Porcelanato técnico vs futuro da cerâmica: análise do projeto de investimento

A globalização da economia associada à grande competitividade do setor cerâmico em Portugal obriga as empresas a estarem em constante adaptação ao meio envolvente. Daí ser fulcral a apresentação de produtos diferenciados, inovadores e com uma boa relação qualidade/preço. Nesse sentido, a Gresart, S.A. pretende investir numa nova linha de produção de grés porcelânico. O objetivo principal da presente análise é aferir a viabilidade económica e financeira do projeto de investimento “Grés Porcelânico”, ou seja, averiguar se a empresa conseguirá aumentar o seu mercado e o seu valor de vendas. Numa primeira parte do trabalho posicionamos o setor cerâmico no mundo e em Portugal e explicamos as principais caraterísticas a ter em conta num projeto de investimento. Posteriormente, realizámos um estudo de viabilidade sobre o projeto de investimento “Grés Porcelânico” para percebermos se a sua implementação seria efetivamente vantajosa para a Gresart, S.A.. Concluímos que a empresa deverá aceitar este projeto de investimento uma vez que os indicadores vendas líquidas, resultado líquido e meios líquidos apresentam um crescimento gradual acompanhados de uma redução do passivo. O que demonstra que o investimento permite o crescimento da empresa. Porém, os seus resultados apenas serão visíveis a longo prazo.The globalization of the economy associated with the great competitiveness of the ceramic sector in Portugal forces the companies to be in constant adaptation to the surrounding environment. This is why it is essential to present differentiated, innovative and good price ratio products. In this sense, Gresart, S.A. intends to invest in a new porcelain stoneware production line. The main goal of the present analysis is to assess the economic and financial viability of the "Porcelain Stoneware" investment project, in other words, to determine if the company will be able to increase its market and its sales value. In a first part of the work we present the ceramic sector in the world and in Portugal and explain the main characteristics to be taken into account in an investment project. Subsequently, we carried out a viability study on the investment project "Porcelain Stoneware" to see if its implementation would be effectively advantageous for Gresart, S.A. We conclude that the company should accept this investment project since the indicators net sales, net income and net assets show a gradual growth accompanied by a reduction of liabilities. This shows that the investment allows the company to grow. However, the results will only be visible in the long term.Mestrado em Economi

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost