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Soil-inhabiting fungi can integrate soil physical indicators in multivariate analysis of Mediterranean agroecosystem dominated by old olive groves

Manici, L.M., Castellini, M., Caputo, F.
Ecological indicators 2019 pp. 105490
Ascomycota, Basidiomycota, Olea europaea, Xylella fastidiosa, agroecosystems, air, available water capacity, bacteria, correspondence analysis, desertification, discriminant analysis, environmental indicators, groves, multivariate analysis, olives, orchards, plant available water, soil fungi, soil texture, total organic carbon, Italy
A study on the relationships between fungi and physical indicators of the soil applying a multivariate approach was performed in an olive growing area affected by a recent outbreak in the Apulia region, caused by the bacterium Xylella fastidiosa. The study was made with a view to improving the decisional tools for selecting disease-decimated groves to be replaced with new olive trees. Relative quantities of rDNA-PCR amplicons targeting soil fungi, ascomycetes and basidiomycetes, and a series of soil physical indicators, which accounted for a proportion of water and air in the soil including total organic carbon or structure stability index, were assessed in twelve olive orchards at six sites across the Xylella infected area in the Salento region. Multiple correlation and canonical correspondence analysis led to identification of a series of soil physical and fungal indicators which were linearly correlated. Further discriminant analysis showed the selected set of variables was able to effectively discriminate sites and classes of plant available water capacity, whilst it discriminated poorly for soil texture. Even though soil fungi showed a relatively low weight compared to soil physical indicators based on the classification function from discriminant analysis, they showed a discriminant ability close to that of soil physical indicators. Therefore, as far as agro-environments on the verge of desertification are concerned, such as those in this study, soil fungi can be effectively associated to soil physical indicators for multivariate analysis of physical soil properties.