Why was this research needed?
Research data rarely provides the information decision makers need in responding to multiple hazards. With this in mind, we designed , as part of the multi-disciplinary HyCRISTAL/Future Climate for Africa (FCFA) programme a rural livelihoods study to address the question: What information do policy and decision makers need now, to reduce vulnerability and enhance resilience?
This research focused on two case study communities in the Lake Victoria Basin, (one in Uganda and one in Kenya) where the climate emergency is just one of many factors impacting on peoples’ ability to maintain and improve their livelihoods and living standards.
The HyCRISTAL project brought together expertise in climate science, hydrology, urban WASH and rural livelihoods. You can read more about HyCRISTAL and the FCFA programme here.
What methods did we use?
Quantitative household economy analysis was used to establish current income sources and levels of income. We also conducted a range of focus group interviews to gain a wider contextual understanding of local social and institutional issues impacting on household livelihoods. .
We selected the Individual Household Method (IHM) developed by Evidence for Development, for the quantitative livelihood analysis. The IHM is an extension of the widely used Household Economy Approach (HEA) (Seaman et al., 2014) but unlike HEA, which was developed for national level food security assessments, IHM is designed for more detailed, local studies. Both are based in Amartya Sen’s entitlement theory (Sen, 1983) with its key insight that food insecurity and emergencies are caused by peoples’ inability to access food rather than the absence of food.
IHM provides a measure of the cash remaining after the household has met its basic food energy requirements (referred to as the household’s disposable income) and a ‘standard of living threshold’, indicating a level of income sufficient to meet social inclusion norms in the study sites. This data is crucial in understanding the potential capability of households to invest, pay interest on loans and cope with natural disasters, price shocks, and adverse life events. Customised software (OIHM) is used to analyse the IHM survey data.
The IHM metrics and analysis we focused on in our study included:
- Household disposable Income
- A detailed analysis of the main sources of cash income , including crops sold, livestock and livestock products sold, employment income, cash gifts and transfers, and sale of wild foods
- A detailed analysis of the main crops and livestock products retained for household consumption (household ‘food income’)
- Asset holdings including land and livestock
Who was involved?
We collaborated closely with local partners in designing and carrying out the research, both to understand local needs and to facilitate the communication of findings to policy makers. Our local partners included the Government of Uganda’s national emergency coordination commission (NECOC) , CAN-U (Climate Action Network Uganda) a local policy and advocacy NGO and academic partners from Gulu University, Uganda, and Maseno University, Kenya.
What are our findings?
Income analysis revealed high levels of inequality in both communities and very low levels of disposable income in the bottom half of the income distribution; these findings are in line with national poverty statistics.
Although all households at both sites could meet basic food energy needs to WHO recommended standards (World Health Organisation, 1985) in the Uganda case study around 11% of households fell below the locally defined ‘standard of living threshold’.
The communities were made up of fishers, farmers and households that combined both activities, along with others specializing in activities such as boat making and lakeshore enterprises, including cooked food, bars and restaurants. Enterprises such as those selling cooked food and petty trade such as vegetables, which are mainly female activities, barely covered their costs resulting in few opportunities for scaling up activities through investment. This issue was explored further in focus group discussions.
At both sites, people under 25 years of age made up most of the population (74% in the Uganda case study and 65% in the Kenya case study). These figures reflect the extremely young populations of both countries. Given the high levels of local unemployment and few potential employers, migration was seen as the only option by many young people. The study communities had also been badly affected by HIV/AIDS and numbers of female headed households, including households headed by grandmothers, was high (10% in the Uganda case study and 20% in the Kenya case study).
In addition to the quantitative insights into income levels and the different income vulnerabilities facing households, qualitative focus group interviews provided additional insight into why some individuals and households were more able to adapt to change than others. These interviews also revealed the factors that had driven social change in the more recent past, most notably in the increased economic activity of women outside the domestic sphere. Women described how they had taken up petty trade and other enterprises as yields from traditional household income sources had collapsed. However, younger female discussants highlighted the fact that legal and social constraints continued to limit their options. Specifically, gender discrimination in access to financial services undermined opportunities to grow their businesses and improve living standards for themselves and their families.
Focus groups with older famers threw light on other drivers of change and obstacles to development. For example, they had adapted to falling yields in cash crops such as coffee and bananas by shifting production to cassava and tomatoes . However, tomatoes are drought intolerant and without irrigation, increasingly erratic rainfall meant that the tomato harvest had become unreliable. Similarly, whilst cassava is more drought tolerant than crops such as maize it is susceptible to waterlogging and in hotter, wetter conditions, this would be a less viable option. Thus, whilst some households had adapted their farming practices, even for them the long term viability of these changes is uncertain.
Finally, our work highlighted the impact of environmental degradation on peoples’ livelihoods and well being. This included illegal sand mining which was contributing to increased flooding of lakeshore communities; lack of sanitation and poor management of human waste, leading to preventable water borne disease and pollution of lake water, and lastly, to overfishing with its long term impact on the lakeshore economy. Problems were exacerbated by a failure to implement existing environmental and fishery regulations at local and national levels, and to invest in public health infrastructure.
So: What information do policy and decision makers need now, to reduce vulnerability and enhance resilience?
Our study revealed a complex vulnerability and resilience landscape that is not served well by siloed, single sector studies. By looking holistically at the livelihood system of these lakeshore communities, we were able to identify specific points of vulnerability, based on detailed data on income sources. This is needed to target preventive action . Combining this with insight into local norms and legal and institutional barriers to investment and enterprise, we could throw a very specific spotlight on areas where action could remove immediate obstacles to adaptation and change.
Overall, our work also showed that without external assistance or unforeseen innovation, adaptation to climate and other shocks was reaching its limits in the study sites. These sites were selected as they were typical of the surrounding hinterland.
What are the next steps?
A core component of our work is to consider livelihoods and environmental sustainability and the links between them. We will be focusing on this question in a new collaborative project, (‘TREETOPS’) with partners from Makerere University, the environmental NGO, EcoTrust , who have already worked with the Walker Institute’s National Scale Impact Based Forecasting of Flood Risk In Uganda (NIMFRU) project, and finally with a senior Evidence for Development Associate based in Uganda, who also led livelihoods field studies in the HyCRISTAL and NIMFRU projects. The approach will combine quantitative livelihoods analysis with in depth consultations across the government and private sectors. The aim is to better understand the institutional as well as economic and social barriers that currently block climate resilient adaptation that promotes the well being and security of both forest landscapes and forest livelihoods.
What further work is needed?
We need to better incorporate climate information with livelihood data for climate adaptation and resilience planning. Further work is needed to realise the use of livelihoods data in climate change scenario planning, integrating climate, hydrology and agronomy models with impacts at household and community levels.
We also need to continue our HEA and IHM capacity building work with local universities, so more local practitioners are available to lead livelihoods research and make the necessary institutional connections so relevant data passes between the agencies that need to understand, incorporate and act on it. The ALiVE courses (link) run in partnership by the Walker Academy and Evidence for Development are leading the way in this endeavour.
You can read more on policy work arising from the HyCRISTAL rural studies in this paper ‘Supporting Climate-Resilient Planning at National and District Levels: A Pathway to Multi-stakeholder Decision-Making in Uganda
For more on this work please contact Dr Celia Petty