CARACTERIZAÇÃO PRODUTIVA E SOCIOECONÔMICA DE MUNICIPIOS INTENSIVOS NA PRODUÇÃO LEITEIRA DO ESTADO DO RIO GRANDE DO SUL

Com o passar dos anos houveram várias mudanças estruturais no setor lácteo no Rio Grande do Sul, havendo um aumento de produtividade no setor. Sendo assim, o presente trabalho tem como objetivo analisar a dinâmica produtiva e socioeconômica dos municípios mais intensivos em produção de leite do estado. Para isso, foi realizado um levantamento dos índices socioeconômicos e de outras características referentes a esses municípios. Como principais resultados verificou-se que apesar da proximidade dos municípios, as produtividades diferentes, e concentração considerável de residentes na zona rural. Os municípios, em geral apresentam o IDH alto, e índice de Gini semelhantes. Além disso, o PIB é composto de serviços, seguido da agropecuária e indústria

EVIDÊNCIAS DA CURVA J PARA A BALANÇA COMERCIAL DO ESTADO DO RIO GRANDE DO SUL (1999-2014)

Os efeitos de curto e longo prazo de depreciações cambiais sobre a balança comercial são teoricamente distintos, retração inicial seguida de recuperação, conceituando a proposição da Curva J. Esses efeitos pautaram a discussão proposta no artigo à análise da balança de comércio do estado do Rio Grande do Sul no período 1999-2014. Para isso, fez-se uso da metodologia do Vetor de Correção de Erros. As evidências indicaram a presença de, pelo menos um estágio, da Curva J. Isso porque, após o choque na taxa de câmbio real, ocorreu ligeira queda nos saldos comerciais, em termos totais e por fator agregado, seguida de breve recuperação, a qual não é suficiente para eliminar os efeitos cambiais. Além disso, no curto prazo, a balança de produtos industrializados mostrou maior sensibilidade, enquanto que, no longo prazo, os produtos básicos apresentaram elasticidade duas vezes maior.

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,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

Mercado Brasileiro de Lácteos: análise do impacto de políticas de estímulo à produção

The study aimed to assess the impact of incentive policies for the production of milk and dairy products in the Brazilian regions from the simulation of two policies: the first consisted of increases of 10% and 20% in subsidies for the production of milk and dairy products (1A and 1B scenarios), and the second, a reduction of 10% to 20% in taxes on the use of primary factors in the production milk and dairy products (scenarios 2A and 2B). Both simulations were performed based on the o General Equilibrium Analysis Project of the Brazilian Economy (Paeg). The results indicated that the Brazilian regions with higher milk production, respectively Southeast, South and Central-West would be the most benefited, as well as displace the production factors such as capital and labor, from the North and Northeastern regions, whose dairy sector would present losses. These results were shown in greater magnitude when simulated the policy of expansion of subsidies compared to the tax relief policy. From this, the implementation of differentiated regional and sectorial policies is the alternative indicated

Mercado Brasileiro de Lácteos: análise do impacto de políticas de estímulo à produção

The study aimed to assess the impact of incentive policies for the production of milk and dairy products in the Brazilian regions from the simulation of two policies: the first consisted of increases of 10% and 20% in subsidies for the production of milk and dairy products (1A and 1B scenarios), and the second, a reduction of 10% to 20% in taxes on the use of primary factors in the production milk and dairy products (scenarios 2A and 2B). Both simulations were performed based on the o General Equilibrium Analysis Project of the Brazilian Economy (Paeg). The results indicated that the Brazilian regions with higher milk production, respectively Southeast, South and Central-West would be the most benefited, as well as displace the production factors such as capital and labor, from the North and Northeastern regions, whose dairy sector would present losses. These results were shown in greater magnitude when simulated the policy of expansion of subsidies compared to the tax relief policy. From this, the implementation of differentiated regional and sectorial policies is the alternative indicated

Mercado Brasileiro de Lácteos: análise do impacto de políticas de estímulo à produção

Resumo: O trabalho objetivou avaliar os potenciais impactos de políticas de incentivo à produção de leite e derivados nas regiões brasileiras a partir da simulação de duas políticas: a primeira consistiu em aumentos de 10% e 20% na concessão de subsídios à produção de leite e derivados (cenários 1A e 1B), e a segunda, de reduções de 10% e 20% nos impostos incididos na produção de leite e derivados (cenários 2A e 2B). Ambas as simulações foram realizadas tendo como base o Programa de Equilíbrio Geral da Economia Brasileira (Paeg). Os resultados indicaram que as regiões brasileiras com maior produção de leite, respectivamente Sudeste, Sul e Centro-Oeste, seriam as mais beneficiadas, além de deslocar fatores produtivos, caso do capital e do trabalho, das regiões Norte e Nordeste, cujo setor lácteo apresentaria perdas. Estes resultados foram evidenciados em maior magnitude quando simulada a política de ampliação da concessão de subsídios comparativamente à política de desoneração fiscal. A partir disso, a implementação de políticas regionais e setoriais diferenciadas faz-se alternativa indicada