Climate Change), Vol

Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

Sudan Academy of Sciences Journal Special Issue

(Climate Change )

Refereed Scientific Journal

Vol. 11, 2015

I Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

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II Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

Editorial Board for the Spcial Issue on Climate Change 1. Prof. Dr. Eisa Ibrahim ElGaali Editor-in-Chief 2. Prof. Dr. Faisal Mohamed Ahmed El-Hag Vice Editor-in-Chief 3. Prof. Dr. Mohamed El-Fatih Khalid Ali Member 4. Prof. Dr. Hamied Hussain Elfaki Member 5. Prof. Dr. Abdel Alla Ibrahim Elhagwa Member 6. Prof. Dr. Mustafa Mohammed Al-Haj Member 7. Associate Prof. Imad-edlin Ahmed Ali-Babiker Advisor 8. Associate Prof. Elshaikh Abdalla Elshaikh Member 9. Associate Prof. Izat Mirgani Taha Member

Supporting Editorial Staff 1. Mr. Mohammed Salman Ali 2. Mrs. Maha Abdalla Eisa 3. Mrs. Alaa Amin Idris

III Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

ECAW Project Note VI

International Research Center (IDRC) Note VII

Forward VIII

The Status of Sience-based Research in Influencing Cimate Change 1 Policies, Plans, and Strategies in Sudan. Imad-Eldin A. Ali Babiker , Faisal M. El-Hag, Abass E. M. Elamin and Bashir A. Eltahir and Abdelmotlib A. Ibnoof

Agro-pastoralists’ Perceptions on the Impact of Climate Change on 15 Browse Trees and Shrubs Cover in the Butana Region, Sudan. Abdelmalik M. Abdelmalik, Ahmed S. El Wakeel, Imadeldin A. Ali- Babiker and Faisal M. El-Hag

Small farmers’ Perception on Cimate Change Risk at the Blue Nile 24 State, Sudan. Hanadi, I. O. Babikir and Muna, M.M. Ahmed

Vulnerability and Potential Adaptation Optionsof Agricultural 33 Sector to Climate Change in Sudan. Abdelrahman K. Osman

Evaluation of Climate Change Effects on the Growing Season in 43 Butana Region and North Kordofan, Sudan. Abdelrahman A. Khatir , Abdelmalik M. Abdelmalik , Mawada G. Abdalla, Sarah A. M. Elmobark, Imad-eldin A. Babiker, Sara A. Babiker and Faisal M. El-Hag

Changing Climate and Farming Productivity in the Drylands of 56 Eastern Sudan. Imad-eldin A Ali Babiker, Faisal A. M. El-Hag, Ahmed M Abdelkarim and Abdalla Khyar Abdalla 62 Impact Assessment of Climate Change on the Livelihoods of Pastoral Communities in Sudan’ Butana Region: A Multidimensional Tradeoff Analysis. Abdelhamed M. Magboul, Abbas E. M. Elamin1, Imad-eldin A. Ali- Babiker, Abdelmotalib A. Ibnoaf and Faisal M. El-Hag

Managing Rainfall Variability in Arid Rainfed Agriculture Using 74 Adaptive Varieties and In-situ Water Harvesting Kawkab, E. Babiker, Abdelhadi, A. W. Mohamed, Imad, A. A. Babiker and Hussni O. Mohammed

Impacts of Climate Change on Biodiversity in Sudan: A Review 83 Ahmed S. El Wakeel

IV Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

ISSN 1816-8272 Copyright © 2015 SAPDH Impact of Climate Change on Natural Resources at EL-Damazine 95 and AT -Tamadon Localities, Blue Nile State, Sudan: Biodiversity perspective Hanadi, I. O. Babikir and Muna, M.M. Ahmed

Coping strategies to water shortages in central Sudan; Almanagil 103 locality Muna, M.M. Ahmed and Magda, M. El-Mansoury

Climate Change and Irrigation in Sudan 115 Hussein S. Adam

Meteorological Measurements in Demokeya, North Kordofan: A 118 Contribution to Climate Change Research Jonas Ardö, Hatim Abdalla M. ElKhidir, Abdelrahman Khatir, Ford Cropley

Climate change and vector-borne diseases in Sudan 128 Mutamad Amin, Faiza Hussien, Hwida Abubakr and Sulafa Abd Algodous

Soil Carbon Seque stration and Climate Change in Semi-arid Sudan 140 Jonas Ardö

Climate Change Adaptation through Sustainable Forest 164 Management in Sudan :Needs to Qualify Agroforestry Application Bashir A. El Tahir

Differences in Acacia senegal Provenances’ Adaptation to Climate 187 Variability and Gum Arabic Production Trends Mohamed E. Ballal and Hiba M. Abdel Rahman

Impacts of climate change on forest tree seeds in Sudan: A review 200 Sayda Mahgoub

Climate Change Adaptation in Sudan :Implementation and Policies 207 Ismail Elgizouli and Mutasim B. Nimir

Climate Change Impacts, Vulnerability and Adaptation in Sudan 217 Sumaya A. Zakieldeen and Nagmeldin G. Elhassan

Indigenous Knowledge and Irrigation in Sudan 234 Hussein S. Adam

V Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

The development externalities associated with climate change will be much felt in Africa due to its limited capacity to adapt. Some climate extremes such as floods and seasonal droughts are already undermining the economies and prosperity of the African continent and its people especially in the GHA. Indeed, mainstreaming adaptation in the African development policy, planning, and investment processes is extremely relevant. Adaptation plans and investments have to happen at different planning scales at global, regional, national, and local levels. Predictions of impacts due to climate change in many sectors rely on biophysical and economic computer models and reliable input data. The best adaptation options to these impacts depend on existing proven actions, which already people are practicing in areas already affected (also called analogue sites) or in some other areas with similar or even worse situation. Therefore, involvement of stakeholders is crucial in choosing adaptation actions to be tested or implemented. The ECAW project aimed at improving the assessment of climate change impacts in agriculture and water resources in the Great Horn of Africa in Ethiopia, Kenya, Sudan and Tanzania. The overall objective of the project was to “improve capacity of research institutions in the Greater Horn of Africa (GHA) to deliver timely scientific advice and expert assessment for climate change adaptation investments and policy decisions in agriculture and water resources”. However, because of heterogeneity of the agricultural enterprises, each country concentrated on one or two systems in which the country has competitive advantage over other countries. Ethiopia‟s focus was on tef, while Sudan was on livestock. Kenya focused on maize mixed cropping while Tanzania was on maize mono-cropping and water resources for irrigation. The ECAW project, therefore, was implemented at the right time (2011 – 2014) when most GHA countries are busy revising their NAPAs and or formulating new programmes and strategies. The support from IDRC is highly appreciated.

Prof. Henry Mahoo, Principal Investigator, ECAW Project SOIL-WATER MANAGEMENT RESEARCH PROGRAMME FACULTY OF AGRICULTURE SOKOINE UNIVERSITY OF AGRICULTURE - Tanzania

VI Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

Climate change extremes such as flooding and seasonal drought are already undermining the economies of countries in the Horn of Africa, with agriculture and water resources being the most affected sectors. Countries in the region are drawing up national adaptation plans (NAPs) to serve as roadmaps for future investment. These plans need to be strengthened by credible and impartial scientific assessment of climate change impacts and informed by economic analyses of adaptation options to recommend investment pathways for the most promising options. With support from Canada‟s International Development Research Centre (IDRC), the Agricultural Research Corporation in collaboration with agricultural research institutions in Ethiopia, Kenya and Tanzania undertook research to achieve multiple objectives including to improve estimates for measuring climate change impacts on agriculture and water resources; to assess the costs and benefits of various adaptation options; to enhance the research capacity of the participating institutions; and to facilitate knowledge-sharing to inform climate change adaptation policies and practices in the Horn of Africa. The research involved case studies of livestock production in Sudan; maize production in Kenya; tef production in Ethiopia, and maize production and water resources in Tanzania. It was funded through Canada‟s Fast-Start Climate Finance Fund as one of seven projects under the African Adaptation Research Centres (AARC) Initiative aimed at supporting leadership and excellence in climate change research in Africa. The works presented in this publication provide new insights in improving estimates for measuring climatic impacts and proposing adaptation options in agriculture and water resources to guide policy decisions. The results are expected to guide climate risk planning and investments choices based on local realities to build long-term resilience among communities. We believe that significant capacity has also been built, through these works, to conduct advanced climate science research and to monitor and evaluate adaptation investments in the region, which can be harnessed.

Edith Ofwona Senior Program Specialist International Development Research Centre

VII Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015

ISSN 1816-8272 Copyright © 2015 SAPDH Forward Climate change has been sneaking up on us for many decades – some say ever since the advent of the Industrial Revolution – but it is only relatively recently that steps began to be taken to confront what we can call a „creeping catastrophe‟. In 1989, the United Nations established the UN Framework Convention on Climate Change (UNFCCC) and called for global action to reverse the alarming, but at the time, not well-understood climate trends. The UNFCCC explicitly requested Member States to enact effective environmental legislation, and that new environmental standards and ecosystem management objectives be embraced. Since then, considerable progress has been made, both in terms of our scientific understanding of climate change and its likely impacts, as well as in the willingness of governments to acknowledge and address the challenge. The Inter-governmental Panel on Climate Change (IPCC) – a scientific body under the auspices of the UN, assessing scientific evidence contributed to it by thousands of researchers worldwide on the causes and likely implications of climate change – confirms that the phenomenon is a manifestation of human activities on our planet, and their impact on the earth‟s natural climate. Yes, there are those who still doubt the anthropogenic causes underlying the climate shifts we are beginning to see and experience, but as the evidence mounts and is becoming more overwhelming, their numbers are dwindling fast. The IPCC warns, unless humanity acts now to address climate change, its effects may be irreversible. One of the key sectors that is already and will increasingly be affected by climate change is agriculture. This is particularly true in developing countries, especially in sub-Saharan Africa. Rapid and uncertain changes in rainfall patterns and temperature regimes threaten food production, increase the vulnerability of farmers, and can result in food price shocks and increased poverty. As noted elsewhere in this publication, agriculture – even the low-input smallholder agriculture– is both a „victim and a culprit‟ relative to climate change. Climate change and variability are major challenges facing smallholder farmers and adaptation is now a priority in Sudan. Farmers and pastoralist living in fragile dryland environments areas are directly exposed to the risks associated with climate change. This is particularly true in areas that already suffer from soil degradation, water scarcity and high exposure to climatic extremes, where poverty and hunger persist. It is high priority for the researcher, policy and decision makers to work on managing ecological, social and economic risks associated with agricultural sector production systems, and supports climate change adaptation as well as climate smart agriculture. We should focus our attention on the vulnerable communities with few assets other than their labor and some land; those rely on farming to produce food for themselves and their families, and to secure their livelihoods. This special issue presents review and findings of efforts in Sudan towards climate change adaptation actions. The ultimate aim is to strengthen the capacity of scientific community to pursue research on climate change adaptation and climate smart agriculture through land and water management among rural communities in Sudan. It focuses on the impacts of climate change on agriculture, natural resources, biodiversity, where most adaptation and coping strategies are needed. While considerable progress is being made on a number of fronts regarding climate change, much more remains to be done. This is a global problem and requires global actions and solutions. We advocate for leaders in government, industry, finance and civil society to take serious practical commitments towards addressing climate change and to find ways to adapt to and mitigate its impacts on our people. Climate-related government programs, whether aiming at adaptation or mitigation (or both), should be mainstreamed into national budgets in order to transform growing political concerns into concrete actions that help large-scale and smallholder farmers to adapt to and mitigate climate change. We all have a role to play in meeting this environmental challenge.

Prof. Dr. Ibrahim El-Dukheri Prof. Dr. Eisa Ibrahim El Gaali Director General President Agricultural Research Corporation (ARC) Sudan Academy of Sciences Wad Medani P.O. Box: 126, Sudan Khartoum P.O. Box: 86, Sudan

VIII Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14

The Status of Science-based Research in Influencing Climate Change Policies, Plans, and Strategies in Sudan

Imad-Eldin A. Ali-Babiker1, Faisal M. El-Hag1, Abass E. M. Elamin2, Bashir A. Eltahir3 and Abdelmotlib A. Ibnoof4

Abstract This study was designed to assess involvement of researchers in climate change adaptation and their capacity to generate scientific evidence on climate change adaptation policies and plans of action. Information used for conducting study included both primary and secondary data. An inventory of research scientists working in climate change in agriculture and water resources including animal agriculture was made. The study showed a clear indication of limited scientific evidence on climate change impact assessment both in water resources and animal agriculture. Only 15.4% of the research programs (4 out of 26) had elements of climate change impact assessment on animal agriculture and water resources. Also, very limited research was conducted to contribute to the understanding of the climate change impact in animal agriculture and water resources. Research programs and projects together with development programs and projects of research involvement (both locally and externally funded) were 49 out of which only 23 were externally funded. Most of the projects handled adaptation options related to development and improvement of adapted crop varieties and enhancing livelihood/income resilience. The low percent of agricultural water management practices (20.0%) and adaptation knowledge (17.8%) may be related to few scientists with background in environmental sciences or water and agricultural engineering compared to crop and soil sciences. Potential adaptation strategies related to climate forecasts and animal agriculture were less common compared to reforestation and agro-forestry and agronomic aspects. It was concluded that there is a high pressing need to enhance the capacity of researchers to generate scientific evidence on impact assessments and adaptation options, and strengthen the communication platforms among researchers and policy makers. This would ensure that science-based research findings are communicated and thereby used in influencing climate change policies, plans, and strategies. This would assist in proper planning and implementing climate change mitigation adaptation strategies, hence improving animal agriculture under pastoral and agro-pastoral in Sudan and similar areas in the Sudan.

Keywards: Science-based Knowledge, Communication Platform, Climate Change, Policsies & Plan, Animal Agriculture.

1 Dryland Research Centre (DLRC), Agricultural Research Corporation (ARC), Sudan, Corresponding author email: [email protected] 2 Planning, Monitoring and Evaluation, Agricultural Research Corporation (ARC), Wad Medani, Sudan. 3 Obied Research Station, Agricultural Research Corporation (ARC), Sudan. 4 Faculty of Commerce, Economics and Social Studies, Khartoum, Sudan. 1 Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14

Introduction Most of the human population lives in areas where food production and nature co- exist. The largest and increasing number of under- and mal-nourished in the world, the prospect of rising inequality, the decreased availability of natural resources and the uncertainty of climate change are among the main challenges facing livelihoods (Gilland, 2002). The 2007 report of the Intergovernmental Panel on Climate Change (IPCC, 2007a) clarified that warming of the climate system is unequivocal and accelerating, and a certain amount of change in the climate is inevitable, necessitating both mitigation and adaptation actions. Over the past 30 years, efforts have been directed to help poor rural people in marginal or unfavorable agro-ecological conditions to manage their natural resources more sustainably, increase their agricultural productivity and reduce their vulnerability to climatic shocks (Ali Babiker and Mohamed, 2010; UNFCCC, 2011; IATP. 2008). Much of this work has been conducted under conditions of change - rising population densities, deteriorating natural resources, and increasingly uncertain and unpredictable climatic conditions. Climate change will exacerbate the existing vulnerabilities of poor people, thus placing additional strain on livelihoods and coping strategies (UNFCCC, 2004). Multiple stresses related to land degradation, trends in economic globalization, and exposure to violent conflict aggravate exposure to climate risks and affect the capacity of poor people to adapt (El-Hag et al., 2011). It is clear that climate change and poverty are interlinked in complex and mutually reinforcing ways. The nature of the development pathway can have a significant impact on the level of climate change impact (Hatfield et al., 2011). As much as climate change can affect sustainable development and constrain achievement of the Millennium Development Goals (MDGs), sustainable development can reduce vulnerability. While climate change impacts will vary from place to place, requiring locally specific adaptation strategies, there are some general indications of the ways in which climate change will affect agro-pastoralists and pastoralists (Scholes and Biggs, 2004). These include increased likelihood of crop failure, increase in diseases and mortality of livestock, and/or forced sale of livestock at low prices, increased livelihood insecurity, resulting in assets sale, indebtedness, outmigration and dependency on food aid, and a downward spiral in human development indicators, such as health and education (UNDP, 2007). More than half Sudan can be classified as desert or semi-desert, with another quarter as arid savannah, despite the diverse ecological zones. Changes in temperature and rainfall are likely to lead to desertification in some regions. The country inherent vulnerability may best be captured by the fact that food security in Sudan is mainly determined by rainfall, particularly in rural areas, where 70% of the total population lives. Changes in temperature and precipitation could cause shifts in the precarious distribution of these ecological zones, in the productive capacity of rain fed agriculture, and thus, in the security of the nation food supply. Historically, average annual rainfall has declined from about 425 mm/year during the period 1941-1970 to about 360 mm/year in the period 1970-2000. This represents a decrease of annual rainfall of about 0.5% per year. At the national 2 Copyright © 2015 SAPDH ISSN 1816-8272

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14 level, there is a trend of greater rainfall variability, increasing at a rate of about 0.2% per year. For the completion of the INC, Sudan developed scenarios to project future temperature and precipitation, due to climate change, in 2030 and 2060, based on a doubling of CO2 emissions (IS92A scenario), milestone years 2030 and 2060 are used in place of IPCC recommended 2015, 2050 and 2100) (IPCC, 2007b). Relative to baseline expectations, the Sudan 1st National Communication (INC, 2003) indicated an average warming range of 1-3˚C and average change in precipitation of -5.8% by 2030 in some areas. As rainfall is already extremely erratic and varies widely from the northern to southern ranges of the country, the severity of drought experienced depends on the variability of rainfall both in amount, distribution and frequency. The Sahelian belt which runs through Sudan is very likely to suffer the impact of climate change (Scholes and Biggs, 2004). Since the 1930s, the Sahara Desert has encroached southwards by between 50 and 200 km, eating into semi-desert and savannah land. Climate change is likely to exacerbate this desertification trend. According to the INC, where between 1961 and 1998, episodes of drought have inflicted Sudan with varying severity. This period witnessed two widespread droughts during 1967-1973 and 1980-1984 - the latter being the most severe. The same period witnessed a series of localized droughts during 1987, 1989, 1990, 1991, and 1993, 2003, mainly in western Sudan (Kordofan and Darfur) and parts of central Sudan. Drought threatens the remaining cultivation of about 12 million hectare of rainfed mechanized farming and 6.6 million hectares of traditional rainfed lands. Pastoral and nomadic groups in the semi-arid areas of Sudan are also severely affected (MARF, 2011). The results of the vulnerability study conducted for the INC suggested that the nation as a whole may be hard hit by even modest changes in temperature and precipitation. In 2030 and 2060, the humid agro-climatic zones would shift southward, rendering areas of the north increasingly unsuitable for agriculture (Zakieldeen, 2009). Crop production is predicted to decline by between 15% and 62% for millet and between 29% and 71% for sorghum and large areas of rangelands would be denuded and suffering from moving sands. The most vulnerable groups are traditional rainfed farmers and pastoralists. As a backdrop to this, increased temperature and variability in precipitation, combined with growing socioeconomic pressures are likely to intensify the ongoing process of desertification in the region and beyond. The projected increases in population, desertification and assorted environmental and socioeconomic pressures, provide a warning signal to stakeholders and decision-makers and would helped to sharpen attempts at identifying and implementing adaptation measures (Thomas and Twyman, 2005). This baseline study attempted to list climate change projects in Sudan, assess involvement of researchers in climate change adaptation and their capacity to generate scientific evidence on climate change adaptation policies and plans of action.

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14

Methodology Information used for attaining this baseline study included both primary and secondary data. Sources of secondary data included development and research projects reports in Sudan during the period 2006 up to now, that had a climate change component. An inventory of research scientists working in climate change in agriculture and water resources including animal agriculture was made and covered the Higher Council for Environment and Natural Resources (HCENR), Ministry of Environment and Physical Planning, Institute of Environmental Studies of the University of Khartoum (IES-UoK), Agricultural Research Corporation (ARC), Sudan Meteorological Authority (SMA), Ministry of Animal Resources and Fisheries. NGOs working on climate change in agriculture were also reviewed. Other secondary data sources were published and unpublished reports and documents, including internet, covering climate change adaptation and mitigation issues in Sudan and other similar areas. This was undertaken to understand the past and ongoing adaptation projects implemented by key adaptation stakeholders. Researchers’ perceptions in climate change adaptation research were also obtained. The search of information was based on a baseline checklist. In analyzing the capacity of researchers to generate scientific evidence on climate change impact assessments, the study collected information on type of researches being conducted, analytical tools, and if any biophysical models employed. Similarly, the study analyzed research on adaptation actions looking at research objectives that addressed adaptation, source of funds, and adaptation options examined. Further, the study wanted to know if costs and benefits of adaptions were considered and the type of tools used for economic analysis. The study also examined existence of knowledge sharing platforms and composition of such platforms if they do exists. In addition, the study had to examine if research do communicate their results and to what type of stakeholders. However, to prove if really the communication was effective, information must then be incorporated in the policy, plans, and strategies. Therefore, this study concluded by analyzing some key policy documents on climate change and environment with specific focus on animal agriculture. Descriptive statistics, tabulations, and graphing were used as a means of presenting results (Steel and Torrie, 1980). Primary data were collected from five States (Gadaref, Kassala, Gezira, Khartoum and River Nile) in Sudan (Figure 1) where NAPA activities were implemented during the period April 12 to September 16, 2012. These data were collected through various participatory methods including: Direct field observations: Direct field observations were confined to visual indicators or aspects of biophysical environment such as agro-climatic zone, soil types, water sources, vegetation cover and constraints as perceived by farmers (both men and women).

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14

Fig. 1. Study area depicting the four States where NAPA is currently working (NAPA, 2007)

Key Informants (KIs): Key informants included individuals involved directly or indirectly in the service sector of agriculture, range-livestock, water and health, farmers and herders unions, and executive authorities and local leaders, Development Projects and Programs and NGOs working in the five States of NAPA activities.

Results and Discussion Table 1 shows the profile of the interviewed respondents who participated in the study. Total number of persons interviewed were 54 out whom 19 (35.2%) were from research and 35 (64.8%) were from other services sectors of agriculture. Research scientist profile was dominated by agronomy and related disciplines (horticulture, agro-forestry, soils) comprising about 52.6% of within research affiliation and 18.5% of the total surveyed sample. Development and extension profile (29.6%) constituted the bulk of the surveyed sample, followed by environment/extension (25.9%) profile and policy planners professional profile (13.0%).

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Table 1. Profile of respondents who participated in the study on science- based evidence in influencing climate change policy, plans, and strategies Profession profile Descriptive Affiliation Total Research Other sectors N 10 0 10 Agronomy and % within Affiliation 52.6% 0.0% 18.5% related disciplines % of Total 18.5% 0.0% 18.5% N 2 0 2 Range-Livestock % within Affiliation 10.5% 0.0% 3.7% % of Total 3.7% 0.0% 3.7% N 1 1 2 Socio-economics % within Affiliation 5.3% 2.9% 3.7% % of Total 1.9% 1.9% 3.7% Agric. N 3 0 3 Engin./Water % within Affiliation 15.8% 0.0% 5.6% Harvesting % of Total 5.6% 0.0% 5.6% N 3 11 14 Envrionment/GIS % within Affiliation 15.8% 31.4% 25.9% % of Total 5.6% 20.4% 25.9% N 0 16 16 Development/Ext % within Affiliation 0.0% 45.7% 29.6% ension % of Total 0.0% 29.6% 29.6% N 0 7 7 Policy/Planning % within Affiliation 0.0% 20.0% 13.0% % of Total 0.0% 13.0% 13.0% By gender: Females 8 14.8% Males 46 85.2% Total N 19 35 54 % of Total 35.2% 64.8% 100.0%

Range-livestock and socio-economic profiles constituted the least (3.7% each) of the surveyed sample. It worth noting here that the GIS within the environment/GIS professional profile was entirely (3 persons) from the research while the other respondents (11) belonged to HCENR and SMA. Females constituted 14.8% of the respondents and males 85.2%. Capacity of researchers to generate scientific evidence on climate change impact assessments within the Agricultural Research Corporation, twenty-six research programs were identified to respond to the various challenges and needs to develop appropriate technologies. These research programs devoted to various crops including cereals, cotton, oilseed crops, sugarcane, grain legumes, vegetables and medicinal plants, fruits and ornamentals, forages, gum Arabic, forestry, land and water, crops protection, food processing, agricultural engineering, pesticides, biotechnology, and genetic resources, together with

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14 technology transfer. In each program research thrusts were identified, weighted and prioritized according to economic importance, export potential, food security. This clearly reflected limited scientific evidence on climate change impact assessment both in water resources and animal agriculture. This was evidenced by the fact that most of the research cadre within the ARC-Sudan (414 research scientists) was composed mainly of agronomists and related disciplines (Figure 2), with very limited research staff in water resources (10.0%) and animal agriculture (2.0%).

Figure 2. Research staff professional staff within the ARC-Sudan

Only 15.4% of the research programs (4 out of 26) had elements of climate change impact assessment on animal agriculture and water resources. The elements included degraded soil fertility, pests and diseases and livestock- rangelands productivity (Table 2). This indicated that very limited research is being conducted to contribute to the understanding of the climate change impact in animal agriculture and water resources (Thornton et al., 2002).

Table 2. Type of impact dealt within ARC research programs Impact N % Declining yields 13 50.0 Degraded soil fertility 2 7.7 Rainfall variability 1 3.9 Livelihoods and declining farm income 2 7.7 Crop/livestock pests and diseases 4 15.3 Livestock-rangeland productivity 1 3.9 Value addition 3 11.5 Total 26 100.0

Analytical tools used to assess climate change impacts as reported by the interviewed respondents revealed that qualitative tools were the most common

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(Table 3), followed by statistical software packages. Software packages included Mstat-C, SAS, SPSS and GENSTAT. Excel Microsoft program was ranked third mostly used by socio-economists and for graphics. The use of GIS, remote sensing, and modeling and simulations was relatively rare. Only two reported to use GIS remote sensing and stated that they mostly use Arc-View program for map drawing, whereas modeling and simulation was reported by only one respondent.

Table 3. Analytical tools used in the analysis of impacts Impact analytical tool N % Conventional statistical software 13 14.1 GIS Remote sensing 2 3.7 Qualitative 33 66.1 Modeling and simulation 1 1.9 Excel 5 9.3 Total 54 100.0

Research programs and projects together with development programs and projects of research involvement (both locally and externally funded; totaling 49 out of which only 23 were externally funded) were thoroughly scrutinized and analyzed for their objectives, identified adaptation options, their costs and benefits, and analytical tools used to derive them. This was done to identify objectives with adaptation elements. The adaptation objectives were grouped into four major categories (Table 4). These categories included agricultural water management category (irrigation systems and management, conservation agriculture, and soil and water conservation practices), variety/breed, and livelihoods/income resilience and adaptation knowledge. Most of the projects handled adaptation options related to development and improvement of adapted crop varieties and enhancing livelihood/income resilience. The low percent of agricultural water management practices (20.0%) and adaptation knowledge (17.8) may be related to few scientists with background in environmental sciences or water and agricultural engineering compared to crop and soil sciences (Figure 2).

