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Smallholder farmers in the Tigray region are highly vulnerable to climate change-induced shocks due to their heavy reliance on rain-fed agriculture. This study aims to assess the multidimensional livelihood vulnerability of smallholder farmers in the Tigray region to climate change using the framework provided by the Intergovernmental Panel on Climate Change (IPCC). The study used a mixed methods research design composed of qualitative and quantitative research methods. Data were collected from 120 randomly selected households, Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs). The findings reveal that more than 30% of the Atsbi Womberta district and 28% of the Tahtay Koraro district are classified as highly vulnerable to climate change. In Atsbi, the primary contributing factor to the High Vulnerability Index (HVI) is exposure, accounting for approximately 37% (mean value: 0.579 ± 0.111), followed by adaptive capacity at 33% (0.523 ± 0.104), and sensitivity at 30% (0.467 ± 0.160). Similarly, in Tahtay Koraro, exposure is the dominant contributing factor, comprising 38% (mean value: 0.618 ± 0.176), followed by low adaptive capacity at 32% (0.553 ± 0.113), and sensitivity at 30% (0.524 ± 0.167). Both districts indicate low adaptive capacity and high exposure to climate variabilities. To address the high vulnerability of smallholder farmers to climate change in the Tigray region, policymakers must prioritize disaster risk management strategies. These strategies should aim to reduce exposure to climate variabilities and strengthen the adaptive capacity of farming households.

The dense settlements at the eastern hills of Rara Lake are at higher risk of existing landslides. Seepage of water from the lake has increased erosion rates, exaggerating the threats to villages. People are worried due to the potential of inadvertent disaster, therefore it became necessary to estimate the vulnerability of the communities and inform concerned authorities.Setting this requirement as an objective, underlying influencing indicators were assessed. The vulnerability assessment was based on the scoring of the responses emanated from indicator-based household's survey.These scores were summed up to generate indices and also mapped with their true locations. Vulnerability scores ranged from 16.50to 21.75 andwere categorized into five classes after standardization. A moderate vulnerability was exhibited by 33.08% of households sampled. High and very high categories of vulnerability occupied 18.80% and 4.51% of households, respectively. Field observation showed solitary households built away from village clusters were highly vulnerable. Most households showed moderate vulnerability and characteristics like stones/mud-built houses, firewood as a primary fuel, decreasing forests and grasslands, increasing temperatures, and decreasing rainfall were major influencing indicators for higher vulnerability in the research area.

Vulnerability to climate change is a product of biophysical and social dynamics. Assessments of community or regional vulnerability, however, often focus on quantitative infrastructure and environmental assessments, or qualitative assessments of a community’s social dynamics and livelihood activities. A dearth of integrated quantitative assessments is a major barrier for decision makers who require quantitative outputs and indicators, which can measure where vulnerability is most severe and can be linked to climate projections. Our framework and analysis helps address such gaps by identifying variables to build climate change vulnerability indices, which we pilot here focusing on Inuit communities in the Canadian Arctic. We start with a systematic literature review of community-based vulnerability studies and assess relationships among 58 social and biophysical variables. We then use multiplex network analysis to determine how social and environmental variables interact among and within the key component of vulnerability: exposure, sensitivity, and adaptive capacity. We identify several structurally important variables that interact within and across the three dimensions of vulnerability. This method is transferable as an integrative means of understanding not only the direct causes of vulnerability, but also relations that are less tangible. The approach of multiplex network analysis can be a building block to ongoing development of vulnerability indices within the human dimensions of climate change field.