Revista de Economia e Sociologia Rural
https://revistasober.org/article/doi/10.1590/1806-9479.2019.187600
Revista de Economia e Sociologia Rural
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Conhecimento sobre mudanças climáticas implica em adaptação? Análise de agricultores do Nordeste brasileiro

Does knowledge about climate change imply adaptation? Analysis of farmers in Northeast Brazil

Sabrina de Matos Carlos; Dênis Antônio da Cunha; Marcel Viana Pires

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Resumo

Este estudo analisa a relação entre conhecimento sobre as mudanças climáticas e adoção de estratégias adaptativas de agricultores do Nordeste (bacia hidrográfica do Rio das Contas, Bahia). Metodologicamente, foi estimado um modelo Probit Bivariado Aparentemente Não Relacionado. Os resultados evidenciaram que conhecimento e adaptação são correlacionados e devem ser pensados de forma conjunta. Agricultores que conhecem os efeitos das mudanças climáticas têm maior probabilidade de adotar medidas adaptativas. Isso reforça a importância de se considerar a percepção, o conhecimento e as condições socioeconômicas dos indivíduos na formulação de políticas públicas de combate aos efeitos das mudanças climáticas.

Palavras-chave

conhecimento, adaptação, mudanças climáticas, bacia hidrográfica do Rio das Contas, probit bivariado aparentemente não relacionado

Abstract

We analyze the relationship between farmer’s knowledge about climate change and the adoption of adaptive strategies. The study area was the Brazilian Northeast (Rio das Contas basin, Bahia). Methodologically, we estimated a Seemingly Unrelated Bivariate Probit model. The results showed that knowledge and adaptation are correlated and should be considered together. Farmers who are aware of the climate change effects are more likely to adapt. This finding reinforces the importance of considering the perception, knowledge and socioeconomic conditions of individuals in the formulation of public policies to counteract the negative effects of climate change.
 

Keywords

knowledge, adaptation, climate change, Rio das Contas basin, seemingly unrelated bivariate probit model

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Submetido em:
08/11/2017

Aceito em:
28/07/2018

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