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

Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region: The role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling

SOC is the most important indicator of soil fertility and monitoring its space-time changes is a prerequisite to establish strategies to reduce soil loss and preserve its quality. Here we modelled the topsoil (0–0.3 m) SOC concentration of the cultivated area of Sicily in 1993 and 2008. Sicily is an extremely variable region with a high number of ecosystems, soils, and microclimates. We studied the role of time and land use in the modelling of SOC, and assessed the role of remote sensing (RS) covariates in the boosted regression trees modelling. The models obtained showed a high pseudo-R2 (0.63–0.69) and low uncertainty (s.d. < 0.76 g C kg− 1 with RS, and < 1.25 g C kg− 1 without RS). These outputs allowed depicting a time variation of SOC at 1 arcsec. SOC estimation strongly depended on the soil texture, land use, rainfall and topographic indices related to erosion and deposition. RS indices captured one fifth of the total variance explained, slightly changed the ranking of variance explained by the non-RS predictors, and reduced the variability of the model replicates. During the study period, SOC decreased in the areas with relatively high initial SOC, and increased in the area with high temperature and low rainfall, dominated by arables. This was likely due to the compulsory application of some Good Agricultural and Environmental practices. These results confirm that the importance of texture and land use in short-term SOC variation is comparable to climate. The present results call for agronomic and policy intervention at the district level to maintain fertility and yield potential. In addition, the present results suggest that the application of RS covariates enhanced the modelling performance

Can animal manure be used to increase soil organic carbon stocks in the Mediterranean as a mitigation climate change strategy?

Soil organic carbon (SOC) plays an important role on improving soil conditions and soil functions. Increasing land use changes have induced an important decline of SOC content at global scale. Increasing SOC in agricultural soils has been proposed as a strategy to mitigate climate change. Animal manure has the characteristic of enriching SOC, when applied to crop fields, while, in parallel, it could constitute a natural fertilizer for the crops. In this paper, a simulation is performed using the area of Catalonia, Spain as a case study for the characteristic low SOC in the Mediterranean, to examine whether animal manure can improve substantially the SOC of agricultural fields, when applied as organic fertilizers. Our results show that the policy goals of the 4x1000 strategy can be achieved only partially by using manure transported to the fields. This implies that the proposed approach needs to be combined with other strategies.Comment: Proc. of EnviroInfo 2020, Nicosia, Cyprus, September 2020. arXiv admin note: text overlap with arXiv:2006.0912

The multidrug resistance 1 (MDR1) gene polymorphism G-rs3789243-A is not associated with disease susceptibility in Norwegian patients with colorectal adenoma and colorectal cancer; a case control study

<p>Abstract</p> <p>Background</p> <p>Smoking, dietary factors, and alcohol consumption are known life style factors contributing to gastrointestinal carcinogenesis. Genetic variations in carcinogen handling may affect cancer risk. The multidrug resistance 1(<it>MDR1/ABCB1</it>) gene encodes the transport protein P-glycoprotein (a phase III xenobiotic transporter). P-glycoprotein is present in the intestinal mucosal lining and restricts absorption of certain carcinogens, among these polycyclic aromatic hydrocarbons. Moreover, P-glycoprotein transports various endogenous substrates such as cytokines and chemokines involved in inflammation, and may thereby affect the risk of malignity. Hence, genetic variations that modify the function of P-glycoprotein may be associated with the risk of colorectal cancer (CRC). We have previously found an association between the <it>MDR1 </it>intron 3 G-rs3789243-A polymorphism and the risk of CRC in a Danish study population. The aim of this study was to investigate if this <it>MDR1 </it>polymorphism was associated with risk of colorectal adenoma (CA) and CRC in the Norwegian population.</p> <p>Methods</p> <p>Using a case-control design, the association between the <it>MDR1 </it>intron 3 G-rs3789243-A polymorphism and the risk of colorectal carcinomas and adenomas in the Norwegian population was assessed in 167 carcinomas, 990 adenomas, and 400 controls. Genotypes were determined by allelic discrimination. Odds ratio (OR) and 95 confidence interval (95% CI) were estimated by binary logistic regression.</p> <p>Results</p> <p>No association was found between the <it>MDR1 </it>polymorphism (G-rs3789243-A) and colorectal adenomas or cancer. Carriers of the variant allele of MDR1 intron 3 had odds ratios (95% CI) of 0.97 (0.72–1.29) for developing adenomas, and 0.70 (0.41–1.21) for colorectal cancer, respectively, compared to homozygous wild type carriers.</p> <p>Conclusion</p> <p>The <it>MDR1 </it>intron 3 (G-rs3789243-A) polymorphism was not associated with a risk of colorectal adenomas or carcinomas in the present Norwegian study group. Thus, this <it>MDR1 </it>polymorphism does not seem to play an important role in colorectal carcinogenesis in this population.</p

