Transitions to crop residue burning have multiple antecedents in Eastern India

Abstract

Far removed from the agricultural fire "hotspots" of Northwestern India, rice residue burning is on the rise in Eastern India with implications for regional air quality and agricultural sustainability. The underlying drivers contributing to the increase in burning have been linked to the adoption of mechanized (combine) harvesting but, in general, are inadequately understood. We hypothesize that the adoption of burning as a management practice results from a set of socio-technical interactions rather than emerging from a single factor. Using a mixed methods approach, a household survey (n = 475) provided quantitative insights into landscape and farm-scale drivers of burning and was complemented by an in-depth qualitative survey (n = 36) to characterize decision processes and to verify causal inferences derived from the broader survey. For communities where the combine harvester is present, our results show that rice residue burning is not inevitable. The decision to burn appears to emerge from a cascading sequence of events, starting with the following: (1) decreasing household labor, leading to (2) decreasing household livestock holdings, resulting in (3) reduced demands for residue fodder, incentivizing (4) adoption of labor-efficient combine harvesting and subsequent burning of loose residues that are both difficult to collect and of lower feeding value than manually harvested straw. Local demand for crop residues for livestock feeding plays a central role mediating transitions to burning. Consequently, policy response options that only consider the role of the combine harvester are likely to be ineffective. Innovative strategies such as the creation of decentralized commercial models for dairy value chains may bolster local residue demand by addressing household-scale labor bottlenecks to maintaining livestock. Secondary issues, such as timely rice planting, merit consideration as part of holistic responses to "bend" agricultural burning trajectories in Eastern India towards more sustainable practices.

Supplementary information: The online version contains supplementary material available at 10.1007/s13593-024-00983-3.

Keywords: Air quality; Bihar; Crop burning; Indo-Gangetic Plain; Mixed crop-livestock systems; Mixed methods; Socio-technical drivers.

Fig. 1

Buxar, Bihar, showing partially burnt rice residue with zero-till wheat sowing is in progress (PC: Anurag Ajay)

Fig. 2

Visible Infrared Imaging Radiometer Suite (VIIRS) remotely sensed fire observations during rice harvest season in Bihar (Urban Cordeiro et al. 2023).

Fig. 3

Livelihood Platforms Approach. Adapted from Brown et al. (2017).

Fig. 4

Variable importance plot of random forest model to predict burn likelihood. Units are the increase in mean square error (MSE) if the predictor was randomized

Fig. 5

Partial dependency plots of random forest model to predict burn likelihood. Note that “yhat” indicates the predicted burn likelihood based on the values of the predictor variables included in the model

Fig. 6

Single regression tree example for residue burning probability to visualize interactions embedded in the random forest model predictions. The values in the nodes indicate the mean of the target variable (i.e., burn likelihood) within the number of observations. For example, in the first node (i.e., root), the mean value of 0.0961 is derived from 402 observations

Fig. 7

Conceptual model of factors influencing rice harvest and residue management