Login / Signup

Geography and habitat predominate over climate influences on arbuscular mycorrhizal fungal communities of mid-European meadows.

Veronika ŘezáčováRenata SlavíkováTereza KonvalinkováLenka ZemkováMilan ŘezáčMilan GryndlerPetr ŠmilauerHana GryndlerováHana HršelováPetra BukovskáJan Jansa
Published in: Mycorrhiza (2019)
Despite the crucial importance of arbuscular mycorrhizal fungi (AMF) for numerous processes within terrestrial ecosystems, knowledge of the determinants of AMF community structure still is limited, mainly because of the limited scope of the available individual case studies which often only include a few environmental variables. Here, we describe the AMF diversity of mid-European meadows (mown or regularly cut grasslands, or recently abandoned lands where grasslands established spontaneously) within a considerably heterogeneous landscape over a scale of several hundred kilometers with regard to macroclimatic, microclimatic, and soil parameters. We include data describing the habitat (including vegetation type), geography, and climate, and test their contribution to the structure of the AMF communities at a regional scale. We amplified and sequenced the ITS 2 region of the ribosomal DNA operon of the AMF from soil samples using nested PCR and Illumina pair-end amplicon sequencing. Habitat (especially soil pH) and geographical parameters (spatial distance, altitude, and longitude) were the main determinants of the structure of the AMF communities in the meadows at a regional scale, with the abundance of genera Septoglomus, Paraglomus, Archaeospora, Funneliformis, and Dominikia driving the main response. The effects of climate and vegetation type were not significant and were mainly encompassed within the geography and/or soil pH effects. This study illustrates how important it is to have a large set of environmental metadata to compare the importance of different factors influencing the AMF community structure at large spatial scales.
Keyphrases
  • climate change
  • human health
  • healthcare
  • plant growth
  • single cell
  • risk assessment
  • single molecule
  • cell free
  • life cycle
  • circulating tumor
  • big data
  • deep learning