Deep Sequencing Whole Transcriptome Exploration of the σE Regulon in Neisseria meningitidis

Bacteria live in an ever-changing environment and must alter protein expression promptly to adapt to these changes and survive. Specific response genes that are regulated by a subset of alternative σ70-like transcription factors have evolved in order to respond to this changing environment. Recently, we have described the existence of a σE regulon including the anti-σ-factor MseR in the obligate human bacterial pathogen Neisseria meningitidis. To unravel the complete σE regulon in N. meningitidis, we sequenced total RNA transcriptional content of wild type meningococci and compared it with that of mseR mutant cells (ΔmseR) in which σE is highly expressed. Eleven coding genes and one non-coding gene were found to be differentially expressed between H44/76 wildtype and H44/76ΔmseR cells. Five of the 6 genes of the σE operon, msrA/msrB, and the gene encoding a pepSY-associated TM helix family protein showed enhanced transcription, whilst aniA encoding a nitrite reductase and nspA encoding the vaccine candidate Neisserial surface protein A showed decreased transcription. Analysis of differential expression in IGRs showed enhanced transcription of a non-coding RNA molecule, identifying a σE dependent small non-coding RNA. Together this constitutes the first complete exploration of an alternative σ-factor regulon in N. meningitidis. The results direct to a relatively small regulon indicative for a strictly defined response consistent with a relatively stable niche, the human throat, where N. meningitidis resides

Transcriptome Analysis of Neisseria meningitidis in Human Whole Blood and Mutagenesis Studies Identify Virulence Factors Involved in Blood Survival

During infection Neisseria meningitidis (Nm) encounters multiple environments within the host, which makes rapid adaptation a crucial factor for meningococcal survival. Despite the importance of invasion into the bloodstream in the meningococcal disease process, little is known about how Nm adapts to permit survival and growth in blood. To address this, we performed a time-course transcriptome analysis using an ex vivo model of human whole blood infection. We observed that Nm alters the expression of ≈30% of ORFs of the genome and major dynamic changes were observed in the expression of transcriptional regulators, transport and binding proteins, energy metabolism, and surface-exposed virulence factors. In particular, we found that the gene encoding the regulator Fur, as well as all genes encoding iron uptake systems, were significantly up-regulated. Analysis of regulated genes encoding for surface-exposed proteins involved in Nm pathogenesis allowed us to better understand mechanisms used to circumvent host defenses. During blood infection, Nm activates genes encoding for the factor H binding proteins, fHbp and NspA, genes encoding for detoxifying enzymes such as SodC, Kat and AniA, as well as several less characterized surface-exposed proteins that might have a role in blood survival. Through mutagenesis studies of a subset of up-regulated genes we were able to identify new proteins important for survival in human blood and also to identify additional roles of previously known virulence factors in aiding survival in blood. Nm mutant strains lacking the genes encoding the hypothetical protein NMB1483 and the surface-exposed proteins NalP, Mip and NspA, the Fur regulator, the transferrin binding protein TbpB, and the L-lactate permease LctP were sensitive to killing by human blood. This increased knowledge of how Nm responds to adaptation in blood could also be helpful to develop diagnostic and therapeutic strategies to control the devastating disease cause by this microorganism