Table 4. Distribution of adaptation objectives by categories (%) Adaptation objectives category N % Agricultural water management 18 20.0 Variety/breed 25 27.8 Livelihood/Income resilience 31 34.4 Adaptation knowledge 16 17.8 Total 90 100.0

Potential adaptation was reported by the interviewed scientists to be higher for strategies related with agricultural water management and improvement of varieties/breeds, recording 38 and 25 counts, respectively (Figure 3). Potential adaptation strategies related to climate forecasts and animal agriculture were less common compared to reforestation and agro-forestry and agronomic aspects.

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14

Fig. 3. Fig. 2: Potential adaptation strategies in agriculture, counts (n=97)

The potential adaptations strategies in the animal agriculture are those related with the areas of feeding management, disease control and breed improvement (Neely and Bunning. 2008). However, rainwater water harvesting for crop production purposes was the most prominent adaptation strategy in the agricultural water sector, with no efforts done for rangelands rehabilitation. For animal agriculture, the most prominent adaptation strategies followed were disease control, value addition (mainly fattening and finishing operations) and feeding management (Table 5).

Table 5. Potential adaptation strategies in animal agriculture Adaptation strategy in animal agriculture N % Water harvesting 12 24.5 Disease control 13 26.5 Feeding management 9 18.4 Breed improvement 5 10.2 Value addition 10 20.4 Total 49 100.0

Knowledge sharing platforms are ranked into four categories (Table 6). Effective platforms were those that had regular meetings. Those are expected to be effective as they are devoted to a particular subject like national technology release committees of the ARC-Sudan and steering committees of programs and projects. Percentage distribution of responses on effective knowledge sharing platforms, as reported by respondents, was 24.1%. Over forty-four percent of the respondents

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14 were with less effective (33.1%) and not effective (11.1) categories of knowledge sharing platforms. This entails high need for strengthening workshops, seminars and publications.

Table 6. Level of effectiveness of knowledge sharing platforms Ranking N % Knowledge sharing platform Effective 13 24.1 Technology release committees, steering committees Moderately effective 17 31.5 Field days, field schools, extension campaingns Less effective 18 33.3 Workshops, seminars, media Not effective 6 11.1 Scientific publications, bulletins, posters and leaflets, States Legislative Councils

The most prominent platforms (Table 7) were those dominated by scientists and NGOs (35.2%), followed by Federal and State ministries (25.9%) and policy and decision makers (24.1%). No media or private sector appeared to be in the composition of knowledge sharing platforms in Sudan. It is a tendency in the country to call media people to cover meetings, workshops and seminars; mainly opening sessions, and not as members in such platforms. Farmers, extension and local communities comprised about 11.1% of knowledge sharing platforms whereas government commissions’ representation was found to be limited (3.7%). There is a high need to involve media and private sector in knowledge sharing platforms.

Table 7. Composition of knowledge sharing platforms Composition N % Farmers, extension, local communities 6 11.1 Policy/decision makers 13 24.1 Scientists, researchers, research institutions, NGOs 19 35.2 Federal and State ministries 14 25.9 Government commissions 2 3.7

Stakeholders mostly communicated with research findings were other researchers within or outside the ARC, followed by farmers/herders and their groups, policy and decision makers, then government agencies and development projects (Table 8). Communication of research results to consultancy agencies was ranked fifth and the least communication was with private sector and NGOs.

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Table 8. Recipients of communication messages Recipient N % Farmers/herders and their groups 91 22.0 Policy and decision makers 34 8.2 Other researches (universities, ARC) 214 51.7 Government agencies and development projects 30 7.2 NGOs, CBOs 10 2.4 Private sector 12 2.9 National Consultancy firms and groups 23 5.6 Total 414 100.0

Use of scientific-based evidence in the adaptation planning process Documents that were reviewed to determine the extent of used of scientific information in developing policies and strategies on climate change and environment in Sudan included National Communication of 2003, National Adaptation Plan of Action (NAPA) of 200, National Action Program (SNAP) for combating desertification of 2006, and Sudan Agricultural Revival Strategy Program of 2011. Sudan First National Communication (INC, 2003): This work was done by a team of researchers who were organized by the Higher Council for Environment and Natural Resources (HCENR) of the Ministry of Environment and Physical Planning (MEPP). The team was formulated from the HCENR, SMA, Institute of Environmental Studies (IES) of the University of Khartoum, Ministry of Agriculture and Forestry, Ministry of Animal Resources and Fisheries and the Agricultural Research Corporation (ARC). Sudan’s First National Communication (INC) to the UNFCCC, submitted in July 2003, provided an assessment of likely impacts of climate change on several sectors including decreasing annual rainfall, increasing rainfall variability, and increasing average annual temperatures. An examination of Sudan’s ecological zones indicated that the majority of its land is quite vulnerable to changes in temperature and precipitation (INC, 2003). Changes in temperature and rainfall patterns also represent a priority threat to food security in Sudan’s agriculture- based economy. Current increasing variability is a manifestation of long term change of climatic conditions in the country, region, and globally. Changes in average temperature or precipitation often do not show strong signals, but the well-observed trends of decreasing annual rainfall and increased rainfall variability have contributed to drought conditions in many parts of Sudan (El- Hag, et al., 2012). The INC (2003) identified agriculture, water and health as the highest priority sectors where urgent and immediate action is needed. Consistent with guidance for the LDCF (GEF/C.28/18, 2006), the NAPA process also yielded a consensus that the highest priority intervention should be a program of adaptation interventions with a major focus on the enhancement of food security by building the adaptive capacities of the rural population, particularly of rainfed farming and pastoral communities, relative to current and future climate risks. Sudan National Adaptation Plan of Action (NAPA): This plan was developed by a multi-disciplinary and multi-sectorial team from various government 11 Copyright © 2015 SAPDH ISSN 1816-8272

Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 1-14 institutions (Ministries, Universities, agencies, etc). Some of the key institutions that were involved included HCENR, IES of the University of Khartoum, Agricultural Research Corporation. Four States with Sudan (Figure 1) were chosen as being most vulnerable to climate change. Consultations were undertaken at federal, State, as well as locality levels. Among the stakeholders who were consulted are public and private sector organizations such as government ministries and departments, academic and research institutions, local authorities, local administration, farmers/herders groups and NGOs. Stakeholder consultations at grassroots level helped to prioritize the 27 top most possible adaptation activities that could address the country’s most urgent needs from all sectors. Sudan National Action Program (SNAP) for Combating Desertification (NDDCU, 2006): The program document was prepared by staff from Ministry of Agriculture and Forestry, HCENR, University of Khartoum, Agricultural Research Corporation, UNDP-Sudan, UNISCO-Sudan, and Arab Organization of Agricultural Development (AOAD). The document provided background information on the present environment and natural resources conditions. It covers climate, renewable natural resources, energy, land use, biodiversity and national heritage. Attention has also been drawn to the impacts of the frequent drought periods that inflicted the country in recent decades on the socio-economic status of the population. The document focused on actions in the form of programs and projects within the context of SNAP and in accordance with the objective of the UNCCD, based on guidelines from the NCS and the Agricultural Sector Strategy. Sudan Agricultural Revival Strategy (SARS): Recently, the Sudan has taken a new and strategic direction to support agriculture. This new direction is manifested in the declaration of "The Green Mobilization" and the preparation of the Five-Year Strategic Plan. This was followed by a fully integrated program that constitutes a national strategy for the Agricultural Revival as well as a compass for correcting the current program and plans of ministries and institutions in the center and the states, besides establishing a monitoring and follow-up system for assessing the results and impacts. All staff in federal and state ministries of agricultural, forestry and animal resources together with research institutions and universities had been mobilized to develop the SARS. Use of scientific based evidence The use of science-based evidence in developing climate related policies, plans, and strategies, is low (Table 9). NAPA used the least number of references compared with the communication strategy and Sudan National Adaptation Program despite being developed four years after the former and one year after the latter. It is surprising to notice that Sudan Agricultural Revival Strategy reported no references in its main document. National communication (34.8%) used the highest number of research related findings followed by SNAP (29.7%).

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Table 9. Use of scientific-based evidence Category National SNAP NAPA SARS Communication Year 2003 2006 2007 2011 N % N % N % N % Books 4 5.6 3 11.1 0 0 0 Referred 8 11.3 1 3.8 0 0 0 journals Proceedings 5 7.0 2 7.4 2 13.3 0 0 Research reports 7 9.9 2 7.4 4 26.7 0 0 RoS documents 23 32.4 10 37.0 7 46.7 0 0 IO documents 24 33.8 9 33.3 2 13.3 0 0 Total 71 100.0 27 100.0 15 100.0 0 0 RoS = Republic of Sudan IO = International Organizations

Acknowledgment This work was part of the Project “Enhancing Climate Change Adaptation in Agriculture and Water Resources in the Greater Horn of Africa” (ECAW) which was funded by the International Development Research Center (IDRC) Grant No. 106552-003.

References Ali Babiker, I. A. and Mohamed, A. A. W., 2010. Climate change current activities in Sudan. The Regional Workshop on the Status of Climate Change in the Nile Basin countries. Entebbe, Uganda, Feb. 8-9, 2010. Pp 19. El-Hag, F.M.; Elhassan, S.M. and Khatir, A. A. 2012. Documentation of National Adaptation Program of Action (NAPA) Best Practices, for the UNDP-HCENR Project on Implementing NAPA Priority Interventions to build resilience in the agriculture and water sectors to the adverse impacts of climate change in Sudan. Higher Council for Environment and Natural Resources (HCENR), Ministry of Environment and Physical Planning. Khartoum, Sudan. El-Hag, FM, Osman, AK, El-Jack, FH, Wagiyalla, NA, Mekki, MA and Khatir, AA., 2011. “Changes and threats facing nomads under drylands – the case of the Shanabla tribe in Western Sudan”. Drylands Coordination Group, Miljøhuset G9, Norway. 85 pp. Gilland, B. 2002. World population and food supply. Can food production keep pace with population growth in the next half-century? Food policy. Food policy v. 27 (1) p. 47-63. Hatfield, J.L., Boote, K.J., Kimball, B.A.,Ziska, L.H.,Izaurralde, R.C.,Ort, D.,Thomson, A.M.,Wolfe, D. 2011. Climate Impacts on Agriculture: Implications for Crop Production. Agronomy journal. 2011 Mar., v. 103, no. 2 p. 351-370. IATP. 2008. The changing climate for food and agriculture. A literature review. IATP (Institute for Agriculture and Trade Policy). Minnesota, USA. 17 pp.

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IPCC (Intergovernmental Panel on Climate Change). 2007a: Climate change 2007: Climate Change Impacts, Adaptation and Vulnerability, IPCC WGII Fourth Assessment Report, online: http://www.ipcc.ch/ SPM6avr07.pdf IPCC (Intergovernmental Panel on Climate Change) 2007b. Synthesis Report. An Assessment of the Intergovernmental Panel on Climate Change. IPCC, Geneva. http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf. INC. 2003. Sudan’s First National Communications under UNFCCC, The Republic of Sudan (2003). Follow-up to Sudan’s report for the third UN conf. on Least Developed Countries (LDC) presented to ECOSOC, Genava, Sudan Program of Action for Devlopment. 106 pp. MARF. 2011. Federal Ministry of Animal Resources and Fisheries (MARF) Reports, Khartoum, Sudan. NAPA. 2007. National Adaptation Program of Action. Republic of the Sudan, Ministry of Environment and Physical Development, Higher Council for Environment and Natural Resources, Khartoum. 54 pp. NDDCU. 2006. (Natioal Drought and Desertification Control Unit) Sudan National Action Program (SNAP). A framework for combating desertification in Sudan in the context of the UNCCD (United Nations Convention to Combat Desertification), Khartoum, Sudan. 54 pp. Neely, C. and S. Bunning. 2008. Review of Evidence on Dryland Pastoral Systems and Climate Change: Implications and opportunities for mitigation and adaptation. FAO – NRL Working Paper. Rome, Italy. Scholes, R.J., Biggs, R., (Eds.), 2004. Ecosystem services in southern Africa: a regional assessment. Millennium Ecosystem Assessment. Online at http://www.millenniumassessment.org. Steel, R. G. D. and Torrie, J. H. 1980. Principles and Procedures of Statistics: Abiometrical approach. McGraw-Hill Co., New York, USA. 633 pp. Thomas, D.S.G., Twyman, C., 2005. Equity and justice in climate change adaptation amongst natural-resource-dependent societies. Global Environmental Change 15, 115–124. Thornton, P.K., Kruska, R.L., Henninger, N., Kristjanson, P.M., Reid, R.S., Atieno, F., Odero, A., Ndegwa, T., 2002. Mapping Poverty and Livestock in the Developing World. ILRI (International Livestock Research Institute), Nairobi, Kenya UNDP. 2007. Adaptation to climate change in poverty reduction strategies. Human Development Report, Office occasional paper, UNDP, 20 pp. UNFCCC. 2011. Assessing costs and benefits of adaptation options: An overview of approaches. UNFCCC (United Nations Framework Convention on Climate Change. Germany. 47 pp. UNFCCC. 2004. Climate change: Impacts, vulnerabilities and adaptation in developing countries. The Information Service of the UNFCCC Sectariat, Bon, Germancy. 59 pp. Zakieldeen, S. 2009. Adaptation to climate change: A vulnerability assessment for Sudan. IIED Gatekeeper Series, No. 142. 18 pp.

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Agro-pastoralists’ Perceptions on the Impact of Climate Change on Browse Trees and Shrubs Cover in the Butana Region, Sudan

Abdelmalik M. Abdelmalik, Ahmed S. El Wakeel, Imadeldin A. Ali-Babiker1 and Faisal M. El-Hag

ABSTRACT A study was conducted with the objectives of assessing farmers’ perceptions on climate change impact on browse trees/shrubs cover and monitoring their distribution in relation to climate change in the Butana region. A total of 150 male and female farmers from 14 villages in the central, western and southern parts of Butana region were interviewed using a structured questionnaire. All data collected were statistically analyzed using the Statistical Package for Several Sciences software program (SPSS Ver. 20.0) and Chi-square test for mean separation. The deterioration in the quantity and quality of trees/shrubs cover was mainly attributed to the decrease in rainfall, in addition to over grazing, expansion in rainfed agriculture and tree cutting for charcoal making. This was evidenced by the disappearance of many tree species from the region such as Commiphora africana (Gufal), Terminalia brownie (Soubagh) and Faidherbia albida (Haraz). The trees and shrubs were mainly reported by the respondent farmers as sources for livestock browsing and firewood. New tree species such as Acacia oerfota (Laoat) were mentioned to have invaded the region especially the central part. Acacia mellifera (Kitir) followed by Acacia tortilis subsp. raddiana (Seyal) were stated as the most preferred browse trees for camels and goats, especially in the dry season.

Keywards: Climate Change, Farmer Perceptions, Trees, shrubs, browsed, rainfed.

Introduction Sudan encompasses a wide range of ecological zones extending from the desert in the north with an annual rainfall of (0-100 mm), semidesert (100-250 mm), arid (250-350 mm) and semi–arid (350-750 mm) to the sub – humid environments in the south that can exceed (750mm). These zones are on sandy and clay soils. Butana refers to the region that lies between the Nile River and Blue Nile and Atbara River, with the Khartoum, El Gadaref and Kassala railways as the southern boundary. It covers an area of approximately 120,000 km2. It excludes the narrow strip of land along the eastern bank of the Blue Nile and western bank of Atbara River which are irrigated areas (Abu Sin, 1970). Expansions in rain fed agriculture, agricultural development irrigated schemes, open grazing and tree cutting are the main causes of climate change in the Butana region, where two irrigated schemes were established, namely New Halfa and Rahad in an area of 202,345 and 121,407 ha, respectively (Elhassan,1981). These schemes have reduced the area available for natural pasturelands. The nomads in

1 Dryland Research Centre, Agricultural Research Corporation, Soba, Khartoum, Sudan, Corresponding author email: [email protected]. 15 Abdelmalik et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 15-23 the Butana area cut trees to build houses and animal enclosures or to use for firewood. They also use the green branches or the whole tree to feed their animals. Rainfall is the most important climatic factor influencing livelihoods in the Butana region in the north-eastern parts of Sudan. All people and their livestock depend on the amount and distribution of rainfall to satisfy human needs, livestock and plant growth. The Butana region has experienced severe droughts in the years 1984, 1990 and 2000 (Elhaj, 2006). Elagib and Mansell (2000) reported that the mean annual temperatures in Sudan have increased significantly by 0.076- 0.20oC per decade specifically in the central and the southern regions. Abdella (2008) concluded that Acacia tortilis subsp. raddiana (Seyal) is the most preferred browse tree in the semiarid areas, since it is preferred by animals and as a legume tree that contributes to soil improvement. Lazim (2003) found that A. tortilis and A. mellifera (Kitir) provide great quantities of browse in the Butana region, through provision of fodder for livestock during critical periods when grasses and herbs are not available. The objectives of this study were to assess farmers’ perceptions of the impact of climate change on browse trees/shrubs cover and monitor their distribution in relation to climate change in the Butana region.

Materials and Methods Study area: The study was carried out in the Butana region (Figure 1) that lies in the east central part of Sudan between latitudes 12o30-16o30N and longitudes 33o35-36o35E. A total of 14 villages from Butana were chosen from different sites of the region. These villages namely, El Bahoogi, Hilat Hamad, El Sufia, Es- Soubagh, El Bogaa, El Idaidat, Gad Allah, Wad El Zain, Surug Munana, El Sadda, Wad Shamoon, El Gudorab, Um Tiki and Wad Hirz Allah. With the use of GPS, the villages were grouped into the following three zones:

Zone 1(Central Includes El Bahoogi, Hilat Hamad, El Sufia, Es-Soubagh part): and El Bogaa villages. Zone 2 (Southern Includes El Idaidat, Gad Allah, Wad El Zain, Surug part): Munana and El Sadda villages. Zone 3 (Western Includes Wad Shamoon, El Gudorab, Um Tiki and Wad part): Hirz Allah villages.

Zone 1 is characterized with high annual rainfall (350 mm) compared to the other two zones. The main tree species in this zone are Acacia mellifera and some of Acacia oerfota (Laoat). This area is inhabited by agro-pastoralists who mainly practice traditional mechanized rain-fed agriculture to produce sorghum besides considerable livestock raising activities. Zone 2 includes El Sobagh, the capital of Butana Locality and is characterized with annual rainfall of less than 250 mm. This zone is dominated by A. mellifera and A. oerfota tree species. Zone 3 is located 27 km to the east of Ruffaa town (Gezira state), with annual rainfall of more than 250 mm. A. tortilis is considered the most dominant tree species in this site.

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All these three zones comprise important rangelands for the Butana communities, especially in the dry season. Camels and goats are the main livestock species that utilize these forest trees. Data collection: A reconnaissance survey was carried out in 2013 to identify forest areas in the region through key informants’ interviews. A structured questionnaire was also conducted covering the 15 villages within the three zones. A total of 150 informants with different ages and different sex groups (males and females) were involved in this questionnaire. Most of the villages selected were located within the domain of the Butana Integrated Rural Development Project (BIRDP), funded by the International Fund for Agricultural Development (IFAD). This survey started in March 2013 and information collected were on climate change and its impact on tree cover by addressing some questions related to the main causes of climate change and the tree species that started to disappear as a result of climate change. Data arrangement and analysis: All data collected were coded and statistically analyzed using the Statistical Package for Several Sciences software program (SPSS Ver. 20.0). Chi-square test was used for mean separation.

Fig 1. Butana map

Results and Discussion Female and male respondents accounted for 34% and 66% of the total interviewed farmers, respectively (Figure 2). Impact of climate change on tree/shrub cover in the Butana region: Tables 1, 2 and 3 show the past and present condition of tree cover and the type of change

Abdelmalik et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 15-23 that has occurred in the region. Most of the interviewees (94%) from the three zones mentioned that the present condition of the tree/shrub cover in the region was poor as compared to its condition in the past (Table 3). The decrease in rainfall was reported by 50% of the informants in the three zones as the major cause for the change in tree/shrub cover (Table 4). Overgrazing and expansion in rain-fed agriculture were also perceived as causes for this change. These findings agree with those of Lazim (2003) and Akhtar (1994) who mentioned that trees and shrubs cover in the Butana region has changed and became inadequate for browsing and grazing. Elhaj (2006) reported that the amount of annual rainfall recorded by many weather stations (Wad Madani and Shambat) around Butana showed a declining trend during the period 1968-1987. Ismail (2009) also stated that the natural vegetation cover in the Butana decreased from 46% in 1984 to 26% in the year 2000 and this decrease was attributed to many factors besides the poor climatic conditions. Mohammed (2013) reported that the activity of rain-fed agriculture has taken more land from the forests and rangelands in the Butana. Deforestation by cutting trees/shrubs and other vegetation became a common phenomenon in the western part of Butana (zone 3). Harrison and Jackson (1958) reported that the degradation in natural vegetation was due to bad grazing practices. Elhaj (2006) mentioned that severe degradation has taken place in the Butana where bare soil and eroded land increased by 3-7%, while vegetation cover decreased by 3-6%. In addition to that, pastures have deteriorated in both quality and quantity.

Figure 2. The percentage of the interviewed males and females in the three zones.

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Table 1. Past condition of tree/shrub cover in the Butana region, Sudan. Zone Condition of tree/shrub cover Good Medium Bad Count % Count % Count % Zone 1 (Centre) 41 83.7 5 10.2 3 6.1 Zone 2 (South) 42 87.5 4 8.3 2 4.2 Zone 3 (West) 51 96.2 2 3.8 0 0.0 Total 134 11 5 Mean (%) 89.3 7.3 3.4 Chi-square = 0.28

Table 2. Present condition of tree/shrub cover in the Butana region, Sudan. Zone Condition of tree/shrub cover Good Medium Bad Count % Count % Count % Zone 1 (Centre) 3 6.1 15 30.6 31 63.3 Zone 2 (South) 3 6.1 17 35.4 28 58.4 Zone 3 (West) 1 1.9 14 26.4 38 71.7 Total 7 46 97 Mean (%) 4.7 30.7 64.6 Chi-square = 0.60

Table 3. Kind of change in tree/shrub cover in the Butana region, Sudan. Zone Kind of change Total For bad For bad Count % Count % Count % Zone 1 (Centre) 45 91.8 4 8.2 49 100.0 Zone 2 (South) 44 91.7 5 8.3 48 100.0 Zone 3 (West) 52 98.1 1 1.9 53 100.0 Total 141 9 150 100 Chi-square = 0.29

Table 4. Reasons for change in tree species in the Butana region, Sudan. Reason Zone Zone 1 Zone 2 Zone 3 Mean Count % Count % Count % Count % Decrease in 22 44.9 12 25.0 41 77.4 75 49.1 rainfall Overgrazing 8 16.3 14 29.2 3 5.7 25 17.1 Expansion in 0 0.0 1 2.1 1 1.9 2 1.3 rainfed agriculture All 19 38.8 21 43.8 8 15.1 48 32.5 mentioned Total 49 48 53 150 100.0 Chi-square = 0.0001

Past and present tree species in the Butana region of Sudan: Because of climate change and other factors, all respondents from the three zones agreed that a large number of trees and shrubs have disappeared from the Butana region. These are Gufal (Combretum Africana), Haraz (Faidherbia albida), Habeel

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(Combretum harmannianum), Subagh (Terminalia brownii), Salam (Acacia ehrenbengiana), Hashab (Acacia senegal), Sunut (Acacia nilotica), Talih (Acacia seyal), Sidir (Ziziphus spina christi) and Hijleeg (Balanities aegyptiaca)(Table 5). Historically, all of the above tree species have been mentioned by Harrison and Jackson (1958). Salih et. al (2011) also reported that these tree species are becoming very rare in the region. The interviewees stated that the remaining tree species in the area are not enough to feed their animals. The remaining tree species are A. mellifera (Kitir), A. oerfota (Laoat), A. tortilis subsp. raddiana (Seyal), A. seyal (Talih), Balanites aegyptiaca (Hijleeg) and others (Table 6).

Table 5. Past tree species in the Butana region, Sudan. Species Zone Zone 1 Zone 2 Zone 3 Mean Count % Count % Count % Count % Sunut, 18 36.7 13 27.1 13 24.5 44 29.3 Higleeg, Sidir Gugal, Haraz, 13 26.6 14 29.2 2 3.8 29 19.3 Habeel, Subagh Talih, Salam, 18 36.7 21 43.7 38 71.7 77 51.3 Hashab Total 49 100.0 48 100.0 53 100.0 150 100.0 Chi-square = 0.001

Table 6 shows that Kitir (A. mellifera) was the dominant tree in both zone 1 and 2. Zone 3. However, the area was dominated by Seyal trees (A. tortilis). Laoat trees (A. oerfota) were reported as the second most dominant tree species in zones 1 and 2. On the other hand, Talih (A. seyal) and Hijleeg (B. aegyptiaca) trees were only reported to be present in the southern part of the region (zone 3) close to the water streams (Wadis and Khors) crossing the Butana region from East to West and from West to East.

Table 6. Present tree species in the Butana region, Sudan. Species Zone Zone 1 Zone 2 Zone 3 Mean Count % Count % Count % Count % Kitir 26 53.1 38 79.2 13 24.5 77 51.3 Laoat 20 40.8 6 12.5 4 7.5 30 20.0 Seyal 2 4.1 2 4.2 18 34.0 22 14.7 Talih 0 0.0 0 0.0 11 20.8 11 7.3 Higleeg 0 0.0 0 0.0 3 5.7 3 2.0 Others 1 2.0 2 4.2 4 7.5 7 4.5 Total 49 100.0 48 100.0 53 100.0 150 100.0 Chi-square = 0.0001

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Livestock species that depend on trees/shrubs in the Butana region: Table 7 shows that most of the interviewees (61%) in the three zones mentioned that camels are highly dependent on trees and shrubs for forage followed by goats. Sheep, however, was considered as less dependent on trees and shrubs for forage. This could be attributed to the nature of these animals. This result agrees with that of Lazim (2003).

Importance of browse trees/shrubs in the Butana region: Most of the interviewees (66%) in the three zones mentioned that trees and shrubs are mainly used as browsing resource by livestock, especially camels and goats that are highly dependent on them (Tables 7 and 8). Abdella (2008) reported A. tortilis (Seyal) as one of the most important trees in the arid and semiarid areas. In addition to that, the interviewees also mentioned that trees and shrubs are also used for firewood, medicine and shade for the people and their livestock. Table 9 shows that most of the informants (82.7%) perceived that the rangeland that consists of both trees and herbs is the most preferred type of range. This finding agrees with that of Lazim (3003) who reported that forested range site (herbs under trees and shrubs) is more preferred by pastoralists than open range (herbs in open). This preference could be attributed to the multiple choices of feed available in the forested sites. Table 10 shows that 51% of the interviewees perceived Kitir (A. mellifera) as the most preferred browse tree followed by Seyal (A. tortilis). In zones 1 and 2, Kitir was perceived as the most preferred browse tree, whereas in zone 3 Sayal was considered the most important browse tree for livestock. This result agrees with that of Lazim (2003) who reported Kitir as the most important tree in the area. This preference could be attributed to the good nutritive value or availability and adaptability of these tree species in these zones.

