~By Pakhi Das
Extreme climatic events and variability are on the rise around the world, with varying implications for populations across socio-economic conditions. The recent assessment report published by the United Nations Intergovernmental Panel on Climate Change in July 2021 has reiterated the urgent need to develop climate resilient strategies to safeguard the health, prosperity and wellbeing of billions of people across the world. With some communities more dependent on natural resources than others, it has become more important now than ever to study the extent to which the changing climate affect various people from various socio-economic settings and develop strategic plans to mitigate the adverse impacts of climate change. A recent study by Pooja Choksi and collaborators examines seasonal migration as an livelihood strategy given current climatic variability amongst the vulnerable populations living in forest-fringe villages of the Central India Landscape (CIL).
Map of the Central India Landscape. Circles represent 500 survey villages included in this survey. The colour and the size of the circles represent the proportion of households (out of a maximum of 10 households) with at least one seasonal migrant
The study analyses a rural household’s decision to adopt migration for the first time as a livelihood strategy in relation to climatic variability, household-level socio-economic characteristics, and surrounding livelihood options reflected in district-level poverty indices. It is focused on the central Indian landscape because it experiences the summer monsoon (subject to climate change exacerbations), has a large proportion of households with members who migrate seasonally and is one of the poorest regions of the country. Moreover, agriculture in CIL is mainly dependent on rainfall – even when using canals and groundwater irrigation. For the purpose of the analysis, the study defines the landscape as 32 administrative districts across the three CIL states (Madhya Pradesh, Maharashtra and Chhattisgarh). 5000 households were surveyed from 500 villages in the CIL and focused on events between the years 2013 and 2017.
Number of first time migrants from 4323 surveyed households across 476 villages in every year since 1981.
The study includes socioeconomic variables at the household, village, and district levels as predictor variables and treats the response variable as binary – whether the household had a first-time seasonal migrant in a particular year between 2013–2017 (coded as 1) or not (coded as 0). The researchers used mixed-effects logistic regression models to analyze their data (please see their paper for more details on the statistical methods used). Their analysis showed that households in poorer districts, with a higher prevalence of seasonal migration overall, are less sensitive to climatic variability in comparison to households in richer districts. Households in richer districts owned more agricultural and irrigated land as compared to those in poorer households, indicating a larger focus on agriculture as their main livelihood. Studies find that factors such as ownership of larger lands, agricultural assets and technology (including irrigation) as well as the higher labor requirements to tend to the large lands act as deterrents for engaging in occupational diversification, such as migration, for income smoothing.In this region, these households instead adopt common agricultural intensification practices, which promote irrigation, without accounting for long term climate resilience. The correlation between climate anomalies and decision to migrate for the first time demonstrated that, precipitation and temperature anomalies significantly impact mainly agricultural households in richer districts increasing their 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. In contrast, mainly non-agricultural households in poorer districts, which already have higher rates of migration, do not experience in the change in their probability of migration as a result of a change in precipitation and temperature.. The paper also discussed agricultural intensification and/or transformation that is still perceived as a pathway out of poverty and a means to tackle climatic variability. Climate projections for the region have indicated variation in rainfall patterns and statistically significant increase in annual temperatures, which must be addressed by means of appropriate policy intervention. In the last few decades, the focus on increased farm production, with policies and schemes aimed at improving farmers’ access to fertilizers, seeds, credit and improved irrigation have maybe had some short-term positive impact but has left parts of central India with depleted groundwater resources. Thus, as a policy recommendation, the paper strongly suggests that investments in agricultural intensification alone may not serve as a reliable pathway out of poverty in the future as it has in the past. Policies promoting climate-resilient agriculture would be more appropriate for ensuring those households increasing their agricultural activities and investments are adequately capacitated to face climatic variability. Finally, the researchers highlight that policies and welfare schemes that encourage alternative livelihood options and provide employability in various other non-agriculture dependent livelihood opportunities will be key for households in central India in the face of climate change affecting agriculture in the region.
Ramlala Nareti, a resident of Urdali Mal village shows the growth of Lantana camara on open grazing land around the village. Several youngsters from Urdali Mal have migrated for seasonal work in peri-urban and urban centres. Credit: Pooja Choksi.
Original Paper: Choksi, Pooja, Deepti Singh, Jitendra Singh, Pinki Mondal, Harini Nagendra, Johannes Urpelainen, and Ruth Defries. 2021. “Sensitivity of Seasonal Migration to Climatic Variability in Central India.” Environmental Research Letters 16(6). doi: 10.1088/1748-9326/ac046f.