Effects of Climate Change on Communities Living and Economic Structure of Indus Riverine Areas of Dera Ghazi Khan

Abstract

Climate change is the most important issue of the top current issues that the globe is experiencing. Climate change is the most significant and hazardous issue not just for Pakistan but globally as well. Pakistan is one of the underdeveloped nations in South Asia and is ranked among the five nations that have been worst affected by climate change. Climate change has severely influenced both the development of human lifestyles and existence, together with food scarcity, wildlife destruction, and risky meteorological conditions problems.  The objectives of the study were (1) to investigate the direct consequences of deforestation on the local ecosystem and (2) to examine how deforestation increases environmental changes. The study was delimited to people only in the Indus riverine areas in District Dera Ghazi Khan. All the people who are living in the Indus Riverine areas in District D.G. Khan served as the population of the study. A total sample size of 225 citizens was selected from District Dera Ghazi Khan. In the first stage, 3 Tehsils of District Dera Ghazi Khan e.g. (Dera Ghazi Khan, Kot Chutta, & Taunsa Shareef) were selected. In the second stage, 3 riverside union councils were selected from each Tehsil through a convenient sampling technique. In the third stage, 25 citizens were selected from each union council. Data was collected through an interview schedule and examined by ‘The Statistical Package for Social Sciences’ (SPSS). Obtained results indicate that climate change also happens in the community (99.1%), climate change decreases the local agricultural productivity (92.9%) and climate change has effect on the overall economic sustainability of the local community (95.5%). The bivariate analysis showed that more will be climate change vs less will be the agricultural productivity; less will the economic sustainability. So, all the hypothesis results are accepted after the analysis of the data.