Abstract:
In pastoral communities of Ethiopia where livelihood is vulnerable to climate change, irregular
rainfall and high temperature affect livestock adversely. Assessing the level of livelihood
vulnerability of pastoralists is essential to identify better adaptation strategies to climate change.
Thus, this study assessed vulnerability of pastoralists’ livelihood to climate change and
adaptation options at Dillo District of Borena zone, Oromia Region, Ethiopia. Accordingly,
historical climate data (1989-2018) was collected from National Meteorological Agency (NMA)
of Ethiopia. In addition, data of livelihood vulnerability and adaptation options were collected
from a total of 145 households that were randomly selected. The Mann-Kendall test and Sen’s
slope estimator were employed to assess trends of rainfall and temperature. Climate data and
vulnerability of pastoralists’ livelihood were analyzed by INSTAT+v.3.36 and XL-2010 whereas
adaptation options used by the pastoralists were analyzed using Statistical Packages for the
Social Sciences (SPSS) (version 20). The results revealed a decreasing trend for both annual (-
8.226 mm/year) and seasonal (-5.53 mm/year for belg and -0.956 mm/year for bega) rainfall
during the study period. In contrast, the annual minimum and maximum temperature showed an
increasing trend with a magnitude of 0.071 and 0.006 0C per year respectively. Overall,
Livelihood Vulnerability Index (LVI) for Golbo and Malbe were 0.41 and 0.32 respectively,
indicating Golbo was more vulnerable to climate change as compared with Malbe. Similarly, the
LVI of Intergovernmental Panel for Climate Change analysis result showed that Golbo (0.275)
was more vulnerable than Malbe (0.238). Increasing livestock mobility and casual labor as a
source of income were mostly used adaptation options in the study area. More emphasis should
be given to pastoralists of the study area especially to Golbo zone by concerned bodies in order
to improve their resilience to changes in climate variables. Further research is needed to adopt
model in the future to identify more suitable adaptation options in the area