Table 7. Livestock species that depend on trees/shrubs in the Butana region. Species Zone

Zone 1 Zone 2 Zone 3 Mean

Count % Count % Count % Count %

Sheep 2 4.1 4 8.3 11 20.8 17 11.3

Camels 32 65.3 25 52.1 36 66.0 18 61.3

Goats 15 30.6 19 39.6 7 13.2 41 27.3

Total 49 100.0 48 100.0 53 100.0 150 100.0

Chi-square = 0.006

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Table 8. Importance of trees and shrubs in the Butana region. Importance Zone Zone 1 Zone 2 Zone 3 Mean Count % Count % Count % Count % Resource for 33 67.3 32 66.7 34 64.2 99 65.0 browsing Firewood 1 2.0 5 10.4 16 30.2 22 14.7 Medicinal 1 2.0 0 0.0 0 0.0 1 0.7 use Shade 7 14.3 6 12.5 1 1.9 14 9.3 All 7 14.3 5 10.5 2 3.8 14 9.3 mentioned Total 49 100.0 48 100.0 53 100.0 150 100.0 Chi-square = 0.002

Table 9. Preferred rangeland type in the Butana region. Rangeland Zone type Zone 1 Zone 2 Zone 3 Mean Count % Count % Count % Count % Herbs in 4 8.2 1 2.1 10 18.9 15 10.0 open Trees in 1 4.1 1 2.1 8 15.1 11 7.3 open Herbs under 43 87.7 46 95.8 35 66.0 124 82.7 shrubs and trees Total 49 100.0 48 100.0 53 100.0 150 100.0 Chi-square = 0.002

Table 10. Most preferred browse tree species in the Butana region. Tree Zone Zone 1 Zone 2 Zone 3 Mean Count % Count % Count % Count % Sidir 3 6.1 12 25.0 2 3.8 17 11.3 Seyal 1 2.0 4 8.3 27 50.9 32 21.3 Kitir 40 81.7 31 64.5 6 11.3 77 51.3 Talih 0 0.0 0 0.0 9 17.0 9 6.0 Laoat 5 10.2 1 2.1 9 17.0 15 10.0 Total 49 100.0 48 100.0 53 100.0 150 100.0 Chi-square = 0.0001

Conclusions Based on the results of this study, the following conclusions could be drawn: 1. Camels were perceived as the most dependent livestock species on trees and shrubs for forage followed by goats. 2. At present, a considerable deterioration in the condition of tree/shrub cover in terms of both quantity and quality has been perceived as compared to its

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condition in the past. This deterioration has been attributed to many factors; the most important one is rainfall. 3. Rangeland that consists of both trees and herbs has been perceived as the most preferred type of range for livestock. 4. Kitir (A. mellifera) has been perceived as the most preferred browse tree followed by Seyal (A. tortilis) in Butana region. Kitir was perceived as the most preferred browse tree in zones 1 and 2, while Seyal is considered as the most important browse tree in Zone.

Acknowledgement This work was part of the Project “Enhancing Climate Change Adaptation in Agriculture and Water Resources in the Greater Horn of Africa” (ECAW) which was funded by the International Development Research Center (IDRC) Grant No. 106552-003.

References Abdella, N. I. 2008. Browsing and its relation to rangeland management in Sudan’s semi - arid areas. M.Sc. Thesis, Sudan University of science and Technology, Sudan. Abu Sin, M. A. 1970. The regional geography of the Butana north of the railway. M.A. Thesis, University of Khartoum, Sudan. 176 pp. Akhtar, M. 1994. Geo-ecosystem and pastoral degradation in the Butana.Animal Research Development 39:17-26. Elagib, N. A. and Mansell, M. G. 2000. Recent trends and anomalies in mean seasonal and annual temperature over Sudan. J. Arid lands. Elhaj, M. A. 2008. Causes and impact of desertification in the Butana area of Sudan. Ph. D Thesis, University of Free State, South Africa. Elhassan, E. A. M. 1981. The environmental consequences of the open grazing in the central Butana-Sudan. Environmental Monograph Series No. 1., University of Khartoum, Sudan. 76 pp. Harrison, M. N and Jackson, J. K. 1958. Ecological classification of the vegetation of the Sudan. Forests Bulletin No. 2 (New Series). Forests Department, Khartoum. Isamail, I, E. 2009. Adaptation mechanisms in semiarid environments and natural resources degradation in the Butana localatiy-Gedaref State. PhD thesis. University of Khartoum. Lazim, A. M. 2003. Study of some aspects related to browse in Sungir and Wad Bogul forests in Butana area. M.Sc. Thesis, Sudan University of Science and Technology, Sudan. Mohammed, H. A. 2013. Analysis of livestock markets and products for pastoralists depending on natural rangelands. Ph.D. Thesis, Sudan University of Science and Technology, Sudan. Salih, M. A., Sulaiman, H. M., Ismail, I. E., Mohamed, A., El Barbari, S.A. and Adam, I. A. 2011. Study on climate change and its impact on the living mechanism of farmers and pastoralists in Gedaref State. Sudanese Environment Conservation Society (SECS) and Oxfam in collaboration with Gedaref University, Faculty of Social Development Peace and Development Study Centre, Sudan. 23 Copyright © 2015 SAPDH ISSN 1816-8272

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Small Farmers’ Perception on Climate Change Risk at the Blue Nile State, Sudan

Hanadi I. O. Babikir1 and Muna M.M. Ahmed2

Abstract The present study aimed at investigating small farmers’ perception on climate changes impact on natural vegetation and crop production at the Blue Nile state, focusing on two localities (El-Damazine and Al-Tamadon) during the years 2010- 2011. Eleven villages (18655 households) were surveyed. About 97% of the respondents suffered from water scarcity, with 51% stating surface water depletion especially during summer when temperatures were high and rainfall was low. They related problems of water scarcity to population growth and concentration of animals around water points. Over 50% of the interviewed households attributed the decrease in grazing areas and animal death to fluctuations in rainfall, whereas 96% related change in vegetation cover to insufficient rainfall, soil fertility and disappearance of water courses and recurrent droughts. Crop failure was related to rainfall and appearance of weeds (96%). It was concluded that most of small scale farmers are fully aware of climate change impact on vegetation cover and crop production attributable to rainfall fluctuation and soil infertility. Deterioration in water availability and plant cover were also attributed to human effect.

Keywords: Climate change, natural vegetation, water availability, human effect

Introduction Africa is the most vulnerable region to climate change, as a result of low adaptive capacity of the African population (IPCC, 2001). This low capacity is due to the extreme poverty of many Africans, frequent natural disasters such as droughts and floods and agriculture heavily dependent on rainfall. Africa already has a highly variable and unpredictable climate, global warming is making that worse. In the Sahel, there has been on average a percent decrease in annual rainfall over the past 30 years consistent with climate change models (Simms and Reid, 2004). The main impacts of climate change will be on the water resources, food security and agriculture, natural resources management and biodiversity, and human health (Haq et al., 2003). Climate change is expected to affect Sudan’s water resources through reduced groundwater recharge brought about by decreased precipitation and/or increased temperatures and evaporation. Soil moisture is also likely to decline under future climate change. When coupled with increased water consumption, population growth and high rainfall variability, these effects mean that the country could face a serious water crisis (SFNC, 2002; NAPA, 2007). The poorest subsistence farmers will face tough pressures to produce more, under adverse conditions, with limited capital resources (FAO, 2008). At the same time,

1 University of El-Geizera. 2 Institute of environmental studies, University of Khartoum, email: [email protected]. 24 Babikir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 42-32 they will be expected to manage their production in a more environmentally sensitive way. Moreover, it is argued that the value of local knowledge in climate change studies has received little attention. Farmers possess valuable indigenous coping strategies that include early warning systems (Ajibade and Shokemi 2003; Nyong et al., 2007) and recognize and respond to changes in climate parameters (Thomas et al., 2007), for example, by maintaining flexible strategies with short and long cycle crop varieties (Lacy et al., 2006). This study was undertaken with the objectives of investigating small farmers’ perception on climate changes impact on natural vegetation and crop production at the Blue Nile state, focusing on two localities (El-Damazine and Al-Tamadon) during the years 2010-2011.

Materials and Methods Area of the study: The area of study (Map 1) was the Blue Nile state (lat 9o30’- 12o30’N, longitudes 33o 5’-35o 3’E). The State population was estimated at 832,112 (Sudan Population Census, 2008) with an annual growth rate of 3%, average family size of 5 and average population density of 21 people/km². Women represented 47% of the population; age group 6-24 represented 46.4% of the population, making Blue Nile State one of the youngest states in Sudan. About 74.3% of the population lives in rural areas, making a living either as small farmers or as seasonal labour in large mechanized schemes (UN, 2010). Administratively, it is divided into five localities: El-Damazin, Rosaries, Bau, Geissan and Kurmuk. Bowt is a new locality formed in may 2007 out of El- Damazine territory. Its economic activity is based on agriculture and livestock and increasing mineral exploitation (Table 1).

Map (3.1): Selected villages at area of study

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Table 1. Population by location Locality Total population El-Damazine 300,881 Rosaires 345,937 Baw 164,346 Kurmuk 325,189 Geissan 129,384 At-Tadamon 121,201 Total 1,380,937 Source: Directorate of children Immunization, Blue Nile State, polio campaign department, 2009.

Impact of climate change: In previous studies, it was shown that both temperature and rainfall fluctuated through the years 1972-2011 at El-Damazine area. There was a general trend for temperature to increase through these years, whereas rainfall showed a declining pattern. The same observations were obtained for the individual month’s rainfall through the years 1972-2006. Fluctuations in rainfall resulted in disappearance of some grass species and appearance of new ones. Crop production yields (Osman, 2015 in this issue) for sorghum, sesame and groundnut declined with time series (1972-2011). Sampling techniques: The study addressed rainfed farmers at two localities; El- Dmazin and Al-Tamadon, out of the six localities present in the Blue Nile state. They both represent diversification in livelihood pattern. Eleven villages were randomly chosen from each locality where 200 families (a total of 18655 persons) were randomly included into the survey. Households’ selection was done according to the following equation: Total 18655 (X £) 200(Y) 100% and the sample size was determined for each village by population size in line with the following equation:

Where: N = sample size in the village. X = the number of households in the village. Y = the sample size selected. X £ = total number of households in a community sample (Table 2).

Guide interview citizens: A guide basic form was used for interviewing household at selected villages. It was developed over several stages until it reached its final form, which consisted of several closed questions. The form was distributed at the stage of the baseline study following villages identification, to test validity of the questions and to make necessary modifications (Table 3).

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Table 2. Distribution of the sample villages community sample (the Sample size (N) per sample Name of the village number of households) (X) (%) Agadi 1670 18 Goli 2181 23 Buk 1980 21 Bowt 4566 49 Il-serio 1212 13 Ahemermugi 904 10 IL-deesia 570 6 Gounia 732 8 Abu-hassem 817 9 Il-ban-gadeed 164 2 Yarioa 3859 41 Total 18655 200

Table 3. Question distribution according to interview guide citizens Item Item number of questions Percentage (%) General information 8 Main activity 8 17 (3) agriculture and soil 12 26 (4) water source 13 28 (5) vegetation cover 8 17 (6) use of fertilizers 2 4 Total 47 100

Results Respondents’ responses on soil types and water aspects: Soil types reported by the respondents showed most (66.2%) of them thought that the soil is clay. This was expected because the study area falls in the central clay plains. About 32.8% said that the soil is a mixture of sandy and clay while about 5% said that it is sandy soil (Table 4). Most of the respondents expressed that they get water from boreholes (~ 72%), followed by excavated ponds (hafirs) while low lands and others were the least source of water (Table 4). Most of the respondents (~ 97%) feel that they are experiencing water problems (Table 4). Many would fetch water on camels and donkeys (56.3%), others would get water through tankers (23.2), and few would hire cars and lorries (6.3%), other means of getting water represented 14.2% (Table 4). Fetching water was shown by most of the respondents (91.1%) to be on daily basis, very few would fetch water twice a week or on a weekly bases (Table 4). Problems of water were expressed as its scarcity by 51% of the respondents, 38% suffered from long distance to fetch water and 11% suffered from getting unhealthy water (Table 4). About 48% of the respondents attributed the problems of water scarcity to population growth, while 25% ascribed the problem to increase in animal population, 23% attributed them to other causes while very few thought the problems were caused by migration of animal around water points or repetitive drought occurrence (Table 5). Most of the respondents thought that the

Babikir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 42-32 problems of water could be solved by the government (~ 85%) while the rest said it could be solved by the inhabitants or civil organizations in the area (Table 5).

Table 4. Main type of soil in the study area, water sources, water constraints and reasons behind these constraints as reported by respondents Items Frequency Percent Soil types: clay soils 131 66.2 sandy soils 2 0.5 sand clay soils 65 32.8 Others 2 0.5 Total 200 100.0 Water Sources: Boreholes 143 72.3 Excavated ponds (Hafirs) 35 17.4 Seasonal streams (Khors) 8 3.6 Others 14 6.7 Means for water from sources: On camels / donkeys 113 56.3 Tankers 46 23.2 cars and lorries 13 6.3 Others 28 14.2 Total 200 100.0 Frequency of fetching water: Daily 179 91.1 Twice / week 16 7.3 Weekly 5 1.6 Total 200 100.0 Water constraints: Lack of water 102 51 Long distant 76 38 Not healthy 22 11 Total 200 100 Main causes for water scarcity: Increase in population growth 97 48.7 Other reasons 51 25.4 Increase of animals around water centers 23 11.6 migration of animals around water center 1 .5 repetitive drought occurrence 1 .5 Total 200 100.0

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Table 5. Respondents’ opinion (Percent) on water problems and bodies responsible for solving them Items Frequency Percent Water problems: No water problem 5 2.7 Yes there are water problems 195 97.3 Total 200 100.0 Responsibility for solving water problems: Government 171 85.7 Inhabitants 25 12.2 civil organizations 4 2.0 Total 200 100.0

Respondents’ response to rainfall fluctuations: Opinions about rainfall fluctuations that most negatively affected natural resources, showed that most of the respondents (81.6%) expressed that there was negative change and few said that there was a positive change (18.4%) (Table 6). Most of the respondents (97.3%) stated that the worst impact occurred during the year 2009 (Table 6). Fluctuations in rainfall were said to be the main cause for agriculture failure (70.7%) (Table 6); others perceived that the impact had resulted in the decrease of their crop production (27.7%). Very few thought it resulted in death of trees (Table 6). As far as the range condition was concerned, most of the respondents (~70%) thought that fluctuations in rainfall decreased the grazing area, other claimed that it increased animal deaths (~15%) and resulted in decreased animal productivity (~13%) (Table 6).

Table 6. Years of most rainfall fluctuations and their effects on grazing, agriculture and animal performances as reported by respondents Items Frequency Percent Change on natural vegetation: Positive 37 18.4 Negative 163 81.6 Total 200 100.0 Years witnessing fluctuating rainfall 1983 – 1984 3 1.4 2002 3 1.4 2009 194 97.3 Total 200 100.0 Effect of fluctuating rainfall on agriculture Death of trees 3 1.6 Decrease in the crop productions 54 27.7 Failure of agriculture season 143 70.7 Total 200 100.0 Effect of fluctuating rainfall on animal

performance Death of animals 31 15.5 Decrease in animals reproduction 27 13.9 Decrease in grazing area 142 70.6 Total 200 100.0

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Respondents’ opinion to change in vegetation species: Change in vegetation species was stated by 97.8% of respondents whereas 96.6% of the respondents confirmed the appearance of new species (Table 16). About 75% of the respondents attributed the deterioration of vegetation cover to over-cultivation, 13.3% to decrease in rainfall and 11.7% believed that over grazing was the main cause (Table 7). About 96% of the respondents agreed that there was a change in plant cover of the area. Most (~97%) of the respondents agreed that there were appearance and disappearance of some grasses and tree species for the last 20 years. Effect of climate change on natural resources as perceived by the respondents showed that the impact of climate was reflected on fluctuation of rainfall (~ 63%), decrease of soil fertility (~ 21%), very few thought that the impact caused change in vegetation cover, decreasing in soil fertility, disappearance of water courses (Table 7).

Table 7. Respondents reporting change in vegetation cover, causes of deterioration and climate change impact Items Frequency Percent Change in vegetation cover: No 5 2.2 Yes 195 97.8 Total 200 100.0 Appearance of new grass and tree species: No 8 3.4 Yes 192 96.6 Total 200 100.0 Causes of deteriorating vegetation cover Over cultivation 150 75.0 Decrease in rainfall amount 27 13.3 Over grazing 23 11.7 Total 200 100.0 Climate change impact: change in vegetation cover 19 9.5 Change in vegetation cover+ decreasing in soil 9 4.5 fertility. Fluctuation in rainfall 127 63.5 Decrease of soil fertility 43 21.5 Disappearance of water courses 2 1.0 Total 200 100

Discussion Most of the respondents related crop failure to fluctuations in rainfall. This could be related to previous studies which showed that the Blue Nile state have witnessed increases in ambient temperature with declining trend in rainfall. Similarly, some authors (Sivakumar, 1988; Paeth and Hense, 2003; Sultan et al., 2005; Mishra et al., 2008., Wheeler et al. 2005) demonstrated the simulated effect of evenly and unevenly distributed intra-annual rainfall on crop yield, independently of the total annual amount. They showed that plant water

Babikir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 42-32 availability strongly depends on the onset, cessation, and length of the rainy season, with the onset of the rainy season being the most important variable for agricultural management (Stewart, 1991; Ingram et al., 2002; Ziervogel and Calder, 2003). Most of the respondents perceived the causes of water scarcity to be to population growth, increase in animal number around water points, and repetitive drought occurrence. They have also expressed that climate change has negative effects on rainfall and soil fertility. The IPCC (2001) stated that climate variability, inter- seasonal as well as annual, affect water levels in aquifers. Also Changes in temperature and precipitation is associated with global warming that alters recharge to groundwater aquifers, causing shifts in water table levels. Changes in precipitation patterns and amount, and temperature can influence soil water content, run-off and erosion, workability, temperature, salinization, biodiversity, and organic carbon and nitrogen content (van Der Kevie and El-Tom, 2003; Nearing et al., 2003). Most of rural rainfed areas in semiarid tropics are facing general water scarcity. This is coupled by natural resources degradation due to the burgeoning population and the increased exploitation of natural resources (Wani et al., 2009; Rockstr, 2009). It is clearly that people perception of climate change is well defined; people would also point out that the government and NGOs would participate in the mitigation of the negative impacts that climate change imposes on their environments.

References Ajibade, L.T. and Shokemi, O.O. 2003. Indigenous approach to weather forecasting in ASA L.G.A., Kwara State, Nigeria. Indilinga-African Journal of Indigenous Knowledge Systems 2:37–44. Haq, S. R., A.; Konate, M.; Sokona, Y. and Reid, H. 2003. Mainstreaming Adaptation to Climate Change in Last Developed countries (LDCs). Russel Press, Nottingham, UK, IIED, BCAS, ENDA. Drought Monitoring. Agr. Forest Meteorol. 133, 69–88. Ingram , K.T, Roncoli, M.C, , and Kirshen P.H. 2002 .“Reading the Rains: Local Knowledge and Rainfall Forecasting among Farmers of Burkina Faso.” Society and Natural Resources, 15, pp.411-430. IPCC. 2001. Climate Change 2001: Impacts, Adaptation and Vulnerability. Intergovernmental Panel on Climate Change, Report of the Working Group II. Cambridge University Press, Cambridge, UK. Lacy, S., Cleveland D. and Soleri D. 2006. Farmer choice of sorghum varieties in Southern Mali. Human Ecology 34:331–353 NAPA. 2007. National Adaptation Programme of Action. Republic of the Sudan, Ministry of Environment and Physical Development, Higher Council for Environment and Natural Resources, Khartoum. Nearing, M.A., Pruski, F.F. and O’ Neal, M.R. 2003. Expected climate change impacts on soil erosion rates: a review. Journal of Soil Water Conservation 59, 33–50. Nyong A., Adesina F. and Osman Elasha B. 2007. The value of indigenous knowledge in climate change mitigation and adaptation strategies in the

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African Sahel. Mitigation and Adaptation Strategies for Global Change 12:787–797 SFNC. 2002. Sudan’s First National Communication. Higher Council for Environment and Natural Resources (HCENR), Khartoum. Simms, A. M. J. and Reid, H. 2004. Up in Smoke? Threats from, and Responses to, the impact of global warming on human development, IIED. Stewart, J. I. 1991. Climatic Risk in Crop Production: Models and Management for the Semiarid Tropics and Subtropics. CAB International, Wallingford, England, UK, pp. 361–382. Thomas, D., Twyman, C., Osbahr, H. and Hewitson B. 2007. Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa. Climatic Change 83:301–322. van Der Kevie, W. and El-Tom, O. A. M. 2003. Manual for Land Suitability Classification for Agriculture with Particular Reference to Sudan. Ministry of Science and Technology, Agric. Research and technology Corporation. Land and Water Research Center, Wad-Medani, Sudan. Wani, S.P., Sreedevi, T.K. and Rockstr, M. J. 2009. Rainfed Agriculture: Unlocking the Potential, Suhas P Wani (Ed), ICRISAT, India, Johan Rockstr, M. J., SEI, Sweden, and Theib Oweis ISBN-13: 978 1 83593 389 0. Rockstr, M. J. 2009. Rainfed Agriculture: Unlocking the Potential, Suhas P Wani (Ed), ICRISAT, India, Johan Rockstr, M., SEI, Sweden, and Theib Oweis, ISBN-13: 978 1 83593 389 0. Ziervogel, G. and Calder, R. 2003. Climate variability and rural livelihoods: assessing the impact of seasonal climate forecasts in Lesotho. Area 35 (4), 403–417.

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Vulnerability and Potential Adaptation Options of Agricultural Sector to Climate Change in Sudan

Abdelrahman K. Osman1

Abstract Agriculture is the main sector of the Sudan’s economy and it is the major livelihood source for more than 70% of the population. Agriculture has been identified as one of the three highest priority sectors most vulnerable to climate change. Several recent studies have indicated the substantial decline in precipitation and rising in temperature in several parts of the country. Current and potential impacts of climate change include reduction in yields and duration of crop period, increased occurrence of dry spells, warm and too short winter, land degradation, increased water requirements and decrease in water availability, increased occurrence of dust storms and sand blast, and socio economic impacts. The degree of vulnerability differs, with the traditional rainfed farming as the most vulnerable. Within this sector, chronically vulnerable and food insecure States are North Kordofan, Red Sea and Darfur States. All these States are located in the drylands and their populations rely entirely on rainfed agriculture for their livelihoods. Rains amount and distribution in these States are generally becoming inadequate to secure an average to above-average rainfed crop. There are several adaptation measures and promising technologies that the agricultural sector can undertake to alleviate the effects of present and future climate changes. These technologies include early maturing-drought and heat tolerant crop varieties, planting time adjustment, seed priming and micro fertilizing, intercropping, agroforestry and water conservation practices. Dissemination of these technologies should be addressed if the vulnerability of agriculture to climate change has to be minimized.

Keywords: Climate change, vulnerability, drought tolerant, heat resistant, short maturing, drylands

Introduction Agriculture, including both crop and livestock production, is the main sector of the Sudan’s economy. It is the major livelihood source for more than 70% of the population and about 80 percent of the labour force is employed in agriculture and related activities. It contributes about 35% to the GDP and generates around700 million US dollars annually. Sudan’s agriculture has four distinct farming sectors. These are irrigated farming, traditional rain-fed farming, mechanized rainfed farming and livestock production system. The total annual cultivated area in Sudan as estimated by the Food Security Administration of the Federal Ministry of Agriculture and Irrigation is 17 million hectares. The shares of the irrigated, mechanized rain-fed and traditional rain-fed sectors in the total cultivated area are

1 Professor of Agronomy, Water Harvesting Research Institute, Agricultural Research Corporation, E- mail: [email protected]. 33 Osman., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 33-42

12, 35 and 53%, respectively. Main food crops grown are sorghum, wheat and millet, while groundnuts, cotton, sesame and sunflower are the main cash crops. According to Sudan’s First National Communication to the UNFCCC (2003), agriculture has been identified as one of the three highest priority sectors most vulnerable to climate change. The purpose of this paper is to assess the vulnerability and impacts of climate change on Sudan’s agricultural sector and explore the potential adaptation options. The information and data included in this paper was collected and built on agricultural production and productivity data, research results, Higher Council for Environment and Natural Resources and other regional and international reports and studies. Agro-climatic zones Based on rainfall and according to the ratio of humid months to arid months and length of the growing season, Sudan can be divided into five agro-ecological zones i.e. desert, semi- desert, arid, semi-arid and sub-humid. The general characteristics of each zone and the area it occupies are shown in Table 1. Agricultural activities are carried out mainly in arid and semi-arid zones in the north to sub-humid in the south. In the arid and semi-arid (a) zones, the annual rainfall is between 250 and 450 mm and traditional small-holders farming is practiced on typically goz soils or stabilized sand dunes. Gum Arabic tree is the major constituent of the vegetation and most of the gum production belt is located in these zones. In these zones, there is a considerable pressure on natural resources and desertification level is very severe, making the environment very fragile. The annual rainfall in the semi-arid (b) zone is between 450 and 750 mm. Traditional farming is practiced on clay soils, while mechanized agriculture is in the southern part of the central clay plains. This is the most important zone for rain-fed agriculture in the country. The sub-humid zone covers a small part not exceeding 10% of the country’s total area and located in the far south neighbouring the Republic of Southern Sudan borders. Annual rainfall in this zone is more than 750 mm. Agriculture and forestry are the main activities.

Table 1. Agro-climatic zones of Sudan: general characteristics and land area occupying Agro- Annual Humid Growing Area (%) ecological rainfall (mm) Months(#) season length zone (days) Desert <100 ≤1 ≤30 34 Semi-desert 100-250 1-2 30-60 21 Arid 250-350 2-3 60-75 10 Semi-arid(a) 350-450 3-4 75-90 13 Semi-arid(b) 450-750 3-4 90-120 14 Sub-humid ≤750 4-5 ≥120 8 Source: compiled (WSRMP 2007 Diagnostic Survey), ITTA Agro-climatic Humidity Classification.

