The present study intends to understand and disclose the role of information infrastructure in climate change adaptation and its underlying barriers in the communities of socio-ecological system (SES) in the Central Himalaya. The study makes use of primary data in its research methodology which comprises the use of questionnaires, oral interviews, and review of relevant literature. The data were collected using a questionnaire-based survey from 85 households in 11 villages. The study results show that road accessibility and irrigation facilities remarkably influence the educational, professional, and economic conditions of the communities. The research reveals how the flow of information through television, newspapers, village elders, and mobile phones influences perceptions of climate change in a different order. Information infrastructure availability is higher with the communities having access to the road network and irrigation facilities. The study concludes that in SES a good information infrastructure is highly relevant for reducing the current and future vulnerability of SESs to climate change. The study also provides recommendations for the dissemination of information on climate adaptation that suit the needs and demands of the Himalayan SESs and thus could help to close existing information gaps and barriers.

The Himalaya is a mosaic of complex socio-ecological systems (SESs) characterized by a wide diversity of altitude, climate, landform, biodiversity, ethnicity, culture, and agriculture systems, among other things. Identifying the distribution of SESs is crucial for integrating and formulating effective programs and policies to ensure human well-being while protecting and conserving natural systems. This work aims to identify and spatially map the boundaries of SESs to address the questions of how SESs can be delineated and what the characteristics of these systems are. The study was carried out for the state of Uttarakhand, India, a part of the Central Himalaya. The presented approach for mapping and delineation of SESs merges socio-economic and ecological data. It also includes validation of delineated system boundaries. We used 32 variables to form socio-economic units and 14 biophysical variables for ecological units. Principal component analysis followed by sequential agglomerative hierarchical cluster analysis was used to delineate the units. The geospatial statistical analysis identified 6 socio-economic and 3 ecological units, together resulting in 18 SESs for the entire state. The major characteristics for SESs were identified as forest types and agricultural practices, indicating the influence and dependency of SESs on these two features. The database would facilitate diverse application studies in vulnerability assessment, climate change adaptation and mitigation, and other socio-ecological studies. Such a detailed database addresses particularly site-specific characteristics to reduce risks and impacts. Overall, the identified SESs will help in recognizing local needs and gaps in existing policies and institutional arrangements, and the given methodological framework can be applied for the entire Himalayan region and for other mountain systems across the world.