Eco-Dharma and Climate Change: An Ecospective Rendition of Valmiki Ramayana and Hindu Eco-Praxis for Environmental Conservation and Sustainable Living.
Published In: International Journal of Religion & Spirituality in Society, 2025, v. 15, n. 1. P. 145 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Neethu M. S.; Bhuvaneswari R. 3 of 3
Abstract
Climate change is widely seen as a prominent and significant concern in contemporary society, representing a pivotal juncture in our collective history. Growing evidence suggests that our approach to climate change is also influenced by our religious beliefs. However, the manner and extent to which religious institutions, practices, and beliefs around the globe interact with the concept of climate change remains a subject that requires further investigation. This study explores the notion of environmental conservation put forth in the epic text The Ramayana and the eco-dharmic principles of Hinduism in the context of climate change, emphasizing Hindu customs as unique ecological spiritualities deeply rooted in profound reverence and connection to the natural world. It argues for the equal inclusion of religious studies and theology in the realm of climate science, highlighting the need to re-envision early Hindu literary traditions through an eco-theological lens for global sustainability, drawing attention to the correlation between the Sanskrit term Vasudhaiva Kutumbakam and Barry Commoner's First Law of Ecology. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Religion & Spirituality in Society. 2025/03, Vol. 15, Issue 1, p145
- Document Type:Article
- Subject Area:Religion and Philosophy
- Publication Date:2025
- ISSN:2154-8633
- DOI:10.18848/2154-8633/CGP/v15i01/145-163
- Accession Number:184409898
- Copyright Statement:Copyright of International Journal of Religion & Spirituality in Society is the property of Common Ground Research Networks and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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