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Collaborative Learning for Ecosystem Services in the Context of Poverty Alleviation: A Case from India


Madhu Bharti
Neeru Bansal

Abstract

Unplanned and unregulated urbanisation and industrialisation has led to large-scale degradation of the environment, including that of water bodies in India (Mukherjee, 2009). Communities and governments have, over time, tried innovative approaches to the development and management of water bodies. Often, these approaches are focused on physical restoration, ignoring the human component – especially the dependence of people on the water body for their livelihood and sustenance. The ecosystem services for poverty alleviation (ESPA) approach seeks to tie together the various social and environmental requirements in a holistic manner and, in the process, recognise the interdependence between humans and nature. The Supporting Urban Sustainability (SUS) Programme focuses on an ESPA approach in urban settings using the methods of collaborative learning. The purpose of this article is to illustrate how an emerging theory, ESPA, can be institutionalised through a collaborative-learning process. The research is qualitative in nature. It explains the local Ahmedabad case study in order to provide insight into the SUS Programme activities, and then takes a broader view of collaborative learning across the other participating cities in the SUS Programme. The data for the case study on Ahmedabad city was collected during the implementation of the SUS Programme at the site, while the data on collaborative learning was collected from city team members engaged in the SUS Programme across a number of SUS Programme sites through a survey questionnaire. The latter data was then analysed by grouping narratives with reference to various aspects of collaborative learning from the participants’ points of view. The outcomes could thereafter be used to support the development of collaborative learning projects elsewhere, and would also be useful for further developing the work done during the Ahmedabad case study.


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eISSN: 2411-5959
print ISSN: 0256-7504