Acknowledgements
6.8. Farmer Coping Strategies and Factors Influencing Them
Following the onset of CWD, farmers adopted a range of different strategies for coping with the effects of the disease. These included the following:
• Re-allocating labour to other on-farm activities
• Diversifying into other crops not previously grown including bananas, beans, cassava, fruit, groundnut, maize, millet, sorghum, onion, peas, sweet potato, tomato, vanilla and yams
• Starting other non-farm activities including brewing, fishing and trade
• Opening up new coffee fields
• Replacing infected coffee trees
• Renting out coffee fields
• Borrowing money from accessible sources.
There were notable variations in the relative importance of different cop- ing strategies across the region. Farmers in Uganda coped with CWD by re-allocating labour to other on-farm activities (57.6%), re-allocating labour
to off-farm activities (22.4%), abandoning coffee fields after CWD (18.2%) and renting out coffee fields (1.8%). In Ethiopia, however, farmers gave their coping strategies as replanting coffee (76.5%) and replacing infected coffee trees (23.5%), which is distinguished from replanting in that replacing means planting new coffee at the same place where the uprooted coffee was. This is common in Ethiopia as farmers often attempt to replant seedlings from forest or other coffee fields. Unlike other countries in the region, farmers in Ethiopia did not start other off-farm activities nor diversify into alternative crops. This is because of the socio-cultural significance of coffee in Ethiopia, which is deeply rooted in traditional culture and sentiment and farmers do not easily resort to production of other crops. Regardless of what happens to productivity, farmers keep their coffee at least for their own consump- tion. Moreover, production of other crops is highly constrained by wildlife because most of the coffee areas have forests harbouring wild animals. In Tanzania, the main coping strategies included diversifying into other crops not previously grown (33%); starting off-farm activities such as brewing, fishing and trading (19%); opening up new coffee fields (4%) and replacing infected coffee trees (48%). In addition to the yield loss and decline in income from coffee, farmers have been obliged to spend money especially for hiring labour to uproot and burn infected trees. Some farmers also incurred addi- tional costs to purchase chemicals and other control methods they felt would control the disease. In Uganda for example, 58% of farmers adopted uproot- ing and burning of infested trees as a control measure. Other technological control measures included the use of ash, urine and tobacco.
Socio-economic factors influencing the choice of coping strategies ad- opted by coffee farmers were evaluated using a binary logistic regression model for each country. In Uganda, the choice of re-allocating labour from coffee to other on-farm activities as a coping strategy for CWD was influ- enced by the number of years of experience of coffee farming, the yield of coffee prior to the onset of CWD and whether coffee was the only source of income for the household. Switching to non-farm activities as a coping strat- egy for CWD was influenced positively by the income of coffee prior to the onset of CWD and the proportion of household labour inputs into coffee. Rel- atively higher coffee income before CWD meant the farmer was more likely to switch to non-farm activities after the onset of CWD. Higher household labour input into coffee prior to CWD meant that farmers were more likely to switch to non-farm activities after infestation of CWD. The likelihood of adopting non-farm activities as a coping strategy was also increased by the proportion of trees lost and quantity of coffee produced before CWD.
In Ethiopia, the choice of coping strategy was influenced by the level of education of the farmer. Farmers with a lower level of education were more likely to replant coffee (97%) than farmers with higher levels of education (P = 0.012). Although replacing coffee trees is not common in Ethiopia, farmers with no education were more likely to replace (29%) than farmers who had primary school or higher levels of education (P <0.05).
Coping strategies were also influenced by two biological factors, namely, severity of CWD on-farm and the yield of coffee prior to the onset of CWD.
The higher the severity of CWD, the higher the probability of the farmer replacing the infected coffee trees (P = 0.024) (Fig. 6.4). Similarly, the higher the yield before CWD, the higher the probability that farmers would replant their coffee (P = 0.037; Fig. 6.4).
In Tanzania, the likelihood of a farmer choosing non-farm activities as a coping strategy was significantly reduced as the age of the farmer increased (Fig. 6.5). Of the non-farm activities, fishing was the most practiced, and because it was done mainly at night, it was particularly suitable for young and/or unmarried men as compared with the older ones. Farmers who had been growing coffee for a longer period of time were also more likely to grow alternative crops (Fig. 6.5). Rather unexpectedly, the length of time CWD had been present on a farm was negatively correlated with the likelihood of a farmer switching to alternative crops (Fig. 6.5).
Yield per Tree (kg) 1
0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Predicted probability of farmer replacing wilted tree
0 0.5 1 1.5 2 2.5 3
1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
0 10 20 30 40
Severity of CWD Predicted probability of farmer replacing wilted tree
50 60 70 80 90 100
Fig. 6.4. Effect of severity of CWD (left) and coffee yield (right) on the predicted probability of a farmer replacing a wilted coffee tree in Ethiopia.
0 0
20 10 20 30 40 50 60 70 80 90 100
40 60 80 100 00 20 10 20 30 40 50 60 70 80 90 100
40 60 80 00
5 10 20 30 40 50 60 70 80 90
10 15 20
Age of Farmer (years) Years of coffee farming Years with CWD on farm
Predicted probability of farmer engaging in non-farm activities Predicted probability of farmer growing alternative crops Predicted probability of farmer growing alternative crops
Fig. 6.5. Effect of age of farmer (left), number of years of coffee farming (centre) and number of years of CWD on farm (right) on predicted probability of farmer diversifying from coffee to alter- native crops as a result of CWD in Tanzania.