Recent climatic trends Climate change and variability is becoming a predominant phenomenon in Sudan. One of the most important anticipated effects of climate change is directly related to changes in temperature and rainfall patterns. Several recent studies have 34 Copyright © 2015 SAPDH ISSN 1816-8272

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indicated the substantial decline in precipitation and rising in temperature in several parts of the country, and global warming models predict that this trend will continue. Mohamed (1998) analysed the rainfall records from twelve meteorological stations in the Sudan located between latitudes 11o and 20o. Results showed that there has been a clear decrease in the annual rainfall over the last 30 to 40 years. As shown in Table 2, the annual drop in mean annual rainfall during the study period varied from about 5.0 mm in Damazine to 0.5 mm at Dongola. Additional evidence reported by UNEP (2007) have indicated that there is a long-term trend towards lower rainfall in Darfur (Table 3), while the high rainfall variability (Table 4) as indicated by the coefficient of variation in several parts of the country during the 30 - year period (1978-2007) was reported by Osman and Ali ( 2009). Moreover, Abdalla (2012) compared two mean annual normal rainfall isohyets; namely, the 200 mm and the 500 mm, for 1941-1970 and 1971-2000, and concluded that there is a remarkable shift in the rainfall belt in western Sudan. Analysis of temperature indicated that there is a clear rising in temperature in four stations representing the northern, eastern, western and southern parts of the country. Mohamed (2005) showed that during the previous decades temperature is increasing in several places from decade to decade. In the extreme northern parts, the highest temperatures vary between 46-49oC during May - June and the lowest minimum temperatures in winter vary between 2° - 10°C during December - January. Time series of annual rainfall and mean temperature for the 1941-2000 period were analysed. The anomalies trends of mean annual temperature and rainfall almost show a rise in temperature and a decline in rainfall in most parts of Sudan during the last three decades of the twentieth century (Mohamed, 2005). Droughts are becoming more frequent and severe, and since the early 1970s, the country has been subjected to a series of drought shocks, the most notable are in 1984/85 and 1990.

Table 2. Analysis of rainfall records from twelve meteorological stations in the Sudan Station Latitude Longitude(E) Years of Yearly drop in (N) record rainfall (mm/year) Dongola 19 42 30 31 1952/92 -0.48 Atbra 17 34 33 56 1952/92 -0.56 Shambat 15 37 32 32 1952/92 -4.9 Wad medani 14 25 33 30 1952/92 -4.7 Damazine 11 45 34 13 1952/91 -5.4 Gedarif 14 02 35 24 1952/92 +0.5 Kosti 14 00 30 00 1952/92 -3.03 Obeid 13 30 29 50 1952/92 -5.0 Sennar 13 33 33 37 1952/92 -3.9 Kadugli 11 00 29 43 1952/90 -3.99 Nyala 12 04 24 53 1952/92 -5.12 Source: Mohamed (1998).

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Table 3. Long-term rainfall reduction in Darfur Location Average annual Average annual Reduction Reduction rainfall(mm) rainfall(mm) (mm) (%) 1946-1975 1976-2005 Fashir - North 272.36 178.9 -93.46 -34 Darfur Nyala - South 448.71 376.5 -72.21 -16 Darfur Genana - West 564.20 427.7 -136.5 -24 Darfur Source: Sudan UNEP (2007):post-conflict environmental assessment

Table 4. Minimum, maximum and mean annual rainfall, and coefficient of variation at some locations during the 30 – year period (1978-2007). Location Minimum Maximum Mean Coefficient of variation (%) Gedarif 305.5 846.7 616.8 21.4 Damazine 497.2 1041.7 629.3 19.0 Wad Medani 115.4 673.1 323.4 43.9 Nyala 194.7 1021.3 396.3 39.7 Elfashir 72.7 361.5 198.0 34.7 Elobeid 161.7 581.6 341.6 33.8 Kadugli 463.2 990.8 684.9 19.5 Kosti 96.0 718.2 328.1 35.0 Source: Osman and Ali (2009).

Projected climatic trends (temperature and rainfall patterns) Projections for East Africa (including Sudan) of annual changes in temperature and rainfall that will occur by the end of the 21st century are presented in Table 5. These projections indicated that the median near-surface temperature will increase. However the impact of climate change will vary both in nature and in magnitude from location to location, from crop to crop and from cultivar to cultivar.

Table 5. Predictions for climate change in East Africa by the end of the 21st century. Season Temperature response (◦C) Precipitation response (%) Min 25 50 75 Max Min 25 50 75 Max DJF 2.0 2.6 3.1 3.4 4.2 -3 6 13 16 33 MAM 1.7 2.7 3.2 3.5 4.5 -9 2 6 9 20 JJA 1.6 2.7 3.4 3.6 4.7 -18 -2 4 7 16 SON 1.9 2.6 3.1 3.6 4.3 -10 3 7 13 38 Annual 1.8 1.5 3.2 3.4 4.3 -3 2 7 11 25 Note: DJF = December, January and February; MAM = March, April and May, JJA = June, July and August; SON = September, October and November. Note: Temperature response indicates the projected increase in temperature over current values. Source: IPCC (2007).

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Status of food security and vulnerability assessment The substantial decline in precipitation, rising in temperature and soil degradation are the most important factors causing loss in the potentiality of farming and resulting in low productivity and production and, hence making the great majority of the population vulnerable to food insecurity. Results of the study by Mohamed (2005) indicated that the degree of vulnerability differs from one region to another, with arid and semi-arid regions in the north being more vulnerable to drought than the southern part of the semi-arid and sub- humid regions in the south. As shown in Table 6, the chronically vulnerable and food insecure states are North Kordofan, Red Sea and Darfur States. All these states are located in the dry lands and their populations entirely rely on rainfed agriculture for their livelihoods and there are no irrigation facilities for production of the major food crops. Rains amounts and distribution in these states are generally becoming inadequate to secure an average to above-average rainfed crop. These states can be regarded as the most vulnerable areas to climate change and variability and food insecurity and deserve particular policy attention. Over the last three decades, livelihood systems in these states have been subject to different environmental and socioeconomic challenges. The vulnerability of these areas is often exacerbated by their low levels of preparedness and capacity to undertake adaptation and mitigation measures.

Table 6. Food grains deficit and levels of self-sufficiency (%) in the vulnerable states State Food grains deficit (000 tons) Average level of self- 7002 2008 7009 2010 2011 sufficiency (%) Red Sea 39 101 189 218 148 14 North Kordofan 79 130 275 346 244 53 North Darfur 227 172 233 329 189 28 South Darfur 111 261 211 356 326 62 West Darfur 189 222 144 145 78 41 Source: SIFSIA. 2010

Food security at household level is influenced by social vulnerability factors such as household health, composition, household head (female, child) and availability of labour and social standing in the community. Table 7 summarizes the trends in the food security situation at household level in the different states (SIFSIA. 2010). Food security at household level in the vulnerable and food insecure states i.e. Red Sea, North Darfur, West Darfur and South Darfur states indicated that 31 to 66 percent of the households are in the moderately to severely food insecure category. North Kordofan has a 54 percent of households in the moderately food insecure category and none in the severely food insecure category. Dry lands region is already among the most food insecure in the world, and climate change has the potential to aggravate the problem. In Sudan, the link between climate and livelihood is very strong, as more than 80 per cent of cultivated land is currently under rainfed agriculture and most of the population depends heavily on rain-fed agriculture and, hence, livelihoods are highly vulnerable to climate variability. Recent studies (IFPRI, 2009) indicated that by 37 Copyright © 2015 SAPDH ISSN 1816-8272

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2050 in sub-Saharan Africa food crops yields will decline by up to 22% as a result of climate change. This decline in crops yields will lead to several socio-economic impacts such as more malnutrition, especially of children, increased rural-urban migration, high frequency of resource use conflicts, increased mortality rate and worsening poverty levels. Without adequate climate change mitigation and adaptation, sub-Saharan African countries will suffer food unavailability, increased malnutrition, unemployment and reduced export earnings.

Table 7. Household food security situation in the different states (2010) State Food Moderately food secur Severely food insecure insecure e Sennar 96 4 0 Gedarif 89 11 0 Kassala 86 13 1 Blue Nile 70 18 12 Red Sea 69 28 3 North Darfur 67 29 4 White Nile 66 34 0 South 59 38 3 Kordofan West Darfur 57 38 4 North 46 54 0 Kordofan South Darfur 34 57 9 Source: Crop and Food Security Assessment Mission (2011)

Current and potential impacts of climate change on agriculture and vulnerabilities Climate change is expected to impact agriculture directly by its effects on production and yields, and indirectly by affecting soil fertility, water availability, pests, flood and droughts, and socio economic impacts (policy, market, migrations and conflicts). The most important impacts are: Changes in agricultural productivity Several studies revealed that the changes in temperature and precipitation have resulted in reduced crop yields. Studies carried out by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) on disaggregated effects of climate change on sorghum yields indicated that in West Africa sorghum yield is reduced by 14% as a result of climate change (temperature and precipitation). Aune (2009) reported a reduction in time to maturity and crop yield by 19 and 56 %, respectively, as a result of mean seasonal temperature increase from 27.6 to 32.6 Celsius (Table 8). As the whole of north Sudan exhibits a typical Sahelian zone, reduction in sorghum yields are expected. This was confirmed by UNFCCC (2003) in the projected sorghum and millet yields in Sudan (Fig. 1). The projections indicate that by 2060 production in these regions will be reduced by more than 75%.

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Table 8. The simulated impact of temperature increases on the mean rate of development and yield of sorghum based on historical daily climatic data (1955-1983), Aurangabad, India Climate Mean seasonal Time to % Reduction Crop % scenario temperature maturity from Current yield Reduction (OC) (d) (kg/ha) from Current Current 27.6 105 - 2941 - Current + 1O °C 28.6 100 4.8 2628 10.6 Current + 2O °C 29.6 95 9.5 2264 23.0 Current + 3O °C 30.6 91 13.3 1913 34.9 Current + 4O °C 31.6 88 16.1 1608 45.3 Current + 5O °C 32.6 85 19.0 1285 56.3 Source: Aune (2009)

Source: Sudan first National Communication under UNCCC, 2003)

Fig. 1. Projected millet and sorghum yields with climate change

Length and on-set of the growing season One of the anticipated effects of climate change on agriculture is the length and on-set of the growing season (LGP). The farming systems in Sudan occupy an area with a wide range of growing periods, with 61% of the surface area of the country having LGP shorter than 90 days (Table 9). Results presented in Table 9 show that climate change is likely to reduce the length of growing season in many parts of the country, as well as forcing large areas of marginal agriculture out of production. The surface areas with a short growing period (< 90 days) will increase, while the surface area with a prolonged growing period (> 180 days) will decrease. Most crops attain the highest yields in areas with prolonged LGP, thus a reduction in LGP is likely to have a negative impact on crop production and yields. In Gedarif area, Ahmed (2011) studied climate change impacts on rainfed sorghum production and the length of growing season trends during the last twenty years 1991- 2010. Decreasing trend of sorghum productivity, as well as climate change was evident. The results showed that the length of the growth

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season has no consistent trend, but the average season length during the studied period was shorter than the average of the preceded period, 1961-1990.

Table 9. Average distribution of surface area (%) of Sudan under different classes of lengths of growing periods for the years 2000, 2030 and 2050 Year Surface Length of growing period (days) area (%) 90-120 120-150 150- 180- 210- >250 180 210 250 2000 61 10 11 11 4 2 0 2030 63 11 11 11 5 0 0 2050 64 11 11 10 3 0 0 Source: ASARECA (2011).

Impact on wheat production Wheat plants require and must experience a period of low winter temperature (vernalization) to initiate or accelerate the flowering process and convert to the reproductive stage. Without adequate vernalization, winter wheat plants will remain vegetative or will produce very low grain yield (Hussein et al., 2005). Typical vernalization temperatures are between 5 and 10 °C (40 and 50 °F). In Sudan, temperature has a great impact on wheat production. The crop has to be grown in winter, but the Sudanese winter is too short. Even then, the temperature in most of Sudan is too warm to realize large yields. The growing season of wheat in the Gezira is from mid-October to mid-April, with temperatures shown in Table 10.

Table 10. Wheat growing season temperatures (°C) in the Gezira Temperature Oct. Nov. Dec. Jan. Feb. March April Mean minimum 21.9 18.4 15.3 14.3 15.0 17.8 20.9 Mean 38.6 37.0 34.6 34.1 35.4 38.6 41.2 maximum Mean daily 30.3 27.7 25.0 24.2 25.2 28.2 31.0

Only in December and January, the Gezira's mean daily temperatures are below the tolerance limit for wheat of 25.0°C. In northern Sudan, north of latitude 18.5°N, the mean daily temperatures stay below this limit from November to March but exceed it in October and April. The climate is, therefore, only moderately suitable for irrigated wheat in the north, and only marginally suitable in central Sudan. Warming presents a great challenge to wheat production. Without adequate climate change adaptation, wheat production might become not possible. The effectiveness of adaptations will depend on how well they reduce crop sensitivity to very hot days. Varieties that maximize the period of growth during favourable temperatures while maturing in time to escape excessive heat seem to be the best adaptation option. Conflict over resources UNEP (2007) listed the erosion of natural resources caused by climate change as among the root causes of social strife and conflict. Several studies have shown that decline in rainfall has resulted in scarcity in water and grazing resources, and

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low rangeland productivity. Communities may find themselves in conflict over increasingly scarce food and water supplies. "The scale of historical climate change, as recorded in Northern Darfur, is almost unprecedented: the reduction in rainfall has turned millions of hectares of already marginal semi-desert grazing land into desert. The impact of climate change is considered to be directly related to the conflict in the region, as desertification has added significantly to the stress on the livelihoods of pastoralist societies, forcing them to move south to find pasture," so competition for resources, resulted from environmental degradation, is one of the driving forces and causes for tension and conflicts. Adaptation options for reducing vulnerability There are several adaptation measures and promising technologies (El-Hag and Abdalla, 2011) that the agricultural sector can undertake to alleviate the effects of present and future climate changes. Some of these technologies and their impact on yield are shown in Table 11.

Table 11. Impact of some recommended climate smart technologies on crops yield Current or potential Recommended adaptation Impact (yield impacts of climate options (technologies) Increase (%) change (Climatic risk) . Reduction in duration of Early maturing-drought and 20-55 crop period and diseases tolerant crop increased occurrence of varieties, alternative crops. droughts and dry spells . Increase in temperature Early maturing, heat tolerant 20-28 and winter is too short wheat varieties, planting time adjustment (sowing dates management), agro-forestry. . Early drought and land Seed priming and micro 5-85 degradation fertilizing. . Increased transpiration Water conservation practices 30-60 and water requirements through rainwater harvesting and decrease in water and storage, agroforestry. availability . Erratic rainfall , frequent Intercropping systems (crops 20-25 pest and disease attack arrangement). . Increased occurrence of Agroforestry (Alley- 15-30 dust storms and sand cropping). blast *Collected from various authors cited in the references

Conclusions and recommendations Climate change and variability and its impact in Sudan are going to be one of the major threats to food security. This change is likely to reduce the agricultural output in the long term and increase risk of hunger. The traditional rainfed

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farming is the most vulnerable. There are already some promising technologies to reduce the negative effects of climate change. If the vulnerability of agriculture to climate change has to be minimized, these technologies should be promoted and disseminated through an efficient extension system.

References Abdalla, A. K. 2012. Indicators of climate change in Sudan. Proceedings of the Workshop on: Research and Adaptation to Climate Change in the Drylands of Western Sudan, El-Obeid, North Kordofan State, Sudan (A. K. Osman, ed.). 26 – 27 December 2011. Published by: Higher Council for Environment and Natural Resources. Ahmed, K. E. 2011. Utilization of Crop Simulation Model ˝APSIM˝ in Investigating Climate Change Effects on Sorghum Yield in Gedarif Area. M. Sc. Thesis, Sudan Academy of Sciences. Aune, J. 2009. The eco-farm: an integrated approach for agricultural development in drylands, Presentation for the Eco-farm National workshop, Nazareth, Ethiopia. October 29, 2009. El-Hag, F. M. and Abdalla, E. A. 2011. Technologies and innovations for adaptation to climate change and constraints to scaling-up. Proceedings of the Workshop on: Research and Adaptation to Climate Change in the Drylands of Western Sudan, El-Obeid, North Kordofan State, Sudan (A. K. Osman, Ed.). 26-27 December 2011. Published by: Higher Council for Environment and Natural Resources. Hussein, H. A., Mohamed, H. A. and Ageeb, O. A. A. 2005. Optimum sowing date for wheat (Triticum aestivum L.) in high terrace and alluvial soils of Northern State, ARC. IFPRI. 2009. Climate change: impact on agriculture and costs of adaptation. International Food Policy Research Institute, Nariobi, Kenya. IPCC (Intergovernmental Panel on Climate Change). 2007. Mohamed I. F. 2005. Assessment of the impacts of climate variability and extreme climatic events in Sudan during 1940-2000. Mohamed, H. A. 1998. Rainfall in the Sudan: trend and agricultural implication. Sudan J. Of Agric. Research, 1: 45 - 48. Osman, A. K. and Ali, M. E. K. 2009. Crop production under traditional rain-fed agriculture. A National Symposium on: Sustainable Rain-Fed Agriculture in Sudan. Organized by UNESCO Chair of Desertification Studies, University of Khartoum in collaboration with Desertification and Desert Cultivation Studies Institute. 17 – 18 November 2009, Al-Sharga Hall, University of Khartoum. Sudan's First National Communications under the United Nations Framework Convention on Climate Change. 2003. Ministry of Environment & Physical Development, Higher Council for Environment and Natural Resources. Sudan UNEP. 2007. Post-conflict environmental assessment. SIFSIA. 2010. Food and nutrition assessment in Sudan (Analysis of 2009 National Baseline Household Survey). Sudan integrated food security information for action (SIFSIA). http:/www.fao.org/sudanfoodsecurity.

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Evaluation of Climate Change Effects on the Growing Season in Butana Region and North Kordofan, Sudan

Abdelrahman A. Khatir1, Abdelmalik M. Abdelmalik2, Mawada G. Abdalla3, Sarah A. M. Elmobark2, Imad-eldin A. Babiker2, Sara A. Babiker4 and Faisal M. El-Hag2*

Abstract This study applied remote sensing to evaluate the effects of climate changes on growing season in different agro-ecological zones, in North Kordofan and Butana region, Sudan, for the period 2001-2011. NDVI data were used for the NDVI time series and phenological analysis. Within the semidesert zone in Butana region, the trend for the starting date of the growing season was stable, while that for the end of the season indicated a shift to an earlier date, resulting in shorter growing season (av. 80 days). Minimum NDVI value was 0.13 in 2011 and maximum value was 0.16 in 2010, indicating an increasing trend. In North Kordofan, however, the average length of the growing season was 69 days and the minimum and maximum NDVI (production) value was 0.12 in 2011 and 0.32 in 2009, respectively, indicating a decreasing trend. Within the arid zone in Butana region, the trend for the end of the growing season indicated a shift towards a later date, resulting in more number of days (av. 81 days). Minimum and maximum NDVI (production) value was 0.27 in 2009 and 0.45 in 2003, respectively, indicating a decreasing trend. In North Kordofan, the shortest length of the season was 59 days in 2005 and the longest was 116 days in 2009, reflecting a considerable increase in the length of the growing season. The minimum and maximum NDVI value was 0.23 in 2011 and 0.39 in 2002, respectively, with an average of 0.31, indicating a decreasing trend. Within the semiarid zone in Butana region, the length of the growing season and the NDVI value showed a trend of increase, whereas in North Kordofan, they showed a decreasing trend.

Keywords: Climate Change, Growing season, NDVI, agro-ecological zones, trend

Introduction Between the early 1970s and the mid 1990s, the African Sahel experienced one of the most dramatic long-term changes in climate observed anywhere in the world in the twentieth century, with rainfall declining on average by more than twenty per cent (Hulme et al., 2001). This period of climatic desiccation was associated with a number of very severe droughts, most notably in the early 1970s and 1980s, during which hundreds of thousands of people and millions of animals died (Glantz, 1976). Since the early 1970s, there has been extensive discussion about the causes of the Sahelian desiccation. Early theories such as that of Charney pointed the finger at land degradation and desertification caused by

1 ARC- El Obied Research Station. 2 ARC-Dry land Research Center. *Corresponding author email: [email protected]. 3 University of Zalengi, Central Darfur State, Sudan. 4 Pasture and Forage Research, Agricultral Reseach Corporation, Madani, Sudan. 43 Khatir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 43-55

overgrazing and “inappropriate land use” (Charney et al., 1977). However, while soil erosion and over-exploitation of resources are undoubtedly problems in some areas, the evidence for anthropogenic-driven land degradation leading to drought throughout the Sahelian region is lacking. It is now well established that, rather than being a consequence of the abuse of the land by humans and animals, the late twentieth century Sahelian desiccation was a product of long-term climate variability driven by changes in patterns of global surface temperature. In the Sahel, dry conditions occur during periods when the southern hemisphere and Indian oceans are warmer than the remaining northern hemisphere oceans, and it is a shift to such a pattern of global temperature distributions that is now widely accepted as being responsible for the turn towards aridity in the Sahel from the late 1960s (Giannini et al., 2003). Climate patterns from intra-seasonal to decadal and century scales directly influence the timing, magnitude (productivity) and spatial patterns of vegetation growth cycles, or phenology (Reed et al., 1994; Schwartz, 1994). Satellite and other remote sensing systems can detect vegetation phenology due to the unique seasonal and spectral reflectance and transmittance characteristics of canopy, plants and leaves (Reed et al., 1994). Remotely sensed vegetation phenological data have been used in global climate change studies, showing trends and responses such as earlier start of the growing season, later end of season and higher seasonal productivity (Parmesan and Yohe, 2003) Time-series of vegetation index derived from satellite spectral measurements can be used to gain information on seasonal vegetation development. This information serves as an aid in the analysis of the functional and structural characteristics of the global and regional land cover and adds to our current knowledge of global cycles of energy and matter. Long time-series of vegetation index data can also provide information on shifts in the spatial distribution of bio-climatic zones, indicating variations in large-scale circulation patterns or land-use changes. Although the value of remotely sensed time-series data for monitoring vegetation seasons has been firmly established, only a limited number of methods exist for exploring and extracting seasonality parameters from such data series. For this reason, the TIMWSAT program package was designed to reduce residual atmospheric noise in the time series data, and provides an either user-friendly output in a point-based or image format (Jönsson and Eklundh, 2009). In Butana region and North Kordofan State, rainfall is limited to the months of July - October and ranges between 100 in the north to 400 mm in the south and is brought by the moist south westerly winds that follow the movement of the inter-tropical convergence zone (ITCZ) to the north, with the amount diminishing northwards. Rainfall variability increases from south to north from 15% in the south to 40% in the northern parts, subjecting the two sites to adverse climate changes (Fadlalla, 2006). Climate change is one of the main drivers of the interannual variation in vegetation activity (Zhou et al., 2001; Schimel et al., 2001). Investigations of the correlation between normalized difference vegetation index (NDVI) and climate factors aid in ﬁnding key factors that control changes in the terrestrial ecosystem carbon cycle and shed light on the mechanisms controlling the response of terrestrial carbon storage to climate variability (Braswell et al., 1997). Copyright © 2015 SAPDH 44 ISSN 1816-8272

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The objective of this study was to apply remote sensing methodology to evaluate the effects of climate changes on growing season in different agro-ecological zones in North Kordofan and Butana region, Sudan.

Materials and Methods Study Area: The study area comprised two locations (Fig. 1); the Butana region in Eastern Sudan and North Kordofan State in western Sudan. Butana region is a flat plain traversed with a series of low mountains, hills and wadies. It is located in the centre of the north-eastern part of Sudan extending between latitude 14o33’ and 16o22’N and longitude 33○33’ and 35○33’E. The region covers an area of approximately 120,000 km2, representing more than one third of the area of Eastern Sudan and 6% of the total area of the country. The Butana region is making a rectangular shape surrounded by River Atbara from the northeast, River Nile from the Northwest, Blue Nile from the Southwest and Gedarif-Kassala Road from southeast. Approximately 800,000 persons inhabit the region, mostly pastoral and agro-pastoral camel-owning tribes with agro-pastoralists practicing rainfed agriculture. The Butana region was for many centuries constituting one socio-economic and political unit. It falls currently in ten administrative localities within the five states of Khartoum, Gedarif, River Nile, Gezira and Kassala (BIRDP, 2011). North Kordofan State is located between latitudes 11o15’ and 16o45’N and longitudes 27o05’ to 32o0’E. It covers an area of about 245,000 km2, representing two third of Kordofan region. It is divided into nine localities. It has a total population of about 2.3 million comprising 70% of the population of Kordofan region (DLRC, 2007).

Fig. 1. Location map

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Climate: Rainfall is the most important climatic factor influencing livelihoods in the study area. Annual rainfall ranges from less than 100 mm in the northern border to more than 500 mm in the southern border. The length of the rainy season varies from about one month or less in the north to about four months in the south. Rains occur between July-October with the peak in August. Within and between seasons, variation in rainfall amount and distribution are common. Overall, a trend of long-term decline in rainfall has been observed over the entire region (Fig. 2). The average daily temperature ranges between 10-40oC, with an annual variation of 15oC. April, May and June are the hottest months of the year, while December, January and February are the coolest ones. Wind direction differs according to season; northeast in winter and south-west in summer.

Fig 2. Rainfall distribution

Soils: The Butana is a flat plain where the cracking clays are the dominant soil type intercepted by silt depressions deposited by seasonal wadies that constitute an important cultivable land. The clay soils are dark, cracking vertisols, and low in nitrogen and phosphorus. Other soil types within the plain are aridisols and alfisols. Soils in North Kordofan range from sandy in the north to heavy cracking clay in the south. The sandy soils cover an area of about 60% of the cultivable area, while the clay and sandy clay soils cover only 30%. The sandy soil is stabilized sand dunes locally known as "goz". These soils are very deep, coarse to fine sand, with low organic matter. The clay soils are dark, cracking vertisols, and low in nitrogen and phosphorus. Interspaced silt depressions and gardud soils are prevalent in the area and cover about 10% of the total cultivable land (Fig. 3).

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Fig. 3. Soil map

Vegetation: Butana region has diverse vegetation resulting from the variability in rainfall. The predominant tree species are: Acacia mellifera (Kitir), Acacia tortilis subsp. tortilis (Samur) and subsp. raddiana (Sayal), Acacia nubica (Laout), and some pockets of Acacia seyal (Talih) and Balanites aegyptiaca (Higlig). The most common annual grasses and herbs are: Sehima ischaemoides (Dambalab), Schoenefeldia gracilis (Gabash), Blepharis edulis (Siha), Ipomoea cardiosepla (Tabar), Aristida spp. and Cymbopogon nervatus (Nal). North Kordofan is generally covered with low desert and semi-desert scrub. The central sandy soils are covered with Acacia senegal savannah. Traditionally, the area is known for production of gum Arabic. The clay soils in the south are covered with broad-leaved savannah woodland, A. seyal and B. aegyptiaca. Agro-ecological Zones: Based on average annual rainfall, potential evapo-transpiration and according to the ratio of humid months to arid months and length of the growing season, the study area may be broadly divided into three agro-ecological zones (Fig. 4). These zones are semi- desert, arid and Semi-arid. This division is based on current rainfall isohyets. Characteristics of the agro-climatic zones are: (a) Semi-desert Zone: Rainfall ranges from 100 to 200 mm/year, with duration of the growing season from 30 to less than 60 days. This short growing season and the low unreliable rainfall in this zone are major risks to agricultural production. However, in the centre and the southern part of

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this zone wadies cultivation is extensively practiced. Irrigated agriculture is practiced along the Nile. (b) Arid Zone: Rainfall ranges from 200 to 350 mm/year, with duration of the growing season from 60 to less than 90 days. The erratic nature of the rainfall and the short duration of the season make crop production extremely risky. Climatically, the area is more suitable for production of livestock than for cultivation of crops. It can be important source for grazing and browse for pastoral and agro-pastoral herds of camels, sheep and goats. (c) Semi-arid zone: Rainfall varies from 350 to 750 mm/year, with growing season duration of 90 to less than 120 days. The cultivated crops depend upon the erratic and variable rains. Introduction of drought resistant varieties of crops, efficient use of soil moisture and application of fertilizers are important to improve production.

