Paleoenvironmental reconstruction of Triassic floras from the Central North Sea

The Triassic sediments of the Central North Sea (CNS) are considered to have been deposited in a continental environment under a semi-arid climate. The Skagerrak Formation in particular, comprises an alternation of sandstone and mudstone members, the development of which is considered to be climatically driven. However, conflicting models exist as to how climate influences member deposition. Here we analyse the climatic signal using a multivariate statistical approach in which de-trended correspondence analysis (DCA) is applied to palynological observations to quantify environmental reconstruction. Using DCA it has been possible to define paleoecological groups and construct a relative hydrological state trend showing hydrological conditions within the centre of the CNS basin during the Triassic. The resultant trends reveal that the relationship between hydrological conditions in the basin and the development of individual sandstones and mudstone members is perhaps not a simple as indicated by existing models. In particular our data suggest that whilst influenced by broader climate trends, in the basin centre, there is no simple relationship between climate change and sandstone/mudstone development. The data also indicates that the Julius and Jonathan mudstone members were deposited under differing hydrological conditions. The DCA trends shown here also suggest that the Carnian Pluvial Episode (CPE) documented from the South Permian Basin and Tethys is not expressed in the CNS.

Reconstructing Herbivore Diets: A Multivariate Statistical Approach To Interpreting Compound-Specific Isotope Values

Stable nitrogen (N) isotope analysis of bulk tissues is a technique for reconstructing the diets of organisms. However, bulk nitrogen isotope (δ15N) values can be influenced by a variety of metabolic and environmental factors that can confound accurate dietary reconstruction. Compound-specific isotope analyses of amino acids (CSIA-AA) have demonstrated the power of the approach in understanding how the δ15N values of bulk collagen are assembled from the constituent AAs. Furthermore, by connecting these AA δ15N values within a robust biochemical framework interpretation of diet and environment are greatly enhanced. Several new proxies have emerged, built around selected AAs; however, the interconnectedness of AA biosynthetic pathways means that patterning of δ15N values across a wider suite of collagen AAs will occur under different environmental or dietary influences. This work seeks to test this idea by situating CSIA-AA within a robust statistical framework using principal component analysis (PCA) and Bayesian statistics to increase the interpretability of a wider range of AA δ15N values in terms of reconstructing herbivore diet. The model was tested using wild and domestic herbivores from the Neolithic settlements of Çatalhöyük (Turkey), Makriyalos (Greece), and Vaihingen (Germany) as case studies. It was found that at Makriyalos there was a sharp separation between domesticated and wild herbivores, which was present to a lesser extent at Çatalhöyük and not observed at Vaihingen. The case studies presented in this work demonstrate that multivariate statistical treatment of CSIA-AA data can deliver new insights into herbivore diet, exceeding those achievable with the Bayesian model.

Carbamazepine Levels Related to the Demographic Indicators in Groundwater of Densely Populated Area

Consumption of pharmaceuticals by people is growing. Carbamazepine (CBZ) is an extensively used anti-epileptic drug that is recalcitrant to degradation. As a result, CBZ has been widely detected in the aquatic ecosystem due to its daily consumption and drainage in sewage systems. Leakages from sewage networks and septic tanks may represent one of the main sources of CBZ in groundwater. In this study, CBZ concentrations in groundwater and their correlations with the demographic structure of the population were investigated in the densely populated Milan urban area. Seventy-six demographic variables were retrieved from the Italian Population and Housing census. Twenty-one groundwater samples were collected from unconfined and semi-confined aquifers of the Milan area and the concentration of CBZ was measured. Groundwater CBZ levels in both aquifers were associated with the demographic data within a circular buffer with a radius of 1.5 km. All data were analyzed using a multivariate statistical approach. The results showed a significant association (p < 0.05) between CBZ concentrations and specific demographic segments of the population. Higher CBZ concentrations were found to be associated with the population aged 70 years and over (aging index), and with families having children aged under 5 years (family index). In addition, the divorce index was correlated with the high concentration of CBZ, whereas the educated and sexagenarian population showed a negative correlation. Our results indicated that the contamination of CBZ follows the same pattern in unconfined and semi-confined aquifers, which are used for drinking water purposes in Milan area. Therefore, changing the CBZ consumption pattern or replacing CBZ with other drugs may strongly influence groundwater contamination of the investigated area.

