SOILS WITH HIGH ORGANIC CARBON STORAGE CAPACITY IN DEPTH

Most studies about soil organic carbon (OC) stock focus on the topsoil storage capacity, however, it has been proved that OC can reach relatively high values also in depth. The aim of this work was a preliminary investigation of the soil types with a high OC content in depth and the relationship with the main pedogenetic factors. The dataset was the 1,414 Italian National Soil Typologies (STU). The selected attributes were: mean value of OC in the superficial functional horizon (L1); weighted average value between 50 and 100 cm (L2) and under 100 cm (L3); WRB classification; main lithology, morphology and land-use. About 92% of typologies had more than 0.58% of OC in L1, about 30% in L2, and 10% in L3. The highest OC contents were in L2 of Histosols, Umbrisols, Podzols, Vertisols, Andosols, and in L3 of Vertisols, Andosols, Fluvisols. STU on volcanic rocks, slope and residual deposits showed relatively higher accumulation in L2; soils on delta plane, lacustrine and alluvial deposits, both in L2 and L3. STU on upland plains, transitional areas with plateau in the mountain, high gradient mountains and low plains, showed higher OC content. Land-use was not significantly connected with OC content in depth. About 65% of the studied territory (47% of Italian surface) had a relatively high CO content in L2, and about 2% in L3. The main processes connected to soil CO storage capacity in depth were morphological, namely colluvium and alluvium, as well as pedological, in particular, podzolization and andisolization

Comparing different approaches - data mining, geostatistic, and deterministic pedology - to assess the frequency of WRB Reference Soil Groups in the Italian soil regions

Estimating frequency of soil classes in map unit is always affected by some degree of uncertainty, especially at small scales, with a larger generalization. The aim of this study was to compare different possible approaches - data mining, geostatistic, deterministic pedology - to assess the frequency of WRB Reference Soil Groups (RSG) in the major Italian soil regions. In the soil map of Italy (Costantini et al., 2012), a list of the first five RSG was reported in each major 10 soil regions. The soil map was produced using the national soil geodatabase, which stored 22,015 analyzed and classified pedons, 1,413 soil typological unit (STU) and a set of auxiliary variables (lithology, land-use, DEM). Other variables were added, to better consider the influence of soil forming factors (slope, soil aridity index, carbon stock, soil inorganic carbon content, clay, sand, geography of soil regions and soil systems) and a grid at 1 km mesh was set up. The traditional deterministic pedology assessed the STU frequency according to the expert judgment presence in every elementary landscape which formed the mapping unit. Different data mining techniques were firstly compared in their ability to predict RSG through auxiliary variables (neural networks, random forests, boosted tree, supported vector machine (SVM)). We selected SVM according to the result of a testing set. A SVM model is a representation of the examples as points in space, mapped so that examples of separate categories are divided by a clear gap that is as wide as possible. The geostatistic algorithm we used was an indicator collocated cokriging. The class values of the auxiliary variables, available at all the points of the grid, were transformed in indicator variables (values 0, 1). A principal component analysis allowed us to select the variables that were able to explain the largest variability, and to correlate each RSG with the first principal component, which explained the 51% of the total variability. The principal component was used as collocated variable. The results were as many probability maps as the estimated WRB classes. They were summed up in a unique map, with the most probable class at each pixel. The first five more frequent RSG resulting from the three methods were compared. The outcomes were validated with a subset of the 10% of the pedons, kept out before the elaborations. The error estimate was produced for each estimated RSG. The first results, obtained in one of the most widespread soil region (plains and low hills of central and southern Italy) showed that the first two frequency classes were the same for all the three methods. The deterministic method differed from the others at the third position, while the statistical methods inverted the third and fourth position. An advantage of the SVM was the possibility to use in the same elaboration numeric and categorical variable, without any previous transformation, which reduced the processing time. A Bayesian validation indicated that the SVM method was as reliable as the indicator collocated cokriging, and better than the deterministic pedological approach

