Natural patterns and anthropogenic disturbance in north Adriatic marine benthic assemblages: descriptive and methodological studies

Marine soft bottom systems show a high variability across multiple spatial and temporal scales. Both natural and anthropogenic sources of disturbance act together in affecting benthic sedimentary characteristics and species distribution. The description of such spatial variability is required to understand the ecological processes behind them. However, in order to have a better estimate of spatial patterns, methods that take into account the complexity of the sedimentary system are required. This PhD thesis aims to give a significant contribution both in improving the methodological approaches to the study of biological variability in soft bottom habitats and in increasing the knowledge of the effect that different process (both natural and anthropogenic) could have on the benthic communities of a large area in the North Adriatic Sea. Beta diversity is a measure of the variability in species composition, and Whittaker’s index has become the most widely used measure of beta-diversity. However, application of the Whittaker index to soft bottom assemblages of the Adriatic Sea highlighted its sensitivity to rare species (species recorded in a single sample). This over-weighting of rare species induces biased estimates of the heterogeneity, thus it becomes difficult to compare assemblages containing a high proportion of rare species. In benthic communities, the unusual large number of rare species is frequently attributed to a combination of sampling errors and insufficient sampling effort. In order to reduce the influence of rare species on the measure of beta diversity, I have developed an alternative index based on simple probabilistic considerations. It turns out that this probability index is an ordinary Michaelis-Menten transformation of Whittaker's index but behaves more favourably when species heterogeneity increases. The suggested index therefore seems appropriate when comparing patterns of complexity in marine benthic assemblages. Although the new index makes an important contribution to the study of biodiversity in sedimentary environment, it remains to be seen which processes, and at what scales, influence benthic patterns. The ability to predict the effects of ecological phenomena on benthic fauna highly depends on both spatial and temporal scales of variation. Once defined, implicitly or explicitly, these scales influence the questions asked, the methodological approaches and the interpretation of results. Problem often arise when representative samples are not taken and results are over-generalized, as can happen when results from small-scale experiments are used for resource planning and management. Such issues, although globally recognized, are far from been resolved in the North Adriatic Sea. This area is potentially affected by both natural (e.g. river inflow, eutrophication) and anthropogenic (e.g. gas extraction, fish-trawling) sources of disturbance. Although few studies in this area aimed at understanding which of these processes mainly affect macrobenthos, these have been conducted at a small spatial scale, as they were designated to examine local changes in benthic communities or particular species. However, in order to better describe all the putative processes occurring in the entire area, a high sampling effort performed at a large spatial scale is required. The sedimentary environment of the western part of the Adriatic Sea was extensively studied in this thesis. I have described, in detail, spatial patterns both in terms of sedimentary characteristics and macrobenthic organisms and have suggested putative processes (natural or of human origin) that might affect the benthic environment of the entire area. In particular I have examined the effect of off shore gas platforms on benthic diversity and tested their effect over a background of natural spatial variability. The results obtained suggest that natural processes in the North Adriatic such as river outflow and euthrophication show an inter-annual variability that might have important consequences on benthic assemblages, affecting for example their spatial pattern moving away from the coast and along a North to South gradient. Depth-related factors, such as food supply, light, temperature and salinity play an important role in explaining large scale benthic spatial variability (i.e., affecting both the abundance patterns and beta diversity). Nonetheless, more locally, effects probably related to an organic enrichment or pollution from Po river input has been observed. All these processes, together with few human-induced sources of variability (e.g. fishing disturbance), have a higher effect on macrofauna distribution than any effect related to the presence of gas platforms. The main effect of gas platforms is restricted mainly to small spatial scales and related to a change in habitat complexity due to a natural dislodgement or structure cleaning of mussels that colonize their legs. The accumulation of mussels on the sediment reasonably affects benthic infauna composition. All the components of the study presented in this thesis highlight the need to carefully consider methodological aspects related to the study of sedimentary habitats. With particular regards to the North Adriatic Sea, a multi-scale analysis along natural and anthopogenic gradients was useful for detecting the influence of all the processes affecting the sedimentary environment. In the future, applying a similar approach may lead to an unambiguous assessment of the state of the benthic community in the North Adriatic Sea. Such assessment may be useful in understanding if any anthropogenic source of disturbance has a negative effect on the marine environment, and if so, planning sustainable strategies for a proper management of the affected area.

Molecular diversity of Primula apennina and phylogeny of Primula Subsection Euauricula

Primula apennina Widmer is endemic to the North Apennines (Italy). ISSR were used to detect the genetic diversity within and among six populations representative of the species distribution range. High levels of genetic diversity were revealed both at population (PPB = 75.92%, HS = 0.204, Hpop = 0.319) and at species level (PPB = 96.95%, HT = 0.242, Hsp = 0.381). Nei gene diversity statistics (15.7%), Shannon diversity index (16.3%) and AMOVA (14%) detected a moderate level of interpopulation diversity. Principal coordinate and bayesian analyses clustered the populations in three major groups along a geographic gradient. The correlation between genetic and geographic distances was positive (Mantel test, r = 0.232). All together, these analyses revealed a weak but significant spatial genetic structure in P. apennina, with gene flow acting as a homogenizing force that prevents a stronger differentiation of populations. Conservation measures are suggested based on the observed pattern of genetic variability. P. apennina belongs to Primula subsect. Euauricula which includes 15 species distributed on the whole Alps and Apennines. A phylogenetic analysis was carried out using AFLP markers in order both to clarify the relationships among the species of subsection Euauricula that remained unresolved in previous works and to make some hypoteses on their evolutive dynamics. NJ, PCO and BAPS analyses strongly confirmed the monophyly of P. subsect. Euauricula and all the species form strongly supported clades. NJ tree topology suggested a simultaneous fragmentations of ancestral species in a large number of isolated populations that survived in refugia along the unglaciated margins of the Alps in response to the Pleistocene climatic oscillations.

Landscape ecology and genetics of the wolf in Italy

This PhD Thesis includes five main parts on diverse topics. The first two parts deal with the trophic ecology of wolves in Italy consequently to a recent increase of wild ungulates abundance. Data on wolf diet across time highlighted how wild ungulates are important food resource for wolves in Italy. Increasing wolf population, increasing numbers of wild ungulates and decreasing livestock consume are mitigating wolf-man conflicts in Italy in the near future. In the third part, non-invasive genetic sampling techniques were used to obtain genotypes and genders of about 400 wolves. Thus, wolf packs were genetically reconstructed using diverse population genetic and parentage software. Combining the results on pack structure and genetic relatedness with sampling locations, home ranges of wolf packs and dispersal patterns were identified. These results, particularly important for the conservation management of wolves in Italy, illustrated detailed information that can be retrieved from genetic identification of individuals. In the fourth part, wolf locations were combined with environmental information obtained as GIS-layers. Modern species distribution models (niche models) were applied to infer potential wolf distribution and predation risk. From the resulting distribution maps, information pastures with the highest risk of depredation were derived. This is particularly relevant as it allows identifying those areas under danger of carnivore attack on livestock. Finally, in the fifth part, habitat suitability models were combined with landscape genetic analysis. On one side landscape genetic analyses on the Italian wolves provided new information on the dynamics and connectivity of the population and, on the other side, a profound analysis of the effects that habitat suitability methods had on the parameterization of landscape genetic analyses was carried out to contributed significantly to landscape genetic theory.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.