance of soil Actinobacteria, Firmicutes and Proteobacteria correlated significantly with annual mean temperature and annual mean precipitation at a watershed scale. A random forest model showed that seasonal change rather than spatial variation was the most important predictor of the composition of soil ARGs. Together, these results constitute an advance in our understanding of the relative importance of spatial and temporal variability in shaping soil ARG profiles, which will provide novel insights allowing us to forecast their distribution under a changing environment.

SUBMITTER: Xiang Q

PROVIDER: S-EPMC9723683 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Seasonal change is a major driver of soil resistomes at a watershed scale.

Xiang Qian Q Qiao Min M Zhu Dong D Giles Madeline M Neilson Roy R Yang Xiao-Ru XR Zhu Yong-Guan YG Chen Qing-Lin QL

ISME communications 20210520 1

Soils harbor the most diverse naturally evolved antibiotic resistomes on Earth that threaten human health, ecosystem processes, and food security. Yet the importance of spatial and temporal variability in shaping the distribution of soil resistomes is not well explored. Here, a total of 319 topsoil samples were collected at a watershed scale during four seasons (spring to winter) and high-throughput quantitative PCR (HT-qPCR) was used to characterize the profiles of soil antibiotic resistance ge ...[more]

PMID: 36732354

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Project description:Soil erosion is a critical global challenge that degrades land and water resources, leading to reduced soil fertility, pollution of water bodies, and sedimentation in hydraulic structures and reservoirs. In Ethiopia, where agriculture forms the backbone of the economy, unplanned LULC changes have intensified soil erosion, posing a significant threat to food security and sustainable development. In the Holota watershed of Ethiopia, rapid population growth and urbanization have accelerated unplanned land use and land cover (LULC) changes, significantly affecting soil erosion patterns. This study aims to assess the spatiotemporal changes in LULC and their impact on soil erosion from 2000 to 2050. Using Landsat imagery from 2000, 2010, and 2020, supervised classification with the maximum likelihood algorithm was applied in Google Earth Engine (GEE) to map five LULC classes: forest, cropland, built-up areas, shrubland, and grassland. The future LULC for 2050 was predicted using the CA-Markov chain model. Soil erosion for 2020 and 2050 LULC maps was estimated using the Revised Universal Soil Loss Equation (RUSLE). Results indicate that annual soil loss in the watershed was 13.3 t ha - 1 yr - 1 in 2020, increasing to 15.9 t ha - 1 yr - 1 by 2050. Cropland, built-up areas, and grassland are expected to be the major contributors to future soil erosion, while forest and shrubland are likely to play a mitigating role. The novelty of this research lies in its integration of cutting-edge remote sensing technologies, such as GEE and the CA-Markov model, to predict the combined impact of LULC changes on soil erosion in a data-scarce region, providing actionable insights for conservation planning in Ethiopian highlands. These findings offer essential guidance for conservation planners to implement sustainable land management practices aimed at reducing soil erosion, including promoting forest restoration, adopting contour farming, and enforcing land use regulations to limit the expansion of cropland and built-up areas in erosion-prone zones.

Project description:BackgroundBiogeochemical exports from watersheds are modulated by the activity of microorganisms that function over micron scales. Here, we tested the hypothesis that meander-bound regions share a core microbiome and exhibit patterns of metabolic potential that broadly predict biogeochemical processes in floodplain soils along a river corridor.ResultsWe intensively sampled the microbiomes of floodplain soils located in the upper, middle, and lower reaches of the East River, Colorado. Despite the very high microbial diversity and complexity of the soils, we reconstructed 248 quality draft genomes representative of subspecies. Approximately one third of these bacterial subspecies was detected across all three locations at similar abundance levels, and ~ 15% of species were detected in two consecutive years. Within the meander-bound floodplains, we did not detect systematic patterns of gene abundance based on sampling position relative to the river. However, across meanders, we identified a core floodplain microbiome that is enriched in capacities for aerobic respiration, aerobic CO oxidation, and thiosulfate oxidation with the formation of elemental sulfur. Given this, we conducted a transcriptomic analysis of the middle floodplain. In contrast to predictions made based on the prominence of gene inventories, the most highly transcribed genes were relatively rare amoCAB and nxrAB (for nitrification) genes, followed by genes involved in methanol and formate oxidation, and nitrogen and CO2 fixation. Within all three meanders, low soil organic carbon correlated with high activity of genes involved in methanol, formate, sulfide, hydrogen, and ammonia oxidation, nitrite oxidoreduction, and nitrate and nitrite reduction. Overall, the results emphasize the importance of sulfur, one-carbon and nitrogen compound metabolism in soils of the riparian corridor.ConclusionsThe disparity between the scale of a microbial cell and the scale of a watershed currently limits the development of genomically informed predictive models describing watershed biogeochemical function. Meander-bound floodplains appear to serve as scaling motifs that predict aggregate capacities for biogeochemical transformations, providing a foundation for incorporating riparian soil microbiomes in watershed models. Widely represented genetic capacities did not predict in situ activity at one time point, but rather they define a reservoir of biogeochemical potential available as conditions change. Video abstract.

Dataset Information

Seasonal change is a major driver of soil resistomes at a watershed scale.

Publications

Seasonal change is a major driver of soil resistomes at a watershed scale.

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