Soil sampling based on field spatial variability of soil microbial indicators
2009
Peigné, Joséphine | Vian, Jean-François | Cannavacciuolo, Mario | Bottollier, B. | Chaussod, Rémi | Institut supérieur d'agriculture et d'agroalimentaire Rhône-Alpes (I.S.A.R.A.) | Ecole Supérieure d'Agriculture (Groupe ESA) | Microbiologie ; Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)
International audience
Afficher plus [+] Moins [-]anglais. Microbial indicators exhibit a high spatial heterogeneity which often masks comparison of the effects of different soil management treatments. It is therefore desirable to use a proper sampling design which integrates spatial heterogeneity at field level. Thus, the objectives were: (1) to study the spatial heterogeneity of biological and chemical soil variables, and (2) with obtained maps of spatial variability to test different sampling strategies to assess the usefulness of this ‘new’ soil map unit. 63 soil samples were collected according to a 10 m × 10 m grid on a 0.48 ha plot. On each of these samples, 10 variables were measured: soil water content, cation exchange capacity (CEC), organic carbon (OC) and total nitrogen (N), C/N, soil microbial biomass (SMB), labile soil organic matter (LOM), mineralisable C (Cmin) and N (Nmin), inverse of specific respiratory activity (1/SRA = SBM/Cmin). The spatial heterogeneity of each variable was charted with geostatistics. The biological variables exhibited spatial variability of the same order of magnitude as physicochemical parameters. From the maps, zones with different levels of organic matter, microbial biomass and specific respiratory activity were identified. The spatial patterns of SMB and SRA were related to CEC (positively for SMB and negatively for SRA), pointing out the effects of soil protection on microbial biomass and availability of organic substrates. The definition of these zones for a pool of variables (OC, N, SMB, LOM, CEC) is useful at 3 levels: (1) to record the initial values of the measured variables for each plot, (2) to integrate these zones as blocks in experimental design for future experiments, and (3) to focus analysis of specific biological mechanisms such as activity of micro-organisms.
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