Biodiversity Indicators: The Accounting Point of View☆

Abstract According to the Convention on Biological Diversity, biodiversity is the variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; this includes diversity within species, between species and of ecosystems. The key value of biodiversity lies in its role in ensuring the functioning of ecosystems and their ability to provide services to humans and other living organisms that comprise them. For that reason, maintaining a sufficient degree of biodiversity is the key to the continued delivery of essential ecosystem services and the need to ensure the conservation of biological diversity is now widely accepted. In spite of this global sentiment, there is not a national or international convergence towards a framework to report to different stakeholders' groups the performance of organizations like protected areas and national parks, in terms of their biodiversity and the conservation activities they are achieving. After describing the concept of biodiversity, its value and the information needs of the community related to it, the main purpose of the paper is to propose a theoretical and systemic framework for its reporting by public sector organizations established for the protection of the natural capital, by means of some specific indicators deduced mainly by the literature concerning biological sciences. Following the GRI (Global Reporting Initiative) guidelines, these indicators, interpreted in terms of KPI (Key Performance Indicators), should lead to an increase in the transparency and in the accountability of Protected Areas

Characterization of GTPBPs involved in ribosome assembly and function in human mitochondria

Mitochondria are organelles often referred to as the powerhouses of the cell as they provide most of the chemical energy via aerobic respiration. However, in the last half a century, it has become clear that their function extends to other fundamental metabolic tasks. These fascinating organelles have their own DNA and protein synthesis machinery, the mitochondrial ribosome (mitoribosome), the latter made of a set of mitoribosomal proteins (MRPs) and rRNA that all together build a 2.7 MDa complex. The mitoribosome translates for 13 polypeptides which are later incorporated in the respiratory chain. Therefore, it is not surprising that mutations in MRPs or auxiliary factors involved in its assembly can lead to multisystemic human disorders. Here lies the importance of studying the molecular mechanisms of the mitoribosomal assembly process, which has been the focus of my PhD studies. Guanosine triphosphate binding proteins (GTPBPs) involved in ribosome biogenesis in bacteria have extensively been studied and have provided key knowledge for the understanding of the role of their human mitochondrial homologues identified so far. In my work, I have addressed the role of human mitochondrial proteins GTPBP5, GTPBP10 and GTPBP8 and their possible involvement in mitochondrial ribosome biogenesis. In paper I, we have biochemically characterised GTPBP5 by assessing its interactome and the effects of its depletion on mitochondrial functionality, showing the importance of this protein as an assembly factor. These data have later been confirmed in paper II, where we have structurally determined in more details the function of GTPBP5 as well as several other late-stage mitoribosomal assembly factors. GTPBP10 involvement in the assembly process has been determined biochemically in paper III, where we also co-immunoprecipitated GTPBP10 with the mitoribosome in vivo using a knock-in mouse model. Additionally, preliminary results discussed in this thesis regard the investigation of GTPBP8 function in mitochondrial gene expression, demonstrating its significance for mitochondrial viability

Diagnostic strategy and risk assessment framework for complex chemical mixtures

Environmental contamination comprises a complex mixture of both organic and inorganic contaminants. Understanding their distribution, behaviour and chemical interactions provides the evidence necessary to make informed decision and implement robust remediation strategies. However most of the current risk assessment frameworks, used to manage land contamination, are based on the total contaminant concentration rather than the concentration likely to pose significant risk, the bioavailable concentration. Further to this, the exposure assessments embedded within the frameworks do not explicitly address the partitioning and bioavailability of chemical mixtures. This inability may contribute to an overestimation of both the eco-toxicological effects of the fractions and their mobility in air and water; leading to an overestimation of health and environmental effects. In turn, this may limit the efficacy of the risk assessment frameworks to inform targeted and proportionate remediation strategies. The aim of this PhD study was to address this gap by delivering an integrated risk assessment framework for sites contaminated with complex chemical mixtures. Specifically, this PhD study investigated the fate and behaviour of complex mixtures of petroleum hydrocarbons, metals and metalloids in soils and its implication for partitioning, bioavailability and risk assessment through a 12 month mesocosms study. Further to this, an integrated approach, where contaminants bioavailability and distribution changes along with a range of microbiological indicators and ecotoxicological bioassays, was used to provide multiple lines of evidence to support the risk characterisation and assess the remediation end-point over a 6 month study. From the empirical data obtained from the two mesocosm studies, two Machine Leaning (ML) approaches have been developed to provide a quick and reliable tool to assess multi-contaminated sites with Visible and Near-Infrared Spectroscopy (Vis-NIRS), and to predict bioavailability and toxicity changes occurring during bioremediation. Overall this PhD study shed light on the behaviour of bioavailability, and toxicity of complex chemical mixtures in soils genuinely contaminated. This was supported through a comprehensive and integrated analytical framework providing the necessary lines of evidence to evaluate the implications for risk assessment and identify the end point remediation. The developed framework can significantly help to identify optimal remediation strategies and contribute to change the over-conservative nature of the current risk assessments

The impact of IFRS 9 and IFRS 7 on liquidity in banks: Theoretical aspects

The conviction that capital markets could always satisfy Liquidity needs of agents has been strongly questioned during recent years.One consequence has been the IASB introducing IFRS 9, as substitute of IAS 39, in order to improve mechanisms of classification and measurement of Financial Instruments, deemed as one of the main causes triggering the financial crisis.Despite the effort of the International Board to introduce provisions able to assure relevant and useful information for the assessment of the amounts, timing and uncertainty of the entity’s future cash flows, there are some critical points associated with those requirements focused in the paper.We first introduced concepts of Liquidity and of Liquidity Risk, instrumental to a critical study of IFRS 9 insides.We then enriched the analysis, investigating IFRS 7 contents (just for what regards disclosure on Liquidity Risk), looking for information that could overcome IFRS 9 limits. According to our conclusions, IASB should think about the chance, among others, to pay more attention to the Business Model pattern and to behavioural liquidity characteristics associated to financial instruments.To sum up, the study aimed at analyse the impact of accounting rules on liquidity in banks.As it is a topic poorly addressed, not only from the academic literature but also by professional bodies, it can be considered as an emerging field of research. This aspect can be considered as one of its strength points

The friendship paradox in scale-free networks

Our friends have more friends than we do. That is the basis of the friendship paradox. In mathematical terms, the mean number of friends of friends is higher than the mean number of friends. In the present study, we analyzed the relationship between the mean degree of vertices (individuals), , and the mean number of friends of friends, , in scale-free networks with degrees ranging from a minimum degree (k_min) to a maximum degree (k_max). We deduced an expression for - for scale-free networks following a power-law distribution with a given scaling parameter (alpha). Based on this expression, we can quantify how the degree distribution of a scale-free network affects the mean number of friends of friends.Comment: 9 pages, 2 figure

Nova proposta tecnológica de aquisição e armazenamento da informação geológica

Dissertação (mestrado)—Universidade de Brasília, Instituto de Geociências, 2012.As geociências estão entre as ciências que mais produzem dados. No entanto, ainda não existem grandes trabalhos e iniciativas que consigam suprir a carência de modelos de armazenamento de dados e sua disponibilização para o território nacional. Dentro deste contexto, esse trabalho se propõe a construir e implementar um modelo de banco de dados geológico geoespacial, bem como o desenvolvimento de um sistema de entrada, manipulação e disponibilização de dados geológicos. Para a modelagem do banco de dados utilizou-se o conceito do OMT-G (Object Modeling Technique for Geographic Applications) tendo sido utilizado o software StarUML (http://staruml.sourceforge.net) para a geração do modelo conceitual. Toda conceituação e padronização adotadas no modelo conceitual do banco de dados estão baseadas na segunda versão do documento ‘Especificações Técnicos para Estruturação de Dados Geoespaciais Vetoriais’, produzido pela comissão Nacional de Cartografia (CONCAR). Este modelo de banco de dados geográfico foi implementado no Sistema Gerenciador de Banco de Dados Postgresql (com extensão Postgis), considerando as premissas estabelecidas pela INDE (Infraestrutura Nacional de Dados Espaciais) e pela Comissão de Gestão das Informações Geológicas (CMI - Commission for the Management and Application of Geoscience Information) da União Internacional de Ciências Geológicas (IUGS - International Union of Geological Sciences - http://www.cgi-iugs.org/tech_collaboration/thesaurus.html) para os requitos referente ao glossário e normatização das informações. O sistema para o gerenciamento de projetos de mapeamento geológico, denominado GEOTOOL - Gerenciamento de dados Geológicos - é um aplicativo que roda em ambiente web e é capaz de gerenciar desde a criação de um novo projeto até o fechamento do mapa geológico. Para a aquisição de dados em campo foi desenvolvida uma caderneta de campo digital capaz de coletar diversas informações relevantes de forma automatizada e sincronizá-las ao banco de dados do projeto de forma simples. Este trabalho também apresenta uma proposta de processo a ser utilizada para obter sucesso com o banco de dados e as ferramentas desenvolvidas. Dessa forma o processo esboça todas as etapas de aquisição, manipulação e publicação de dados indicando as melhores práticas para obter sucesso. ______________________________________________________________________________ ABSTRACTThe Geosciences are recognized as one of the scientific areas that generate the greatest amount of data. However, there are, as of yet, no comprehensive studies, nor initiatives that have been able to make up for the lack of data storage and availability models on a national scale. In light of this situation, the present study intends to construct and implement a geological geospatial database, as well as develop entrance, manipulation and availability systems for geological data. With regard to the database modeling, the Object Modeling Technique for Geographic Applications (OMT-G) was used, as well as the StarUML software (http://staruml.sourceforge.net) for generating the conceptual model. All of the concepts and standards adopted in the conceptual model of the database were founded on the second version of the document ‘Technical Specifications for the Structuring of Geospatial Vector Data’, produced by the National Commission of Cartography (CONCAR). This geographic database model was implemented in the System Manager of Postgresql Database (with a Postgis extension), taking into account the premises established by the National Infrastructure of Spatial Data (INDE)and on the Commission for the Management and Application of Geoscience Information (CMI) of the International Union of Geological Sciences – (http://www.cgi- iugs.org/tech_collaboration/thesaurus.html) for the requirements regarding the information glossary and norms. The system to manage the geological mapping projects, denominated GEOTOOL (Geological Data Management), is a device that runs in a web environment and is capable of managing, from the inception of the creation of a new project to the close of the geological map. For the acquisition of field data, a digital field notebook was developed with the capacity to collect diverse relevant information, which is automatically and easily synchronized to the project database. This study also presents a process proposal for appropriate use of the database and the tools developed, outlining all the steps necessary for data acquisition, manipulation and publication, indicating the best practices for successful use

