Physical land degradation and loss of soil fertility: soil structural stability and bio-physical indicators

This study investigates the changes in soil fertility due to the different aggregate breakdown mechanisms and it analyses their relationships in different soil-plant systems, using physical aggregates behavior and organic matter (OM) changes as indicators. Three case studies were investigated: i) an organic agricultural soil, where a combined method, aimed to couple aggregate stability to nutrients loss, were tested; ii) a soil biosequence, where OM chemical characterisation and fractionation of aggregates on the basis of their physical behaviour were coupled and iii) a soils sequence in different phytoclimatic conditions, where isotopic C signature of separated aggregates was analysed. In agricultural soils the proposed combined method allows to identify that the severity of aggregate breakdown affected the quantity of nutrients lost more than nutrients availability, and that P, K and Mg were the most susceptible elements to water abrasion, while C and N were mainly susceptible to wetting. In the studied Chestnut-Douglas fir biosequence, OM chemical properties affected the relative importance of OM direct and indirect mechanisms (i.e., organic and organic-metallic cements, respectively) involved in aggregate stability and nutrient losses: under Douglas fir, high presence of carboxylate groups enhanced OM-metal interactions and stabilised aggregates; whereas under Chestnut, OM directly acted and fresh, more C-rich OM was preserved. OM direct mechanism seemed to be more efficient in C preservation in aggregates. The 13C natural abundance approach showed that, according to phytoclimatic conditions, stable macroaggregates can form both around partially decomposed OM and by organic-mineral interactions. In topsoils, aggregate resistance enhanced 13C-rich OM preservation, but in subsoils C preservation was due to other mechanisms, likely OM-mineral interactions. The proposed combined approach seems to be useful in the understanding of C and nutrients fate relates to water stresses, and in future research it could provide new insights into the complexity of soil biophysical processes.

Methods for the Quantification of Motor Stability for the Assessment of Fall Risk

The research field of the Thesis is the evaluation of motor variability and the analysis of motor stability for the assessment of fall risk. Since many falls occur during walking, a better understanding of motor stability could lead to the definition of a reliable fall risk index aiming at measuring and assessing the risk of fall in the elderly, in the attempt to prevent traumatic events. Several motor variability and stability measures are proposed in the literature, but still a proper methodological characterization is lacking. Moreover, the relationship between many of these measures and fall history or fall risk is still unknown, or not completely clear. The aim of this thesis is hence to: i) analyze the influence of experimental implementation parameters on variability/stability measures and understand how variations in these parameters affect the outputs; ii) assess the relationship between variability/stability measures and long- short-term fall history. Several implementation issues have been addressed. Following the need for a methodological standardization of gait variability/stability measures, highlighted in particular for orbital stability analysis through a systematic review, general indications about implementation of orbital stability analysis have been showed, together with an analysis of the number of strides and the test-retest reliability of several variability/stability numbers. Indications about the influence of directional changes on measures have been provided. The association between measures and long/short-term fall history has also been assessed. Of all the analyzed variability/stability measures, Multiscale entropy and Recurrence quantification analysis demonstrated particularly good results in terms of reliability, applicability and association with fall history. Therefore, these measures should be taken in consideration for the definition of a fall risk index.

A New Prediction Model for Slope Stability Analysis

The instability of river bank can result in considerable human and land losses. The Po river is the most important in Italy, characterized by main banks of significant and constantly increasing height. This study presents multilayer perceptron of artificial neural network (ANN) to construct prediction models for the stability analysis of river banks along the Po River, under various river and groundwater boundary conditions. For this aim, a number of networks of threshold logic unit are tested using different combinations of the input parameters. Factor of safety (FS), as an index of slope stability, is formulated in terms of several influencing geometrical and geotechnical parameters. In order to obtain a comprehensive geotechnical database, several cone penetration tests from the study site have been interpreted. The proposed models are developed upon stability analyses using finite element code over different representative sections of river embankments. For the validity verification, the ANN models are employed to predict the FS values of a part of the database beyond the calibration data domain. The results indicate that the proposed ANN models are effective tools for evaluating the slope stability. The ANN models notably outperform the derived multiple linear regression models.