Climate changes and environmental migrations in the Northeastern Semiarid

Type

Journal Article

Author(s)

Bilar, A.
De Carvalho, R.
Galvincio, J.
De Souza, W.

Title

Climate changes and environmental migrations in the Northeastern Semiarid

Year

2016

Journal

Journal of Hyperspectral Remote Sensing

Vol (No), pp

6(1), 36-43

Abstract

The present exploratory and descriptive study brings some thoughts and inferences about the relationships between rainfall, climate changes and environmental migrations in the small-sized municipalities of the northeastern semiarid, that is, the ones which are a part of the Caatinga biome. For this purpose, it was examined the case of Santana de Mangueira, municipality of Paraíba state, which currently has less than six thousand habitants, according to data from the Instituto Brasileiro de Geografia e Estatística – IBGE (2010), bordering in the South with Serra Talhada/PE, which was used as the rainfall data collection source, due to the lack of such records in Santana de Mangueira/PB.The studied municipality presented a significant decrease in population, in approximately eigth per cent, according to the IBGE census performed during the years of 2000 and 2010, respectively. The central inquiry that subsidized the present study was: How are the relationships between climate changes and rainfall affecting small-sized municipalities’ citizens’ lives in the Caatinga biome?As for the conclusions, it was found, through obtained data analysis, that the small-sized municipalities of the northeastern semiarid region, traditionally used to lose their citizens for bigger cities in the pursuit for better living conditions, tend to suffer an increase of the migration flow with the climate changes consequences worsening, as: drought period increase, desertification, and, consequently, family agriculture and cattle raising reduction.

Citation

Bilar, A., De Carvalho, R., Galvincio, J., & De Souza, W. (2016). Climate changes and environmental migrations in the Northeastern Semiarid Journal of Hyperspectral Remote Sensing, 6(1), 36-43. doi:10.5935/2237-2202.20160004.

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