Effect of Climate change in the Albertine Rift of Uganda

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1 Effect of Climate change in the Albertine Rift of Uganda Policy Brief Executive Summary Climate change is one of the leading global threats that has gained much recognition in the recent past. The 5 th assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) confirms a reduction in precipitation and high temperatures over much of Africa, predicting substantial effects to African ecosystems, agricultural systems and amplifying existing stresses on water availability. On the local level, a key concern is the lack of empirical assessments that quantify the effect of climate change as a shock to agricultural systems for both the current and future populations in addition to benefits from adoption of climate change mitigation strategies. Latest research by the Agricultural Intercomparison Improvement Project (AGMIP), a multidisciplinary working group, followed climate, crop and economic protocols to fill this void by conducting integrated assessments of the effect of climate change on livelihoods in the Albertine Rift of Uganda. Results from the integrated assessments show a negative trend of effects of climate change on yields, net returns and per capita incomes translating into increased poverty rate for small holder farmers. Depending on the crop and the climate model, economic simulation results show that net returns reduce by as much as 52%, depressing per capita incomes by as much as 24% and increasing poverty rate to a high of 77%. Adoption of climate resilient strategies such as planting higher yielding, pest and drought resistant crop varieties, timing of cropping activities to reduce the risk of soil moisture stresses and intensive input use to improve agricultural land productivity will reverse this negative trend. Adoption of such strategies has the potential to increase net farm returns by as high as 75% and reduce poverty rates by 17%. Introduction Climate change is one of the leading global threats that has gained much recognition in the recent past. The 5 th assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) confirms a reduction in precipitation and high temperatures over much of Africa, predicting substantial effects to African ecosystems, agricultural systems and amplifying existing stresses on water availability. Climate change has been demonstrated to be one of the leading causes of the 2008/2009 global food crisis that saw prices rising beyond the 10year averages.. In Uganda, climate change has been blamed for the frequent landslides in the mountainous region of Eastern Uganda in addition to frequent floods in the lowlying areas of the country. These, coupled with a higher frequency of droughts has led to loss of agricultural output and worse still, loss of lives among other ills. Already, 1

2 climate change is thought to lead to increasing conflictive circumstances that lead to violence in droughtprone areas of the cattle corridor in Uganda (USAID, 2010). A key concern is the lack of empirical assessments that quantify the effect of climate change as a shock to agricultural systems for both the current and future populations in addition to benefits from adoption of climate change mitigation strategies. This policy brief draws on the latest research by the Agricultural Intercomparison Improvement Project (AGMIP) that sought to establish the sensitivity of the current agricultural production systems to climate change, the impact of climate change on future agricultural production systems and the benefits of climate change adaptation. The AGMIP project is a multidisciplinary working group comprised of researchers with major competencies in crop, climate, ICT and economic modeling. The teams follow the AGMIP climate, crop and economic protocols to generate integrated assessments of the effect of climate change on livelihoods in general. To understand the effect of climate change on subpopulations in the Albertine region, downscaled climate data for the region was obtained from the Meteorological services. Two crop models and were calibrated using survey data from 307 smallholder maize farmers in 2 districts of the Albertine region Hoima and Masindi. The TradeOff Analysis economic model was used to simulate the effect of climate change on per capita incomes, net farm returns and poverty rate. What is the sensitivity of the current agricultural production systems to climate change? Effect on Net Farm Income % Change in Net Returns AGGREGATE % Change in Net Returns Figure 1: Effect of climate change on net returns 2

3 Economic models predict a negative impact on livelihoods through depressed net farm incomes arising out of declining yields. However, there are variations in the magnitude of the effect ranging from 40 to 49% reductions in net returns (from the crop model) and from 38 to 52% (from the model). Farm households in places with Petric plinthosols experience the largest reductions in net returns while farm households in locations with Acric ferralsols register the lowest effect on net farm incomes according to the two crop models. These variations are due to differences in soil characteristics that determine yield of crops in the farming system. The implication of these results is that climate change is likely to impinge on peoples livelihoods and at the same time exacerbate poverty levels amongst the rural communities in the Albertine region due to the associated reduction in crop yields and crop incomes. Therefore, given the impact of climate change on crop production, it is imperative that adaptation and mitigation strategies that are location specific be sought so as to lessen the effects of climate change on crop production. Additionally, diversification strategies such as getting the right enterprise mix could help smallholder farmers improve their production and cope with the adverse effects that are induced by climate change. Also, improving offfarm income generating activities could help in bolstering farmers income given that such activities are not adversely affected by climateinduced stresses. Effect on Per Capita Income 5.00 % Change in Per Capita Income % Change in Per Capita Income AGGREGATE Figure 2: Effect of climate change on per capita incomes Another livelihood indicator impacted on by climate change is per capita income. Per capita income is often used as a measure of the level of vulnerability of populations. Climate change has the effect of exacerbating the already precarious situation in the study area by further reducing the per capita incomes by as high as 24%. Results are consistent across all the models with slight variations across climate, crop models and 3

4 stratification. For instance, the model predicts a 20% reduction in per capita incomes on average while the model on average shows per capita income reductions ranging between 18% and 20% depending on the climate model. The apparent controversy in the effect of climate change on the percapita income of households (visavis the changes on net returns) with farms located on acric ferralsols compared to those farms on petric plinthosols can be explained by a higher than average population on the former soils. As a result of higher population, climate change depresses per capita incomes more in regions with a dense population than sparsely populated regions owing to scarcity of resources and competition for production resources. Therefore a lower population density results in realization of a relatively lower negative impact of climate change on net returns. Effect on Poverty Rate Economic model results generated from climate and crop models predict an increase in poverty rate ranging between 7% and 16% depending on the model. While there is consistency in the general direction of the effect of climate change on poverty rate, the magnitude of the effect differs with the level of stratification. For example location specific analysis shows that households with farms on dystric and petric soils achieve the lowest increases in poverty rate compared to farms with agricultural production on acric ferralsols. These results are consistent across the 5 climate and 2 crop models considered. By and large, the finding that climate change is likely to amplify the existing vulnerabilities and livelihoods of smallholder farmers calls for the need for development policy to focus on interventions that can uplift people s living standards % Change in Poverty Rate AGGREGATE % Change in Poverty Rate AGGREGATE

5 Figure 3: Effect of climate change on poverty rate What is the impact of climate change on future agricultural production systems? An economic assessment of the effect of climate change on future production systems reveals a different pattern that there will be losers and gainers from climate change. To understand the effect of climate change on agricultural systems in the future requires transposing the current agricultural system into the future. A number of global economic models were used to determine the direction and extent of movement of key variables including prices, costs, yield growth factors and changes in landuse over a 30year period. Stakeholders with diverse knowledge on social, economic and biophysical processes in the area were engaged in generating Representative Agricultural Pathways (RAPs) for other farm activities in the farmers production systems. The effect of climate change in the future was obtained by comparing a future production system without climate change and a future system after the climate shock on productivity. TOA simulation results from the model data and model data show there are recognizable differences in the ranges predicted by the two crop models. For example; economic model simulation results generated from model data predict an increase in net returns not exceeding 4% while simulations generated from model data predict a percentage increase in net returns of about 25%. However, in aggregate terms there is an outright reduction in net returns for the predictions given by the model but by and large an opposite pattern given under the models These results may be due to differences in the two crop models. Effect on net returns 4.00 % Change in Net Returns 3 2 % Change in Net Returns () (4.00) (6.00) DYSTR PETRI AGGR () A D P A (8.00) (2) () (3) Figure 4: Effect of climate change on future agricultural systems: Effect on net returns in the future 5

6 Effect on per capita income As with the net returns, the crop models showed the same pattern for per capita income. They predicted an inconsistent pattern showing both increases and reductions in per capita income. Unlike the model that predicts increases in per capita income of less than 2%, the model predicts of about 10% for the Dystric soils. Also, the model shows an increase in per capita income for farms under Dystric and Petric soils albeit marginal increases. However, its important to note that the climate change models exhibit an inconsistent pattern in predicting the effects, for example the CCSM4 predicts an increase in per capita income for farmers under Petric soils for using the model and an outright decrease of over 10% for Petric soils under the model. In aggregate terms, there is by and large a reduction in per capita income. That is, there is congruence in all climate change models under model that a reduction in per capita income is likely to result while only two climate change models (GFDL and MIROC5) out of five predicted an increase in per capita income. Therefore, given the likely effect of climate change on per capita income of people in the Albertine region, there is need for promotion and adoption of resilient technologies and strategies if farmers in the area are to realize increases in per capita income and standard of living (1.00) () (3.00) (4.00) (5.00) (6.00) % Change in Per Capita Income ACR DYS PET AGG Figure 5: Effect of climate change on future agricultural systems: Effect on per capita incomes in the future (5.00) () (15.00) % Change in Per Capita Income Effect on poverty rate Climate change has been found to generally amplify the vulnerabilities of the rural communities in the Albertine rift of Uganda. Indeed, such increased vulnerability to climatic changes is a potential threat for their income, food security and overall welfare (Nelson et al., 2009) as evidenced by the predictions in the graphs below. On aggregate terms, the poverty rate has been found to increase by at least 2.5% according to the predictions from the crop models and climate change models. On the other hand, there is inconsistency from the models in that three out of the five climate change models predict an increase in poverty rate of at 6

7 least 0.5% while two of the climate change models predict a reduction of at least 1%. The two climate change models with such predictions are GFDL and MIROC5. In terms of location specific predictions, poverty rate is set to increase for households under Acric and Dystric soils while the predictions show a decrease for households under Petric soils: according to the models. On the other hand, models predicted a reduction in poverty rate of at least 2% for households under Dytric soils according to four out of five climate change models while the prediction that poverty rate would increase under Dystric soils was from the CCSM4 climate change model. The implication of the above findings is that development policy should come up with viable adaptation strategies that can reduce and mitigate the climate change risks while at the same time improving the productivity of the enterprises undertaken by the smallholder farmers. Ultimately, improvement in economic activity in the region, through development of factor markets and infrastructure will improve livelihoods and enhance the standard of living in the area % Change in Poverty Rate 8.00 % Change in Poverty Rate DYSTR 4.00 ACRI DYST 1.00 AGGRE () PETR AGGR (1.00) (4.00) () (6.00) Figure 6: Effect of climate change on future agricultural systems: Effect on poverty rate in the future What are the benefits of climate change adaptation? On net farm returns 7

8 % Change in Net Farm Returns AGGREG % Change in Net Farm Returns ACR DYS PET AGG Figure 7: Effect of adaptation to climate change on net farm returns Adaptation to climate change involves adoption of improved agricultural practices that seek to change the plant genotype, planting density, planting pattern and intensity of resource use. Adoption of an improved variety of higher productivitiy reduces yield risk due to its tolerance to agroclimatic conditions and tolerance to pests and diseases thereby contributing to optimal input use while saving on the farmer s meager resources. In the Albertine region, adoption of Longe 9, application of fertilizer and increasing plant spacing allows sufficient uptake of soil nutrients which contribute to higher crop yields. Adoption of this adaptation strategy will benefit populations through increased agricultural output from all crops in the farmer s production system. Although there are variations in the effect of adaptation across the different soil types, crop models and climate scenarios, the general trend is positive for net returns and per capita incomes and negative for poverty rate. The minor differences in the magnitude of effect predicted from model data compared to model data arise due to differences in the model physics. Differences in the results from the different soil types highlight the specificity of properties of soil as an important input in the production process. On per capita incomes With climate change adaptation, simulation input data from both the and models predict an emphatic rise in per capita income across all the climate change models. Using input data According to the two crop models, all the climate models predict an increase in the per capita income ranging from negatives to at least 10% both in aggregate and location specific terms. This finding implies that in order to improve the living standards of smallholders in the Albertine rift of Uganda, there should be development, promotion/dissemination of resilient adaptation strategies and that the adoption of such adaptation options would be instrumental in mitigating the effects of climate change at the same time improving people s incomes. In light of the above, it is imperative to note that even though emphasis on adaptation strategies is very critical, such adaptation options must be developed within the broader economic development policy context (IPCC, 2007) if improved incomes and welfare are to be realized among the grass root communities. 8

9 CCMS4 GFDL HadGEM MIROC5 MPIESM % Change in Per Capita Income AGGREGATE % Change in Per Capita Income AGGREGATE Figure 8: Effect of adaptation to climate change on per capita incomes Effect on poverty rate Another benefit of climate change with adaptation is that poverty rate is predicted to decrease both in aggregate terms and in location specific instances. There is congruence across all crop and climate change models that poverty rate is set to reduce once the smallholder communities adopt suitable adaptation strategies. This finding emphasizes the need for development and adoption of location specific strategies if poverty reduction is to be realized among rural communities in the Albertine rift of Uganda. % Change in Poverty Rate () () (4.00) (6.00) (4.00) (6.00) (8.00) () (8.00) (1) AGGREG () (14.00) (1) (16.00) (14.00) (18.00) (16.00) Figure 9: Effect of adaptation to climate change on poverty rate % Change in Poverty Rate DYSTR AGGRE 9

10 References IPCC (Intergovernmental Panel on Climate Change), Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK. Nelson, G.C., Rosegrant, M.W., Koo, J., Robertson, R., Sulser, T., Zhu, T., Ringler, C., Msangi, S., Palazzo, A., Batka, M., Magalhaes, M., ValmonteSantos, R., Ewing, M., Lee, D., (2009). Climate change: impact on agriculture and costs of adaptation. Food Policy Report 21, International Food Policy Research Institute (IFPRI), Washington DC, USA. USAID (2010). Climate Change and Conflict in Uganda: The Cattle Corridor and Karamoja. Office of Conflict Management and Mitigation (CMM) Discussion Paper No. 3 10