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The intensity and extent of climate change impacts differ significantly with the geographical and ecological structure of the landscape. This is especially evident in mountain ecosystems where topographic, climatic and biological gradients make them extremely vulnerable to global environmental changes. Designing strategies to mitigate and adapt to global climate change on such local landscapes requires a context-specific vulnerabilities that take into account their particular characteristics. Presently, there are two main challenges in assessing climate change vulnerability in mountain ecosystems: 1) The models that are used for vulnerability assessments at global scales are being used at local scales with broad variables from few sectors that do not capture the range of characteristics of mountain ecosystems 2) indigenous knowledge about climate change are not considered in these models, which makes the implementation of mitigation/adaptation measures less successful. In this study, we highlight these issues drawing from our data collected in India's Lesser Himalayan region (Darjeeling). We used a mixed research approach that combines a vulnerability assessment model with a participatory knowledge approach. We based climate change vulnerability around the socio-ecological system of the mountain landscape. The results from the interactive process showed that Darjeeling region is experiencing higher climate change vulnerability than the results produced by the model at the subregional level. We highlight critical variables that influence the socio-ecological system and need to be taken into account when assessing vulnerability and future adaptation scenarios. The study offers a decision support process for policymakers to plan climate mitigation/adaptation measures and future sustainability pathways. [ABSTRACT FROM AUTHOR]

Herpetospermum darjeelingense (C.B.Clarke) H. Schaef. & S.S. Renner is a rare cucurbit found in Darjeeling, Himalaya. It is known for its use as food and medicine with possible pharmaceutical applications. Here we assess the current and future habitat suitability of H. darjeelingense in the study area using MaxEnt modeling. In order to obtain accurate results for future models, the ensemble method was used. The current suitable habitat covers only 13% of the study area, while the future models for 2050 and 2070 show zero habitat suitability for the species. This strongly indicates a possible local extinction of the species indicating a need for rapid and decisive conservation efforts. [ABSTRACT FROM AUTHOR]