The present study aims to assess the socioecological vulnerability of smallholders through an index of Tehri Garhwal Himalaya. The index provides a realistic approach to recognize the contributions of social and ecological factors for household welfare vulnerability to climate change. The approach puts forward various indices for each component of vulnerability to climate change - exposure, sensitivity, and adaptive capacity including two more indices: one for overall impact under the exposure of climate change and another for overall vulnerability. The five indices were proposed to assess the vulnerability status of with and without agroforestry practicing households in Himalayan region. These indices are based on 35 indicators (8 for exposure; 12 for sensitivity, 15 for adaptive capacity), selected through inductive approaches. A questionnaire for households was designed for the above aim and was administered to 121 heads of households through face-toface interviews with 77 households practicing agroforestry and 44 without agroforestry. The questionnaire dealt the general household information, and indicators of the vulnerability including the issues related to agroforestry. The results highlight slightly higher adaptive capacity of agroforestry practicing households due to specific contribution of agroforestry. The low contribution of agroforestry among smallholders was due to small land holding. The study also results that remoteness, specific issues of smallholders’ such as poverty, education and employment are responsible for the present condition. In particular this study clearly shows that poverty is the key driver for vulnerability. All of these issues can be addressed if future programs and policies, include and implement regulations to remedy attributive factors. This paper may be applicable to other mountainous regions providing insights for effective adaptation strategies to climate change.

In recent times, the use of traditional herbal medicines in healthcare has declined, particularly amongst the rural population. This implies a risk of losing vital information from previous generations regarding plants and their use in traditional medicine. The objective of this study is to catalog the ways employed by inhabitants of the Garhwal Himalayas as part of their traditional approaches to healthcare. Information was gathered through snowball sampling using a questionnaire combined with informal interviews. This was supplemented by discussions with peers and practitioners prominent in this healing technique. The homogeneity within ethnomedicinal knowledge of these rural residents was tested using the informant consensus factor (Fic). The calculation of the fidelity value (FL) and the cultural importance index (CI) were made regarding the population’s dependency on plants. A total of 88 plant species from 44 families and 80 genera were identified as medicines for various complaints. Leaves were the most frequently used plant part followed by fruits, seeds, roots, bark, and flowers/buds. The largest number of taxa (15 species) were used for treatment of skin ailments (with Fic score of 0.85) followed by wounds, coughs, and digestive problems. There was a significant relationship observed between the medicinal plants used and distance (time of access) and family income. The present study will provide baseline information to be established for future research. The available information could help to discover new drugs for the pharmaceutical industry. Thus, the study revealed that the plants that have high scores of FL and CI can be used to discover new drug extraction in the future for further studies.

Understanding climate change vulnerability of Indian forests has received wider attention in recent years and a number of assessments with different approaches have emerged over time. These assessments have mostly used climate-sensitive vegetation models to explain the climate change impacts. In these studies, trees constituting a particular forest are often clubbed together into small number of groups having similar functional traits referred as Plant Functional Types (PFTs). Most of the Forest Vegetation Models (FVMs) are still in their developmental stage and there have been attempts at various levels to develop more versatile and precise models. Several developing countries, including India, still lag behind in developing dynamic vegetation models (DVMs), which could be appropriate for the local applications to predict the impact on forests at regional level. This is restrained mainly because of the lack of long-term observations with respect to various interacting biotic, abiotic and climatic (or environmental) variables in a forest ecosystem, like water and nitrogen use efficiency, response to elevated concentration of CO2, nutrient cycling, net primary productivity, etc. The observations on influence of the environmental variables on forest ecosystems are available in discrete form. Existing FVMs integrate observations more appropriately for their place of origin for which they have been developed. Different types of forests in different climatic zones are supposed to respond differently to climatic changes. Hence, it is imperative that models are developed for the specific biogeographic regions in order to predict the influences more accurately. It may not be wise to use existing FVMs in their pristine form for all of the region without considering the regional influences. Various challenges associated with the usage of the generic models of external origin with special reference to Integrated Biosphere Simulator (IBIS) model - being widely used and accepted in Indian policy documents- is presented in this paper. We also discuss on the need for developing a regional FVM for climate change impact studies, so that the impact prediction is more precise and reliable.

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Conservation faces the challenge of reconciling human activities with the simultaneous presence of wildlife in cultivated landscapes. In attempt to estimate biomass and associated carbon loss due to the removal of agroforestry trees species the present study was carried out in two villages of Pauri Garhwal. The results revealed that due to human-animal interaction caused substantial biomass loss (7.365 and 2.453 t ha-1) and carbon loss (3.386 and 15.133 t ha-1) in the two studied villages Manjgaon and Mald Bada, respectively. The estimates of the present study demands protecting existing forests and planting trees through reforestation and afforestation as a measure to enhance carbon sequestration capacity. The success of these management practices will depend on the potential to minimise human-animal interactions especially in the fringes of the village community and agricultural landscapes.