Modelling study finds rural employment scheme important for forest cover

Social welfare schemes such as the one under the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) could have a positive impact on forest cover, apart from providing income and employment, a new research paper studying the relationship between tree plantations and livelihood benefits has suggested.

Researchers from the Swedish University of Agricultural Sciences Uppsala, Florida State University, University of Minnesota and the Forest Department in Himachal Pradesh sought to understand what conditions helped improve both forest and livelihood outcomes in Kangra district in Himachal Pradesh, where tree plantation drives are common.

They found that joint positive outcomes were more likely in areas where marginalised groups had histories in engaging with collective action, of mutually exchanging labour for ​​the purposes of forestry, agriculture, construction and cultural activities. They also found that, after a certain threshold, employment generation schemes like the MGNREGA scheme led to big gains for both livelihood and forest cover in areas with plantations.

The MGNREGA scheme is a government scheme implemented in 2006 which ensures livelihood security in rural India by providing guaranteed employment for 100 days a year for at least one adult of every household.

MGNREGA as a social safety net

Though changes in forest cover and poverty have been studied before, the interrelationships between the two in forested areas is less understood. The researchers used 36 variables covering socioeconomic and demographic characteristics of local communities, institutional dynamics of forest governance and plantation activity, and the biophysical characteristics of 377 plantations in Kangra district as part of the study.

The researchers used interpretable machine learning (IML) to create predictive insights into which variables produced win-win outcomes for both livelihood and forest cover, as well as win-lose and lose-lose outcomes. “The results need to be read with caution, because this type of analysis only provides associations between factors and multiple outcomes based on predictive analysis, and it doesn’t give us the cause for why we see these patterns,” said Pushpendra Rana, a senior officer with the Indian Forest Service in Himachal Pradesh and lead author of the study.

For a win-win outcome, where the model showed improvements in forest cover from tree plantations as well as improvements in livelihood, the presence of Scheduled Tribes and Scheduled Castes were found to be the biggest influencing factor, followed by level of education and number of work days under MGNREGA. Higher levels of education coincided with lower levels of win-win outcomes, which the researchers speculate could be due to less dependence on forest resources as education levels rise. The impact of MGNREGA, however, leads to a high win-win probability when an individual’s job days cross 1210, the researchers found.

In settings where marginalised groups don’t have access to higher levels of education, MGNREGA can act as a “robust social safety net,” which “may help to reduce dependence on forest resources for the poor and marginal, thus making it more possible to support livelihoods at a base level while also achieving forest growth,” the paper says.

Ashwani Chhatre, Associate Professor at the Indian School of Business (ISB), who was not involved with the study, said the MGNREGA scheme offers flexibility in that the design of the scheme, which guarantees employment for 100 days a year, allows for rural infrastructure development to be considered alongside environmental conservation. “With MGNREGA, it’s possible to find places where forest restoration opportunities and livelihood opportunities overlap, and to build a project that can satisfy both at a village level. But this type of high resolution design is not possible in central planning. Often this type of overlap is invisible to the district collector and other planners,” he said.

To understand how plantations impact livelihoods, the researchers limited the definition of livelihood benefits to dependence on forest resources. This definition builds on previous research by the same researchers which found that mass tree planting in Kangra shifted the composition of trees away from broadleaf varieties which were valued by local people, and led to less use of them, thus negatively impacting livelihood goals. Broadleaf varieties and grasses are popularly used for fuelwood and fodder.

While it helps clarify the impacts of plantations on resource use, such a definition of livelihood benefits may not be able to accommodate the changing aspirations of rural populations, said Chhatre. “Accessing fuel wood and fodder is not the only interest or livelihood benefit among these groups, especially as you climb up the education ladder. Forests also need to be able to generate jobs and wealth among these communities, through sustainable means. More research needs to be done in this area too.”

Addressing poverty and forest cover

Other measures for poverty alleviation have also been found to help forest outcomes. A study from the dry tropical forests of central India found that alternatives to fuelwood for cooking and non-forest-based housing material led to improvements in living standards and reduced pressure on the degradation of forests.

Apart from livelihood schemes, strengthening local decision-making bodies which are based on collective action could also help livelihood and forest outcomes, said Rana. “Whether these local institutions are focussed on forestry or not, we find that more institutions focussing on collective action lead to the best outcomes. Strong consolidated committees can help avoid conflict and facilitate decision-making, which we found benefited both forests and people,” he said.

Read more: A framework for quantifying the climate co-benefits of MGNREGS

Banner image: MGNREGA work underway, removing mud from a pond, in Sirsa, Haryana. Image by Mulkh Singh via Wikimedia Commons (CC BY-SA 4.0).