<p>Climate change poses significant challenges to vulnerable communities, particularly in regions like Central India, where livelihoods depend heavily on natural resources and agriculture. Despite that, limited research has explored these marginalized groups’ socio-economic and climatic impacts in these regions. The study evaluates the climate data, socio-demographic characteristics, perceptions of climate change, and its environmental and socio-economic impacts on tribal households in the Dhar and Chhindwara districts, Central India. The study used a mixed-method approach employing Innovative Trend Analysis (ITA), Standardized Precipitation Index-3 (SPI-3), household surveys, binary logistic regression, and multiple linear regression to analyse climatic and socio-economic data. The ITA revealed declining rainfall (ITA = -0.193 &amp; -0.072) and increasing temperature trends (ITA = 0.058 &amp; 0.075 for mean temperature) in both districts, worsening agricultural challenges, water scarcity, and health risks. Tribal communities’ perceptions reflected these changes, with over 90% of respondents observing erratic rainfall and summer days becoming hotter. The binary logistic regression results revealed that education, occupation, and access to infrastructure appeared as essential determinants of climate change perception, with disparities between the districts (Pseudo R<sup>2</sup> = 0.2584 &amp; 0.3286). Moreover, the multiple linear regression model demonstrated that socio-demographic factors, such as income and occupation, significantly influenced perceptions of climate change impacts on agricultural productivity, water availability, and health risks. The findings highlight the need for targeted policies, as over 90% of tribal households reported climatic variations impacting agriculture and water, commending policymakers for promoting climate-resilient agriculture, strengthening water management, and integrating tribal people’s perception into adaptation strategies.</p>

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Perceptions of climate change and it’s impacts on tribal livelihoods: an empirical study from central India

  • Amit Kumar,
  • T. Mohanasundari

摘要

Climate change poses significant challenges to vulnerable communities, particularly in regions like Central India, where livelihoods depend heavily on natural resources and agriculture. Despite that, limited research has explored these marginalized groups’ socio-economic and climatic impacts in these regions. The study evaluates the climate data, socio-demographic characteristics, perceptions of climate change, and its environmental and socio-economic impacts on tribal households in the Dhar and Chhindwara districts, Central India. The study used a mixed-method approach employing Innovative Trend Analysis (ITA), Standardized Precipitation Index-3 (SPI-3), household surveys, binary logistic regression, and multiple linear regression to analyse climatic and socio-economic data. The ITA revealed declining rainfall (ITA = -0.193 & -0.072) and increasing temperature trends (ITA = 0.058 & 0.075 for mean temperature) in both districts, worsening agricultural challenges, water scarcity, and health risks. Tribal communities’ perceptions reflected these changes, with over 90% of respondents observing erratic rainfall and summer days becoming hotter. The binary logistic regression results revealed that education, occupation, and access to infrastructure appeared as essential determinants of climate change perception, with disparities between the districts (Pseudo R2 = 0.2584 & 0.3286). Moreover, the multiple linear regression model demonstrated that socio-demographic factors, such as income and occupation, significantly influenced perceptions of climate change impacts on agricultural productivity, water availability, and health risks. The findings highlight the need for targeted policies, as over 90% of tribal households reported climatic variations impacting agriculture and water, commending policymakers for promoting climate-resilient agriculture, strengthening water management, and integrating tribal people’s perception into adaptation strategies.