Forecasting Lake-Effect Snow in the Great Lakes Using NASA Satllite Data

This slide presentation reviews the forecast of the lake effect snow in the Great Lakes region using models and infrared estimates of Great Lake Surface Temperatures (GLSTs) from the MModerate Resolution Imaging Spectroradiometer (MODIS) instrument on Terra and Aqua satellites, and other satellite data. This study analyzes Lake Erie and Lake Ontario which produce storm total snowfall ranged from 8-18 inches off of Lake Ontario and 10-12 inches off of Lake Erie for the areas downwind

Forecasting Lake-Effect Precipitation in the Great Lakes Region Using NASA Enhanced-Satellite Data

Lake-effect precipitation is common in the Great Lakes region, particularly during the late fall and winter. The synoptic processes of lake-effect precipitation are well understood by operational forecasters, but individual forecast events still present a challenge. Locally run, high resolution models can assist the forecaster in identifying the onset and duration of precipitation, but model results are sensitive to initial conditions, particularly the assumed surface temperature of the Great Lakes. The NASA Short-term Prediction Research and Transition (SPoRT) Center has created a Great Lakes Surface Temperature (GLST) composite, which uses infrared estimates of water temperatures obtained from the MODIS instrument aboard the Aqua and Terra satellites, other coarser resolution infrared data when MODIS is not available, and ice cover maps produced by the NOAA Great Lakes Environmental Research Lab (GLERL). This product has been implemented into the Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS), used within forecast offices to run local, high resolution forecasts. The sensitivity of the model forecast to the GLST product was analyzed with a case study of the Lake Effect Storm Echinacea, which produced 10 to 12 inches of snowfall downwind of Lake Erie, and 8 to 18 inches downwind of Lake Ontario from 27-29 January 2010. This research compares a forecast using the default Great Lakes surface temperatures from the Real Time Global sea surface temperature (RTG SST), in the WRF-EMS model to the enhanced NASA SPoRT GLST product to study forecast impacts. Results from this case study show that the SPoRT GLST contained less ice cover over Lake Erie and generally cooler water temperatures over Lakes Erie and Ontario. Latent and sensible heat fluxes over Lake Ontario were decreased in the GLST product. The GLST product decreased the quantitative precipitation forecast (QPF), which can be correlated to the decrease in temperatures and heat fluxes. A slight increase in precipitation coverage was noted over Lake Erie due to a decrease in ice cover. Both the RTG SST and the GLST products predicted the precipitation south of the actual location of precipitation. This single case study is the first part of an examination to determine how MODIS data can be applied to improve model forecasts in the Great Lakes region