NMR, RP-HPLC-PDA-ESI-MSn, and RP-HPLC-FD Characterization of Green and Oolong Teas (Camellia sinensis L.)

Untargeted (NMR) and targeted (RP-HPLC-PDA-ESI-MSn, RP-HPLC-FD) analytical methodologies were used to determine the bioactive components of 19 tea samples, characterized by different production processes (common tea and GABA tea), degrees of fermentation (green and oolong teas), and harvesting season (autumn and spring). The combination of NMR data and a multivariate statistical approach led to a statistical model able to discriminate between GABA and non-GABA teas and green and oolong teas. Targeted analyses showed that green and GABA green teas had similar polyphenol and caffeine contents, but the GABA level was higher in GABA green teas than in regular green tea samples. GABA oolong teas showed lower contents of polyphenols, caffeine, and amino acids, and a higher content of GABA, in comparison with non-GABA oolong teas. In conclusion, the results of this study suggest that the healthy properties of teas, especially GABA teas, have to be evaluated via comprehensive metabolic profiling rather than only the GABA content.

Landslide Susceptibility Assessment Using Statistical Multivariate Analysis “PCA” in the Mediterranean Kabylia

Landslides are one of the most catastrophic geo-risks observed in northern Algeria, particularly in the regions of mountain ranges (Mediterranean Kabylia), where the processes are spectacular. Over the past decade, the landslides risk has become increasingly amplified in urban space, mainly affecting the economy and human life. This highlights the importance and the need to predict the spatial occurrence of these events in the national territory. In order to better manage this phenomenon, decision-makers must be able to have susceptibility maps, allowing them to identify areas in their region where new landslides will have a higher probability of being triggered in the future and of predefine the damage associated with this phenomenon. However, approaches to assessing landslide sensitivity require a good knowledge of previously observed scenarios and include data collection and management, as well as spatial and statistical analyzes. In this study, a new multivariate statistical approach "PCA" was proposed to produce landslide susceptibility maps of the study area in a GIS system. This study allows the automatic analysis of most of the parameters related to the occurrence of slope failures while reducing the factors not influencing the triggering of landslides, this eliminates the effect of redundancy between the factors studied.

Preharvest Factors Affecting Quality on “Abate Fetel” Pears: Study of Superficial Scald with Multivariate Statistical Approach

Although superficial scald (SS) is well characterized on apples, there are only a few insights concerning the influence that agronomic and management variability may have on the occurrence of this physiological disorder on pears. In this study, we aimed to improve our understanding of the effect of different preharvest factors on SS development using a multivariate statistical approach. Pears (Pyrus communis L.) cv “Abate Fetel” were picked during two consecutive seasons (2018-2019 and 2019-2020) from twenty-three commercial orchards from three growing areas (Modena, Ferrara, and Ravenna provinces) in the Emilia-Romagna region of Italy. Bioclimatic indices such as weather and soil, agronomic management such fertilization and irrigation, orchard features such as rootstock and training systems, and SS incidence were carried out at harvest and periodically postharvest in all producers. Two different storage scenarios (regular atmosphere and use of 1-MCP) were also evaluated. Our data in both seasons showed high heterogeneity between farms for SS symptoms after cold storage either in the regular atmosphere or with 1-MCP treatment. Nevertheless, in 2018, all the producers showed SS at the end of the storage season, but in 2019 some of them did not exhibit SS for up to 5 months. In fact, some preharvest factors changed considerably between the two seasons such as yield and weather conditions. Indeed, some factors seem to affect SS in both growing seasons. Some can increase its occurrences such as physiological and agronomical factors: high yields, late date of blooming, heavy downpours, improper irrigation management (low watering frequency and high volumes), nitrogen (included that deriving from organic matter), soil texture (presence of clay), orchard age, and canopy volume in relation to training system and rootstock. Others can decrease SS such as climatic and management factors: late harvest dates, rain, gibberellins, calcium, manure, absence of antihail nets or use of photoselective nets, and site (probably related to better soils toward the Adriatic coast). Initial preharvest variability is an important factor that modulates physiological plant stress and, subsequently, the SS after cold storage in “Abate Fetel” pears. Multivariate techniques could represent useful tools to identify reliable multiyear preharvest variables for SS control in pear fruit different batches.