Molluscs of the marine protected area "Secche di Tor Paterno"

The thesis describes the molluscan biodiversity of the infralittoral off-shore reefs in the "Secche di Tor Paterno" marine protected area lying in the Central Tyrrhenian Sea off the coasts of Lazio south of Roma. Data originate from underwater sampling activities carried out by SCUBA diving in four biocoenoses: Posidonia oceanica leaves and rhizomes, coralligenous concretions and detritic pools. The representativeness of molluscs as descriptors of biocoenoses is evaluated by preliminary comparisons with data about Polychaeta, Pleocyemata (Crustacea) and Brachiopoda obtained in the same survey. The malacocoenoses of the four biocoenoses are treated in detail. Then data are compared with other data sets to assess differences and similarities with other communities. The agreement between death and living assemblages in the reefs is evaluated for the Posidonia oceanica and the coralligenous biocoenosis and was carried out by a set of standard metrics and some benthic ecology methods. Molluscs perform very well as descriptors of biocoenoses, better than the other phyla. The molluscan assemblages of the reefs are very rich in species despite richness is mainly concentrated in the coralligenous and in the rhizomes of Posidonia oceanica. The leaves of Posidonia oceanica host a rather poor assemblage. Detritic pools host a poor but peculiar species assemblage. The dead-live agreement showed that death assemblages are highly representative of sediments of nearby biocoenoses as a result of low bottom transport. Fidelity metrics suggest a good agreement between the living and death assemblages when species richness and taxonomic composition are considered. The study suggests that fidelity is lower when considering the species dominance. These differences could be associated to the trophism of species and possibly to the species life span.

A molecular phylogeny of bivalve mollusks: ancient radiations and divergences as revealed by mitochondrial genes

The main scope of my PhD is the reconstruction of the large-scale bivalve phylogeny on the basis of four mitochondrial genes, with samples taken from all major groups of the class. To my knowledge, it is the first attempt of such a breadth in Bivalvia. I decided to focus on both ribosomal and protein coding DNA sequences (two ribosomal encoding genes -12s and 16s -, and two protein coding ones - cytochrome c oxidase I and cytochrome b), since either bibliography and my preliminary results confirmed the importance of combined gene signals in improving evolutionary pathways of the group. Moreover, I wanted to propose a methodological pipeline that proved to be useful to obtain robust results in bivalves phylogeny. Actually, best-performing taxon sampling and alignment strategies were tested, and several data partitioning and molecular evolution models were analyzed, thus demonstrating the importance of molding and implementing non-trivial evolutionary models. In the line of a more rigorous approach to data analysis, I also proposed a new method to assess taxon sampling, by developing Clarke and Warwick statistics: taxon sampling is a major concern in phylogenetic studies, and incomplete, biased, or improper taxon assemblies can lead to misleading results in reconstructing evolutionary trees. Theoretical methods are already available to optimize taxon choice in phylogenetic analyses, but most involve some knowledge about genetic relationships of the group of interest, or even a well-established phylogeny itself; these data are not always available in general phylogenetic applications. The method I proposed measures the "phylogenetic representativeness" of a given sample or set of samples and it is based entirely on the pre-existing available taxonomy of the ingroup, which is commonly known to investigators. Moreover, it also accounts for instability and discordance in taxonomies. A Python-based script suite, called PhyRe, has been developed to implement all analyses.

A new method for the estimation of the reverberation time from measured room impulse responses with application to Italian opera houses

The Schroeder's backward integration method is the most used method to extract the decay curve of an acoustic impulse response and to calculate the reverberation time from this curve. In the literature the limits and the possible improvements of this method are widely discussed. In this work a new method is proposed for the evaluation of the energy decay curve. The new method has been implemented in a Matlab toolbox. Its performance has been tested versus the most accredited literature method. The values of EDT and reverberation time extracted from the energy decay curves calculated with both methods have been compared in terms of the values themselves and in terms of their statistical representativeness. The main case study consists of nine Italian historical theatres in which acoustical measurements were performed. The comparison of the two extraction methods has also been applied to a critical case, i.e. the structural impulse responses of some building elements. The comparison underlines that both methods return a comparable value of the T30. Decreasing the range of evaluation, they reveal increasing differences; in particular, the main differences are in the first part of the decay, where the EDT is evaluated. This is a consequence of the fact that the new method returns a “locally" defined energy decay curve, whereas the Schroeder's method accumulates energy from the tail to the beginning of the impulse response. Another characteristic of the new method for the energy decay extraction curve is its independence on the background noise estimation. Finally, a statistical analysis is performed on the T30 and EDT values calculated from the impulse responses measurements in the Italian historical theatres. The aim of this evaluation is to know whether a subset of measurements could be considered representative for a complete characterization of these opera houses.

Stream sediments analysis for geochemical mapping of Romagna Apennines (Northern Italy): monitoring and management tool of environmental resources at various scales

Geochemical mapping is a valuable tool for the control of territory that can be used not only in the identification of mineral resources and geological, agricultural and forestry studies but also in the monitoring of natural resources by giving solutions to environmental and economic problems. Stream sediments are widely used in the sampling campaigns carried out by the world's governments and research groups for their characteristics of broad representativeness of rocks and soils, for ease of sampling and for the possibility to conduct very detailed sampling In this context, the environmental role of stream sediments provides a good basis for the implementation of environmental management measures, in fact the composition of river sediments is an important factor in understanding the complex dynamics that develop within catchment basins therefore they represent a critical environmental compartment: they can persistently incorporate pollutants after a process of contamination and release into the biosphere if the environmental conditions change. It is essential to determine whether the concentrations of certain elements, in particular heavy metals, can be the result of natural erosion of rocks containing high concentrations of specific elements or are generated as residues of human activities related to a certain study area. This PhD thesis aims to extract from an extensive database on stream sediments of the Romagna rivers the widest spectrum of informations. The study involved low and high order stream in the mountain and hilly area, but also the sediments of the floodplain area, where intensive agriculture is active. The geochemical signals recorded by the stream sediments will be interpreted in order to reconstruct the natural variability related to bedrock and soil contribution, the effects of the river dynamics, the anomalous sites, and with the calculation of background values be able to evaluate their level of degradation and predict the environmental risk.