USING WRB TO MAP THE SOIL SYSTEMS OF ITALY

Aim of this work was to test the 2010 version of the WRB soil classification for compilating a map of the soil systems of Italy at 1:500,000 scale. The source of data was the national geodatabase storing information on 1,414 Soil Typological Units (STUs). Though, basically, we followed WRB criteria to prioritize soil qualifiers, however, it was necessary to work out an original methodology in the map legend representation to reproduce the high variability inside each delineation meanwhile avoiding any loss of information. Each map unit may represent a combination of three codominant STUs at the most. Dominant STUs were assessed summing up the occurrence of STUs in the Land Components (LCs) of every soil system, where each LC is a specific combination of morphology, lithology and land cover. STUs were classified according to the WRB soil classification system, at the third level, that is, reference soil group and first two qualifiers, when possible. Since the large number of delineations, map units grouping was needed to make the map more legible. Legend colours were organized according to soil regions groups firstly, then by considering the highest level of soil classification, so resulting a nidificated legend. The map showed 3,357 polygons and 704 map units. The most common STU were Calcaric Cambisols, by far followed by Calcaric Regosols, Eutric Cambisols, Haplic Calcisols, Vertic Cambisols, Cutanic Luvisols, Leptic Pheozems, Chromic Luvisols, Dystric Cambisols, Fluvic Cambisols, and others STUs belonging to almost all the WRB soil references. Keywords: geodatabase, soil system

Comparing Different Approaches - Data Mining, Geostatistic, and Deterministic Pedology - to Assess the Frequency of WRB Reference Soil Groups in the Italian Soil Regions

The assessment of class frequency in soil map legends is affected by uncertainty, especially at small scales, where generalization is larger. The aim of this study was to test the hypothesis that data mining or geostatistic techniques provide better estimation of class frequency than traditional deterministic pedology in a national soil map. In the map of Italian soil regions compiled at 1:5,000,000 reference scale, soil classes were the WRB Reference Soil Groups (RSGs). Different data mining techniques, namely neural networks, random forests, boosted tree, classification and regression tree, supported vector machine (SVM), were tested and the last one gave the best RSGs predictions, using selected auxiliary variables and 22,015 classified soil profiles. Given the categorical target variable, the multi-collocated indicator cokriging was the algorithm chosen for the geostatistic approach. The first five more frequent RSGs resulting from the three methods were compared. The outcomes were validated with a Bayesian approach on a subset of 10% of geographically representative profiles, kept out before the elaborations. The most frequent classes were uniformly predicted by the three methods, which instead differentiated notably for the classes with a lower occurrence. The Bayesian validation indicated that the SVM method was as reliable as the multi-collocated indicator cokriging, and both more than the deterministic pedological approach. An advantage of the SVM was the possibility to use numeric and categorical variable in the same elaboration, without any previous transformation, which notably reduced the processing time

A Changing Temperature Response With Elevation For Lagarostrobos Franklinii In Tasmania, Australia

A network of seven Huon pine ring-width chronologies is constructed from sites ranging in elevation from 200 to 950 metres above sea level in western Tasmania. The chronologies are analysed individually and collectively to explore Huon pine‘s response to climate as a function of elevation. Three chronologies from greater than 700 metres in elevation exhibit a strong, direct response to temperature for most growing season months (p<0.05), while three from below 700 metres exhibit a weaker, direct response to growing-season temperature, and a strong, inverse relationship with temperature of the prior season of growth, also significant at the 0.05 level. Moisture availability at these temperate rainforest sites is less growth-limiting than temperature, and significant correlations for January (inverse) and April (direct) of the year of growth largely reflect the inter-relationships between temperature, precipitation and cloudiness, and their combined influence on photosynthesis, particularly at higher-elevation sites. A rotated Principal Component Analysis reveals a clear grouping of the high and low-elevation chronologies, represented by the first and second eigenvectors, respectively. The 700 metre Lake Marilyn Low chronology is revealed to be a transitional site between the two groupings, and likely reflects an important climatic ecotone where both temperature and photosynthetically-active radiation drop below optimum levels for the species, and begin to directly inhibit growth. Tasmania's west coast climate has been shown to exhibit a distinct vertical structure, exemplified by a subsidence-inversion layer above 900 metres. Temperature increases slightly with altitude above 930 metres (the elevation at which a peak in daily minimum and maximum humidity levels is observed) before decreasing again. A dense, orographically-generated cloud-zone of reduced light and temperature has a mean altitude between 700 and 900 metres, with the steepest drop in both air and soil temperature exhibited between 850 and 930 metres. This structure can account for Huon pine‘s changing response to climate with elevation as described in this paper, and reinforces the importance of careful site selection for dendroclimatic research. In the case of reconstructing warm-season temperature from Tasmanian Huon pine, the desired signal might be maximised through sampling at the few rare, subalpine stands which have been located in western Tasmania. The great length afforded by the low-elevation Huon pine resource may ultimately yield a far more detailed reconstruction of regional climate throughout the Holocene, with respect to a vertical profile, following the development of more sound, mechanistically-based response models

