Abstract
PurposeKnowledge about the spatio-temporal variability of soil microbial properties is crucial in evaluating their structure-function relationship and their impact on ecosystem functions. The aim of the study was to determine the spatio-temporal variation of the selected microbial properties at the surface horizon in a conventionally managed arable field.Materials and methodsThe area selected for the research, which was mainly covered with typical Luvisols, was a uniformly managed system that was considered to be homogenous in respect to texture (mostly loamy fine sand). Winter wheat was cultivated after winter rape as the forecrop. A grid soil sampling (10 m × 10 m) was used to assess the spatial heterogeneity of soil properties across a 0.5-ha field. Soil samples were collected at 50 points from the upper 20 cm of soil in April and August 2007. Colony-forming units (CFUs) of bacteria, fungi and actinomycetes, and basal respiration (BR) were analyzed. Data were evaluated using classical statistical and geostatistical methods.Results and discussionFungal CFUs were significantly lower than the bacterial ones with a B/F (bacteria/fungi) ratio of 80.0 in April and 45.1 in August. Bacterial CFUs, B/F ratio, and BR level revealed significantly higher values in April than in August, while fungi showed the opposite trend. Other studied properties did not show significant differences between sampling months. Only some of the properties, such as the bacterial community in August, the number of actinomycetes in April, and qCO2 on both sampling dates, revealed significant spatial autocorrelation (Moran’s I) and were spatially dependent at the scale of sampling grid, whereas the qCO2 revealed a higher differentiation in the spatial pattern between April and August than the other studied properties. Most of the spatially correlated properties were in the weak variability class (a nugget effect > 75%), while only the qCO2 (August) ratio was in the moderate variability class (a nugget effect between 25 and 75%).ConclusionsMost of the microbial-related properties did not exhibit a spatial structure at the examined scale, thus suggesting that changes in these properties would be detectable at a distance shorter than 10 m. More frequent seasonal sampling must be included in the sampling strategy in order to better understand whether studied properties show any permanent spatial patterns in soil over time or whether they are more randomized.
Highlights
Fungal Colony-forming units (CFUs) were significantly lower than the bacterial ones with a B/F ratio of 80.0 in April and 45.1 in August
Some of the properties, such as the bacterial community in August, the number of actinomycetes in April, and qCO2 on both sampling dates, revealed significant spatial autocorrelation (Moran’s I) and were spatially dependent at the scale of sampling grid, whereas the qCO2 revealed a higher differentiation in the spatial pattern between April and August than the other studied properties
Most of the microbial-related properties did not exhibit a spatial structure at the examined scale, suggesting that changes in these properties would be detectable at a distance shorter than 10 m
Summary
J Soils Sediments (2019) 19:345–355 homogenous than natural systems, biological processes (e.g., growth and colony formation) may produce aggregations of microorganisms at various spatial scales (Franklin and Mills 2003). Soil microorganisms and microbial processes are controlled by factors such as organic matter content, soil moisture, texture, and pH, all of which exhibit spatial heterogeneity as well (Guox et al 2012). The spatial variability is often determined for one scale (e.g., Peigné et al 2009), but multi-scaled comparisons have been considered as well (e.g., Franklin and Mills 2009). Franklin and Mills (2003) had previously explored the multi-scale spatial distribution of microbial community structure in an agricultural field and found that several scales of spatial autocorrelation can exist within the centimeter to 10-m scale The spatial variability is often determined for one scale (e.g., Peigné et al 2009), but multi-scaled comparisons have been considered as well (e.g., Franklin and Mills 2009). Franklin and Mills (2003) had previously explored the multi-scale spatial distribution of microbial community structure in an agricultural field and found that several scales of spatial autocorrelation can exist within the centimeter to 10-m scale
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
