Dataset Information

Biodiversity of cultivable Burkholderia species in Argentinean soils under no-till agricultural practices.

ABSTRACT: No-tillage crop production has revolutionized the agriculture worldwide. In our country more than 30 Mha are currently cultivated under no-till schemes, stressing the importance of this management system for crop production. It is widely recognized that soil microbiota is altered under different soil managements. In this regard the structure of Burkholderia populations is affected by soils management practices such as tillage, fertilization, or crop rotation. The stability of these structures, however, has not been evaluated under sustainable schemes where the impact of land practices could be less deleterious to physicochemical soils characteristics. In order to assess the structure of Burkholderia spp. populations in no-till schemes, culturable Burkholderia spp. strains were quantified and their biodiversity evaluated. Results showed that Burkholderia spp. biodiversity, but not their abundance, clearly displayed a dependence on agricultural managements. We also showed that biodiversity was mainly influenced by two soil factors: Total Organic Carbon and Total Nitrogen. Results showed that no-till schemes are not per se sufficient to maintain a richer Burkholderia spp. soil microbiota, and additional traits should be considered when sustainability of productive soils is a goal to fulfil productive agricultural schemes.

SUBMITTER: Draghi WO

PROVIDER: S-EPMC6042781 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Biodiversity of cultivable Burkholderia species in Argentinean soils under no-till agricultural practices.

Draghi Walter Omar WO Degrossi Jose J Bialer Magalí M Brelles-Mariño Graciela G Abdian Patricia P Soler-Bistué Alfonso A Wall Luis L Zorreguieta Angeles A

PloS one 20180712 7

No-tillage crop production has revolutionized the agriculture worldwide. In our country more than 30 Mha are currently cultivated under no-till schemes, stressing the importance of this management system for crop production. It is widely recognized that soil microbiota is altered under different soil managements. In this regard the structure of Burkholderia populations is affected by soils management practices such as tillage, fertilization, or crop rotation. The stability of these structures, h ...[more]

PMID: 30001428

Similar Datasets

Project description:The rise in the world demand for food poses a challenge to our ability to sustain soil fertility and sustainability. The increasing use of no-till agriculture, adopted in many areas of the world as an alternative to conventional farming, may contribute to reduce the erosion of soils and the increase in the soil carbon pool. However, the advantages of no-till agriculture are jeopardized when its use is linked to the expansion of crop monoculture. The aim of this study was to survey bacterial communities to find indicators of soil quality related to contrasting agriculture management in soils under no-till farming. Four sites in production agriculture, with different soil properties, situated across a west-east transect in the most productive region in the Argentinean pampas, were taken as the basis for replication. Working definitions of Good no-till Agricultural Practices (GAP) and Poor no-till Agricultural Practices (PAP) were adopted for two distinct scenarios in terms of crop rotation, fertilization, agrochemicals use and pest control. Non-cultivated soils nearby the agricultural sites were taken as additional control treatments. Tag-encoded pyrosequencing was used to deeply sample the 16S rRNA gene from bacteria residing in soils corresponding to the three treatments at the four locations. Although bacterial communities as a whole appeared to be structured chiefly by a marked biogeographic provincialism, the distribution of a few taxa was shaped as well by environmental conditions related to agricultural management practices. A statistically supported approach was used to define candidates for management-indicator organisms, subsequently validated using quantitative PCR. We suggest that the ratio between the normalized abundance of a selected group of bacteria within the GP1 group of the phylum Acidobacteria and the genus Rubellimicrobium of the Alphaproteobacteria may serve as a potential management-indicator to discriminate between sustainable vs. non-sustainable agricultural practices in the Pampa region.

Project description:Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils.Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species.Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.

Dataset Information

Biodiversity of cultivable Burkholderia species in Argentinean soils under no-till agricultural practices.

Publications

Biodiversity of cultivable Burkholderia species in Argentinean soils under no-till agricultural practices.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets