Sensitivity of seasonal migration to climatic variability in central India

Abstract

Extreme climatic events and variability are on the rise around the world, with varying implications for populations across socio-economic conditions. Effective strategies for climate adaptation and development depend on understanding these differential sensitivities to climatic variability. This study focuses on a vulnerable population living in forest-fringe villages of central India, where seasonal migration is a common livelihood strategy for poor households to supplement their incomes with remittances. We quantify the relative sensitivity of a decision to migrate for the first time to climate and socio-economic variables and how the sensitivities vary for different segments of the population. We surveyed 5000 households in 500 forest-fringe villages to identify patterns of migration from 2013 to 2017. Using a mixed-effects logistic regression model, we predicted the probability of first-time migration of a household member based on climate variables and household- and district-level characteristics. We find that households in more agricultural and prosperous districts experience lower rates of migration but are more sensitive to climatic variability than households in poorer districts. The probability of first-time migration from a household in the most prosperous district increases by approximately 40% with one standard deviation in mean maximum temperature or rainfall from the 1981–2017 mean. However, the probability of migration does not vary as a function of climatic variability for households in the poorest district. We attribute this difference in sensitivities to the greater dependence on agriculture and irrigation in more prosperous districts and poverty-driven dependence on migration regardless of the climate in poorer districts. Households investing remittances from migration in agricultural intensification could become increasingly sensitive to climate variability, particularly with water shortages and projected increases in climate variability in the region. Promotion of non-agricultural livelihood options and climate-resilient agriculture could the reduce sensitivity of migration to climate variability in the study region.

Listening for change: quantifying the impact of ecological restoration on soundscapes in a tropical dry forest

“…The average elevation in the district is 539 m above sea level. Tropical deciduous vegetation dominates this region (Agarwala et al 2019), and one of the largest populations of constitutionally recognized socio‐economically disadvantaged scheduled castes and tribes in India is dependent on timber and NTFPs for livelihoods in this region (Choksi et al 2021; DeFries et al 2021). These forests represent classic socio‐ecological systems, which have been managed by local communities for their livelihood and subsistence needs for generations (Agarwala et al 2019).…”

“…These forests represent classic socio‐ecological systems, which have been managed by local communities for their livelihood and subsistence needs for generations (Agarwala et al 2019). While intensive agricultural expansion is taking place in parts of this region, locals largely engage in subsistence and small‐scale market‐oriented agriculture, which is primarily rain‐fed (Choksi et al 2021). The region has been experiencing a weakening of the monsoon as well as an increase in the frequency and intensity of heatwaves in recent decades (Choksi et al 2021).…”

“…While intensive agricultural expansion is taking place in parts of this region, locals largely engage in subsistence and small‐scale market‐oriented agriculture, which is primarily rain‐fed (Choksi et al 2021). The region has been experiencing a weakening of the monsoon as well as an increase in the frequency and intensity of heatwaves in recent decades (Choksi et al 2021).…”

Climate change and migration: A review and new framework for analysis

“…Most notably, there is strong evidence that shocks are most clearly associated with migration in countries, regions, and communities with higher reliance on agricultural production and incomes (Beine & Parsons, 2015; Cai et al, 2016; Coniglio & Pesce, 2015; Hoffmann et al, 2020; Nawrotzki & Bakhtsiyarava, 2017; Wesselbaum, 2019); and in rural as against urban areas (Murray‐Tortarolo & Salgado, 2021; Nawrotzki, Hunter, et al, 2015). In contrast, evidence on the impact of income is contradictory: some studies find a stronger shock‐migration relationship in low‐income countries and regions (Choksi et al, 2021; Defrance et al, 2022; Falco et al, 2019; Kakinuma et al, 2020), while others find effects to be stronger in middle‐income areas, where economic constraints do not affect migration capacities to the same degree (Beine & Parsons, 2017; Delazeri et al, 2022; Hoffmann et al, 2020). The impacts of shocks on migration are also mediated by the presence of infrastructures and services such as irrigation (Benonnier et al, 2022).…”