1,721,017 research outputs found
Comparative plant diversity and seed germination patterns of alpine species in the context of climate change
Full text linkClimate is a major determinant of the distribution of ecosystems on earth and influences the latitudinal and altitudinal distribution of both plant species and vegetation. Over the least decades, global warming has been affecting ecosystems worldwide, especially cold regions such as the arctic and alpine biomes. European mountains are considered hotspots of biodiversity, hosting approximately 20% of the continent's native vascular flora, with a high number of endemic species. Yet, these rich and diverse environments are projected to experience one of the highest rates of climate warming, compared to other regions of the world. Climate change has direct impact on plant species, causing species migration and extinction. Consequence, vegetation dynamics in these cold adapted ecosystems are difficult to predict.
In this Thesis, I firstly investigated the variation of species richness, α-diversity, β-diversity and total cover of plant functional types on an alpine long-term monitoring site (belonging to the GLORIA network, https://www.gloria.ac.at), with the aim to promote a better understanding of climate-driven changes of alpine vegetation. I identified significant increment in plant species richness, along with trend of biodiversity loss and signals of biotic homogenization: Cold-adapted and rare species declined while dominant species like nitrophilous graminoids and shrubs increased. The results obtained highlight that long-term vegetation monitoring activities paired with multiple measures of diversity are required to properly assess biodiversity and to obtain useful indications for future conservation activities in alpine environments.
Secondly, I investigated the germination ecology of 75 alpine plants of interest, to evaluate the role of seed germination as a driver for plant species population dynamics in response to climate warming. One of the key processes in determining the species capacity to migrate, establish and persist is, in fact, seed dispersal, followed by seed germination and seedling development. In alpine plants, seed germination is under strong environmental control, suggesting that climate change will inevitably affect recruitment success. In the present study, I selected 75 alpine plant species which populations either increased, decreased or remained stable in five long-term monitoring alpine study sites (belonging to the GLORIA network), along a time period of 15 years. Increasing species germinated at a broader spectrum of environmental conditions than those of the other groups, and were characterized by higher germination, especially at low temperature after cold stratification treatment). These results suggest that germination during early spring, right after snowmelt, may be an advantage in a warmer climate, promoting seedling emergence when water is more available and drought/heat hazards are low.
Finally, I investigated the relationship between seed germination and environmental cues of 28 species of the genus Saxifraga, with the aim to disentangle their germination response from ecological cues and phylogenetic relatedness. Saxifraga seed germination resulted overall promoted by cold stratification and cool temperatures, while being strongly inhibited by darkness. Germination traits in the genus Saxifraga were overall unconstrained by phylogeny, while they were driven by the species ecological niche, as it was possible to observe different germination strategies depending on species requirements for water availability, soil acidity and texture. These results highlight that microenvironmental variables play a major role than phylogeny in determining the germination strategies across species of this genus.Climate is a major determinant of the distribution of ecosystems on earth and influences the latitudinal and altitudinal distribution of both plant species and vegetation. Over the least decades, global warming has been affecting ecosystems worldwide, especially cold regions such as the arctic and alpine biomes. European mountains are considered hotspots of biodiversity, hosting approximately 20% of the continent's native vascular flora, with a high number of endemic species. Yet, these rich and diverse environments are projected to experience one of the highest rates of climate warming, compared to other regions of the world. Climate change has direct impact on plant species, causing species migration and extinction. Consequence, vegetation dynamics in these cold adapted ecosystems are difficult to predict.
In this Thesis, I firstly investigated the variation of species richness, α-diversity, β-diversity and total cover of plant functional types on an alpine long-term monitoring site (belonging to the GLORIA network, https://www.gloria.ac.at), with the aim to promote a better understanding of climate-driven changes of alpine vegetation. I identified significant increment in plant species richness, along with trend of biodiversity loss and signals of biotic homogenization: Cold-adapted and rare species declined while dominant species like nitrophilous graminoids and shrubs increased. The results obtained highlight that long-term vegetation monitoring activities paired with multiple measures of diversity are required to properly assess biodiversity and to obtain useful indications for future conservation activities in alpine environments.
Secondly, I investigated the germination ecology of 75 alpine plants of interest, to evaluate the role of seed germination as a driver for plant species population dynamics in response to climate warming. One of the key processes in determining the species capacity to migrate, establish and persist is, in fact, seed dispersal, followed by seed germination and seedling development. In alpine plants, seed germination is under strong environmental control, suggesting that climate change will inevitably affect recruitment success. In the present study, I selected 75 alpine plant species which populations either increased, decreased or remained stable in five long-term monitoring alpine study sites (belonging to the GLORIA network), along a time period of 15 years. Increasing species germinated at a broader spectrum of environmental conditions than those of the other groups, and were characterized by higher germination, especially at low temperature after cold stratification treatment). These results suggest that germination during early spring, right after snowmelt, may be an advantage in a warmer climate, promoting seedling emergence when water is more available and drought/heat hazards are low.