Variazioni di carbonio organico nei suoli italiani dal 1979 al 2008

I suoli contengono circa tre volte la quantit\ue0 di carbonio disponibile a livello mondiale nella vegetazione e circa il doppio di quella presente in atmosfera. Tuttavia il carbonio organico del suolo (SOC) si \ue8 ridotto in molte aree, mentre \ue8 stato rilevato un aumento della CO2 atmosferica. Ricerche recenti hanno dimostrato che sono stati i cambiamenti di uso e gestione del suolo a provocare le maggiori perdite di SOC nel recente passato, piuttosto che le pi\uf9 alte temperature e i cambiamenti delle precipitazioni conseguenti il cambiamento climatico. Lo scopo principale di questo lavoro \ue8 quello di stimare le variazioni del contenuto di carbonio organico dei suoli (carbon stock, CS) in Italia durante le ultime 3 decadi (dal 1979 al 2008) e di legarlo ai cambiamenti di uso del suolo. Lo studio ha come fine anche quello di studiare le relazioni tra SOC e i fattori della pedogenesi (pedoclima, morfologia, litologia e uso del suolo). La Banca Dati dei Suoli d\u2019Italia \ue8 stata la principale fonte di informazione. Il CS \ue8 stato calcolato a partire dai dati di SOC, densit\ue0 apparente e scheletro, i quali sono stati riferiti ai primi 50 cm di suolo, ottenendo un solo valore per ogni osservazione puntuale per mezzo della media pesata sulla base della profondit\ue0 degli orizzonti. Una serie di attributi geografici sono stati utilizzati per spazializzare le informazioni puntuali, in particolare il DEM (100 m) e le derivate classi morfologiche SOTER, le Soil Region d\u2019Italia (scala di riferimento 1:5.000000), i gruppi litologici dei Sistemi di Terre Italiani (scala di riferimento 1:500.000), i regimi di umidit\ue0 e temperatura del suolo (mappe raster con pixel di 1 km), l\u2019uso del suolo (progetto CORINE land cover, scala di riferimento 1:100.000; CORINE 2009) a due date di riferimento 1990 e 2000 e una carta di uso del suolo aggiornata al 2008 a partire da quella 2000, utilizzando punti di osservazione a terra. Il metodo di interpolazione utilizzato \ue8 stato quello della regressione multipla lineare (MLR), con il CS come variabile target e gli attributi geografici come variabili predittive. Un\u2019analisi statistica di base \ue8 stata realizzata per indagare singolarmente le relazioni fra le variabili predittive considerate e il CS. Infine \ue8 stato trovato un modello generale di regressione lineare multipla, considerando insieme tutte le variabili predittive. Le migliori variabili predittive sono state selezionate con una step-wise regression, utilizzando l\u2019Akaike Information Criterion (AIC) come criterio di selezione delle migliori variabili e del miglior modello finale. Il modello finale ottenuto considerava le seguenti variabili predittive: i) le decadi, ii) l\u2019uso del suolo, iii) le classi morfologiche SOTER, iv) le Soil Region, v) i regimi di temperatura del suolo, vi) i regimi di umidit\ue0 del suolo, vii) i gruppi litologici dei Sistemi di Terre, viii) la temperatura del suolo, ix) l\u2019indice di aridit\ue0 del suolo (giorni di suolo secco), e x) la quota. Nel modello \ue8 stata considerata anche l\u2019interazione fra la decade e l\u2019uso del suolo. I risultati indicano che il CS \ue8 altamente correlato con i principali raggruppamenti di uso del suolo (foreste, pascoli, aree agricole), con i regimi di umidit\ue0 e temperatura del suolo, con la litologia, con le classi morfologiche, ed \ue8 diminuito notevolmente nella seconda decade, mentre si \ue8 registrato un debole recupero fra la seconda e la terza decade, passando da 3,32 Pg, a 2,74 Pg e a 2,93 Pg rispettivamente

