Impact of conservation tillage and organic farming on the diversity of arbuscular mycorrhizal fungi

Summary

Communities of arbuscular mycorrhizal fungi (AMF) are strongly affected by land use intensity and soil type. The impact of tillage practices on AMF communities is still poorly understood, especially in organic farming systems. Our objective was to investigate the impact of soil cultivation on AMF communities in organically managed clay soils of a long-term field experiment located in the Sissle valley (Frick, Switzerland) where two different tillage (reduced and conventional mouldboard plough tillage) and two different types of fertilization (farmyard manure & slurry, or slurry only) have been applied since 2002. In addition, a permanent grassland and two conventionally managed croplands situated in the neighborhood of the experiment were analyzed as controls. Four different soil depths were studied including topsoils (0e10 and 10e20 cm) of different cultivation regimes and undisturbed sub-soils (20e30 and 30 e40 cm). The fungi were directly isolated from field soil samples, and additionally spores were periodically collected from long-term trap culture (microcosm) systems. In total, >50,000 AMF spores were identified on the species level, and 53 AMF species were found, with 38 species in the permanent grassland, 33 each in the two reduced till organic farming systems, 28e33 in the regularly plowed organic farming systems, and 28e33 in the non-organic conventional farming systems. AMF spore density and species richness increased in the top-soils under reduced tillage as compared to the ploughed plots. In 10e20 cm also the ShannoneWeaver AMF diversity index was higher under reduced tillage than in the ploughed plots. Our study demonstrates that AMF communities in clay soils were affected by land use type, farming system, tillage as well as fertilization strategy and varying with soil depth. Several AMF indicator species especially for different land use types and tillage strategies were identified from the large data set.