Evaluating the effectiveness of CBNRM in increasing the adaptive capacity of communities to climate change
Climate change is predicted to have severe implications on all the natural and social sectors. Recent literature on climate change suggests merits in both mitigation and adaptation strategies to tackle climate change. Since Community Based Natural Resource Management (CBNRM) has become a popular strategy for managing natural resources around the world, it is also being evaluated for its effectiveness in increasing the adaptive capacity of local communities. There are arguments for and against CBNRM’s ability to increase the adaptive capacity of local communities. A deeper understanding in CBNRM’s effectiveness has policy and hence financial implications on how we approach climate change around the world. My research will focus on identifying indicators that can measure local adaptive capacity and then assess the effectiveness of CBNRM in increasing the resilience by taking Joint Forest Management (JFM) in India as a CBNRM strategy.
The Government of India has recognized Community Based Forest Management as one of the major strategies of conservation and sustainable management of the forest areas in the country. Currently it is estimated that 27% of total forestlands are being managed under the (JFM) program, through around 99,000 committees in 28 states. My research will focus on three states: Madhya Pradesh, Andhra Pradesh and Orissa, which are the poorest and the largest (in terms of population) states in India and have a high percentage of their forest area managed through JFM. These states by the year 2085 are predicted to see a dieback in forest and loss of biodiversity due to increase in temperatures and precipitation. This will directly affect the 3 million members of the 22,000 JFM committees that manage approximately 85,000 sq km of forest area in these three states.
My research will assess JFM communities present and future adaptation capacity by measuring the social vulnerability as they are highly inversely correlated. The study will start with identification of indicators that are best suited for measuring the vulnerability of local JFM communities based on socio-institutional and ecological attributes. Suitable indicators (new/adopted) will be tested for their ability to measure local vulnerability of a small number (10) of JFM communities. The final set of indicators that have significant correlation with local level vulnerability will then be used to carry out assessments in a greater number (≈1% of the total) of JFM communities in respective states. Control communities (communities without JFM) will also be studied to assess the vulnerability and hence adaptive capacity in the absence of JFM. The results will be a cross-comparison of JFM communities through a local level Vulnerability Index (similar to the Environmental vulnerability index) providing understanding on the effectiveness of CBNRM in changing the adaptive capacity of local communities.
The understanding developed through this research will have significant implications on both science and policy dimensions of adaptation. The need for inclusion of adaptation and adaptive capacity in future regional climate modeling exercises to increase precision as mentioned by many experts will be partly fulfilled by my research through the identification of the indicators that can measure local level vulnerability across different regions of India. Finally, a greater understanding of the effectiveness of CBNRM in increasing adaptive capacity will help the governments and donor agencies in making informed decisions when choosing an appropriate adaptation strategy.