Carbon and nitrogen stock and fluxes in coastal Atlantic Forest of southeast Brazil: potential impacts of climate change on biogeochemical functioning

The Atlantic Forest is one of the most important biomes of Brazil. Originally covering approximately 1.5 million of km(2), today this area has been reduced to 12% of its original size. Climate changes may alter the structure and the functioning of this tropical forest. Here we explore how increases in temperature and changes in precipitation distribution could affect dynamics of carbon and nitrogen in coastal Atlantic Forest of the southeast region of Brazil The main conclusion of this article is that the coastal Atlantic Forest has high stocks of carbon and nitrogen above ground, and especially, below ground. An increase in temperature may transform these forests from important carbon sinks to carbon sources by increasing loss of carbon and nitrogen to the atmosphere. However, this conclusion should be viewed with caution because it is based on limited information. Therefore, more studies are urgently needed to enable us to make more accurate predictions.

The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]

Food-Retail Development and the Myth of Everyday Low Prices: The Case of Brazil

This article analyses the changes in Brazilian food retailing by investigating the co-existence of, and the pricing variation across, large supermarket chains and small independent supermarkets. It uses cointegration tests to show that, despite the widespread belief that small supermarkets are inefficient and charge higher prices, they in fact charge lower prices. Accordingly, in contrast to the prevailing literature on food-retail development, competition in food retail is complex and cannot be described as a simple Darwinian process of market concentration. The article explores the survival of small retail and its consequences for the current discussion on modern food retail in developing countries.

Stock of biomass and carbon in the montane mixes shade forest, Parana

The aim of this study was to estimate the stock of biomass and organic carbon in a montane mixed shade forest located near General Carneiro, PR. 20 plots of 12 m x 12 m were installed, in which all trees with a CBH (Circumference at Breast Height) >= 31.4 cm were felled. From these the following information was obtained: total height, commercial height (agreed as being the morphological inversion point in the natural forest and the height of the first live branch), CBH, identification and collection of herbarium specimens. For the quantification of biomass in the understory and roots, three subunits 1 m x 1 m in each sampling unit were installed (12 m x 12 m) arranged in the lower left corner, center and diagonal upper right corner. To quantify accumulated litter at random, eight samples in each sampling unit were collected (12 m x 12 m), using a metal device measuring 0.25 m x 0.25 m. The montane mixed shade forest has more than 85% of its total biomass and total organic carbon stored in above ground plant structures. The total stock of organic carbon found in this study (104.7 Mg ha(-1)) demonstrates the importance of maintaining and preserving natural ecosystems as a way of maintaining this stock of organic carbon fixed in plant biomass.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

A new global wheat marketmodel (GLOWMM) for the analysis of wheat export prices

Food commodity prices fluctuations have important impacts on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, while there is an urgent need for appropriate policy responses. Perhaps new approaches are needed in order to better understand international spill-overs, the feedback between the real and the financial sectors and also the link between food and energy prices. In this paper, we present results from a new worldwide dynamic model that provides short and long-run impulse responses of wheat international prices to various real shocks.

Identification of stock units of Mullus barbatus (Linnaeus, 1758) in the Italian seas: development of genomic 2b-RAD markers and biological variation analysis.

This thesis is settled within the STOCKMAPPING project, which represents one of the studies that were developed in the framework of RITMARE Flagship project. The main goals of STOCKMAPPING were the creation of a genomic mapping for stocks of demersal target species and the assembling of a database of population genomic, in order to identify stocks and stocks boundaries. The thesis focuses on three main objectives representing the core for the initial assessment of the methodologies and structure that would be applied to the entire STOCKMAPPING project: individuation of an analytical design to identify and locate stocks and stocks boundaries of Mullus barbatus, application of a multidisciplinary approach to validate biological methods and an initial assessment and improvement for the genotyping by sequencing technique utilized (2b-RAD). The first step is the individuation of an analytical design that has to take in to account the biological characteristics of red mullet and being representative for STOCKMAPPING commitments. In this framework a reduction and selection steps was needed due to budget reduction. Sampling areas were ranked according the individuation of four priorities. To guarantee a multidisciplinary approach the biological data associated to the collected samples were used to investigate differences between sampling areas and GSAs. Genomic techniques were applied to red mullet for the first time so an initial assessment of molecular protocols for DNA extraction and 2b-RAD processing were needed. At the end 192 good quality DNAs have been extracted and eight samples have been processed with 2b-RAD. Utilizing the software Stacks for sequences analyses a great number of SNPs markers among the eight samples have been identified. Several tests have been performed changing the main parameter of the Stacks pipeline in order to identify the most explicative and functional sets of parameters.

Stock boundaries of Parapenaeus longirostris (Lucas, 1846) populations in the Italian seas: Development of genomic 2b-RAD markers and biological variation analysis.

This thesis is developed in the contest of Ritmare project WP1, which main objective is the development of a sustainable fishery through the identification of populations boundaries in commercially important species in Italian Seas. Three main objectives are discussed in order to help reach the main purpose of identification of stock boundaries in Parapenaeus longirostris: 1 -Development of a representative sampling design for Italian seas; 2 -Evaluation of 2b-RAD protocol; 3 -Investigation of populations through biological data analysis. First of all we defined and accomplished a sampling design which properly represents all Italian seas. Then we used information and data about nursery areas distribution, abundance of populations and importance of P. longirostris in local fishery, to develop an experimental design that prioritize the most important areas to maximize the results with actual project funds. We introduced for the first time the use of 2b-RAD on this species, a genotyping method based on sequencing the uniform fragments produced by type IIB restriction endonucleases. Thanks to this method we were able to move from genetics to the more complex genomics. In order to proceed with 2b-RAD we performed several tests to identify the best DNA extraction kit and protocol and finally we were able to extract 192 high quality DNA extracts ready to be processed. We tested 2b-RAD with five samples and after high-throughput sequencing of libraries we used the software “Stacks” to analyze the sequences. We obtained positive results identifying a great number of SNP markers among the five samples. To guarantee a multidisciplinary approach we used the biological data associated to the collected samples to investigate differences between geographical samples. Such approach assures continuity with other project, for instance STOCKMED, which utilize a combination of molecular and biological analysis as well.

Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar

Madagascar is currently developing a policy and strategies to enhance the sustainable management of its natural resources, encouraged by United Nations Framework Convention on Climate Change (UNFCCC) and REDD. To set up a sustainable financing scheme methodologies have to be provided that estimate, prevent and mitigate leakage, develop national and regional baselines, and estimate carbon benefits. With this research study this challenge was tried to be addressed by analysing a lowland rainforest in the Analanjirofo region in the district of Soanierana Ivongo, North East of Madagascar. For two distinguished forest degradation stages: “low degraded forest” and “degraded forest” aboveground biomass and carbon stock was assessed. The corresponding rates of carbon within those two classes were calculated and linked to a multi-temporal set of SPOT satellite data acquired in 1991, 2004 and 2009. Deforestation and particularly degradation and the related carbon stock developments were analysed. With the assessed data for the 3 years 1991, 2004 and 2009 it was possible to model a baseline and to develop a forest prediction for 2020 for Analanjirofo region in the district of Soanierana Ivongo. These results, developed applying robust methods, may provide important spatial information regarding the priorities in planning and implementation of future REDD+ activities in the area.