Finally, I investigated the relationship between seed germination and environmental cues of 28 species of the genus Saxifraga, with the aim to disentangle their germination response from ecological cues and phylogenetic relatedness. Saxifraga seed germination resulted overall promoted by cold stratification and cool temperatures, while being strongly inhibited by darkness. Germination traits in the genus Saxifraga were overall unconstrained by phylogeny, while they were driven by the species ecological niche, as it was possible to observe different germination strategies depending on species requirements for water availability, soil acidity and texture. These results highlight that microenvironmental variables play a major role than phylogeny in determining the germination strategies across species of this genus
How We Can Evaluate the Inequality in Flint
No full textThe inequality analysis plays an important role since the beginning of the last century, in the economic, social and political debate. From the rst pioneering paper of Gini, this subject has become more and more fascinating. The several tools proposed in the literature for evaluating the inequality belong basically to two families: on the one hand there are inequality curves which represent (also graphically) the local pattern of inequality in all segments of the considered population; on the other hand, inequality indexes (that often can be derived from a particular inequality curve) which summarize its measure in one number. Different indexes are needed to reveal different viewpoints toward inequality. In this paper, the features of the relatively new inequality I(p) curve are described. Beyond many theoretical results, also an empirical analysis based on real income data of Flint is performed
Decomposition by subpopulations of the Zenga-84 inequality curve and the related index ζ : an application to 2014 Bank of Italy survey
No full textThis paper describes an innovative procedure to decompose by subpopulations the values assumed by the Zenga-84 inequality curve Z(p). This decomposition allows to identify the contributions to the inequality at the subpopulation level, feature that the most of the decomposition procedures do not have. Since the synthetic inequality index ζ is obtained as the average of the values of Z(p)—which are appropriate relative variations—the results of such first decomposition can be used to obtain many other different decompositions of the synthetic index ζ. In this framework, the classical decomposition of the index ζ in the “Between” and the “Within” components can be performed as a special case. The proposed procedure is illustrated through an application with real data from a sample survey provided by Bank of Italy in 2015
On the income distribution models and inequality curves
No full textIn this work the characteristics of some distribution models used in the literature for describing income distribution are analysed. The analysis focuses on the inequality curves generated by such models. In particular, the role of the parameters related to the inequality curves is analysed, also by considering the influence of their variations from a pointwise perspective
The joint decomposition of the Pietra index
No full textIn this paper, a multi-decomposition of the Pietra index is presented. This innovative methodology allows to achieve a relevant task, since it combines simultaneously the two most celebrated kinds of decomposition: by sources and by subpopulations. The key result of the proposed procedure is the detail level of decomposition: it allows to split the value of the index, by assessing the contribution of each source in each subpopulation. It is worth noting that this final result is not reached by all the decomposition procedures, since most of them do not permit to identify the contributions at so detailed level. The proposed joint decomposition is a sort of generalization, since from it two decompositions by sources and by subpopulations of the Pietra index, already proposed in the literature, can be obtained. Beyond the methodological details, an application based on the Survey Household Income and Wealth 2018 – carried out by Bank of Italy – is provided in order to clarify the advantages of the procedure
The decomposition by subgroups of the inequality curve Z(p) and the inequality index Z
No full textThis paper provides a procedure to decompose by subgroups the inequality
index Z , proposed by Zenga in [3]. Through this decomposition, such index can
be seen as the weighted average of two terms, which represent the “within” and
the “between” components. This decomposition arises from the decomposition by
subgroups of the inequality Z(p) curve, that originates the index itself
Two decompositions of the Pietra index with applications to Italian professional football teams
No full textTwo innovative procedures for the decomposition of the Pietra inequality index are proposed. Both are based on a two-step approach, already successfully applied in the literature to decompose other indexes. The first procedure allows the decomposition of the index by sources, while the second one provides the decomposition by subpopulations. A very important advantage of these two new procedures is that the first one allows to assess the relevance of each source, while the second one provides the contribution due to each subpopulation. The ”classical” decomposition of the Pietra index in the Within and the Between components can be easily obtained as a special case of the proposed decomposition procedure by subpopulations. Beyond the methodological details, two applications with real data regarding the professional football teams in Italy are illustrated
A test to assess the dynamic evolution of preferences in marketing surveys
No full textThe subject of this paper is a two-stage hypothesis test, which may have interesting applications in several situations related to the opinion research field. Such test is based on the components of a Bivariate Correlated Normal random variable. In particular, it is based on the exact distribution of their minimum and maximum modulus. This test was proposed for the first time by Duncan in Miller (1981), and was recently improved by Pollastri (2008). In the latter paper a variant of such test is described, since two samples in two different times or situations are considered. Two kinds of applications are provided to show the wide range of usage
A compositional analysis of tourism in Europe
No full textTourism plays an important role in the economy of many European countries. For this reason many analyses have been performed to improve the understanding of such a relevant sector. In the literature many innovative statistical methodologies have been applied to tourism. In this paper the Decompositional Data (CoDa) approach is used for analyzing the touristic presence in Europe over the years 2016-2021. The considered time range also includes the last two years (2020 and 2021) affected by the COVID-19 pandemic
Regression Models with Compositional Covariates and Structural Zeros
No full textIn the last few years, the regression models with compositional explanatory variables have been approached in the literature, and some procedures to manage them have been developed. One issue requiring more investigation regards the presence of structural zeros in the explanatory variables. A structural zero is a value that is intrinsically zero because of a physical limitation: it is not a rounded zero, it is not a value below a certain detection limit, and it is not related to then variability of the selected sampling procedure. It is a sort of ”true” zero. It follows that the presence of structural zeros is problematic in the compositional framework, since a composition is not allowed to have a part equal to zero. Moreover, a quite standard approach used for compositional regression models is to transform the compositional explanatory variables by applying a (isometric log-ratio, usually) transformation keeping as much as possible the information represented by the compositional nature of them (see, for example, Hron et al., 2012): unfortunately, such transformation is not allowed in the case of null parts. Beyond the well-known naive practice of replacing the zeros with an arbitrary small positive value, which represents an easy and intuitive but sometimes non-suitable procedure, in recent years a couple of more sophisticated methodologies to overcome this blocking issue have been proposed in the literature (see Verbelen et al. 2018). The aim of this talk is to illustrate these two procedures, describing in detail how they work. Moreover, it will be shown that they can be seen as special cases of a more general model already known in the literature as the ANCOVA model (Analysis of Covariance
Model)
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