Relevance of the Lin's and Host hydropedological models to predict grape yield and wine quality

The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy) on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI), and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ&lt;sup&gt;13&lt;/sup&gt;C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing. &lt;br&gt;&lt;/br&gt; The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW) during the growing season differed considerably between the vineyards and increased significantly along the three positions on slope in both vineyards. The water accumulation along slope occurred in every year, even during the very dry 2006. The installation of indicators of reduction in soils (IRIS) tubes allowed confirmation of the occurrence of reductive processes in the most shallow soil. &lt;br&gt;&lt;/br&gt; Both Sangiovese grape yield and quality of wine were influenced by the interaction between TSW content and salinity, sometimes contrary to expectations. Therefore, the studied hydropedological models were not relevant to predict grape yield and wine quality in all the hydrological functional units. The diffusion of hydropedological models in precision viticulture could be boosted considering salinity along with topography and soil hydrological characteristics

severe insulin resistence in disguise: a familial case of reactive hypoglycemia associated with a novel heterozygous INSR mutation

AIM: Hypoglycemia in childhood is very rare and can be caused by genetic mutations or insulin-secreting neoplasms. Postprandial hypoglycemia has previously been associated with insulin receptor (INSR) gene mutations. We aimed to identify the cause of postprandial hypoglycemia in a 10-year-old boy. SUBJECTS: We studied the symptomatic proband and his apparently asymptomatic mother and elder brother. All of them were lean. METHODS: Metabolic screening of the proband included a 5-hour oral glucose tolerance test (OGTT), angio-magnetic resonance imaging, and 18 F-dihydroxyphenylalanine positron emission tomography/computed tomography imaging of the pancreas. INSR gene sequencing and in vitro functional studies of a novel INSR mutation were also undertaken. RESULTS: Fasting hyperinsulinemia was detected during metabolic screening, and 5-hour OGTT showed hypoglycemia at 240' in the proband, his mother, and brother. Pancreatic imaging showed no evidence of neoplasia. Acanthosis nigricans with high fasting insulin levels in the proband suggested severe insulin resistance and prompted INSR gene sequencing, which revealed the novel, heterozygous p.Phe1213Leu mutation in the patient and his family members. In vitro studies showed that this mutation severely impairs insulin receptor function by abolishing tyrosine kinase activity and downstream insulin signaling. CONCLUSIONS: The identification of etiological cause of hypoglycemia in childhood may be challenging. The combination of fasting hyperinsulinemia with acanthosis nigricans in a lean subject with hypoglycemia suggests severe insulin resistance and warrants INSR gene screening

Elevated miR-34a expression and altered transcriptional profile are associated with adverse electromechanical remodeling in the heart of male rats exposed to social stress

This study investigated epigenetic risk factors that may contribute to stress-related cardiac disease in a rodent model. Experiment 1 was designed to evaluate the expression of microRNA-34a (miR-34a), a known modulator of both stress responses and cardiac pathophysiology, in the heart of male adult rats exposed to a single or repeated episodes of social defeat stress. Moreover, RNA sequencing was conducted to identify transcriptomic profile changes in the heart of repeatedly stressed rats. Experiment 2 was designed to assess cardiac electromechanical changes induced by repeated social defeat stress that may predispose rats to cardiac dysfunction. Results indicated a larger cardiac miR-34a expression after repeated social defeat stress compared to a control condition. This molecular modification was associated with increased vulnerability to pharmacologically induced arrhythmias and signs of systolic left ventricular dysfunction. Gene expression analysis identified clusters of differentially expressed genes in the heart of repeatedly stressed rats that are mainly associated with morphological and functional properties of the mitochondria and may be directly regulated by miR-34a. These results suggest the presence of an association between miR-34a overexpression and signs of adverse electromechanical remodeling in the heart of rats exposed to repeated social defeat stress, and point to compromised mitochondria efficiency as a potential mediator of this link. This rat model may provide a useful tool for investigating the causal relationship between miR-34a expression, mitochondrial (dys)function, and cardiac alterations under stressful conditions, which could have important implications in the context of stress-related cardiac disease