Describing the vertical root distribution of alpine plants with simple climate, soil and plant attributes

Alejandro Gonzalez-Ollauri*, Csilla Hudek, Slobodan B. Mickovski, Davide Viglietti, Nicole Ceretto, Michele Freppaz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The vertical root distribution (VRD) in the soil remains unknown for most plant species, as studying root systems in different pedo-climatic settings is time-consuming and methodologically challenging. Yet, information on the VRD of different vegetation types is essential to understand better the biogeochemical processes occurring at the soil-plant-atmosphere continuum. The aim of this study was to describe the (VRD) of three dominant alpine, herbaceous plants (i.e. Euphrasia minima Jacq., Leucanthemopsis alpina L., and Poa alpina L.) on the basis of simple and easy-to-measure climate, soil, and plant attributes in order to test the validity of existing descriptive protocols and parametric ecohydrological models. The results showed that the VRD decreased with soil depth for the three plants and that it can be effectively described with a negative exponential equation. Key VRD parameters, such as the mean rooting depth, cross-sectional area at the root collar, and root biomass, were both site and species-specific but they were chiefly influenced by the attributes regulating the soil’s water mass balance. The existing parametric ecohydrological models were not able to portray successfully the VRD of the studied alpine plants but we found a strong correlation between empirical and parametric VRD models that establish a clear direction for future research. Future work should address the influence of the snowpack characteristics and the length of the snow-free and frozen ground periods on the soil’s ecohydrology and VRD in alpine ecosystems.
Original languageEnglish
Article number105305
Number of pages27
JournalCatena
Volume203
Early online date31 Mar 2021
DOIs
Publication statusPublished - Aug 2021

Keywords

  • root
  • model
  • ecohydrological
  • alpine
  • data mining

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