Piemonte Rurale 2019. Rapporto Annuale dell'Osservatorio Rurale

Osservatorio rurale. Rapporto annuale. Piemonte rurale 2019- Indice #6- Il settore agricolo e agroalimentare in Piemonte #12- Le aree rurali #40- Le politiche #6

Impact of stochastic hydrological forcing on root distribution and functioning

The objective of this thesis is to study and model the influence of climate and soil on the dynamics of root water uptake and root development. The assessment of the vertical root distribution and functioning by means of simple parameters linked to hydrologic, pedologic and vegetation characteristics can be useful for several purposes, both practical and theoretical. The more important novelty brought by this work is the analysis of the effect of the stochasticity of the hydrological forcing on these root dynamics. The stochastic ecohydrological models that we have developed show how different profiles of mean soil moisture influence the shape of the root system and favour different strategies of water uptak

Osservatorio Rurale. Rapporto Annuale. Piemonte Rurale 2021

Osservatorio Rurale. Rapporto Annuale. Piemonte Rurale 2021- Indice #4- Capitolo 1. L'agricoltura in Piemonte #8- Capitolo 2. Le aree rurali #16- Capitolo 3. Le politiche #5

Mean root depth estimation at landslide slopes

tPlant rooting systems affect slope stability through the soil reinforcement given by the root network.The vertical root distribution in particular is crucial for the assessment of the critical slip surface in slopestability analyses. We propose here an expeditious way to assess the major characteristics of the rootsystem at landslide slopes.More in detail, we extend and validate an ecohydrological model proposed for flat terrain and water-dependent ecosystems by Laio et al. (2006). This model has the merit to use readily available climaticand pedologic descriptors to predict the mean root depth, but its extension to hillslopes in semi-humidenvironments requires validation. The model has been improved and then tested on a case study innorthern Tuscany (Italy) which considers 17 landslide sites where the tree rooting systems have beenmeasured.The results show a quite good match between observed and modeled mean root depths. The accuracyof the results largely depends on the improvements brought to the model in the parameters estimationphase, in particular through the application of the Curve Number method and through the refinement ofthe definition of the growing season. The results show that in 14 cases out of 17 the error is lower than30%. Furthermore, the error becomes lower than 30% at all sites if we take into account differences amongsoils in the estimation of the portion of precipitation which infiltrates into the soil. These results provethe potential of the proposed method: using few and quite readily available parameters, it allows one todetermine the mean root depths of vegetation with good accuracy: an important parameter for stabilityassessment of vegetated slopes on a large scal

The signature of randomness in riparian plant root distributions

Known as “the hidden half”, plant roots are fundamental contributors to the riparian ecosystem functioning. Roots show an extraordinary architectural complexity that recalls their remarkable ability to adapt to environmental heterogeneity, resources availability, and climate. In fluvial environments, phreatophytes and hydrophytes cope with flow and sediment processes, and hydrotropism and aerotropism are the main drivers for root growth. In this work, we show how the vertical root density distribution in riparian plants is the result of how plants respond to the random fluctuations of river flows. A root data set from field and controlled outdoor experiments is used in combination with a physically based analytical model to demonstrate that the root vertical density distribution can be ascribed to the interplay of randomness and determinism in a simple mathematical form. The shape of the distribution reflects the profitability of plant roots to grow in different soil layers depending on the soil moisture availability. For the first time, this model helps understanding in an analytical manner the adaptation strategy of plant roots to different scenarios, paving the way for the comprehension of the effects of future changes in climate and environmental conditions

Modelling water uptake efficiency of root systems

Water uptake is crucial for plant productivity. Trait based breeding for more water efficient crops will enable a sustainable agricultural management under specific pedoclimatic conditions, and can increase drought resistance of plants. Mathematical modelling can be used to find suitable root system traits for better water uptake efficiency defined as amount of water taken up per unit of root biomass. This approach requires large simulation times and large number of simulation runs, since we test different root systems under different pedoclimatic conditions