Soil erosion risk, Sicilian Region (1:250,000)

Assessing the risk of soil erosion caused by water at the regional level is important for current and future planning of land use and environmental actions to combat land degradation. The gravity of the risk depends not only on the rate of soil erosion by water, but also on other factors, primarily soil depth and workability of the underlying rocks and sediments, which may be used to calculate the eroded soil. We estimate the rate of erosion by water (tons ha-1 year-1) applying the Universal Soil Loss Equation model. The map of soil content (tons ha21) to the effective rooting depth was divided by the map of soil erosion rate to obtain the risk of erosion by water in Sicily, expressed in terms of years of complete loss of soil cover. This map was intersected with a map of workability of the underlying bedrock to give advice on where the cost of soil recovery by deep ripping and rock grinding are very high. 8382.9 km2 (32.6% of the Sicilian territory) were rated as at high or very high risk (< 100 years), of which 1230.9 km2 developed on bedrock with low workability and so very costly to be recovered

The influence of climate change on the soil organic carbon content in Italy from 1961 to 2008

Soils are the biggest carbon store in theworld (1500 Gt, e.g. 1.5 71021 g). The European Commission indicates the accounting of soil organic carbon (SOC) variations in space and time as the first step in the strategy for soil protection. It is indeed necessary in evaluating the risk of soil organicmatter decline and soil biodiversity decline, andwhen evaluating the role played by soils in global CO2 accounting. Previousmaps of SOC variations in Italy did not consider the direct effect of climate. There is a marked inter-dependence between SOC and climate. SOC increaseswith the increase in precipitations and decreaseswith a rise in temperatures. It is also known that land use and management have a bigger impact on SOC than climate. The aim of this work is to understand to what extent the SOC variations occurring in Italy from 1961 to 2008 could be explained by climate change. The soil database of Italy was the source of information for SOC content: 17,817 observations (3082 before and 14,735 after 31 Dec 1990). SOC contentwas referred to the first 50 cmof soil depth, one single data obtained byweighted horizon thickness. SOC content was expressed as percentage by weight (dag kg 121) analyzed by the Walkley\u2013 Black procedure and converted to ISO standard. The CRA\u2013CMA (Research Unit for Climatology andMeteorology Applied to Agriculture) databasewas the source of information for climatic data.Weconsidered themean annual temperature (MAT) andmeanvalue of total annual precipitation(MAP) of the two periods 1961\u20131990 and 1991\u2013 2006, and we mapped them by regression kriging with elevation and latitude as predictors. The climate change between the two periodswas characterized by a generalMAT increase,whichwas greater at lower altitudes and higher latitudes. The precipitation generally decreased, with some local exceptions. Some linear regression analyseswere used to investigate the relationship between SOC content and climate/land use. Temperatures had most relevant impact on SOCwith an inverse correlation. SOC contentwas directly correlatedwith precipitations on arable lands and inversely inforests andmeadows. Two generalmultiple linear regression analyses considered all the pedogenesis factors and: either by time periods (1979\u20131990; 1991\u20132009), model 1; or byMAT andMAP, model 2. The twomodels both had lowprecision(multipleR-squared=0.26\u20130.27; RMSE=1.42; IoA=0.61), but very different accuracies. Model 1 correctly predicted the mean SOC values for the 3 land uses in the 2 periods, detecting a significative decrease in all three land uses. Model 2 was not accurate every time. SOC decreases estimated with model 2 were always significatively lower than the observed ones. Model 2 did not estimate a significative SOC decrease in forests. Climate change had a general lowinfluence on SOC variations. The relatively higher climatic influence occurred inmeadows and in agricultural areas with a moderate or highMAP decrease (b 12100 mm/y) and a moderate to high MAT increase (N0.62 \ub0C). Other changes, probably linked to land management, need to be investigated to explain SOC variations