3. Methodology

This chapter adopts qualitative approach to research as emphasized by Chambers [25] and Creswell [26]. Data were collected from smallholder farmers and agro-pastoralists using focus group discussions (FGDs). Table 1 shows villages, number of FGDs, their size [27] and age of participants involved. There were separate groups for men, women and youth for each tool used to collect data in each village to get insights from different gender groups. The United Republic of Tanzania (URT) in its National Policy of Youth Development [28] defines youth as those whose age is within a range of 15–35 years. During FGDs, the study employed historical time line to assess trends and frequencies of vulnerability hazards related to climate change and those that are non-climatic hazards. Three time lines were established, one for each gender group: men, women and youth. This method also helped to get insights about past hazards and their changes in the previous 30 years since 1985. It also helped men and women to make sense of the trends of the hazards and changes over time. Special attention was given to major hazards and their effects, changes in land use and land cover, changes in food security and major political events like local governments and national elections. Adaptation and coping strategies, their changes and effectiveness, were also assessed.

Secondly, the study used seasonal calendar to identify periods of stress, famine and vulnerability, to understand livelihoods and coping strategies, to analyze changes in seasonal activities, and to evaluate how vulnerability varied seasonally between men and women. Other Farmers' Vulnerability to Climate Change Impacts in Semi-arid Environments in Tanzania: A Gender Perspective http://dx.doi.org/10.5772/intechopen.72108 59


Table 1. Information on FGDs and participants involved.

are prone to droughts and other manifestations of climate change. The districts were selected for the study because poverty, defined as the inability to meet a minimum standard of living, is as high as 80% [1] suggesting that the districts were likely to be vulnerable to the climate change impacts [4, 7]. Being contiguous, the two districts were good for assessing differences in terms of manifestation of climate change and gender vulnerability to the phenomenon for

The mean annual rainfall in Meatu ranges between 400 mm and 900 mm in the southern and northern parts respectively [21]. In Iramba, the mean annual rainfall ranges between 500 mm and 850 mm and the surface temperature ranges between 15C in July and 30C in October [22]. The rainfall regime in both districts is unimodal, which starts in November and ends in April [23]. In Meatu, vegetation is mostly shrub and thorny trees scattered or clustered in some parts while Iramba's vegetation include Miombo woodlands, acacia woodlands and grasslands [24]. Three villages were involved in the study: Mwamanimba and Mwashata in Meatu and Kidaru in Iramba. The two villages in Meatu are dominated by the Sukuma while Kidaru in Iramba is dominated by the nyiramba. All villages in the study areas are dominated by the smallholder farmers. Mwamanimba is dominated more by agro-pastoralists whose livelihoods rely on rainfall. This means that any change in rainfall is likely to affect livelihoods. Since smallholder farmers and agro-pastoralists are poor in the study areas [1], it was anticipated

This chapter adopts qualitative approach to research as emphasized by Chambers [25] and Creswell [26]. Data were collected from smallholder farmers and agro-pastoralists using focus group discussions (FGDs). Table 1 shows villages, number of FGDs, their size [27] and age of participants involved. There were separate groups for men, women and youth for each tool used to collect data in each village to get insights from different gender groups. The United Republic of Tanzania (URT) in its National Policy of Youth Development [28] defines youth as those whose age is within a range of 15–35 years. During FGDs, the study employed historical time line to assess trends and frequencies of vulnerability hazards related to climate change and those that are non-climatic hazards. Three time lines were established, one for each gender group: men, women and youth. This method also helped to get insights about past hazards and their changes in the previous 30 years since 1985. It also helped men and women to make sense of the trends of the hazards and changes over time. Special attention was given to major hazards and their effects, changes in land use and land cover, changes in food security and major political events like local governments and national elections. Adaptation and coping

Secondly, the study used seasonal calendar to identify periods of stress, famine and vulnerability, to understand livelihoods and coping strategies, to analyze changes in seasonal activities, and to evaluate how vulnerability varied seasonally between men and women. Other

the two communities: the Wasukuma in Meatu and the Wanyiramba in Iramba.

that they are likely to be vulnerable to climate change impacts.

strategies, their changes and effectiveness, were also assessed.

3. Methodology

58 Arid Environments and Sustainability

things analyzed using this tool include time for leisure and traditional dances, planting and harvesting periods, periods of food and income insecurity, timing of hazards like droughts and floods and seasons for illnesses. Thirdly, vulnerability matrices were used to determine hazards, which have the most impacts on livelihoods resources. Livelihoods resources are defined, in this study, as those resources considered most important by smallholder farmers and agropastoralists in supporting livelihoods. Participants were asked to prioritize four important livelihoods resources. The matrices also helped to determine the most vulnerable livelihoods resources and to identify adaptation and coping strategies used, and whether the strategies to address the hazards had changed over time. Participants were also asked to decide on the degree of impact of each hazard against the livelihoods resources. The score for a significant impact was 3, for medium was 2, for low was 1 and zero was for no impact. During data analysis, information for each gender group was put together based on similarities and differences between gender groups.
