Search

The sampling method is a key aspect when designing a soil monitoring network. The determination of any physical and chemical property can be subject to uncertainties because of the sampling method. In this study, we compared the efficiency of sampling with a spade and a gouge auger for the physicochemical characterization of topsoil samples from 150 mineral soils under various land cover (LC) classes in Switzerland taken within the LUCAS 2015 Survey. The sampling methods differed in their scheme, accuracy of litter removal and control of sampling depth, which were more rigorous with the gouge auger than the spade method. Values of root mean square error of properties ranged between 1/2 and 1/30 of their mean values. Lin's concordance correlation coefficient showed that the spade and gouge auger methods produced similar results for all properties (LCCC ≥0.73), with a better relation for arable land than other LC classes. A poor relation was observed for potassium (LCCC = 0.35) in coniferous forest because of its shallow distribution in depth. We concluded that the simpler and cheaper spade method is an accurate method for topsoil sampling at the continental scale. From this study, it is clear that some improvements in the control of sampling depth and the accuracy of litter removal are needed, especially when monitoring forest soils and properties that change rapidly with depth. Spade sampling can help to expand the implementation of soil monitoring surveys at the continental scale at relatively low sampling cost. Highlights: Spade and gouge auger sampling methods were compared to monitor topsoil properties in the LUCAS Survey.The gouge auger is the method of choice for properties with patchy and shallow distribution.The spade method is efficient if sampling depth and litter removal are carefully controlled.Spade sampling can expand topsoil monitoring at continental scale at relatively low sampling cost. [ABSTRACT FROM AUTHOR]

Soil microbial diversity has major influences on ecosystem functions and services. However, due to its complexity and uneven distribution of abundant and rare taxa, quantification of soil microbial diversity remains challenging and thereby impeding its integration into long-term monitoring programs. Using metabarcoding, we analyzed soil bacterial and fungal communities at 30 long-term soil monitoring sites from the three land-use types arable land, permanent grassland, and forest with a yearly sampling between snowmelt and first fertilization over five years. Unlike soil microbial biomass and alpha-diversity, microbial community compositions and structures were site- and land-use-specific with CAP reclassification success rates of 100%. The temporally stable site core communities included 38.5% of bacterial and 33.1% of fungal OTUs covering 95.9% and 93.2% of relative abundances. We characterized bacterial and fungal core communities and their land-use associations at the family-level. In general, fungal families revealed stronger land-use associations as compared to bacteria. This is likely due to a stronger vegetation effect on fungal core taxa, while bacterial core taxa were stronger related to soil properties. The assessment of core communities can be used to form cultivation-independent reference lists of microbial taxa, which may facilitate the development of microbial indicators for soil quality and the use of soil microbiota for long-term soil biomonitoring., (© The Author(s) 2021. Published by Oxford University Press on behalf of FEMS.)