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.

Three Essays in Economics of Gender

During recent decades, economists' interest in gender-related issues has risen. Researchers aim to show how economic theory can be applied to gender related topics such as peer effect, labor market outcomes, and education. This dissertation aims to contribute to our understandings of the interaction, inequality and sources of differences across genders, and it consists of three empirical papers in the research area of gender economics. The aim of the first paper ("Separating gender composition effect from peer effects in education") is to demonstrate the importance of considering endogenous peer effects in order to identify gender composition effect. This fact is analytically illustrated by employing Manski's (1993) linear-in-means model. The paper derives an innovative solution to the simultaneous identification of endogenous and exogenous peer effects: gender composition effect of interest is estimated from auxiliary reduced-form estimates after identifying the endogenous peer effect by using Graham (2008) variance restriction method. The paper applies this methodology to two different data sets from American and Italian schools. The motivation of the second paper ("Gender differences in vulnerability to an economic crisis") is to analyze the different effect of recent economic crisis on the labor market outcome of men and women. Using triple differences method (before-after crisis, harder-milder hit sectors, men-women) the paper used British data at the occupation level and shows that men suffer more than women in terms of probability of losing their job. Several explanations for the findings are proposed. The third paper ("Gender gap in educational outcome") is concerned with a controversial academic debate on the existence, degree and origin of the gender gap in test scores. The existence of a gap both in mean scores and the variability around the mean is documented and analyzed. The origins of the gap are investigated by looking at wide range of possible explanations.