Dataset Information

Characterizing changes in soil microbiome abundance and diversity due to different cover crop techniques.

ABSTRACT: Soil-based microorganisms assume a direct and crucial role in the promotion of soil health, quality and fertility, all factors known to contribute heavily to the quality and yield of agricultural products. Cover cropping, used in both traditional and organic farming, is a particularly efficient and environmentally favorable tool for manipulating microbiome composition in agricultural soils and has had clear benefits for soil quality and crop output. Several long-term investigations have evaluated the influence of multi-mix (multiple species) cover crop treatments on soil health and microbial diversity. The present study investigated the short-term effects of a seven species multi-mix cover crop treatment on soil nutrient content and microbial diversity, compared to a single-mix cover crop treatment and control. Analysis of 16S sequencing data of isolated soil DNA revealed that the single-mix cover crop treatment decreased overall microbial abundance and diversity, whereas the control and multi-mix treatments altered the overall microbial composition in similar fluctuating trends. Furthermore, we observed significant changes in specific bacteria belonging to the phyla Acidobacteria, Actinobacteria, Planctomycetes, Proteobacteria and Verrucombicrobia for all treatments, but only the single-mix significantly decreased in abundance of the selected bacteria over time. Our findings indicate that the control and multi-mix treatments are better at maintaining overall microbial composition and diversity compared to the single-mix. Further study is required to elucidate the specific difference between the treatment effect of the multi-mix treatment and the control, given that their microbial composition changes over time were similar but they diverge into two populations of unique bacterial types by the end of this short-term study.

SUBMITTER: Wang CH

PROVIDER: S-EPMC7199946 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundCover cropping is an agricultural practice that uses secondary crops to support the growth of primary crops through various mechanisms including erosion control, weed suppression, nutrient management, and enhanced biodiversity. Cover crops may elicit some of these ecosystem services through chemical interactions with the soil microbiome via root exudation, or the release of plant metabolites from roots. Phytohormones are one metabolite type exuded by plants that activate the rhizosphere microbiome, yet managing this chemical interaction remains an untapped mechanism for optimizing plant-soil microbiome interactions. Currently, there is limited understanding on the diversity of cover crop phytohormone root exudation patterns and how these chemical messages selectively enrich specific microbial taxa and functionalities in agricultural soils.ResultsHere, we link variability in cover crop root exudate composition to changes in soil microbiome functionality. Exudate chemical profiles from 4 cover crop species (Sorghum bicolor, Vicia villosa, Brassica napus, and Secale cereal) were used as the chemical inputs to decipher microbial responses. These distinct exudate profiles, along with a no exudate control, were amended to agricultural soil microcosms with microbial responses tracked over time using metabolomes and genome-resolved metatranscriptomes. Our findings illustrated microbial metabolic patterns were unique in response to cover crop exudate inputs over time, particularly by sorghum and cereal rye amended microcosms where we identify novel microbial members (at the genera and family level) who produced IAA and GA4 over time. We also identify broad changes in microbial nitrogen cycling in response chemical inputs.ConclusionsWe highlight that root exudate amendments alter microbial community function and phytohormone metabolisms, particularly in response to root exudates isolated from cereal rye and sorghum plants. Additionally, we constructed a soil microbial genomic catalog of microorganisms responding to commonly used cover crops, a public resource for agriculturally-relevant microbes. Many of our exudate-stimulated microorganisms are representatives from poorly characterized or novel taxa, highlighting the yet to be discovered metabolic reservoir harbored in agricultural soils. Our findings emphasize the tractability of high-resolution multiomics approaches to investigate processes relevant for agricultural soils, opening the possibility of targeting specific soil biogeochemical outcomes through biological precision agricultural practices that use cover crops and the microbiome as levers for enhanced crop production.

Project description:The dataset presented here supports the research paper entitled "A calculator to quantify cover crop effects on soil health and productivity". Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters - erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity - to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

Project description:The diversity-productivity, diversity-invasibility, and diversity-stability hypotheses propose that increasing species diversity should lead, respectively, to increased average biomass productivity, invasion resistance, and stability. We tested these three hypotheses in the context of cover crop mixtures, evaluating the effects of increasing cover crop mixture diversity on aboveground biomass, weed suppression, and biomass stability. Twenty to forty cover crop treatments were replicated three or four times at eleven sites using eighteen species representing three cover crop species each from six pre-defined functional groups: cool-season grasses, cool-season legumes, cool-season brassicas, warm-season grasses, warm-season legumes, and warm-season broadleaves. Each species was seeded as a pure stand, and the most diverse treatment contained all eighteen species. Remaining treatments included treatments representing intermediate levels of cover crop species and functional richness and a no cover crop control. Cover crop seeding dates ranged from late July to late September with both cover crop and weed aboveground biomass being sampled prior to winterkill. Stability was assessed by evaluating the variability in cover crop biomass for each treatment across plots within each site. While increasing cover crop mixture diversity was associated with increased average aboveground biomass, we assert that this was the result of the average biomass of the pure stands being drawn down by low biomass species rather than due to niche complementarity or increased resource use efficiency. At no site did the highest biomass mixture produce more than the highest biomass pure stand. Furthermore, while increases in cover crop mixture diversity were correlated with increases in weed suppression and biomass stability, we argue that this was largely the result of diversity co-varying with aboveground biomass, and that differences in aboveground biomass rather than differences in diversity drove the differences observed in weed suppression and stability.

Dataset Information

Characterizing changes in soil microbiome abundance and diversity due to different cover crop techniques.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets