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Impacts of and Adaptation to Climate Change and Variability in Tanzania Agricultural Systems: A Review B.P. Mbillinyia*, H.F. Mahooa, S.D. Tumboa, E. Mpetab, F.B. Rwehumbizaa, K. Mutabazia and F.C. Kahimbaa a Sokoine University of Agriculture, P. O. Box 3003 Morogoro, Tanzania. Tanzania Meteorological Agency, P. O. Box 3056, Dar es Salaam, Tanzania b *Corresponding autgor email: [email protected] ABSTRACT The effects of climate change and variability are undeniably clear with impacts already affecting the agricultural sector, ecosystems, biodiversity and people. Recent scientific evidence suggests that the frequency and severity of climatic extremes is increasing, making adaptation an absolute necessity. This paper reviews the impacts of climate change and variability in agricultural systems of Tanzania and existing adaptation strategies, including their deficit. The review indicated that agriculture remains the most important livelihood strategy to the majority of the population in Tanzania. The sector needs to be strengthened to facilitate survival in a changing climate. The sector is quite vulnerable to projected climate change, making adaptation an extreme necessity. It was also noted that, while some adaptation to current climate variability is taking place, this is insufficient to cope with future changes in climate. In addition, deficiencies still exist on the current adaptation strategies. The paper urges that risk management strategies should aim at addressing the existing adaptation deficit and be adjusted to face additional climate risks associated with climate change. The implication for adaptation may not be to only focus on minimizing risks, but also to capitalize on opportunities associated with the changing climate. Keywords: agricultural systems, climate change, climate variability, adaptation to climate change, Tanzania 1. Introduction The agricultural sector is the leading sector of the economy of Tanzania and accounts for over half of the Gross Domestic Product (GDP). It provides 85% of export earnings, and employs over 80% of the work force (URT, 2001). Unfortunately, as in other African countries, the sector is highly vulnerable to climate change and variability because of its over-dependence in rainfall. According to World Bank (2002), only 3.3% of the cropland was irrigated as of 1999. Any attempt to improve agriculture must therefore tackle the problems associated with rainfall variability in amount and timing. In response to climate variability and change, farmers have developed different farming systems finely tuned to many aspects of their environment. Adaptation measures include adjustments to planting dates, rainwater harvesting and selection of animal species. However, while local coping strategies may be able to deal with shocks in the short-term, they are unlikely to be able to cope with more frequent and severe climate events (Orindi et al. 2005) and expected future climate change. In order to reduce such impacts and vulnerability of climate change and variability on agricultural systems, adaptation to climate variability and change should include measures aimed at addressing the existing “adaptation deficit”. Adaptation deficit is lack of adaptive capacity to deal with climate variability and climate change. A useful starting point in addressing adaptation can be to tackle the adaptation deficit before embarking on new adaptation activities. Without action to reduce exposure and improve the capacity to cope, the gradual and sudden changes associated with climate change will increase vulnerability in many areas (IDS, 2006). Sound government policies, backed up by technologies to aid drought prediction, monitoring, and management, are expected to lead to more self-reliant management at the farm level, and the development of agricultural systems that are physically, biologically, and financially sustainable. Effective and sustainable adaptation to climate change and variability depends on, among other things, our ability to assess and understand the impacts and potential opportunities in relation to and help develop functional strategies to address them. However, according to a number of reports, for example UNFCC (2006), DFID (2004), and IIED (2006), in Africa, including Tanzania, there is still a general deficiency of knowledge, expertise and data on the current climate variability and the impacts of climate change. This is also a constraint to better understanding of current and future climate variability (DFID, 2004). This paper reviews the current vulnerability to climate variability, the projected impacts of climate change and the various strategies and policies that are being deployed to address climate issues, including their deficit, focusing mainly on the agricultural sector of Tanzania. 2. Climate variability and trends The climate of Tanzania is mainly influenced by its location close to the equator, the impact of the Indian Ocean and the physiography in general. As a consequence, Tanzania experiences a variety of climatic conditions ranging from humid coastal to alpine deserts. The coastal area and all of the islands in the Indian Ocean experience a tropical climate, and most of the country is sub-tropical except for the areas at higher altitudes. Average temperatures range between 17°C and 27°C, depending on location. Temperature variations have significant impact on the agroecological zones and the adaptation strategies in the agriculture sector. Rainfall in about 75% of the country is erratic and only 21% of the country can expect an annual rainfall of more than 750 mm with a 90% probability. As a result, crop and livestock production under such conditions remains vulnerable to the adequacy, reliability and timeliness of rainfall. The mean annual rainfall varies considerably, ranging from less than 400 mm to over 2,500 mm per annum. Analysis of monthly minimum and maximum temperatures over years for meteorological stations located in regions of Arusha, Bukoba, Dodoma, Iringa, Kilimanjaro, Mbeya, Morogoro, Mwanza, Songea, Tanga, Zanzibar and Shinyanga showed an upward trend (Figure 1). The increasing trend was mostly associated with the months of January, July and December. The retreat of the glaciers of Mt. Kilimanjaro., the submersion of Maziwe Island in the Indian Ocean near the coast of Tanga, and decrease in water levels of Lake Victoria and increasing malaria endemicity in highland areas of the country could be linked to the observed temperature trend (NAPA, 2005). Estimates made through analyzing pictures taken in 1912 and then in 2001 have claimed that Mount Kilimanjaro has lost 82 percent of its ice cover, with the warning that the snow cap would disappear between 2015 and 2020 (Thompson et. al., 2002). However, a field study, done by researchers from Portsmouth University of UK, on the mountain top, determined that the rate at which the snow cap is melting does not suggest that it will disappear in the near future (http://www.thaindian.com/newsportal/world-news/mt-kilimanjaros-snow-cap-may-notdisappear-by-2020-or-2030_10084058.html). (Insert Figure 1) Analysis of annual rainfall time series for most of the stations indicated a decreasing trend and a greater variability in cycles (TMA, 2007). Figure 2 shows the trend of rainfall observed from 1952 to 2006 at Songea, Bukoba, Arusha and Zanzibar meteorological stations. (Insert Figure 2) Rainfall and temperature are critical determinants of crop performance and eventual agricultural production. Increase in temperature could, for instance, result in increase in evapo-transpiration which could, in turn, reduce the soil moisture, and ultimately, the rate of plant growth, development and yields. However, analysis of only annual rainfall and temperature to explain the effect of climate variability on crop production is limited and might not give a full picture. The analysis lacks important information on growing season characteristics such as occurrence of dry spells. As shown in Figure 3, while the analysis of rainfall amount for Same station, Kilimanjaro Region showed no significant changes (p=0.318)., the analysis showed a significant increase in occurrence of long dry-spells (21 days or longer) during Masika (p=0.024). (Insert Figure 3) Tanzania is also prone to droughts and flooding. According to Hatibu and Mahoo (2000), historically, floods have caused about 38% of all declared disasters, while droughts caused 33%. Over the last four decades, the country has been hit by a string of severe droughts and flooding, the most recent droughts occurring in 1971, 1975-76, 1983, 1985, 1987, 1992, 1996-97, 19992000. On the other hand, some of the most severe flooding episodes in recent years occurred in 1993, 1997/98 (El Niño) and 2000/01 (Kandji et. al. (2006)). 3. Climate change projections Projections in temperature and rainfall changes over Tanzania are well documented in URT (2003) and OECD (2003). While OECD (2003), based on outputs from over a dozen Global Circulation Models (GCMs) processed using MAGICC/SCENGEN), predicts an average annual increase of 2.2°C in temperature by 2100, URT (2003) predicts that the mean annual temperatures will rise by 3-5°C under doubling of carbon dioxide by 2075. Both studies agree, however, that the rise in temperature will be greater during cooler months (June to August) than warmer ones (December to February) and consistent patterns of seasonal temperature increase. Rainfall predictions are less certain. Indeed, major discrepancies remain between climate models. However, the most commonly used projection for Tanzania foresees an overall annual increase of rainfall by 10 % by 2100 (OECD, 2003). Significant regional variations will also occur. According to URT (2003), areas with two rainfall seasons including the north eastern part, the north western, the Lake Victoria basin and the northern part of the coastal belt may experience an increase in rainfall for both the short and long rainy seasons ranging from 5 to 45% while areas experiencing unimodal rainfalls like the southern, south-western, western, central and eastern parts of the country will potentially experience reduced rainfall by 5 to 15%. The results should, however, be interpreted with caution as they do not include an uncertainty analysis and rely on one or two older climate models (OECD, 2003). It is also projected that extreme events, in the form of droughts, flooding, tropical storms and cyclones to become more frequent, intense and unpredictable (IPCC, 2003). In order to capture the climate issues relevant for livelihoods, location based assessments are needed to complement the broad impact assessments such as those described in URT (2003), OECD (2003) and (Feenstra et al. 1997). However, downscaling the global reference scenarios to local conditions remains a significant methodological challenge in Africa and Tanzania in particular and few institutions have the capacity to do it. This is also a constraint to better understanding of current and future climate variability (DFID, 2004). To address this gap, coordinated effort of capacity building, training, research and development should be emphasized. There is also a need to explore the capacity of these institutions in enriching the development of reliable climate change scenarios, which can then be transformed into useful products for wide spectrum stakeholders. 4. Impacts and vulnerability of climate change and variability on agricultural systems The effects of climate change and variability are undeniably clear with impacts already affecting ecosystems, biodiversity and people. Large-scale events, such as the 1997/98 El Niño, illustrate ways in which many communities are already suffering from less predictable and more extreme weather patterns. The 1997/98 El Niño, for example, resulted in cereal deficit at 916,000 metric tons in Tanzania. As a consequence, the President of the United Republic of Tanzania declared a national food crisis and appealed for additional food aid (Karen O'Brien et. el., 2000). The livestock sector also underwent severe losses due to increased disease infection (especially Rift Valley Fever), drowning, damaged water facilities (dams, boreholes, water troughs), and disruptions in market infrastructure and road systems (Kandji et. al., 2006). Despite these massive losses, the abundant rainfall was beneficial in some areas. In some agriculturally marginal areas, production of crops was above average and there were improved fodder and water stocks, leading to an improvement in livestock performance in those areas. The La-Niña event of 1996/97 was responsible for the severe drought that occurred in most parts of Tanzania leading to insufficient rainfall for hydroelectric power generation and urban water supplies. Crop failure was widespread and rangelands could not support livestock resulting in massive production shortfalls. Recently, farmers in Dodoma region have reported an 80% fall in expected yields due to late and poor rains. Food Assessment Reports conducted by Food Situation Investigation Team in 2005 showed that poor rains during the short rainy season (locally called “vuli”) resulted in food relief distribution in over half of the districts in the north-east and coastal regions (Karen O'Brien et. el., 2000).In 2005 the agricultural sector grew by only 5.2% compared to 5.8% growth in 2004 and the GDP was targeted to grow by 6.9% but it grew by 6.8%. This was attributed to severe drought that affected most parts of the country, triggering food shortage and power crisis (NAPA, 2005). Systematic documentation and publication of these impacts is required to build up a knowledge base of how much damage is occurring and where. As information on impacts of climate change becomes more available and understood, it is possible to study, discuss, and implement adaptation measures (Downing, 1996). Current national annual statistical summaries need to incorporate the information which will contribute to the monitoring of climate change and its impacts, information that will be very useful in national communications to the Framework Convention on Climate Change (Desanker and Justice, 2001) and National Adaptation Programme of Action (NAPA). Predicted changes in climate will have significant impacts on Tanzania’s rain-fed agriculture and food production, and possibly undermine economic development, increasing poverty and delaying or preventing the realization of the Millennium Development Goals (MDGs). The predictions indicate that Tanzania may suffer a loss of over 10% of its grain production by the year 2080 (Parry et al., 1999). The cultivation of maize is going to be particularly hard hit. Estimates from Crop Environment Resource Synthesis Model (CERES-Maize) (Jones and Kiniry, 1986) show that the average yield decrease over the entire country would be 33% and as high as 84% in the central regions of Dodoma and Tabora. Yields in the north-eastern highlands showed decreases of 22% while in the Lake Victoria region decreases of 17% were indicated. The southern highland areas of Mbeya and Songea were estimated to have decreases of 10-15%. Consequently, the continued reliance on maize as a staple crop over wide areas of the country could be at risk. Change of staple crops to millet and cassava may be necessary in the hinterland. There is considerable uncertainty regarding the effects of climate change on the yields of most important cash crops such as coffee and cotton. However, according to URT (2003), the two cash crops are projected to experience increases in yield. For example, coffee yields are expected to increase by 18% and 16% for areas located within bimodal and unimodal rainfall respectively. The agriculture sector thus may have both negative and positive impacts. Climate change is expected to further shrink the rangelands which are important for livestock keeping communities and change the prevalence of vector-borne diseases. Projected climate change could result in a shift of the distribution of tsetse fly north-eastwards, which would further reduce the area of land suitable for grazing and human settlement (IPCC, 2001). Shrinkage of rangelands is likely to exacerbate conflicts between farmers and pastoralists in many areas (NAPA, 2005). In addition to its direct effect on the agricultural sector, climate change could affect the sector in a number of different ways. For instance, the projected 10% and 6% decrease of annual basin runoff in the Wami-Ruvu basin and the Rufiji River, respectively, (URT, 2003), will reduce the potential area for irrigation, leading to decline in rice production in these areas. 5. Adaptation to climate change and variability: Options and challenges 5.1 Use of indigenous and improved soil-water management technologies In response to climate change and variability, farmers and livestock keepers have developed different farming systems finely tuned to many aspects of their environment. Adaptation measures include adjustments to planting dates, rainwater harvesting (RWH), selection of animal species, transhumance (strategic movement of livestock to manage pasture and water resources), distributing stock among relatives and friends in various places to minimize the risk of losing all animals if a drought strikes one particular area, and the opportunistic cultivation of food and cash crops to meet some of their needs. In Tanzania, and elsewhere in the world, studies have shown that indigenous technologies are good in reducing the risk in bad years/seasons. For example, in Same District of Tanzania, macro-catchment RWH was found to give yield benefits by alleviating the impacts of intra-seasonal dry spells, especially when direct rainfall and run-on occur nonsynchronously (Hatibu et. al., 2003). The same was observed in Botswana where sorghum yield doubled compared with a control years with below average or poorly distributed rainfall (Carter and Miller, 1991). Imbira (1986) obtained even greater increases (more than 500%) with sorghum in Baringo district of Kenya. However, as shown in Machakos, Kenya, the indigenous technologies are not so effective in capitalizing the opportunities from good season. It was revealed that farmers could harvest only 600–700 kg/ha in seasons with good rainfall as opposed to more than 2 t/ha with carefully planned investments in low-risk technologies (ICRISAT, 2007). In addition, a rapid change of the vulnerability context due to more frequent and severe climate events does not always allow for traditional coping mechanisms to take place and often results in an overall loss or severe ineffectiveness in the adaptive capacity of the communities. In this regard, exogenous and improved technologies may play a crucial role through their integration, where appropriate, into local strategies. As observed by Thiombiano (2004), the efficiency of traditional practices can be increased, not by introducing completely different ones, but by identifying those elements, which could be improved in the local context. Some of the potential exogenous and improved technologies for adaptation to climate change and variability include; small scale irrigation, drought tolerant seed varieties, strengthen early warning system, cross breeding for resistant breeds, strengthened livestock extension services, improve livestock marketing infrastructure and zero grazing (NAPA, 2005). Although there have been some success stories with these technologies, adoption is still very low. For example, despite all the efforts to promote the use of improved maize varieties (drought resistant seed), by 1997, about 90 percent of farmers in Tanzania were still relying on their farm-saved seed (ICRISAT, 2005). Some of the reasons for the observed low use of improved varieties are; lack of information and incentives or means to purchase them. Efforts to enhance adoption of these technologies and hence the adaptive capacity of the communities to climate change, should consider among other things levels of risk, local priorities and experiences, net benefits in terms of economic viability, environmental sustainability, and public acceptability, and implementability, as central evaluative criteria. Since climate is changing and climate variability is expected to increase in frequency and intensity (IPCC, 2001), it will be expected that current coping strategies may not be considered as sufficient adaptation strategies in the future. Far more work is needed if adaptation itself has to be seen as an essentially dynamic, continuous and non-linear process (ILRI, 2006). The projected trends in temperature, precipitation, and extremes will push future climate variations and extremes beyond the bounds of what people and places have been exposed to and had to cope with in the past. The implication is that current practices, processes, systems and infrastructure that are more or less adapted to the present climate will become increasingly inappropriate and maladapted as the climate changes. Fine tuning current strategies to reduce risks from historically observed climate hazards will not be sufficient in this dynamically changing environment. More fundamental adjustments will be needed. This will require recognizing what changes are happening, predicting the range of likely future changes, understanding the vulnerabilities and potential impacts, identifying appropriate adjustments, and mobilizing the resources and will to implement them. 5.2 The Role of Policy and Institutions Tanzania is a party to various international environmental agreements, including the UNFCCC, UNCCD, and UNCBD. In 1997 Tanzania developed her first National Action Plan on Climate Change, and in July 2003 submitted its Initial National Communication to the UN FCCC and recently submitted its National Adaptation Programme of Action (NAPA). NAPA undertakes climate change vulnerabilities assessment across key sectors, including agriculture, develops and prioritizes key adaptation options and strategies that would best address those vulnerabilities. NAPA is a valuable means of identifying impacts and vulnerabilities and building multistakeholder participation through joint problem solving exercises. However, according to CARE (2006), there has been little evidence of stakeholder consultation or civil society involvement. The actors involved have largely been government-based. In addition, according to Orindi et. al., (2006), the current NAPA methodology of assessing climate change vulnerabilities takes scenarios of climate change rather than existing adjustments and sources of vulnerability to climatic changes as a starting point for analysis. This leads to a lack of emphasis on local coping strategies and adjustments. As a consequence, many of the options suggested in NAPA are technical and expensive, making them inaccessible to vulnerable groups including the poor, who are supposed to benefit from using them. In addition to country commitment to international environmental agreements, Tanzania has developed a number of national and district level sectoral policies and plans that are intended to increase its ability to cope with climate variability. Such policies include increasing agriculture's drought resistance by, for example, promoting early maturing seeds and drought resistant crops. Drought-resistant crops and technologies are perceived in policies as a principal means of addressing problems related to climate variability and drought in particular. Promotion of such crop varieties is integrated into national, multi-sectoral and sectoral policies, and District Agricultural Development Programmes (DADPs). However, efforts to promote drought resistant crops face several constraints. Farmers are reluctant to adopt certain drought-resistant crop varieties, in part due to low market and consumption values. It is likely that successful increasing cultivation of drought-resistant species requires numerous measures addressing socio-economic and technical constraints. Warehouse Receipt Systems (WRS), whereby small farmers are assured of the market, input, and credits, could provide answers to some of the problems. A further advantage of WHRS, is that it offers stable prices, linking the small farm sector to sources of extension advice, mechanization, seeds, fertilizer and credit, and to guaranteed and profitable markets for produce. However, the system is currently limited to a small area and applied mainly on coffee and cotton production systems (Mukwenda 2005). The National Strategy for Growth and Reduction of Poverty (NSGRP) explicitly recognizes the fact that poor people rely heavily on natural resources and are most vulnerable to external shocks and environmental risks, including drought and floods. As a result, the strategy stresses a need to have approaches to mitigate effects of natural disasters, halt desertification and promote water conservation practices. However, some of these goals have been articulated in previous plans, but have not been successfully implemented. Therefore, despite the obvious synergies between such policies and climate change adaptation, a key obstacle facing successful “mainstreaming” is successful “implementation” (OECD, 2003). Early warning systems have been realized as one of the adaptation measures to climate change. Currently, the government is implementing Famine Early Warning System and Livestock Early Warning System (LEWS). Case studies carried out in Laikipia, Kenya indicate that LEWS is capable of alerting pastoral communities to emerging drought conditions earlier than the use of traditional methods (Ryan, 2004). This should allow pastoralists to respond early and utilize coping mechanisms more effectively. However, according to Ryan (2004), further research is necessary to ensure the accuracy of the extrapolation and projection techniques. This will require, among other things, improved weather data. 5.3 The Role of Seasonal Climate Forecasting As climatic extremes such as droughts increase in frequency and intensity, predicting the interannual and inter-seasonal variations in rainfall will be paramount for short-term decision making. Use of seasonal climate forecasts is obvious and efficient contributor that can facilitate adaptation to climate change and variability. For example, yield simulations using the APSIM model suggest that average maize production could increase by 61 percent compared to farmers’ current practices if farmers accessed climate outlook information and adjusted their farming techniques accordingly (Rao and Okwach, 2005). In Tanzania, the Tanzania Meteorological Agency (TMA) is responsible for provision of agrometeorological services, including daily weather forecast, 10-days forecast, monthly forecasts, seasonal forecasts and agronomical advisory (such as when to prepare fields, and what to plant). The information is also used in early warning and drought risk monitoring. However, lack of widespread use of this information and knowledge to improve farm management suggests that access to the information has been a problem and farmers have difficulty translating the information into tangible economic farm outputs. Difficulties in interpreting and applying the forecasts in their current form include, mismatch between the variables forecast and the operational needs of farmers, and lack of trust or comprehension of the forecasts (Eakin, 2000; Phillips et al., 2001; Roncoli et al., 2002). The above deficiencies in weather forecasts provided by TMA were also reported during a workshop conducted in Same, Tanzania. The workshop was designed to explore, among other things, on the climate information needs of various stakeholders [SWMRP, 2007]. The workshop revealed that some of the information not provided by the current forecasts but farmers would prefer to get included: the amount and distribution of the expected rains, changes likely to occur during the season, such as possibility of dry spells and periods of excessive rainfall. Such information was important to them since it would enable them to determine and prepare for the risks ahead if the rains are poor. They also wanted to know the type of crop and seed varieties they should grow in view of the predicted/forecast. The eventual benefits from climate forecasts to prepare for expected adverse conditions or take advantage of expected favourable conditions, will rely not only on the accuracy of the forecasts, but also on other conditions which must be in place. These include, among others, viable decision options that benefit from forecast information, identification of components of climate variability that are relevant to decisions, and adequate communication and understanding of relevant information by the right audience at the right time. All these require capacity building not only of the researchers but the whole spectrum of stakeholders who are or will be affected by climate change and variability. 6. The IDRC research project To address some of the observed challenges and deficiencies in the existing adaptation strategies, a research project titled “Managing risk, reducing vulnerability and enhancing agricultural productivity under a changing climate” is being implemented in four GHA countries, namely Ethiopia, Kenya, Sudan and Tanzania with financial support from IDRC/DFID. The project has adopted the conceptual framework developed by Klein et al. (1999) of the process of planned adaptations, aimed at changing existing management practices in coastal zones. In this model, adaptation is considered as a continuous and iterative cycle, involving several steps: information collection and awareness raising, design and evaluation of strategies (incorporating policy criteria and development objectives), continuous assessment of evolving needs and opportunities, and strengthen institutions and capacities to assess, monitor, communicate and implement appropriate strategies (Figure 4). An understanding of how the climate system works, why climate matters and how social systems respond to climate change and variability requires knowledge and information on how they are affected by those conditions today and how they might respond in the future if those conditions change. This provides an opportunity for businesses, governments, community leaders, resource managers and scientists to explore ways in which GHA communities could reduce their vulnerability, either by reducing exposure or sensitivity, or enhancing resilience, or both. The project has started to generate the required information, knowledge and strategies while building the capacity of the research and developmental community to continuously monitor, communicate and implement appropriate strategies. (Insert Figure 4) The project is guided by the following assumptions/hypotheses; i) the existing knowledgebase and capacity in the GHA region are inadequate to deal with current and future impacts of climate change and variability ii) the current coping strategies will not be adequate to address the future climate change and variability iii) current tools that support decision making for selecting appropriate responses are not robust enough to address climate change and variability; and iv) improved communication of existing climate information can lead to reduced vulnerability and improved adaptation to climate change and variability. The research design involves a critical interpretive analysis for qualitative and quantitative assessment of impacts of and vulnerability to climate variability, and participatory action research to develop innovative approaches and identify best practices for reducing risks and take advantage of opportunities created by variable climate. The action research is being in the four countries and conducted at limited but carefully selected representative sites based on characteristics such as impacts of current and projected climate, vulnerability of small-scale farmers, and regional significance in terms of agro-ecological and socioeconomic conditions. Special emphasis is given to assess and take into consideration the impacts of climate change on vulnerable sections of the society especially women. An understanding of how the roles, status, and economic power of men and women affect, and are affected differently by, climate change will improve actions taken to reduce vulnerability and combat climate change. The project is planned to be completed in four years but though partnerships with different stakeholders (e.g. NGos, CBOs, inputs suppliers) the activities developed through the project are expected to be sustained beyond the project life. 7. Conclusions The following conclusions can be drawn from this paper: 1). Agriculture, which includes crop growing and livestock production, remains the most important livelihood strategy to the majority of the population in Tanzania. The sector needs to be strengthened to facilitate survival in a changing climate. 2). The effects of climate change and variability are undeniably clear with impacts already affecting agricultural systems. Given the low level of human development, extreme poverty, and high dependence on rainfed agriculture, Tanzania is quite vulnerable to projected climate change, making adaptation an extreme necessity. 3). While some adaptation to current climate variability is taking place, this is insufficient to cope with future changes in climate. In addition, a number of deficiencies do still exist on the current adaptation strategies. Risk management strategies should therefore aim at addressing the existing adaptation deficit and be adjusted to face additional climate risks associated with climate change. One effective option could be a combination of local strategies and “recommended” adaptive measures. Ongoing monitoring, documentation and dissemination of good agricultural practices, indigenous and newly developed ones, is therefore an essential part. 4). The agricultural sector is expected to experience both negative and positive impacts under climate change. For example, while production of maize is projected to decline, the production of coffee and cotton is expected to increase. The implication for adaptation therefore may be not to only focus on minimizing risk, but also to capitalize on opportunities associated with the changing climate. Acknowledgements This publication was supported by the Climate Change Adaptation in Africa (CCAA) program, a joint initiative of Canada’s International Development Research Centre (IDRC) and the United Kingdom’s Department for International Development (DFID). 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Thesis, Graduate Studies of Texas A&M University Figure y = 0.0207x + 26.277 y = 0.0185x + 25.281 2 R = 0.221 2 R = 0.3975 2005 2002 1999 1996 1993 1990 1987 1984 1981 1978 1975 1972 1969 1966 1963 1960 2006 2003 2000 1997 1994 1991 1988 1985 1982 23 1979 1958 24 1976 25 1973 26 1970 27 1967 28 1964 29 1961 Temperature(°C) Temperature(°C) 30 27 26.5 26 25.5 25 24.5 24 23.5 23 YEAR YEAR b) Bukoba station a) Songea station y = 0.0156x + 25.272 y = 0.0066x + 30.397 2 R2 = 0.0817 Temperature(°C) 32 31.5 31 30.5 30 29.5 2006 2003 2000 1997 1994 1991 1988 1985 1982 1979 1976 1973 1970 1967 1964 1961 1958 2005 2002 1999 1996 1993 1990 1987 1984 1981 1978 1975 1972 1969 1966 1963 29 1960 Temperature(°C) R = 0.1154 27.5 27 26.5 26 25.5 25 24.5 24 23.5 23 22.5 22 YEAR YEAR d) Zanzibar station c) Arusha station Figure 1: Mean annual maximum temperature time series for Songea, Bukoba, Arusha and Zanzibar stations (1958 – 2005) (Source: TMA, 2007). 1200 yjfm = -2.6146x + 782.8 1000 yond = -3.1783x + 324.81 1200.0 1000.0 Linear (JFM) Linear (OND) Linear (JFM) Linear (JFM) Linear (OND) 400 200 yjfm = -2.8658x + 623.79 800.0 600.0 400.0 200.0 YEAR a) Songea station b) Bukoba station JFM Linear (JFM) 2005 2001 1997 1993 1989 1985 1981 1977 1973 0.0 1969 YEARS 1965 19 61 19 63 19 65 19 67 19 69 19 71 19 73 19 75 19 77 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 0 1961 Rainfall (mm) 600 Rainfall (mm) OND 800 yond = -2.5321x + 614.57 JFM OND Linear (OND) yjfm = 1.8196x + 300.24 y = -2.1387x + 470.28 yond = 0.6557x + 140.76 MAM 600 y = -1.7962x + 268.86 SOND 2005 2001 1997 1993 1989 1985 1981 1977 1973 1969 1965 YEAR Rainfall (mm) 500 Linear (MAM) Linear (SOND) 1961 Rainfall (mm) 700 1000.0 900.0 800.0 700.0 600.0 500.0 400.0 300.0 200.0 100.0 0.0 OND JFM Linear (JFM) Linear (OND) Linear (OND) 400 300 200 100 20 05 20 03 20 01 19 99 19 97 19 95 19 93 19 91 19 89 19 87 19 85 19 83 19 81 19 79 19 77 19 75 19 73 19 71 19 69 19 67 19 65 19 63 19 61 0 YEAR c) Arusha station d) Dodoma station Figure 2: Year to year rainfall fluctuations for Songea, Bukoba, Arusha and Dodoma stations (Source: TMA, 2007). Figure 3: Rainfall variations and dryspells distribution for Same station, Kilimanjaro Region (Enfors, E. I. and L. J. Gordon. (2007). Climate variability Climate Change Impacts Information/ awareness Design and evaluation of strategies Assess future needs and opportunities Communicat ion/outreach/ education Management practices External influences Figure 4: Conceptual framework showing, in shaded area, iterative steps involved in planned adaptation to climate variability and change based on Klein et al., 1999