Fig. 4. Agro-ecological zones

MODIS NDVI Time Series: NDVI data at 250 m resolution and 16-day composite intervals, acquired by MODIS on the Terra platform (MOD13Q1), were used for the NDVI time series and phenological analysis. Both the MODIS NDVI data and associated quality assurance (QA) data, [36, 45] were used. This resulted in 23 composite NDVI images (periods) per year, providing a total time series of about 161 NDVI/QA images. The MODIS NDVI images were re- projected into a WGS_1984_UTM_Zone_36N projection, which is suitable for analysis. For each of the selected homogeneous sites, we extracted MODIS NDVI

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time series data from the 12th period of 2000 through the 11th period of 2012. Seasonal phenological metrics were then extracted for the same period. These data provided the basis for examining the trends, seasonality and anomalies in NDVI and the associated phenology metrics for the different agro-ecological zones in the study area. Derivation of Phenological Metrics: Since time series of NDVI are a proxy for recurring vegetation activity at the land surface, MODIS NDVI based phonological metrics were calculated seasonally to characterize the phenology of different vegetation type in the study area. Phenometrics for selected site were derived by applying a local second order polynomial fitting function known as an adaptive Savitsky-Golay filter (Jonsson and Eklundh, 2009). This filter is the most consistent at maintaining unique vegetation time series fits, while accounting for atmospheric effects like clouds. The phenometrics for each growing season are depicted in Fig. 5.

Fig. 5. The points (a) and (b) mark the start and end of the season, respectively. Points (c) and (d) give the 80 % levels. Point (e) displays the largest value. Point (f) displays the seasonal amplitude and point (g) the seasonal length. Finally, (h) and (i) are integrals showing the cumulative effect of vegetation during the season (Jönsson and Eklundh, 2009).

Results Semidesert agroecological zone: In Butana region, the earliest and latest starting date for the growing season was on 18 July 2003 and 31 July 2008, respectively, and the average starting date is 27 July. Trend in starting date was stable. Earliest date for the end of the season was on 3 October 2003, while the latest date was on 5 November 2008. Average date for the end of the season is 6 September. The trend for the end of the season indicates a shift

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towards an earlier date, which would result in shorter days. Shortest season length was 70 days in 2011 and the longest was 90 days in 2004, with an average of 80 days. Trend in season length indicated that the number of days would be shorter. Minimum NDVI (production) value was 0.13 (2011), maximum value was 0.16 (2010) and average value is 0.15. Trend indicates that NDVI value is increasing (Fig. 6a and Fig.7a). In North Kordofan, the earliest and latest starting date for the growing season was on 8 July 2006 and 25 August 2001, respectively, and the average starting date is 29 July. The trend indicated that the start of the season is shifting to earlier dates. Earliest date for the end f the season was 19 September 2009, while the latest date was 4 November 2001. Average date for the end of the season was 5 October. The trend indicated that the end of the season is shifting to earlier dates. The shortest season length was 55 days in 2004, while the longest was 85 days in 2006, and the average season length was 69 days. Trend in season length indicated a slight increase in number of days. Minimum NDVI (production) value was 0.12 in 2011, while maximum value was 0.32 in 2009, and the average value is 0.24, indicating a decreasing trend in NDVI value (Fig. 6b and Fig.7b). Arid agroecological zone: In Butana, the earliest starting date for the growing season was 3 July in 2009, while the latest starting date was 12 August in 2006, with an average at 21 July. Trend in starting date was stable. Earliest date for the end of the season was 26 September in 2007, while the latest date for the end of the season was 4 November in 2001, with an average at 17 October, indicating that the season ends in later dates, which would result in more number of days. Shortest season length was 71 days in 2002, while the longest season length was 96 days in 2009, with an average of 81 days, indicating an increasing trend in numbers of days. Minimum NDVI value was 0.27 in 2009, while the maximum NDVI value was 0.45 in 2003, with an average of 0.37, reflecting a decreasing trend in NDVI value (Fig. 8a and Fig. 9a). a. Butana Area b. North Kordofan

Direction of trend Fig. 6. Direction of trend in timing of start and end of growing season in the semidesert zone

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a. Butana Area b. North Kordofan

Fig. 7. Direction of trend in season length and maximum NDVI values in the semidesert zone

In North Kordofan, the earliest and latest starting date for the growing season was 10 July in 2007 and 12 August in 2008, respectively, with an average at 24 July. The trend in starting date is stable. The respective earliest and latest date for the end of the season was 19 September in 2002 and 24 November in 2003, with an average at 11 October. The trend of the end of the season indicated a slight shift towards an earlier date. Shortest season length was 59 days in 2005, while the longest was 116 days in 2009, with an average of 69 days. Trend in season length indicated that there was considerable increase in number of days. Minimum NDVI (production) value was 0.23 in 2011, while maximum value was 0.39 in 2002, with an average value of 0.31, indicating a decreasing trend (Fig. 8b and Fig. 9b). a. Butana Area b. North Kordofan

Fig. 8. Direction of trend in timing of start and end of growing season in the arid zone

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a. Butana Area b. North Kordofan

Fig. 9. Direction of trend in season length and maximum NDVI values in the arid zone

Semiarid agroecological zone: In Butana, the earliest and latest starting date for the growing season was 6 July in 2007 and 12 August in 2008, respectively, with an average at 19 July, indicating a slight shift in trend to earlier dates. The respective earliest and latest date for the end of the season was 11 September in 2007 and 3 November in 2009, with an average at 17 October, reflecting a shift towards later dates. Shortest season length was 76 days in 2003, while the longest was 96 days in 2005, with an average of 81 days, showing an increasing trend. Minimum NDVI (production) value was 0.26 in 2009, while the maximum value was 0.49 in 2003, with an average of 0.32. The NDVI value showed a trend of a slight increase (Fig. 10a and Fig. 11a). In North Kordofan, the earliest and latest starting date for the growing season was 8 July in 2007 and 12 August in 2001, with an average at 24 July. The trend indicated a shift towards an earlier date. The respective earliest and latest date for the end of the season was 26 September in 2012 and 19 December in 2003, with an average at 27 October, reflecting a drastic shift to earlier dates resulting in shorter season length. Shortest season length was 90 days in 2010, while the longest was 130 days in 2007, with an average of 69 days, showing a decreasing trend in season length. Minimum NDVI (production) value was 0.34 in 2011, while the maximum value was 0.45 in 2002, with an average of 0.31, reflecting a decreasing trend (Fig. 10b and Fig.11b).

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a. Butana Area b. North Kordofan

Direction of trend Fig. 10. Direction of trend in timing of start and end of growing season in the semiarid zone

a. Butana Area b. North Kordofan

Direction of trend Fig. 11. Direction of trend in season length and maximum NDVI values in the semiarid zone Discussion Climate patterns directly influence the timing, magnitude (productivity) and spatial patterns of vegetation growth cycles or phenology (Reed et al., 1994; Schwartz, 1994). Fadlalla (2006) postulated that the Butana region and North Kordofan have been subjected to climatic changes. In the semidesert zone, the starting dates for the growing season in Butana region were stable, while those in North Kordofan showed great variations (Fig. 6 and Fig.7). Variations in the dates for the end of the growing season at both sites were observed. The trend for an earlier start and end of the growing season was much observed in North Kordofan than in Butana area. Zhou et al. (2001) and Schimel et al. (2001) ascribed interannual variations in vegetation activity to climate change. The NDVI value in Butana area showed a trend of increase, whereas in North Kordofan it showed a decreasing trend (Fig. 7). In the Arid zone, the starting dates for the growing season in both Butana area and North Kordofan were stable. The end of the growing season in North Kordofan

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was more stable than that in Butana where it showed a tendency towards later dates (Fig. 8). The NDVI values showed a decreasing trend at both sites (Fig. 9). In the semiarid zone, the behavior of the start and end of the growing season (Fig. 10) was similar to that of the arid zone; being stable in Butana region and with a downward trend in North Kordofan resulting in shorter season length in that site. NDVI values were stable in Butana area and increasing in North Kordofan (Fig. 11). NDVI and climate factors aid in ﬁnding key factors that control changes in the terrestrial ecosystem and shed light on the mechanisms controlling the response to climate variability (Braswell et al., 1997). Many studies have used models that include dynamic representations of vegetation and land-atmosphere interactions (Claussen et al., 2003; Liu et al., 2002). These new modelling studies increasingly suggest a “greening” of the Sahel and parts of the Sahara in response to anthropogenic-driven climate change. Claussen et al. (2003) reported a potential increase of vegetation cover of up to 10% of the Saharan land area per decade due to increased CO2 concentrations, triggering increased rainfall, sustained through vegetation-atmosphere feedbacks. Other modelling studies suggest that the Saharan climatic zone will shift north, resulting in increasingly humid conditions in the Sahel and southern Sahara (Liu et al., 2002). Global warming would cause an expansion of the world's deserts (Braswell et al., 1997), but now some scientists are predicting a contrary scenario in which water and life slowly reclaim these arid places (Giannini et al., 2003). The evidence is limited and definitive conclusions are impossible to reach but recent satellite pictures of North Africa seem to show areas of the Sahara in retreat, which could be attributed to an increase in rainfall (Yahya, 2009).

References BIRDP. 2011. BIRDP (Butana Integrated Rural Development Project) Results and Impact Management System (RIMS), Baseline RIMS Survey, SUDAN. Submitted By El-Zanaty & Associates Braswell, B. H., Schimel, D. S., Linder, E., Moore, B. 1997. The response of global terrestrial ecosystems to interannual temperature variability. Science (238): 870–872. Charney, J., Quirk, W. J., Chow, S. H. and Kornfield, J. 1977. A comparative study of the effects of albedo change on drought in semi-arid regions. Journal of the Atmospheric Sciences 34 (9): 1366-1386. Claussen, M., Brovkin, V, Ganopolski, A. 2003. Climate change in northern Africa: The past is not the future. Climatic Change 57 (1-2): 99-118. DLRC. 2007. Dry land Research Center, Agricultural Research Corporation, Diagnostic Survey of Greater Kordofan. Final report submitted to Western Sudan Resources Management Program (WSRMP). Fadlalla, B. 2006. Capability assessment survey of rural communities in the Copyright © 2015 SAPDH 54 ISSN 1816-8272

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Butana area, Draft Report, 23 March 2006, IFAD. Giannini, A., Saravanan, R. and Chang, P. 2003. Oceanic forcing of Sahel rainfall on interannual to interdecadal timescales. Science (302): 1027-1030. Glantz, M. (Ed.) 1976. The Politics of Natural Disaster. Praeger Publishers. Hulme, M., Doherty, R., Ngara, T., New, M. and Lister, D. 2001. African climate change: 1900-2100. Climate Research (17): 145-168. Jönsson, P. and Eklundh, L. 2009. TIMESAT–a program for analyzing time- series of satellite sensor data. Comput. Geosci. (30): 833-845. Liu, P., Meehl, G. A. and Wu, G. X. 2002. Multi-model trends in the Sahara induced by increasing CO2. Geophysical Research Letters (4): 1881. Parmesan, C. and Yohe, G. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature (421): 37- 42. Reed, B. C., Brown, J. F., Vanderzee, D., Loveland, T. R., Merchant, J. W. and Ohlen, D. O. 1994. Measuring phenological variability from satellite imagery. J. Veg. Sci. (5): 703-714. Schimel, D. S., House, J. I. and Hibbard, K. A. 2001. Recent patterns and mechanism of carbon exchange by terrestrial ecosystems. Nature (414): 169 – 172. Schwartz, M. D. 1994. Monitoring global change with phenology: the case of the spring green wave. Int. J. Biometeorol. (38): 18 - 22. Yahya, A. 2009. BBC, World Service, http://news.bbc.co.uk/go/pr/fr/- /2/hi/africa/8150415.stm, Published: 2009/07/16 10:45:21 GMT, © BBC Zhou, L. M., Tucker, C. J., Kaufmann, R. K., Slayback, D., Shabanov, N. V. and Myneni, R. B. 2001. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research 106 (D17): 20069–20083.

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Changing Climate and Farming Productivity in the Drylands of Eastern Sudan

Imad-eldin A. Ali Babiker1, Faisal A. M. El-Hag1, Ahmed M Abdelkarim2 and Abdalla Khyar Abdalla2

Abstract This study analyzed and discussed the impacts of changes in incidence frequencies in rainfall and temperature on the productivity of dryland farming systems in Gadaref State, Sudan, during two periods (1943-1978 and 1979-2009). The results indicated an increase in the frequencies of maximum temperatures recorded within the ranges in the upper 30 and 40oC during the period 1979-2009. In contrast, recorded incidences of the maximum temperatures within the ranges in lower 30 and upper 20oC increased throughout the period 1943-1978. The same period 1943-1978 had more incidences of 20oC than those of the period 1979- 2009. Recent years have hotter days and warmer nights than earlier ones. The occurrence of showers in the range 15-40 mm decreased in recent years, while those equal or less than 5 mm increased, especially in the months of August and September. There was a steady decline in the yields of crops per unit area, accompanied by a steady increase in the total grown area.

Keywords: temperature frequency, rainfall frequency, sorghum, sesame

Introduction Africa is the most vulnerable to climate variability and change. The Sub-Saharan semi-arid zone in Africa, with annual rainfall varying from 100–200 mm in the North to 600–700 mm in the South (Nicholson, 1978), has a long history of climatic drought stress events. Droughts are understood as part of the normal climatic pattern in arid and semi-arid regions (Glantz, 1987). The irregular alternating patterns of wet and dry periods in the semi-arid zone on annual and decadal timescales are typical indicators for high climate variability. In this context, the droughts that affected the Sahel in the late 1960s through the 1980s and resulted in devastating famines, particularly during the 1970s, were extraordinary in the region in this century (Hulme, 2001). Extended dry spells and hot spells may be more prevalent in this region under climate change, putting rainfed agriculture systems at risk (Huntingford et al. 2005). However, some researchers showed that the climate of this region in late 1990s and early this century seems to have recovered (Brooks, 2004; Nicholson, 2005). Along this prospective, the scientists and practitioners always raise the question to what extend the climate is changing and how severe its impacts on the agricultural systems (Eltayeb, 1985). This study presented the changes in temperature and rainfall incidence frequencies and its impacts on the productivity of rainfed agriculture system in Gedarif state area, eastern Sudan.

1 Dry Land Research Center (DLRC) Agricultural Research Corporation (ARC)-Sudan, email: [email protected]. 2 Sudan Meteorological Authority. 56 Ali Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 56-61

Methodology Study area: Gedarif State is located in the eastern part of the Sudan (Fig. 1). It lies between longitudes 33-36oE and latitudes 14-16oN with an area of approximately 78,000 km2. According to 1993 population census data, about one million inhabitants live in Gadarif State. About 90% population of Gedarif are farmer. The average population density was estimated at 10 people per square kilometer. Based on rainfall amount and main agricultural characteristics the area is divided into three main agro-ecological zones. The southern zone with highest rainfall ranging from 600 to 900 mm, the central zone with medium rainfall about 500-600 mm, and northern zone with very littlerain fall <500 mm. The Gedarif produces 17 and 30% of total sesame and sorghum production in Sudan, respectively, with significant impact on the food security of the country.

Fig. 1: Location of Study area (Gedarif State).

Data and Analysis: Four months, June, July, August, and September (JJAS) daily maximum, minimum temperatures and rainfall data for Gedarif State was obtained from SMA (the Sudan Meteorological Authority) for the period 1943 to 2009. The missing data in the data set were checked and Hennessy et al. (1999) assumption was considered to accept any particular year if it had less than 10% of days missing and less than five consecutive days missing. Missing daily data in the present study were found in June and September 1952 for the maximum temperature and in June 1996 for the minimum temperature, which is around 2.8% for each individual month in the data set. A simple statistical frequency analysis was performed for the temperatures and rainfall data sets. The data records were treated into 3 sets: the whole period 1943 to 2009 as a base line, from 1943 to 1978, and from 1979 to 2009. The average, lowest and the highest value ever recorded in the data sets, were calculated for the 3 sets for comparison. The software used for this analysis was Microsoft Excel.

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Results and Discussion Fig. 2 shows the differences between frequencies of temperature incidences recorded for the two data sets (1943-1978 and 1979-2009). The frequencies differences were calculated by subtracting the frequencies of the period 1943- 1978 from those of the period 1979-2009 at the same range of temperature. The results indicated an increase in the frequencies of maximum temperatures recorded within the ranges in the upper 30s and 40soC (Figure 2-A) during the period 1979-2009. In contrast, recorded incidences of the minimum temperatures within the ranges in lower 30s and upper 20soC increased throughout the period 1943-1978 (Figure 2-B). The same period 1943-1978 had more incidences of 20soC than those of the period 1979-2009. These results clearly indicated that the recent years have hotter days and warmer nights than those of the earlier years.

Fig. 2: Differences of daily temperature frequency incidences in the period 1979- 2009 minus those in the period 1943-1978. (A) Maximum and (B) Minimum.

Rainfall frequencies were treated similarly for the two sets of the years (1943- 1978 and 1979-2009). The occurrence of showers equal or less than 5 mm increased in the recent period (1979-2009), especially in the months of August and September (Fig. 3). The analysis showed that the most frequent rainfalls in June-July-August-September season were in the range 15-40 mm. However, the incidences in this range clearly showed a decrease in the recent period (1979- 2009). Due to the nature of the vertisols (heavy clay) in Gedarif area, too little (less than 10 mm) or too much (more than 60 mm) rainfall in a short storm are not favored. Too little rainfall is not enough to fill the cracks of the dry vertisols (Bronswijk, 1988) or to meet the demand of the crops under the semi aridhot conditions. On the other hand, too much rainfall in one storm would cause a runoff and waterlogging; both would results in crop damage in the field. Moreover, it is important the sensitivity of crops to drought and periods of heat

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stress at particular stages of development. This should rise an imperative question for research on the thresholds above which crops become highly vulnerable to climate and weather (Challinor et al., 2005; Porter and Semenov, 2005).

Fig. 3: Differences of daily rainfall frequency incidences in the period 1979- 2009 minus those in the period 1943-1978.

Crop production is predicted to decline across the tropics and subtropics even under moderate climate change (Fischer et al. 2005; Parry et al., 2005). This is in agreement with the yields of rainfed crop production in the Gedarif area. Figure 4 shows a steady decline in the yields of the crops per unit area, while a steady increase in the total grown area. The compensation measure for the decreasing productivity is to increase the cultivated area. Climate variability plays an important role in determining productivity in the semiarid rainfed agriculture. However, management, farming and agronomic practices have a remarkable function in the productivity of the rainfed agriculture (Farah et al. 1996). Another serious point to raise is that the increase in the cultivated land would be at the expenses of the forestland (Ali-Babiker and Bongo, 2009). This support the emerging evidences that major land use changes have already had detrimental effects on the local climate (Betts, 2005). To improve crop-climate prediction, more attentions need to be given to sub-seasonal effects of variability in climate and the impacts of weather thresholds on rainfed agriculture; both factors are likely to result in further reduction in crop yields. Moreover, the research and scientific community should pay special attentiveness to press forward on research for climate smart farming management practices and climate smart technologies.

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Fig. 4: Productivity (A) and total area (B) of sorghum and sesame in Gedarif area during the period 1979-2009.

In conclusion, this study showed that climate change was evidenced through the increase of high temperature incidences in Gedarif area and the clear reduction in the incidences of the optimum rainfall storms during the June-July-August- September rainy season. Decisions for climate smart farming practices and technologies are deemed necessary to offset the negative impacts of the climate change on the productivity of dry rainfed farming under semiarid conditions.

References Ali-Babiker, I. A. and Bongo, A. 2009. Agroforestry a Sustainable Way to Adapt To Climate Change. In: The Role of Scientific Research in Agricultural Development. The 9th Scientific Conference, National Center for Research. Friendship Hall, Khartoum. 22-24 December 2009. Betts, R. 2005 Integrated approaches to climate-crop modeling: needs and challenges. Phil. Trans. R. Soc. B360, 2049-2065. (doi: 10.1098 /rstb .2005.1739.)

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Bronswijk, J.J.B. 1988. Modeling of water balance, cracking and subsidence of clay soils Journal of Hydrology Volume 97, Issues 3-4, 15 February 1988, Pages 199-212 Brooks, N., 2004. Drought in the African Sahel: long term perspectives and future prospects. Working Paper 61, Tyndall Centre for Climate Change Research, Norwich, UK. Challinor, A. J., Wheeler, T. R., Slingo, J. M. and Hemming, D. 2005. Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates. Phil. Trans. R. Soc. B360, 2085-2094. (doi:10.1098/rstb.2005.1740.) Eltayeb, G. E. (ed.) 1985. Environmental management in the Sudan: Gedarif district study area. Institute of Environmental Studies, University of Khartoum, Sudan. 201 p. Farah, S. M., I. A. Ali and S. Inanaga. 1996. The role of climate and cultural practices on land degradation and desertification with reference to rainfed agriculture in the Sudan. Fifth International Conference on Desert Development: The Endless Frontier. August 12-17, 1996 .Texas Tech University, Texas, USA. Fischer, G., Shah, M., Tubiello, F. N. and van Velhuizen, H. 2005. Socio- economic and climate change impacts on agriculture: an integrated assessment, 1990-2080. Phil. Trans. R. Soc. B 360, 2067-2083. (doi:10.1098/rstb.2005.1744.) Glantz, M.H., 1987. Drought and economic development in sub-Saharan Africa. In: Glantz, M.H. (Ed.), Drought and Hunger in Africa: Denying Famine a Future. Cambridge University Press, Cambridge. Hennessy, K.J., Suppiah R., Page C. M. 1999. Australia rainfall changes, 1910– 1995. Aust Meteorol Mag 48:1–13 Hulme, M., 2001. Climatic perspectives on Sahelian desiccation. 1973–1998. Global Environmental Change 11, 19–29. Huntingford, C., Lambert, F. H., Gash, J. H. C., Taylor, C. M. and Challinor, A. J. 2005 Aspects of climate change prediction relevant to crop productivity. Phil. Trans. R. Soc. B 360, 1999-2009. (doi:10.1098/rstb.2005.1748.) Nicholson, S., 1978. Climatic variations in the Sahel and other African regions during the past five centuries. Journal of Arid Environments 1, 3–24. Nicholson, S., 2005. On the question of ‘‘recovery’’ of the rains in the West African Sahel. Journal of Arid Environments 63, 615–641. Parry, M., Rosenzweig, C. and Livermore, M. 2005 Climate change, global food supply and risk of hunger. Phil. Trans. R. Soc. B 360, 2125-2138. (doi:10.1098/rstb.2005.1751.) Porter, J. R. and Semenov, M. A. 2005. Crop responses to climatic variation. Phil. Trans. R. Soc. B 360, 2021-2035. (doi: 10.1098/rstb.2005.1752.

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Impact Assessment of Climate Change on the Livelihoods of Pastoral Communities in Sudan’ Butana Region: A Multidimensional Tradeoff Analysis

Abdelhamed M. Magboul1, Abbas E. M. Elamin1*, Imad-eldin A. Ali-Babiker2, Abdelmotalib A. Ibnoaf3 and Faisal M. El-Hag2

Abstract This study aimed at assessing the impact of climate change on the livelihoods of pastoral communities in Sudan’ Butana Region. Emphasis was put on the forecasted climate factors such as annual rainfall, minimum and maximum monthly temperatures and their impacts on the grazing system, milk productivity and livelihoods. Three States; Gadarif, Gezira and Khartoum states, out of five states constituting Butana region were chosen. A comprehensive questionnaire and farm survey were conducted in 2013. About 203 pastoralists’ households, 100 from Gadarif, 53 from Gezira and 50 from Khartoum were chosen and interviewed. Simple and multiple linear regression was used to assess the impact of the climate factors on milk productivity. The forecasted value of milk productivity in 2030 was used as a livestock productivity parameter in Tradeoff Analysis model for Multi-Dimensional Impact Assessment (TOA-MD) to assess the impacts of climate change on the livelihoods of pastoral communities. Results showed that Gezira State was mostly suffering from climate variability and change, as reflected in significant increases in minimum and maximum monthly temperatures and significant decrease in annual rainfall. This negatively affected rangelands productivity, grazing systems, with significant reduction in animal productivity. Monthly minimum and maximum temperatures had the highest effect on milk productivity than that of annual rainfall. The Gedarif expansion in Butana was considered as the part mostly suffering from high losses in forecasted milk productivity by 2030 accompanied by high losses in forecasted pastoralist’ income. It was recommended that urgent intervention to rehabilitate rangelands, encourage pastoralist to change their herd structure into productive stock and keep sheep or goats in the herd composition should be advocated.

Keywards: Climate Change, Multidimensional Tradeoff, Pastoral, livelihoods.

Introduction Livestock production is an important component in the Sudanese economy. Animal wealth was responsible for 19.3% of the GDP and over 80% of rural households in Sudan depend on both pastoral and agricultural activities for their livelihoods (MFNE, 2005). Sudan ranks top in terms of livestock population in the Arab World and comes second to Ethiopia among the African countries. Livestock population was estimated at about 103 million heads (Osman et al.,

1 Planning, Monitoring and Evaluation, Agricultural Research Corporation (ARC), Wad Medani, Sudan, *Corresponding Author email: [email protected]. 2 Dryland Research Centre (DLRC), Agricultural Research Corporation (ARC), Soba, Khartoum, Sudan. 3 Faculty of Commerce, Economics and Social Studies, Al Neelain University, Khartoum, Sudan. 6 2 Magboul et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 62-73

2012). Those include 39, 30, 29 and 4 million heads of sheep, goats, cattle and camels, respectively (MAF, 2011). Within the geographical distribution of total livestock in the country 7.2, 5.3, 4.7, 2.3 and 1.3 million are found in the Gezira, Kassala, Gadarif, Nile River and Khartoum states, respectively. These five states sharing the Butana region contribute about 20.7 million heads (about 20% of the total animals in the country, Table 1). In addition, Butana region hosts approximately 8.2 million heads of livestock during the rainy season.

Table 1: Total Livestock populations (million heads) in the states sharing the Butana region State Cattle Sheep Goats Camels Totals Gezira 2.40 2.50 2.10 0.12 7.20 River Nile 0.08 1.01 1.20 0.01 2.30 Khartoum 0. 25 0.44 0.64 0.001 1.30 Kassala 0.96 2.02 1.67 0. 67 5.30 Gadarif 1.04 2.14 1.06 0. 33 4.65 Totals 4.80 8.08 6.71 1.15 20.74 Country’s Total 29.4 39.14 30.45 4.62 103.57 Source: Osman et al., 2012

According to satellite images, the total area of the Butana is about 81,567 km², of which 62% is located in Gadarif and Nile River States. About 21% of the Butana area is under cropland, 41% under rangeland cover and about 29% is bare land, which are desert and semidesert areas. About 63% and 24% of Butana bare land is in the Nile River and Kassala States, respectively (Table 2). Fig. 1 shows the agro-climatic zones of the Butana region by State.

Table 2. Total area, land use (1000 km²) and % share of each state in Butana area Gadarif Gezir Kassala Khartou River Total land a m Nile use Bare land 0.69 0.26 5.65 2.19 14.91 23.64 (29%) Cropland 10.11 1.98 0.52 3.5 1.03 17.11 (21%) Grassland 12.98 4.31 5.74 4.40 5.64 34.92 (41%) Tree 3.86 0.74 0.66 1.45 1.4 10.30 (9%) cover Total 27.63 7.29 11.97 11.53 23.06 81.48 land use (34%) (9%) (15%) (14%) (28%) (100%) Total 27.63 7.31 12.00 11.56 23.07 81.57 Butana (34%) (9%) (15%) (14%) (28%) (100%) area Source: Osman et al., 2012

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Figure 1. Butana region

Climate change and variability is a predominant phenomenon in semidesert, arid and semiarid zones and droughts are becoming more frequent and more severe. Since the early 1980s, due to the reduction in the quantity and uneven distribution of the rainfall, there is an observed fluctuation of the rainfall, long dry spells, drop in relative humidity and rise of temperature. Elhag (2006) stated that Gezira and Khartoum states were subjected to a significant reduction in their monthly and annual rainfall during the period 1996-2006. A consensus clearly emerged among pastoralists in the region that climate has been changing over the past few decades and has adversely affected the productivity of Butana's rangelands. This has resulted in the steady deterioration of both the productivity and biological diversity of the Butana rangelands. Furthermore, Butana hosts other pastoralists from drought-affected areas in other parts of the Sudan. This has intensified pressure on its fragile and deteriorating resource base and further exacerbating the vulnerability of its pastoralists. This study attempted to assess trends and changes in climate factors such as annual rainfall, minimum and maximum monthly temperatures over time in Butana region, impacts of climate change on the grazing system and animal productivity and on livelihoods of the pastoral communities in Butana area.

Materials and Methods Site selection and data collection: Three States namely; Gadarif, Gezira and Khartoum were chosen out of the five States constituting Butana area (Figure 1). Gezira State had the highest share in almost all species of animals, about 35% of animals in Butana region, and it is the most affected area by climate change as demonstrated by the decreasing trend of rainfall and rise of temperatures over the 64 Copyright © 2015 SAPDH ISSN 1816-8272

Magboul et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 62-73 last five decades. It is worth mentioning that Gezira and Gadarif contribute about 57% of the total animal wealth in Butana region. Khartoum represented the second most-affected area by climate change. Gadarif ranks second in terms of cattle and sheep but with less camels and goats compared with Kassala State. A comprehensive questionnaire and a farm survey were conducted in 2013 under the project entitled “Enhancing Climate Change Adaptation in Agriculture and Water Resources in the Greater Horn of Africa” (ECAW). About 203 Pastoralists households, 100 from Gadarif, 53 from Gezira and 50 from Khartoum were directly interviewed.

Regression analysis: Simple regression analysis was used to estimate the trend of the historical climate data to detect whether there is a climate change in the Butana region as postulated by annual rainfall and monthly minimum and maximum temperatures during the period 1961-2013 recorded in five weather stations in Butana region. The linear trend is simply represented by the following equation:

Where: Ty = quantity of the climate variable in question i.e., annual rainfall, minimum or maximum monthly temperature in the main weather stations in Butana region. a = intercept or estimated value when x equals to zero b = slope of the line or average change in Y per unit of time x = time factor in years from 1961 to 2013 used to forecast the estimated values of rainfall and temperatures into 2030.

Again, a multiple linear regression was used to assess the impact of the climate factors on annual milk productivity per unit of four animal species in the three States of the study area. The multiple regression equation is expressed as follow:

Where y is the annual milk productivity, i represents the three chosen States namely Gadarif, Gezira and Khartoum, j is the observations within each state, represent the coefficients of the variables, represents the intercept term, and ε is an error term. T and R represent the historical data of temperature and rainfall in the Butana states, which are used to forecast the estimated value of milk productivity per unit for the four animal species in 2030 and then used the forecasted livestock productivity in Tradeoff Analysis model for Multi-Dimensional Impact Assessment (TOA-MD).

TOA-MD model: The development and application of relatively simple and reliable methods for assessing the impacts of climate change at the agricultural system and/or household level are needed to provide timely recommendations on the potential impacts of alternative technologies and policies. This study used the TOA-MD impact assessment model (Antle and Valdivia 2006; Antle and Ogle,

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2011; Antle, 2011). The model uses statistical description of a heterogeneous farm population to simulate adoption and impacts of a new technology or change in environmental conditions (Seth, 2012). TOA-MD model was used to assess the impact of technology and climate changes using economic, environmental and social indicators. Claessens et al. (2012) pointed that this model has been used for the analysis of technology adoption, payments for environmental services and set up and interpreting of climate change applications. The model simulates technology adoption with associated economic, environmental and social outcomes in a heterogeneous farm population for regional impact assessment. The methodology uses the surveys, experimental and modeled data to assess simulated management practices that are typically available in countries where semi- subsistence systems are important, combined with future socio-economic scenarios based on new scenario pathway concepts being developed by the climate change and impact assessment modeling communities (Hugo, 2011). The model includes the following parameters: Population, which targets the pastorals households in Butana region. About 203 respondents from three States (Gedarif, Gezira and Khartoum) out of five stretching into the Butana region. Systems scenarios: where system1 describes the current economic situation of pastoralists, which refers to base climate and base technology, and system2 describing a changing economic situation of pastoralists in the future (in 2030) with reference to change in climate and base technology. The model captured the adoption rate of those pastoralists who continue using the existing technologies of 2012 in the future (2030) despite changes in climate. Strata: three strata, 1, 2 and 3 target the pastoralists in Gadarif, Gezira and Khartoum States with 100, 53 and 50 sampled respondents, respectively. Subsystems: include types of livestock activities; cattle, sheep, goats and camels. Source of data for system1 was the survey data while the data input for system2 was the projection with respect to the change in milk production due to change in climate factors. Types of data: included farm household data such as area/ha, farm size in ha, family size, average milk production in liters, prices of milk in SDG/liter at the current price and cost data (average variable costs), standard deviation of net return from livestock; and an outcome variable represented by a poverty line of USD 1/person/day. Outcomes variables and indicators: These included poverty rate, defined as the percentage of farm population living on less than USD 1 per day, net loss, defined as the percentage of farm income losses as a result of climate change impacts, and the adoption rate, defined as the number of households or the percentage of farm population from the sample continuing to adopt the prevailing technology. The model hypothesizes that only milk productivity will be affected as a result of climate change while the herd size, operation costs and farm size will remain the same during the period 2012 to 2030. TOA-MD is used as a climate impact assessment tool to measure: a) the impact of climate change without adaptation, i.e., assuming all farmers use the base technology (system1) or the impact of climate change, when farmers choose 66 Copyright © 2015 SAPDH ISSN 1816-8272

Magboul et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015, 62-73 whether to adopt the adapted technology under the perturbed climate. In this respect, a comparison was made between pastoralists' economic and social situations under public rangeland and the prevailing technology options on the one hand, and facilities provided by the Butana Development Agency (BDA) to develop the local public rangelands, on the other hand. This included establishment of small protected grass areas to use in the dry season, reseeding of some preferred grasses and water harvesting techniques. There is no definite farm size for trans-humans whereby animals are predominantly grazed in public rangelands. For this reason, returns and costs were calculated on the basis of herd size and then converted to per farm size based on the estimated areas surrounding the pastoralist villages. It is also likely that the impact of climate change on productivity is underestimated because the effects of increasing climate and weather variability have not been included, and this is one of the biggest constraints in the rain-fed agriculture.

Results and Discussion Results showed that Gezira state was subjected to significant reduction in monthly and annual rainfall during the period 1961-2013. This indicated that Gezira state was the state mostly affected and impacted by climate change. With the exception of Gadarif, which was subjected to non-significant increases in the annual and monthly rainfall, other states were subjected to non-significant decreases in the annual and monthly rainfall (Table 3). With respect to temperatures, the five states were subjected to a high significant increase in winter (November to February) minimum temperatures with variable changes in summer and autumn temperatures. The River Nile state recorded insignificant increase in summer (March - June) minimum temperature while, along with Gedarif, recording rising minimum temperatures in autumn (Table 4). Moreover, the Gezira, Gedarif and the River Nile states were subjected to highly significant increases in the maximum temperature during the three seasons; summer, winter and autumn. Kassala and Khartoum, on the other hand, were subjected to significant increases in maximum temperature during winter (Table 5).

Table 3. Trends of the annual and monthly rainfall and their significance levels Location Annual rainfall Monthly rainfall Trend P-value Trend P-value Khartoum -1.226 0.128ns -0.136 0.128ns Kassala -0.109 0.803ns -0.047 0.811ns Gezira -1.761 0.016* -0.22 0.016* Gadarif 1.623 0.104ns 0.180 0.104ns River Nile -0.260 0.611ns -0.037 0.611ns ns = not significant; * = significant (p = 0.05) 67 Copyright © 2015 SAPDH ISSN 1816-8272

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Table 4. Trends of minimum temperature and their significance levels Minimum temperature State Summer Winter Autumn Trend P-value Trend P-value Trend P-value Khartoum state 0.030 0.000** 0.058 0.010** -0.023 0.167ns Kassala state 0.025 0.004** 0.039 0.000** 0.014 0.054ns Gezira state 0.013 0.059ns 0.047 0.003** -0.006 0.520ns Gadarif state 0.033 0.000** 0.031 0.000** 0.024 0.000** River Nile state 0.012 0.09 ns 0.058 0.01** 0.015 0.008** ns = not significant; *’** = significant (p = 0.05,0.01) Source: calculated by author

Table 5. Trends of maximum temperature and their significance levels State Maximum temperature Summer Winter Autumn Trend P-value Trend P-value Trend P-value Khartoum state -0.023 0.316ns 0.089 0.01* -0.064 0.037* Kassala state 0.011 0.077ns 0.024 0.010* -0.007 0.589ns Gezira state 0.026 0.000** 0.036 0.000** 0.024 0.004** Gedarif state 0.034 0.000** 0.029 0.000** 0.031 0.000** River Nile state 0.032 0.000** 0.032 0.000** 0.036 0.000** ns = not significant; *,** = significant (at p = 0.05, 0.01)

The amount of milk per each species of animal during the period 1961-2013 (FAO, 2006 and survey data, 2013) for the three States; Gedarif, Gezira and Khartoum was regressed on the amount of annual rainfall and minimum and maximum monthly temperature for the same period to trace the effect of these climatic factors on the grazing system reflected in milk productivity. Monthly maximum and minimum temperatures affected milk productivity more than the annual rainfall. This was reflected by the higher negative coefficients of monthly maximum and minimum temperatures compared with the coefficients of annual rainfall (Table 6). Gedarif was the state with highest suffering from increases in minimum and maximum temperatures. In spite of a rising, though insignificant, forecasted annual rainfall, Gedarif has encountered high losses in forecasted milk productivity by 2030 as a result of the impacts of these climate factors (Tables 6 and 7). Annual milk production in Gedarif in 2030 is expected to decrease to 86%, 93% and 99% for sheep, goats and camels, respectively, from its base-system level in 2012 as a result of climate change, although, cattle milk is expected to increase to 102%. In the Gezira, milk production is expected to decrease to 72% and 87% for sheep and goats, respectively of the base-system levels, but milk productivity will simultaneously increase to 107% and 101% for cattle and camels, respectively. Production of milk in Khartoum will witness increases to 104%, 115% and 101% for sheep, cattle and camels respectively, but it will decrease to 96% for goats. 68 Copyright © 2015 SAPDH ISSN 1816-8272

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The forecasted minimum temperatures depict increases by 5%, 4% and 3% by 2030 in Gedarif, Gezira and Khartoum States, respectively, over their base-period levels. Annual rainfall is also forecasted to increase by 17% in Gedarif (102.84mm) while it would decrease to 60.8% (-139.9) and 52.4% (-89.12mm) by 2030 in the Gezira and Khartoum States, respectively (Table 7). The simulation model showed large negative impacts of climate change on the milk productivity in Butana region as demonstrated by high income declines of the respondent herders by 2030 due to reduction in milk production (Table 8). Increased severity of climate factors (minimum and maximum temperatures) and the relatively high operating costs of animal grazing and drinking-water provision had resulted in high positive annual losses in net income in 2030 (SDG1445.56 and SDG282.16 thousands in Gedarif and Gezira). Further, there were positive annual net losses in farm income (616SDG and 2.3 thousands in Gedarif and Gezira) and annual net losses in incomes as a percent of mean net farm returns (23.08% and 9% in Gedarif and Gezira). On the other hand, Khartoum recorded negative annual net losses for the same items. These findings indicated that Khartoum State would gain under climate change situations due to the combination of insignificant change in climate factors (maximum and minimum temperatures) and cost-effective animal production (Table 8).

Table 6. Estimated coefficients for milk productivity for the four animal species in the three states Animal species Gedarif Gezira Khartoum Coefficient Significant Coefficient Significant Coefficient Significant Camels Constant 236.62 0.000** 236.59 0.000** 237.09 0.000** Maximum temperature 0.041 0.392 ns 0.447 0.416ns 0.37 0.268 ns Minimum temperature 0.076 0.867 ns 0.085 0.827 ns -0.34 0.909 ns Annual rainfall 0.001 0.725 ns 0.002 0.411 ns -0.003 0.285ns Cows Constant 2154.27 0.000** 2452.75 0.000** 1764.90 0.000** Maximum temperature -16.04 0.252 ns -50.7 0.000** -23.04 0.082* Minimum temperature -48.65 0.000** -7.24 0.580ns -19.06 0.098 * Annual rainfall -0.083 0.078* 0.157 0.072 * 0.032 0.781 ns Goats Constant 743.38 0.002** 1063.44 0.000** 787.91 0.003** Maximum temperature 4.52 0.607ns -31.43 0.000** -9.67 0.179 ns Minimum temperature -35.16 0.000 ** 8.56 0.276 ns -14.97 0.023 ns Annual rainfall -0.068 0.021* 0.051 0.307 ns 0.004 0.952ns Sheep Constant 671.26 0.000** 1051.23 0.000** 825.41 0.001** Maximum temperature -11.16 0.097* -32.71 0.000** -13.30 0.043 * Minimum temperature -9.91 0.094 * 9.48 0.172 ns -12.54 0.034 * Annual rainfall 0.011 0.248 ns 0.045 0.236 ns 0.009 0.605ns ns = not significant; *,** = significant (p = 0.05,0.01)

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Table 7. Summary of the average data used in the TOA-MD sensitivity and scenario analysis

Table 8. Impacts of climate change on Pastoralists in Butana area (losses and gains in SDG/year) Items Gedarif Gezira Khartoum Total gains in income of respondent herders 801.12 624.21 457.25 Total losses in income of respondent herders 2246.67 906.36 335.30 Net losses income of respondent herders 1445.56 282.16 -121.95 Gains in farm income 3.41 5.10 3.78 Losses in farm income 9.57 7.40 2.77 Net losses in farm income 6.16 2.30 -1.01 Gains in incomes as a percent of mean net farm returns 12.79 19.90 29.42 Losses in incomes as a percent of mean net farm returns 35.87 28.90 21.57 Net losses in incomes as a percent of mean net farm returns 23.08 9.00 -7.85 Source: TOA-MD model results (Herders income in 000 SDG); USD 1 = SDG 5.7

Results of the analysis showed the simulated adoption rate of prevailing technologies in grazing animals and using public rangelands in Butana area under the situation of prevailing climatic conditions (System 1) and that of climate change (System 2) as a function of the opportunity cost of changing from System 1 to System 2. The rate that would occur if pastorals are behaving economically rational and maximizing expected returns to their rangelands near their villages (farms) is the point where the curves crossed the horizontal axis. The simulation results designated adopters at 35.3% out of the sampled respondents of the population of pastoral households (Fig.2).

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Fig. 2. Adoption rate and opportunity cost of prevailing technologies.

The results provide predicted annual net returns per farm in SDG in relation to the adoption rate of available technologies in grazing animals and using the public rangelands in Butana region under the situations of base and change climate. The baseline poverty rates were at the zero adoption rates. However, the annual net return per farm would decrease from 23.913 to 23.58 thousand SDG under climate change at the economically efficient rates of adoption (Figure 3).

Fig. 3. Net returns per farm versus adoption rate of prevailing technologies

NRFM1_A = Net returns per farm for system1: with animal production at the base climate situations. NRFM2_A = Net returns per farm for system2: with animal production under changing climate NRFM_A = Net Returns per farm for systems 1& 2: with base animal production methods and climate change situation.

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Results of the analysis depict predicted poverty rates as a percentage of the respondent pastorals' households in relation to the adoption rate of prevailing technologies in grazing animals using the public rangelands in Butana area under the situations of base changing climate. Taking the baseline poverty rates at zero adoption rates, the poverty rate at a poverty line of USD 2 per person per day would increase from 43.9% to 71.4% of the respondent pastoralists of Butana region under climate change situations and economically efficient rates of adoption (Figure 4).

Fig. 4. Poverty rate and adoption rate of prevailing technologies

POVERY1_A = Poverty rate for system1: when animal production at the base climate situations. POVERT2_A = Poverty rate for system2: when animal production under change climate situations. POVERTY_A = Poverty rate for system 1&2: when animal production at the base and under change climate situations.

Conclusions The Gezira part of Butana was the area mostly suffering from both climate variability and climate change. This was manifested as significant increases in minimum and maximum monthly temperatures, and a significant decrease in annual rainfall with negative impacts on public rangelands’ productivity and the grazing system leading to a highly significant reduction in animal production. Much higher effect of monthly minimum and maximum temperatures on milk productivity than that of annual rainfall was depicted. The Gedarif State part of the Butana region was the mostly suffering from high losses in forecasted milk productivity by 2030 accompanied by high losses in forecasted pastoralist’ income as a result of the impact of rising temperatures despite some increase in rainfall. Therefore, urgent intervention to rehabilitate rangelands, encourage pastoralist to improve their herd structure to favor productive animals and to diversify their herd through keeping sheep or goats should be undertaken. 72 Copyright © 2015 SAPDH ISSN 1816-8272

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Acknowledgements This work was part of the Project “Enhancing Climate Change Adaptation in Agriculture and Water Resources in the Greater Horn of Africa” (ECAW) which was funded by the International Development Research Center (IDRC) Grant No. 106552-003. The advice of Dr. Antle, John M. of Oregon State University and Dr. Roberto Valdivia of Montana State University is highly appreciated.

References Antle, J.M. 2011. “Parsimonious Technology Impact Assessment.” American Journal of Agricultural Economics. Vol 93(5): 1292-131. Antle, J.M, S. Ogle. 2011. “Influence of Soil C, N2O and Fuel Use on GHG Mitigation with No-till Adoption”. Climatic Change. Vol. 111:609-625. Antle, J.M., Valdivia, R. 2006. “Modelling the Supply of Ecosystem Services in Agriculture: A Minimum-data Approach.” Australian Journal of Agricultural and Resource Economics 50: 1–15. Claessens, L., J.M. Antle, J.J. Stoorvogel, R.O. Valdivia, P.K. Thornton, M. Herrero (2012). A method for evaluating climate change adaptation strategies for small-scale farmers using survey, experimental and modeled data. Agricultural Systems 111 (2012) 85–95. Elhag, Muna Mohamed. 2006. Causes and Impact of Desertification in the Butana Area of Sudan. PhD thesis Department of Soil, Crop and Climate Sciences, Faculty of Natural and Agricultural Sciences, University of the Free State Bloemfontein, South Africa p 31.38 FAO Stat, 2006 Website www.fao/org.net. Hugo, R. 2011. Ex-Ante Economic and Ecosystem Service Potential of Simulated Conservation Practices in Ghana Using A Minimum Data Approach. M.Sc. thesis Department of Agricultural Economics College of Agriculture Kansas State University Manhattan, Kansas 2011. MAF. 2011. Ministry of Agriculture and Forest (MAF) Reports,Khartoum, Sudan. MFNE. 2005. Ministry of Finance and National Economy (MFNE) Reports, Khartoum, Sudan. Osman, A. K., El Wakeel, A. S. and ElGameri, M. A. 2012. Ecological Zonation of the Butana Region. Report of the Butana Integrated Rural Development Project (BIRDP). Seth, T. W. 2012. Pacific Northwest Rangeland Carbon Sequestration. M.Sc thesis Oregon State University. P 13.

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Managing Rainfall Variability in Arid Rainfed Agriculture Using Adaptive Varieties and In-situ Water Harvesting

Kawkab E. Babiker1, Abdelhadi A. W. Mohamed2, Imad-eldin A. Ali-Babiker1 and Hussni O. Mohammed3

Abstract This investigation was to establish a water harvesting technique for adaptation to rainfall variability in rainfed sorghum production and relate it to yield in Gedarif area. A field experiment was conducted for two successive seasons (2009-2010). A split-split plot design was used to test the hypothesis that crop yield was affected by three methods of sowing representing in-situ water harvesting techniques, namely; wide level disc in rows 80 cm apart using row planter and at bottom of ridges 80 cm. Three sorghum varieties were used, Arfa Gadamak8, Wad Ahmed and Bashaer. Nitrogen fertilizer of zero and 0.5N of urea was applied. In season 2009, there was a significant difference between mean of yield of Arfa_Gadamak8 and Wad-Ahmed varieties, with the latter requiring longer time to mature. Water harvesting technique increased yield as a result of increased soil moisture content. There were high simple correlation coefficients between rainfall and grain per head, head weight and length of head. It was concluded that climate change adaptation strategies for rainfed agriculture under low rainfall conditions should consider the combination of short maturing variety such as Arfa-Gadamak8 variety and in-situ water harvesting techniques.

Keywords: Sorghum; climate variability, sowing method, crop water requirement, water harvesting

Introduction Agriculture is directly affected by climatic change especially that under rainfed conditions due to the high vulnerability of this sector with limited adaptation options (Mertz et al., 2009). The productivity of the rainfed agriculture is a function of climate and cultural practices, where climate variables have major effects on crop yield distribution. One of the major effects on average yield is the frequency and the length of dry spells (Rockström et al., 2002) that may affect the length of the growing season. Changes in season lead to changes in the growing and maturation period of crops (Dong et al., 2009). Rainfed agriculture depends on rainfall as its sole source of water. Therefore, it is imperative to maximize the efficiency of rainwater use. This leads to the question that what are the adaptation options to increase crop production in dry land rainfed farming systems without further water inputs. Rawhani et al. (2011) studied the climate variability and crop production in Tanzania. They showed that climate variability reduces agricultural yields by 4.2, 7.2 and 7.6% for maize, sorghum and rice, respectively.

1 Forest Research Center, Agriculture Research Cooperation, Sudan, email: [email protected]. 2 Arabian Gulf University, Bahrain. 3 Cornell University, USA. 74 Babiker et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 74-82

In Sudan, rainfed agriculture constitutes the major backbone of food security. The main staple food crop is sorghum (Sorghum bicolor) (L), mainly produced under rainfed conditions. Mechanized rainfed farming in Gedarif State constitutes around 30% of total sorghum area in Sudan since the early sixties (Ahmed, 1994). Farah et al. (1996) studying the role of climate and cultural practices on rainfed agricultural production in Sudan showed a decline of sorghum yields over the years. They also presented strong association between rainfall distribution in time and yields. Yields of rainfed sorghum are deteriorating year after year in Gedarif area (Hassan and Elasha, 2008), and there is evidence of resources degradation. Average Sorghum yields have declined from 0.7 t/ha during the period 1970-1979 to 0.36 t/ha in last ten years (Ministry of Agriculture, 2011). However, traditional approaches in rainfed field studies have ignored investigating statistical role of one of the important components, which is the total rainfall and its distribution in time during the season, on crop yield. Accordingly, this study was conducted with the objectives of determining the effect of water harvesting techniques and rainfall variability on sorghum productivity under different fertilizer application rates and sowing methods in Gedarif area, eastern Sudan.

Materials and Methods Site and Field Experiment: The study was undertaken in Gedarif State, which is located in eastern Sudan and characterized by semiarid climatic condition. Agricultural production in Gedarif depends mainly on seasonal rainfall. Observational and experimental studies were carried out to address the stated objective in two rainfall seasons in 2009 and 2010. Field experiments were conducted at “Tewawa” site in Northern Gedarif (latitude 14.02N, longitude 35.24E). A wide-level disc initially prepared Land to 8 cm depth. The layout of the experiment was a split-split plot design (Steel and Torrie, 1980) with the method of sowing designated for the main plot. Sowing methods comprised of sowing with wide level disc at a seed rate of 2.2 kg/ha as a control sown in rows 80 cm apart using planter and sowing at bottom of ridges 80 cm apart done manually using 4-5 seeds/hole. Plants were later thinned to two per hole in rows and ridges. The subplots were assigned to two sorghum varieties; Arfa Gadamak8 as an early maturing and Wad Ahmed as a late maturing in the first season, Arfa Gadamak8 and Bashaer in the second season. Nitrogen fertilizer applied at zero and 0.5N rates were assigned to the sub-subplots. These treatments were replicated three times. Samples for yield and yield component were taken at harvest from each plot with a sampling area of three m3 in the first season and (3×8) m2 in the second season. The following yield components were also measured; number of plant per square meter, number of head per square meter, number of grains per head, straw weight per square meter, plant height for ten plant per plot, length of head for five head per plot and 100-grain weight. Climate data: The climate data comprising rainfall (mm), maximum and minimum temperatures (oC) relative humidity (%), wind speed (m/sec) and sun shine (hr) for the study site were obtained from the Sudan Meteorological Authority (SMA) for seasons 2009 and 2010 to calculate reference Evapotranspiration (ETo) for decadal data according to Penman (1948) and

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Monteith (1965) methods. The ETo was calculated using a tested computer program developed by Allah Jabow (2007). The crop water requirement (CWR) of grain sorghum was computed using the crop coefficient KC (Elhadi, 2006) for decadal data set for two seasons. FAO equations (year) were used to calculate effective rainfall. The following equations were used to calculate the amount of crop water requirement and seasonal and decadal water deficit for each season as follow: Effective rainfall =0.6*total rainfall-10 (if rainfall less than 70mm) Effective rainfall =0.8*total rainfall-24 (if rainfall more than 70mm) (Adam, 2008) CWR = KC * ETo Deficit = Effective Rainfall – CWR. Where ETo = the reference crop evapotranspiration in mm per unit of time CWR = the water requirement of a given crop in mm per unit of time Kc = the crop coefficient corresponding to the same period of time above Data collection and analysis: The comparison among mean for all variables that were used in the study was performed using SPSS (Ver. 20). The associations between continuous variables Yield kg/ha, head weight, number of grains per head, plant height and 100-grain weight were evaluated using the Pearsonʼs correlation coefficient (Steel and Torrie, 1980). Regression analyses (Steel and Torrie, 1980) were also carried out using the general linear model in SPSS to assess the effect of each factor that was associated with yield components while controlling for other factor at the same time.

Results Figure 1 shows the maximum and minimum temperature for both seasons. Temperature for season 2009 was more than that for season 2010. Figure 2 shows the water balance for the two seasons so when the amount was positive this was decadal surplus and when negative denoted a decadal deficit. Total amount of water balances were -246.4 and-110.8 for seasons 2009 and 2010, respectively, which was deficit. Sowing in bottom of the ridge with Arfa-Gadamak8 without fertilizer had the highest mean yield of 1.8 t/ha during the first season in 2009 (Table 1). Sowing in the bottom of the ridge with Wad-Ahmed without fertilizer resulted in the highest straw yield at a mean of 0.0008 ton/ha in the first season (2009) (Table 1). Arfa-Gadamak8 sown in the bottom of the ridge with without fertilizer gave the highest grain yield at a mean of 1.4 ton/ha during the second season (2010), whereas Bashaer sown in the bottom of the ridge without fertilizer gave the highest straw yield at a mean of 0.0003 ton/ha (Table 2).

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Fig 1. Minimum and maximum temperature Fig 2 Decadal water balance for season for season 2009 and 2010. 2009 and 2010

Table1. Mean grain and straw yields (ton/ha) for the first season (2009) Sowing Varieties fertilizer Grain yield (ton/ha) Straw yield (ton/ha) Method mean ±SD Mean ±SD Ridger Arfa- N0 1.8 0.7 0.0004 0.00003 Gadamak8 N0.5 1.1 0.9 0.0001 0.00006 Wad- N0 0.7 0.6 0.0008 0.00002 Ahmed N0.5 1.0 0.4 0.0007 0.00002 Planter Arfa- N0 1.1 0.3 0.0002 0.00008 Gadamak8 N0.5 0.6 0.4 0.0002 0.00007 Wad- N0 0.4 0.4 0.0005 0.00003 Ahmed N0.5 0.5 0.2 0.0005 0.00002 Wide Arfa- N0 1.9 0.2 0.0004 0.00001 level Gadamak8 N0.5 1.3 0.1 0.0002 0.00001 disc Wad- N0 0.5 0.4 0.0006 0.00002 Ahmed N0.5 0.4 0.2 0.0007 0.00002

Table 2. Mean grain and forage yields (ton/ha) for the second season (2010) Sowing varieties fertilizer Grain yield Forage yield (ton/ha) Method (ton/ha) mean ±SD mean ±SD Ridger Arfa- N0 1.4 0.7 0.0002 0.00001 Gadamak8 N0.5 1.1 0.2 0.0002 0.00001 Bashaer N0 1.2 0.1 0.0003 0.00001 N0.5 0.9 0.0 0.0003 0.00001 Planter Arfa- N0 1.1 0.3 0.0002 0.00004 Gadamak8 N0.5 1.1 0.4 0.0002 0.00008 Bashaer N0 1.0 0.4 0.0002 0.00003 N0.5 0.9 0.2 0.0002 0.00003 Wide level Arfa- N0 1.2 0.7 0.0003 0.00003 disc Gadamak8 N0.5 1.2 0.3 0.0003 0.00002 Bashaer N0 1.1 0.1 0.0002 0.00003 N0.5 1.1 0.2 0.0002 0.00003

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There were positive simple correlation coefficients between rainfall and grain per head, head weight and length of head (Table 3). Furthermore, the results based on general linear model revealed that the yield components were significantly affected and associated with varieties (Table 4). There was significant difference among the three varieties of sorghum when the impact of the deficit was not taken into consideration. In Table 3 the regression coefficient of the factor, the standard error and the 95% confident interval are reported. Arfa_Gadamak8 was significantly different and had less Grain per head compared to Bashaer when the impact of the deficit was not taken into consideration (Table 4). However, there was no significant difference between Arfa-Gadamak8 and Wad-Ahmed. The grain per head was negatively affected by the deficit. On average, the grain per head decreased at a rate of 69.7 g per unit increase in the deficit.

Table 3. Simple correlation coefficients among some variables used in the analyses in Gedarif variable Seasonal Yield Grain/ Plant 100- Head deficit (kg/ha) head height seed weight (mm) (cm) weight (g) (g) Yield (kg/ha) 0.1679 Grain/head 0.8722 0.2117 Plant height 0.3960 0.3971 0.4528 100-seed weight 0.3951 0.6155 0.1884 0.3060 (g) Head weight (g) 0.8796 0.3082 0.9445 0.5177 0.4261 Length of head 0.6512 0.1235 0.7248 0.6107 0.1031 0.7001 (cm)

There was significant difference among the three varieties of sorghum when the impact of the deficit was not taken into consideration, with Arfa-Gadamak8 recording more hundred seed weight compared with Wad-Ahmed and Bashaer. The hundred seed weight was inversely affected by the deficit, increasing at a rate of 0.003 g per unit increase in the deficit. No varietal differences were found in head weight when not taking into consideration the impact of the deficit (Table 4).

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Table 4. Relationships between varieties with yield components while controlling for climate factor. Variable Regression SE T Significance 95% Conf. Interval Coefficient Lower Upper Bound Bound Grains Per Head: Intercept 27220.876 1328.827 20.484 0.000 24568.458 29871.724 Arfa_Gadamak -3617.928 1229.989 -2.941 0.004 -6072.333 -1163.523 Wad_Ahmed -2737.182 1739.467 -1.574 0.120 -6208.234 733.871 Bashaer 0a - - - - - Deficit 90.387 9.070 9.965 0.000 72.288 108.486 100-Seed Weight: Intercept 2.721 0.164 16.602 0.000 2.394 3.048 Arfa_Gadamak 0.681 0.152 4.486 0.000 0.378 0.983 Wad_Ahmed -0.188 0.215 -0.875 0.385 -0.616 0.240 Bashaer 0a - - - - - Deficit 0.003 0.001 2.725 0.008 0.005 0.098 a: This parameter was set to zero to avoid redundancy.

There was significant difference among the three methods of sowing when not taking the impact of the deficit into account. Sowing at the bottom of the ridge resulted in taller plants compared with sowing with planter and wide level disc when not taking into consideration the impact of the deficit (Table 5). Sowing at the bottom of the ridge gave the highest head length in comparison with both planter and wide level disc sowing. The plant height and the length of head were negatively affected by the deficit. On average, the plant height had increased at the rate of 0.069 cm per unit increase in the deficit while the length of head had increased at the rate of 0.032 cm per unit increase in the deficit (Table 5).

Table 5. The relation between methods of sowing with yield component while controlling for climate factor. Parameter Regression SE T Significance 95% Conf. Interval Coefficient Lower Upper Bound Bound Length of Head: Intercept 20.719 0.850 24.383 0.000 19.023 22.415 Ridger 2.968 0.660 4.494 0.000 1.650 4.285 Planter 1.504 0.660 2.278 0.260 0.186 2.822 Wide level 0a - - - - - disc Deficit 0.032 0.004 9.965 0.000 0.024 0.040 Plant Height: Intercept 114.511 3.644 31.421 0.000 107.239 121.784 Ridger 13.038 2.832 4.604 0.000 7.386 18.689 Planter 7.200 2.832 2.542 0.013 1.549 12.851 Wide level 0a - - - - - disc Deficit 0.069 0.017 4.075 0.000 0.035 0.104 a: This parameter was set to zero to avoid redundancy.

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Discussion Total rainfall for season 2009 was 523.7 mm and the effective rainfall was 338.12, while in season 2010 the total rainfall was 549.2 and the effective rainfall was 376.18. Regardless the difference between the effective rainfalls in the two seasons, this was not reflected in a significant difference between the yields for the two seasons. This could be attributed to the fact that the two seasons were affected by deficits at different stages of sorghum growth, which is in agreement with Harmsen et al. (2009). Establishment stage in both seasons was not affected by deficit whereas vegetative stages were affected by deficit 41.5% and 69.9 % for 2009 and 2010, respectively. Flowering stage in 2009 was not affected by deficit. In contrast, the flowering stage in 2010 season was affected by 56% of deficit. Maturity stage in both seasons was affected by deficit 100% and 78% for 2009 and 2010, respectively. Vegetative growth is the most critical in its demand for assured water supply (Hukkari and Shukla, 1983). Lower soil moisture and increases in the relative crop yield reduction are associated with increasing precipitation deficits (Mansouri-Far et al., 2010). However, using proper water harvesting technique, additional water could be saved during the wet time to offset increased water requirements during the dry spells (Harmsen et al., 2009). The difference between Arfa-Gadamak8 and Wad-Ahmed in season 2009 might be attributed to the fact that Wad-Ahmed variety requires longer season to mature compared with Arfa-Gadamak8 (Mohamed et al., 2009). Although the water harvesting technique has increased the yield (Elamin et al., 2010), sowing in the bottom of the ridge (in-situ water harvesting) increased soil moisture content (Elamin, 2008) compared with other methods of sowing. The effects of sowing with row planter were masked by the high competition between plants especially in areas infested with Striga. Sorghum yield had increased when sown under a water harvesting technique as such techniques increased soil moisture within the root zone (Mohamed et al., 2002). Biazin et al. (2011) showed that micro- catchment and in-situ rainwater harvesting techniques could improve the soil water content of the rooting zone by up to 30% in sub-Saharan Africa. McHugh et al. (2007) studied the performance of in-situ rainwater conservation tillage technique on dry spell mitigation and erosion control in the drought prone north Wello zone of the Ethiopian highlands. They found that open ridge had increased seasonal root-zone soil moisture by 15-24%.

Conclusions The results of the study clearly indicated that climate factor had impacts on sorghum yields through variable amount of moisture deficit. Arfa-Gadamak8 variety and in-situ water harvesting technique with sowing at the bottom of the ridge were the best in some yield components compared with the other varieties and methods of sowing. Consequently, climate change adaptation strategies for rainfed agriculture under low rainfall conditions should consider the combination of short maturing variety (e,g, Arfa-Gadamak8 variety) with in-situ water harvesting techniques (e.g. sowing at the bottom of the ridge) for improved grain productivity.

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Acknowledgements This study was supported as a part of the project "Managing Risks, Reducing Vulnerability and Enhancing Agricultural Productivity under a Changing Climate" funded by the International Development Research Centre (IDRC) and the Department for International Development (DFID). The authors are very grateful to the Sudan Meteorological Authority for kind cooperation. This paper was, also, presented at ASARECA General Assembly Dec.2013.

References Ahmed, M. A. M. 1994. Introducing New Technologies on Vertisols of Eastern Sudan: A Dynamic Programming Approach. Ph.D Thesis, Purdue University, USA. Allah Jabow, M. K. 2007. Effects of weather Data processing Reference Evapotranspiration (ET0) Calculation, MSc. Thesis, University of Gezira, Water Management and Irrigation Institute. Biazin, B., Stark, G., Temesgen, M., Abdulkedir, A. and Stroosnijder, L. 2011. Rain Water Harvesting and Management in Rainfed Agricultural Systems in Sub-Saharan Africa. A review, Physics and Chemistry of the Earth,Parts A/B/C, 3 September 2011. Dong, W., Jiang, Y. and Yang, S. 2009. Response of the starting dates and length of seasons in Mainland China to global warming. SPRINGER Science+Business media B.V.2009. Elamin, E. M. 2008. Effect of in-situ water harvesting techniques and slope gradient on soil moisture and millet yield in North Gedarif area. Proceeding of the 43rd Meeting of the national crop husbandry committee. ARC, Wad Medani. Elamin, E. M, Badawi, S. and Abd el Tawab, H. 2010. Effect of Some Water Harvesting Technique on Productivity of Two Sorghum Cultivars in North Gedarif. Proceeding of the 48rd Meeting of the national crop husbandry committee. ARC, Wad Medani. Elhadi, M. A. 2006. Water Management of Irrigated grain Sorghum in Central Gezira, Farah, MSc. Thesis, Sudan Academy of Sciences. Farah S. M., Ali I. A. and Inanaga. S. 1996. The Role of Climate and Cultural Practices on Land Degradation and Desertification with References to Rainfed Agriculture in the Sudan, Proceeding of the Fifth International Conference on Desert Development, Volume 1, Texas Tech University, August 12-17 1996. Harmsen, Eric. W., Miller, Norman. L., Schlegel, Nicole. J. and Gonzalez. J. E. 2009. Seasonal Climate Change impacts on Evapotranspiration, Precipitation deficit and Crop yield in Puerto Rico. Agricultural Water Management, Volume 96, Issue 7, Pages 1085-1095. Hassan, A. E. and Elasha, E. A. 2008. Intercropping effect of using local cowpea of Striga hermonthica (Del.) Benth. Control and grain yield of Sorghum bicolor (L) Moench. Sudan Journal of Agricultural Research. 11: 53-60.

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Hukkari, S.B. and Shukla, N.P. 1983. Effect of soil moisture stress at different stages of growth on folder yield of sorghum (Sorghum bicolor L.) Cv. MP- CHARI. Indian J. Agric. Sci.,53(1):44-48. Mansouri-Far, C., Sanavy, S. A. M. and Saberali, S. F. 2010. Maize Yield response to deficit irrigation during low-sensitive growth stages and nitrogen rate under semi-arid climatic conditions. Agricultural Water Mnagement. Volume 97.Issue 1. Pages12-22. McHugh, O. V., Steenhuis, T. S., Abebe, B. and Fernandes, E. C. M. 2007. Performance of in situ rainwater conservation tillage technique on dry spell mitigation and erosion control in the drought-prone North Wello zone of the Ethiopian highlands, Soil and Tillage Research,Voulme 97, Issue 1, November 2007, pages 19-36. Mertz, O., Halnaes, K., Olesen, J. E. and Rasmussen, K. 2009. Adaptation to Climate Change in Developing Countries. Environmental Management volume 43, Number 5, 743-752, DOI: 10.1007/s00267-008-9259-3 Ministry of Agriculture. 2011. Natural and Animal Resources and Irrigation., Bank of Sudan, Gedarif branch and Ministry of Agriculture., Natural and Animal Resources and Irrigation, Gedarif state. Mohamed, A. H., Gamar, Y. A., Abu-Assar, A. H., Elagib, T. Y., Elgada, M. H., Elhassan, O. M. and Hassan, H. A. 2009. A proposal for the release of two early maturing, high yielding sorghum genotybe for commercial use, especially in the drought prone areas of the Sudan proceeding of the Meeting of verities release June 2009. Mohamed, A., A. W., Salih, A. A., Yosif, M. and Takeshi H. A. T. A. 2002. Effect of water harvesting methods on sorghum (Sorghum vulgare) yield in the Butana area, Sudan. Proceeding of the International Workshop on Crop Water Management for food production under limited Water Supplies. Montreal, Canada, July 21-28, 2002, pp. 17-24. Monteith, J. L. 1965. Evaporation and the environment. In: The State and Movement of Water in Living Organisms. XlXth Symposium.Soc.For Exp. Biol., Swansea. Cambridge University Press. Pp. 205-234. Penman, H. L. 1948. Vegetation and Hydrology. Tech. Comm. No. 53, Commonwealth Bureau of Soils, Harpenden, England. Rawhani, P., Lobell, D. B., Linderman, M. and Ramankutty, N. 2011. Climate Variability and Crop Production in Tanzania, Agricultural and Forest Meteorology, Volume 151, Issue 4, 15 April 2011, Pages 449-460. Rockström, J., Barron, J. and Fox, P. 2002. Rainwater management for Increased Productivity among Smallholder Farmer in Drought, prone Environments. Phys. Chem. Earth 27, 949-959. Steel, R. G. D. and Torrie, J. H. 1980. Principles and Procedures of Statistics: A biometrical approach. McGraw-Hill Co., New York, USA. 633 pp.

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Impacts of Climate Change on Biodiversity in Sudan: A Review

Ahmed S. El Wakeel1

Abstract The Central Bureau of Statistics in 2008 classified the population of Sudan into rural (67%) and urban (33%) categories. The pastoral group of the population has been added to the rural category. This implies that most of Sudan’s population secures their livelihood by using natural resources. This situation has put intensive pressure on these resources, and has thereby led to serious degradation in biodiversity and the rest of ecosystems components. The end result has been negative impact on the well–being of the rural communities. The indirect factors for the degradation of the natural resource base can be attributed to population’s growth, globalization in trade, market, and technology and policy framework. While the direct ones are change in land use and cover, species introduction and removal, technology and climate change. With the secession of South Sudan, Sudan lost a third of its area which is the richest in biodiversity. Climate change will profoundly affect agriculture worldwide. Similar to most African nations, Sudan’s economy relies heavily on agriculture. Although Sudan is endowed with diverse ecosystems and species, it is adversely affected by climate change and other factors. The ecological zones extend from the desert in the extreme north to the savannah in the south. Forests and rangeland represent 35.6% of the total country’s area. Food security in Sudan is under threat from unpredictable changes in rainfall and more frequent extreme weather. Under harsh climatic conditions, poorer farmers in Sudan with will be most affected. An increase in biodiversity has been reported as the most effective strategy to adapt to climate change in agriculture. A mix of different crops and varieties in one field has been reported as an effective farming method to increase resilience to climate change, while monocultures of genetically identical plants would not be able to cope with a changing climate. Genetic diversity within a field provides a buffer against losses caused by environmental changes, pests and diseases, and thereby contributes to food security. The fastest way to develop stress tolerant varieties is through the use of modern breeding techniques such as marker assisted selection. More research on the effects of climate change on biodiversity and ecosystem functioning is needed, especially the interaction between climate change and other factors such as habitat fragmentation, biological invasions, pollution and overexploitation.

Kewards: Parooral groups, Climate change, biodiversity, Biological.

Background and Introduction Sudan is a vast country with an area of 1.8 million km2. It lies between latitudes 10o and 22o N and longitudes 22 o to 38o E. Its landscape consists primarily of

1 Professor of Ecology (formerly, in the Agricultural Research Corporation (ARC). Then as Project Manager Biodiversity – Sudan, (Higher Council for Environment and Natural Resources (HCENR). This manuscript was submitted couble of monthes before his sudden death. 8 3 El Wakeel et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 83-94

gently sloping plain, with the exception of Jebel Marra Masssif, Red Sea Hills, and Nuba Mountains. Mean annual temperatures vary between 26oC and 32oC across the country. The northern part is almost desert and semi-desert, with average annual temperature and annual rainfall around 30oC and 150 mm, respectively. The central area is semi-desert to savanna, with average annual temperature and annual rainfall around 27 oC and about 200 mm, respectively. Rainfall, which supports the great majority of the agricultural activity, is erratic and varies significantly from the northern to southern ranges of the country. Sudan can be ecologically divided into five vegetation zones according to rainfall patterns from North to South. The diversity of the Sudan’s climate is responsible for its rich flora and fauna. Agricultural activity, including animal production and forest related activities in Sudan, is based to a great extent on the indigenous heritage of plant and animal species that forms an important component of the country's wealth of biodiversity. The forestry sector contributes some 12% of the Sudanese GDP, besides the indirect benefits it renders in the way of environmental protection, biodiversity conservation, soil amelioration, work opportunities for rural population and others. Perhaps the most tangible benefit derived by the people of the Sudan from their forests is fuel wood in the form of firewood and charcoal, as well as Gum Arabic with an annual export that ranges between 20-40 thousand tons. Rangelands contribute substantially to the income and subsistence of a large sector of the population who are either pastoralists or agro-pastoralists by providing important forage feed resource. It supplies about 70 % of the total feed requirement of national herds, which are estimated at 104.9 million heads (Ministry of Livestock, Fisheries and Rangelands (MoLFR), 2012). Sudan possesses an immense and diversified wealth of animal resources, ranging from the domesticated livestock species to the wild and aquatic life which contributes significantly to the food security, as well as forming a considerable base for the economy of the country. Livestock goes beyond its influence on the economy to its role in securing national and strategic food. It allows self- satisfaction in meat (100%) and export of 3770240 heads, of which 3415739 heads of sheep had contributed to about 451 million US dollars in 2012 (Ministry of Livestock, Fisheries and Rangelands (MoLFR), 2012). Also the contribution of the sector in the national income is estimated to be 18–25 % and it represents a livelihood activity for about 60% of the population, as well as providing labour for about 40% of the population. The density of mammal species in Sudan ranges between 21-50 animal species per 10,000 km2 (Talhouk and Abboud, 2005). These estimates were before the secession of South Sudan.

Status and Trends of Ecosystems and Biodiversity in Sudan Agro-biodiversity Sudan is considered as part of the centres of origin and/or diversity for some of the cultivated crops such as sorghum, pearl millet, okra, melons, sesame and dry dates. It is also a secondary centre of diversity for others such as hot pepper and Roselle. Wild relatives of different crops are also known growing in the country.

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These include wild relatives for crops such as sorghum, pearl millet, rice, okra, watermelon, melon and sesame. Specifically, Sudan is part of the East African Region of crop genetic diversity. Local cultivars from old introduced germplasm for other crops such as maize, faba bean, cowpea and chickpea, are still existing and being utilized by some framers. Sudan embraces diverse biological resources which represent an important national asset and heritage (HCENR, 2013). Insects life (Diversity of bees and honey production) Morphological studies on populations of native honey bees in Sudan showed more than one subspecies. El-Sarrag et al. (1992) mentioned two subspecies of honeybees in Sudan. The first, Apis mellifera sudanensis nov subsp, is distributed all over Sudan between latitudes 3°N and 16 20°N. The other, Apis mellifera nubica Ruttner, exists along the borders of Ethiopia and Uganda. The morphometric studies carried out to differentiate honey bee populations showed more than one subspecies. It has been estimated that there are about 200,000 honey bee hives in Sudan and 50,000 beekeepers. About 99% of them are traditional beekeepers and 1% using modern beekeeping technology The protein structure, physicochemical properties and mineral composition of Apis mellifera honey of different floral origin, commercialized in several states of Sudan were studied (Mohammed and Babiker, 2009). A recent study provided information related to geographical and botanical origin of honey based on honey protein (Mohammed and Azim, 2012). Honey samples from five floral sources: Ziziphus sp., Helianthus annuus, Acacia nilotica, Acacia seyal, and Azadarichta indica were studied. Ziziphus sp, Helianthus annuus, Acacia seyal and Azadarichta indica honeys were 100% correctly classified, and Acacia nilotica honey was 66.67% correctly classified (Mohammed and Babiker, 2009). There is an urgent need for more studies and information to assist in developing policies for conservation of the native honeybees in Sudan (Updated NBSAP, Unpublished). Forest ecosystem It is estimated that there are about 533 trees species in the Sudan, 25 of which are exotics. Also there are about 184 shrub species in the Sudan, of which 33 are exotics. Some of the species have a wide range of distribution and considerable variation within the species exists. However, the vegetation of Sudan forests is neither adequately explored nor adequately documented. Some forest formations are unique in the Sudan such as the Mangrove Forests along the Red Sea Coast and other unique forests on mountains and hills. Those considered seriously threatened are 241 tree or shrub species, which showed marked retreat in their distribution and/or regeneration due to climatic conditions and also due to the intensity of their removal for wood, fodder or clearance for cultivation. Of the exotic shrubs or tree species, 43 are also endangered. The Forest National Corporation (FNC) estimates that, after secession of South Sudan, forests cover about 11.60% of the total area, while agricultural land 13.70%, Rangelands 26.40% and water bodies 0.17%. The average annual increment of growing stock volume is estimated as 1.340 million m3, of which 5

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% is removed per year. The majority is used for firewood and charcoal, while 9% is used for high quality timber and the rest is lost because of fires, drought, overgrazing and unsustainable agricultural practices. UNEP has indicated that between 1990 and 2005 the country lost 11.6 % of its forest cover. Little information is available on genetic makeup of harmful invasive plants invading the valuable agricultural lands such as Prosopis, although there is ongoing debate on the identity of the problematic Prosopis, whether it is Prosopis juliflora or P. chilensis. Range plants ecosystem Some natural range plants are of great value to rural people especially during periods of food scarcity and famine such as Dactyloctenium aegyptium, Echinochloa colona (Difra), Chrosophora brochidiana, Boscia senegalensis, Curbonia virgate, Brachiaria obtusiflora, (Um chir), Chenopodium album, (porridge foods), Sonchus oleraceus (Moleita) used as fresh salad, Cassia obtusiflora (kawal) used as traditional food flavour etc. Some range plants have also medicinal importance such as Blepharis linariifolia (Beghail) and Cassia senna (Sannameka). Different local and indigenous plants are known for their importance in the folk medicine in Sudan. The list of such plants includes both cultivated and wild species. The forestry and rangelands of Sudan support about 101 million heads of cattle, sheep, goats and camels, mostly under pastoral and small agro-pastoral systems in the traditional rainfed lands. Sudan possesses an immense and diversified wealth of domesticated livestock species, farm animal resources which include cattle, sheep, goats and camels. There are different types and breeds of livestock, the majority of which is raised within tribal groups and often carries the names of the tribe or locality. Other domesticated local types of animals include horses, donkeys, pigs and poultry and a wide range of wildlife species. The wildlife occurs in protected areas and in fragmented habitats outside protected areas in desert, semi-desert, Low rainfall savanna woodland, high rainfall savannah woodland and sea coastal habitats. Wildlife includes mammals, birds and reptiles. The number of many species has either noticeably declined or disappeared from many of their former habitats. Other fauna like amphibians, insects and other invertebrates are important and are hosted in protected areas. Freshwater (Inland waters) ecosystem The term “Inland Waters” denotes all aquatic systems that are not part of the marine system i.e. seas and oceans. The term embraces different types of water bodies and is not restricted to freshwater bodies only. Within this context inland waters could be classified into two categories; running water “Lotic” or Non- running water “Lentic”. The Nile River System is the main lotic system in Sudan. The biodiversity in inland waters in Sudan is in limited locations and of limited distribution and include aquatic macrophytes which have always been regarded as nuisance, useless organisms and at the best cases, they have always been neglected. This attitude has been reflected in the fact that the aquatic macrophytes of the Sudan have received little scientific attention, almost no attempt to utilize and of course, no policy to conserve. Furthermore, the taxonomy of the aquatic

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fauna and flora is neither accurate nor complete. Not all inland waters have been surveyed (HCENR, 2013). Marine and coastal habitats diversity The Sudanese coastline of the Red Sea is about 750 km long, including bays and inlets. Typical features of the coast are coastal lagoons and sheltered bays (marsas) that form natural harbours and fish landing places. Several of these lagoons are fringed by mangroves. Sea grass beds are frequently found in the shallow waters of marsas and in the lagoons between the coast and the reefs. These features contain a spectacular biological diversity of ecosystems and species that require considerable efforts for conservation (HCENR, 2013).

Mangroves Avicennia marina was the only mangrove species found in the Sudanese coast during a relatively recent survey conducted on the coast (PERSGA, 2004). Mangroves are distributed along the Sudanese coast from Mohammed Qol north of Port Sudan to Shabarango-Gafud south of Suakin. Mangrove lagoons and channels are occupied by numerous fish species including many commercially important species. The leaves and shade zones provide additional habitat. The mangrove fauna includes true residents that spend their entire life cycle in mangroves (e.g. Aphanius dispar, Gerres oyena and some gobiids), closely associated species that are found there as juveniles e.g. Acanthopagrus berda, Chanos chanos, Crenidens crenidens, Hypoatherina temminckii, Leiognathus equulus, Terapon jarbua, Pomadasys commersonni and some mugilid species), and loosely associated species that are occasional visitors seeking food or shelter e.g. Silago sihama and Thryssa baelama (PERSGA/GEF, 2004b). In addition to marine organisms, mangroves are used as a food source by terrestrial vertebrates and as a roosting and nesting site by many species of birds. Corals and coral reef communities The Sudanese coast is characterized by the extreme diversity of its reefs compared to the rest of the Red Sea coast. The primary coral reef habitats are barrier reefs, fringing reefs, isolated patch reefs, and one oceanic atoll (Sanganeb). The assessment of the condition of Sudan’s coral reefs showed that average live coral cover on reefs in less than 10 m depth ranged from 5–75%. Healthy colonies of framework corals were observed below 10 m. Algal film was the dominant substrate cover in water less than 10 m deep and was attributed to a thermal event. Live coral cover ranged from 5–60%, with dead coral cover higher than 1% noted at only five sites (Nasr and Al-Sheikh, 2000; PERSGA/GEF, 2003b). Assessment of coral reefs in the Dungonab Bay and Mukawwar Island marine protected area (MPA) showed major differences in the health of coral communities between parts of the MPA. The coverage of living coral was generally greatest within Dungonab Bay (PERSGA, 2006). Dungonab Bay is the home for the pearl oyster (Pinctada margaritifera).

Sea-grasses Although sea-grass beds are widely distributed in sheltered shallow water and bays of the Sudanese Red Sea coast, only Dungonab Bay and Mukkawar Island MPA was extensively surveyed. The survey showed that it included at least seven

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species of sea grasses (Thalassia sp., Thalassodendron sp., Halophila stipulacea, H. ovalis, Halodule uninervis, Cymodocea sp. and Enhalus sp.). The total area of sea-grass estimated from Landsat 7ETM image is 11.68 km2. The extensive sea- grass beds are a nationally and regionally important feature of the Dungonab Bay and Mukawwar Island area where the substantial population of the globally endangered dugong is found here (PERSGA/GEF, 2004) Fishes and elasmobranches The Dungonab Bay and Mukawwar Island MPA is significant for the conservation of fish diversity in Sudan. Major differences exist between the inside and outside of Dungonab Bay in the communities of butterfly fish (family Chaetodontidae) and angelfish (family Pomacanthidae). Communities inside Dungonab Bay closely resemble communities from the southern Red Sea, while communities outside the Bay are similar to communities from the north-central Red Sea. The basis of this pronounced difference in community structure is likely to be differences in water quality, temperature and turbidity (PERSGA, 2006). Additionally, the Dungonab Bay–Mukawwar Island MPA is also well known for its aggregations of whale sharks (Rhyncodon typus) and manta rays (Manta birostris) during summer (PERSGA/GEF, 2004f). Groupers were more abundant in Sudan in comparison to other sites in the Red Sea, with more than 20 groupers recorded in over half of 20-minute timed swims (PERSGA/ GEF, 2003b). Parrotfish (family Scaridae) are important consumers of algae on coral reefs and contribute to coral dynamics and habitat formation (Bellwood et al., 2003). Their conservation is, therefore, important for the maintenance of coral reef ecosystems. Assessment of fishes in Mukawwar Island and Dungonab Bay MPA prior to the MPA declaration in 2005 (PERSGA/GEF, 2004f) showed that large groupers (family Serranidae) were rare and Nagil (Plectropomus spp.) over 30 cm in length were rarely observed, suggesting a high fishing pressure on these species. Regionally important populations of sharks are known to occupy the waters off the coast of Sudan, and are a very important attraction for the marine tourism trade. Hammerhead sharks are known to occur around Sanganeb Atoll and around many of the reefs of Dungonab Park in winter, but very few were observed during the recent survey. Turtles The eastern shore of Mukawwar Island is a turtle nesting site of regional and possibly international significance. There is no deliberate capture of turtles within the MPA (PERSGA/GEF, 2004f). Green turtles nest all year at the following key nesting sites: Seil Ada Kebir Island, Suakin Archipelago and Mukawwar Island. Hawksbill turtles, on the other hand, nest during March- July at the following key nesting sites: Mukawwar Island, Seil Ada Kebir and Suakin Archipelago. Key foraging sites for Hawksbill include all fringing and barrier reefs. All species of marine turtle are globally endangered and are CITES- listed. The eastern shore of Mukkawar Island is one of the two or three most important turtle nesting sites in the entire Red Sea region. This important site merits immediate protection, and the application of a rigorous monitoring program.

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Marine mammals Three species of marine mammals (cetaceans) are present in the Sudanese waters including the Spinner dolphin (Stenella longirostris), the common dolphin (Delphinus delphis) and the Bottle nosed dolphin (Tursiops truncates). It appears to show that the cetacean population of the Sudan seems to be strong and is not under much pressure at the moment. The Bottle-nosed dolphins appear to be breeding well and seems to cope being around the many vessels along the coast. Like the shark species the cetacea are apex predators in the park and as such will be an indicator of the state of the health of the park, so their needs will need to be considered in the long term planning of the park. Dugong occurs in the Mukawwar Island and Dungonab Bay MPA. The population there may be the most important remaining on the coast of Africa. However, numbers have declined sharply in recent years. The cause is most likely accidental capture in fixed fishing nets. Two species of dolphin occur in the MPA (PERSGA/GEF, 2004f). Seabirds The whole area of Dungonab Bay and Mukawwar Island MPA is internationally recognized as an Important Bird Area (IBA). Breeding seabird species include: Sterna bengalensis, Sterna repressa, Sterna anaethetus, Larus hemprichii and Larus leucophthalmus (PERSGA, 2006). Suakin Archipelago, which is an unprotected area, is also an important bird area including the following breeding seabird species: Sterna bergii, Sterna bengalensis, Sterna repressa, Sterna anaethetus, Anous stolidus, Sula leucoaster and Larus hemprichii (PERSGA, 2006). Marine planktons Very few studies have been carried out on plankton in the Sudanese Red Sea although currently some post graduate studies are being carried out. Previous investigations included studies in planktonic populations in Port Sudan coastal area (El Hag et al., 1989) and studies in coastal plankton fauna of the Sudanese Red Sea (Nasr, 1980).

Climate Change in Sudan Climate change presents an additional stress for Sudanese people already struggling with poverty, post-conflict recovery and environmental degradation. Straddling north and sub-Saharan Africa, with the Sahel running through the centre of the country, Sudan is a country of extreme geographic and climatic contrasts. However, rainfall and the length of the dry season are the most significant climatic variables. The rainy season in Sudan usually lasts from July to September in the north. There is less rainfall in the north and the driest regions suffer from massive sand storms. In the northern and western semi-desert areas, including Darfur and Kordofan, people rely on scant rainfall for basic rainfed agriculture and many are nomadic pastoralists. Nearer to the Nile, there are well- irrigated farms growing cash crops. Decreasing annual rainfall and increased rainfall variability are contributing to extreme dry spells and periods of drought in many parts of Sudan, even in the south. A succession of dry years from 1978 to 1987 resulted in severe social and

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economic impacts, including many human and livestock fatalities and the resettlement of about three million people close to the Nile and in urban areas. Drought will increase if these trends continue, without efforts to adapt. Devastating floods have also troubled Sudan in the last few decades leading to widespread loss of property, damage to irrigation facilities and water services, and the spread of waterborne diseases. The country’s long history of conflict has had significant impacts on the environment. Population displacements, a lack of governance, conflict-related resource exploitation and underinvestment in sustainable development have been the most severe consequences to date. Any discussion of climate change in Sudan must take into account the political context. The interrelation of climate change with other factors is complex and evolving. Climate change is projected to affect agriculture, water resources and health. A recent United Nations Environment Programme (UNEP) report states: “An estimated 50 to 200 km southward shift of the boundary between semi-desert and desert has occurred since rainfall and vegetation records were first held in the 1930s. This boundary is expected to continue to move southwards due to declining precipitation. The remaining semi-desert and low rainfall savannah which represent some 25 percent of Sudan’s agricultural land are at considerable risk of further desertification. This forecast is expected to lead to a significant drop (approximately 20 percent) in food production.” Projections indicate that climate change will also impact water resources. Reduced groundwater, either through decreased precipitation or increased temperatures and evaporation, would have serious repercussions. National studies show that soil moisture would decline. Coupled with increased water consumption, population growth, a high variation in rainfall and a high rate of evaporation, climate change is increasing the likelihood of a water crisis for Sudan, particularly in the arid north. Experts also expect climate change to threaten health. Many communities in Sudan will be at a significantly increased risk of malaria, which could threaten the country’s already limited health care system. In an attempt to address climate change and related issues, Sudan has already completed several activities. It ratified the United Nations Framework Convention on Climate Change (UNFCCC) in 1993 and submitted its initial national communication in 2003. The government of Sudan also signed the Convention on Biological Diversity (CBD) in 1992 and ratified in 1995. The Higher Council for environment and natural Resources (HCENR), the government’s national focal point for both conventions, plays an advisory policymaking role with regard to climate-related initiatives. The HCENR is also the national executing agency for Sudan’s National Adaptation Program of Action (NAPA), completed in 2007, which focuses on major impacts and vulnerabilities in four regions: Gedaref, North Kordofan, South Darfur and the River Nile States representing different ecological settings across the country. The NAPA for Sudan deals with the task of identifying adaptation priorities in four separate ecological zones. The two dominant themes are inevitably water and agriculture, with public health concerns such as the spread of malaria not far behind. Enhancing Adaptation to Climate

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Change in Agriculture and Water Resource (ECAW) in the Horn of Africa is a regional initiative. ECAW-Sudan Project is aiming at strengthening NAPA by economic analysis of adaptation investments and informing NAPA by credible and impartial scientific assessment of climate change impacts. To achieve this, the project is delivering the following outputs: i) Estimates of climate change impacts in agriculture and water resources improved ii) Costs and benefits of the adaptation options to guide climate change risk planning and investments assessed iii) Capacities of institutions to advance climate change adaptation assessments, options and plans enhanced iv) Knowledge sharing platforms to inform climate change adaptation policies and actions facilitated.

The Biodiversity and Climate Change Interaction There are numerous effects on both terrestrial and aquatic biodiversity from climate change. Climate change is a major threat to species, communities and ecosystems due to the rapid rate at which the climate is expected to change in the near future. Increasing plant diversity through agricultural expansion within Sudan can lead to decreased nutrients/water, prey and dead organic matter, respectively. This would be a negative effect on supporting ecosystems services, which are defined as nutrient cycles and crop pollination. However, in turn, implementation of such agricultural availability would have a positive impact on provisioning ecosystem services, such as production of food, as well as water as the proposed food security solution includes water retention and irrigation in order to allow for agriculture throughout the dry months in Sudan. Desertification and soil erosion are an issue that Sudanese deal with every year, decreasing their crop yields and enforcing nomadic behaviour, therefore not lending itself to sustainable agriculture or human well-being. The question of sustainable well-being comes into play as it is of utmost importance for the people of Sudan to have available food sources from more sustainable agriculture. Biodiversity is a natural insurance policy against climate change. Diversity farming is the single most important modern technology to achieve food security in a changing climate. Scientists have shown that diversity provides a natural insurance policy against major ecosystem changes, be it in the wild or in agriculture (McNaughton, 1977; Chapin et al., 2000; Diaz et al., 2006). It is now predicted that genetic diversity will be most crucial in highly variable environments and those under rapid human-induced climate change (Reusch et al., 2005; Hajjar et al. 2008; Hughes et al., 2008). The larger the numbers of different species or varieties present in one field or in an ecosystem, the greater the probability that at least some of them can cope with changing conditions. Species diversity also reduces the probability of pests and diseases by diluting the availability of their hosts (Chapin et al., 2000). It is an age old insurance policy of farming communities to hedge their risks and plant diverse crops or varieties. The strategy is not to maximize yield in an optimum year, but to maximize yield over years, good and bad, by decreasing the chance of crop failure in a bad year (Altieri, 1990).

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Dry and carbon sequestration, particularly in soils, can provide other ecosystem and social benefits such as the rebuilding of the biophysical foundations of a sustainable natural environment – biodiversity, forests, livestock, soils, water, natural ecosystems - thus increasing productivity, improving water quality, and restoring degraded soils and ecosystems. Increasing carbon stocks in the soil increases soil fertility, workability and water holding capacity; and reduces erosion risk and can thus reduce the vulnerability of managed soils to future global warming. However, hidden costs in intervention strategies need to be considered. There is a limited institutional capacity to manage natural resources. Government institutions and State level agencies charged with biodiversity (including forest) conservation are still in nascent stages of development. Many of the valuable range plants species are endangered. Considering climate change issues when designing response activities is essential for ensuring environmental sustainability. Biodiversity conservation activities that address the impacts of climate change mitigation and adaptation also help achieve MDG 7. For example, from 1992 to 2000, a group of 17 villages in the drought-prone Bara Province in Western Sudan took part in a project to rehabilitate overexploited and highly vulnerable rangelands through the use of community-based natural resource management techniques. The project’s objective was to create a locally sustainable natural resource management system that would both prevent overexploitation of marginal lands and rehabilitate rangelands for the purpose of carbon sequestration, preservation of biodiversity and reduction of atmospheric dust. As a result, 700 hectares of rangeland were improved and properly managed. With improved land management and a more secure environmental and social asset base, communities were able to increase their resilience to climate change impacts.

Alternatives, Options and Recommendations Farmers and governments worldwide have several options to counter continued, long-run global warming.  Farmer adaptations, such as switching crop varieties, introducing more suitable crops, or shifting from crops to grazing, can often be undertaken by individual farmers.  Governments can provide reliable 6- to 8-month weather projections or information about suitable crop and livestock alternatives to help farmers increase production efficiency.  Governments can encourage agronomic research for the development (by either traditional breeding or biotechnology) of new varieties better able to withstand the effects of global warming.  Agronomists may be able to increase the ability of crops to use CO2 more efficiently in photosynthesis.  Other options, such as providing irrigation (or increasing its efficiency) and maintaining flood control, require long-term cooperation with farmers or other members of society. These options would benefit from reliable, long run information about climate change and its effects on land and water resources.

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 Adaptation does not guarantee that farming will be able to continue in an area, or if it does, that farm incomes will remain unchanged. Some adaptation will involve shifting agricultural production from one location to another. This adaptation, too, would benefit from government policies that provide reliable, long run information that identifies suitable and unsuitable crop locations as climate changes.  Government policies that facilitate the migration of people from one location to another or the transition from one profession to another would likewise be helpful. Policies that stimulate economic growth and development and thereby provide more alternatives to agriculture as a source of livelihood would benefit farmers transitioning to new professions.  Long-term policy responses require accurate information about the economic impacts of future climatic conditions. Despite recent advances in analyzing the economic effects of global warming, information about climate change and food security in developing countries remains extremely limited. Specific details are lacking about the location, timing, magnitude, and probability with which food security issues might arise. ERS!!!!! will continue to conduct economic research that helps to assess the effectiveness of public policies for responding to global warming.  More research is needed to improve our understanding of the effects of climate change on biodiversity and its components, and on ecosystem functioning, especially taking into account the interaction between climate change and multiple other factors such as habitat fragmentation, biological invasions, pollution and overexploitation.  Conversely, there is need to improve our knowledge on the effect of biodiversity and its components, on climate change, either mitigating (e.g., ecosystem service of carbon sink or of local climate regulator), or exacerbating (e.g., release of greenhouse gas by livestock or from wetlands).

References Altieri, M. A. 1990. Agroecology. Pages 551–564, In: Agroecology (Carrol, C.R., Vandermeer, J.H. and Rosset, P.M., eds.). McGraw Hill, New York. Chapin, F. S., Zavaleta, E. S., Eviner, V. T., Naylor, R. L., Vitousek, P. M., Reynolds, Diaz, S., Fargione, J., Chapin F. S. and Tilman, D. 2006. Biodiversity loss threatens human well-being. PLoS Biology 4: 1300-1306 Durable Rust Resistance in Wheat 2008. Project Objectives. http://www.wheatrust.cornell.edu/about/ El-Sarrag, M. S. A., Saeed, A. A., Hussien, M. A. 1992. Morphometrical study on Sudanese honeybees. J. King Saud. Univ. Agric. Sci. 1, 99–100. FAO. 2012. The Land Cover Atlas of Sudan. Hajjar, R., Jarvis, D. I. and Gemmill-Herren, B. 2008. The utility of crop genetic diversity in maintaining ecosystem services. Agriculture Ecosystems & Environment 123: 261-270. Higher Council for Environment and Natural Resources. 2013. Stocktaking and national Biodiversity Targets Setting Report. HCENR, Khartoum, Sudan.

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http://www.monsanto.com/monsanto/ag_products/crop_protection/products/round up_power_max.asp.Roundup Power MAX ™ is advertised as “proven on hard-to-control weeds such as velvetleaf, lambs quarters, purslane, kochia and morning glory”. Hughes, A. R., Inouye, B. D., Johnson, M. T. J., Underwood, N. and Vellend, M. 2008. Ecological consequences of genetic diversity. Ecology Letters 11: 609- 623. International Assessment of Agricultural Science and Technology for Development (IAASTD) (in press) www.agassessment.org. Ministry of Livestock, Fisheries and Rangelands. 2012. 2012 Report. Mohammed, S. A. and Babiker, E. E. 2009. Protein structure, physicochemical properties and mineral composition of Apis mellifera honey samples of different floral origin. Australian Journal of Basic and Applied Science, 3, 2477–2483. Mohammed, S. A. and Kamran, A. A. Azim, M. 2012. Characterization of natural honey proteins: implications for the floral and geographical origin of honey. International Journal of Food Science & Technology. Vol. 47 (2) 362–368. Nasr, D. and Al-Sheikh, K. 2000. Assessment of coral reefs in the Sudanese Red Sea in the context of coral bleaching. In: Proceedings of the International Workshop on the Extent and Impact of Coral Bleaching in the Arabian Region (H. Tatwany, ed.). National Commission for Wildlife Conservation and Development, Riyadh. PERSGA. 2006. Report on the State of Marine Environment in the Red Sea and Gulf of Aden. PERSGA, Jeddah. PERSGA/GEF. 2003b. Coral reefs in the Red Sea and Gulf of Aden. Surveys 1990 to 2000 summary and recommendations. PERSGA Technical Series No. 7. PERSGA, Jeddah. PERSGA/GEF. 2004f. Survey of the proposed marine protected area at Dungonab Bay and Mukawwar Island, Sudan. Report for PERSGA. PERSGA, Jeddah. Reusch, T. B. H., Ehlers, A., Hammerli, A. and Worm, B. 2005. Ecosystem recovery after climatic extremes enhanced by genotypic diversity. Proceedings of the National Academy of Sciences, 102: 2826-2831. Talhouk, A. and Abboud, T. 2005. Impact of Climate Change: Vulnerability and Adaptation Chapter 8: Ecosystems and Biodiversity. In: The Atlas of Endangered Species. 12 pp.

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Impact of Climate Change on Natural Resources at EL-Damazine and AT - Tamadon Localities, Blue Nile State, Sudan: Biodiversity perspective

Hanadi I. O. Babikir1 and Muna M.M. Ahmed2

Abstract The present study aimed at detecting climatic changes impacts on natural vegetation at the two localities of El-Damazine and Al-Tamadon, Blue Nile State, Sudan, during 2010-2011. Remote sensing techniques were used for depicting changes in vegetation for the years 1972-2011. Descriptive statistics were used for data analyses using SPSS (Ver. 16). Fluctuations in rainfall through the years (from 1972 to 2011) reflected a general declining pattern while that of temperature tended to increase. Higher fluctuations in areas of vegetation cover could be detected for the years from 1973 to 2011, with rock and bare land attributes showing small changes. The increase in vegetation cover in most recent years was correlated with the appearance and disappearance of some species. In conclusion, rainfed agriculture is inherently sensitive to climatic factors and is one of the most vulnerable sectors to the risks and impact of climate change. Rainfall and warming of air temperatures imposed shifts in the ecosystem causing appearance and disappearance of plant species, but with no effect on bare land and rock attributes.

Keywords: Biodiversity, Ecosystems, vegetation cover, climate change, rainfall, temperature

Introduction During the last decade, there has been a virtual explosion of interest in climate change, which is now considered as one of the most serious problems facing most of the regions in Sudan (NAPA, 2007). A World Bank study (2009) assessed Sudan to be at risk from the effects of climate change on agriculture. The largest operations of world food programs are currently involved in providing aid to eleven million people over the vast country that encompasses the full range of ecological diversity, being semiarid in the north, savannah in the central regions (UN, 2009). There is ample evidence that climate has recorded a clear change during the last three decades of the 20th century throughout the country, including areas with the highest rainfall (UN, 2008). Climate change effects are reflected in reduction of rainfall (Walsh et al., 1988; Eldredge et al., 1988), warming of air temperatures (Elagib and Mansell, 2000a; Elagib, 2010, 2011), solar dimming, increasing reference evapotranspiration and intensifying aridity (Elagib and Mansell, 2000b), with warming and dryness trends having strong association (Elagib and Mansell, 2000a). Findings indicated that drought has become recurrent in recent decades, of which those of the early to mid-1970s, mid-1980, early 1990s and early 2000s noted as common drought years and were among the driest 10 years in the central region of Sudan (Elagib, 2009). These droughts

1 University of Gezira. 2 Institute of Environmental Studies, University of Khartoum, email: [email protected] 9 5 Babikir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 95-102

emphasized the vulnerability of the country to desertification, social and economic damage (Abu Sin, 1986; Walsh et al., 1988; Webb et al., 1991; Olsson, 1993; Larsson, 1996; Ayoub, 1999).

Materials and Methods Study Area: The Blue Nile State is located in central east Sudan between latitudes 9o30‟-12o30‟N and longitudes 33o5‟-35o3‟E. It borders Ethiopia to the east and southeast, Upper Nile State to the west and south, and Sinnar State in the north (Fig. 1). Its capital is El-Damazin, 550 km south to Khartoum. It lies in the fertile woodland savannah belt of eastern Sudan, and receives significant rainfall throughout most of the year. It is characterized by vast clay plains, the Ingessana Mountains and the Blue Nile River flowing northwest from the Ethiopian highlands. There are vast areas for cultivation in both mechanized and traditional rain fed sectors, high potential for fishing grounds. Seasonal streams also traverse the State fertile land along the banks of Blue Nile River, rendering the area highly suitable for vegetable and fruit production and raising of livestock (practicalaction.org, 2007). Remote sensing Data: Remote sensed data produced by Landsat Thematic Mapper (TM) images and IKONOS data. Maps were used to calculate the occurrence and extent of changes on land surface during years (1973 to 2012). Fives sub images from landsat (TM) and (ETM) covering the study area (10,000 km²) were studied. These included images for 1999, 2008 and 2012 via Enhanced Thematic mapper (ETM) while the other image were thematic mapper (TM 1987 and MSS 1972). Landsat (ETM) 2012 was used to detect vegetation change and to combine between these Images. For vegetation cover Normalized Difference Vegetation Index (NDVI) was calculated using data acquired in the normalized infrared (NIR) channel and Red channel. The NDVI equation for Landsat TM and ETM used to evaluate the vegetation cover was:

NDVI = NIR – R/NIR + R

NDVI were visually interpreted using RS and GIS software. These computer programs used for data capture, input, manipulation, transformation, visualization, combination, query, analysis, modeling and output. The software is used as follows: ERDAS imagine 9.3 was used for image processing and analysis. The second software, ArcGIS 9.3 was used for data input, data analysis, management, manipulation and final production. Changes in land cover, land use, drainage system and soil pattern had been detected and different maps were generated. Statistical analysis: Descriptive statistics were used to present results (Mead and Curnow, 1983), Statistical Package for Several Sciences (SPSS, ver. 16) was used for the statistical analyses. Regression analysis performed to assess the effects of climatic variations on crop production; paired t-test was used to compare production between the beginning and end of the season (Mead and Curnow, 1983).

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Fig. 1. The study area

Results Temperature and Rainfall: Both temperature (Fig. 2) and rainfall (Fig. 3) fluctuated through the years 1972-2011 at El- Damazine area. There was a general trend for temperature to increase through these years, whereas rainfall showed a declining pattern (Fig. 4). The same observations were obtained for the individual month‟s rainfall through the years 1972-2006 (Fig. 5). An estimation of mean annual rainfall (mm) by locality (for 1971-2000) was adapted from SIFSIA/FAO, 2008; it confirmed that the southern part of the State had received more rainfall than its northern neighboring localities.

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Fig. 2. El-Damanzine annual mean maximum Fig. 3. El-Damazine total annual rainfalls temperatures (oC) (mm) for (1972-2010)

350

300 April 250 May June 200 July

150 August September Rain fall (mm) fall Rain 100 October November 50

1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Year

Fig. 4. Fluctuation of the rain fall during Fig. 5. Monthly (April-November) (1930-2011) fluctuations in rainfall during 1972-2010 Source: SMA (2011)

Vegetation: Vegetation data collection depended on respondents‟ observation through 1972-2010 and compared with those of Harrison and Jackson, (1958) who classified Blue Nile state area vegetation according to rainfall amount as: within the broad belt of low rainfall woodland savannah (600-800 mm rainfall) of dominant tree species: Acacia seyal and Balanites aegyptiaca (Table 1). Two main vegetation patterns were observed: i) Acacia seyal, A. fistula, Balanites aegyptiaca and Zizyphus spinachristi in depression areas within the plain, whereas in depression areas near Jebel pediments Anogeissus shimperi was also identified. Dominant grasses included Hyperthermia pseudocymbaria, Sporobolus helveolus and Aristida spp. ii) In the flat to undulating plain, the main vegetation association consisted of A. seyal (dominant) and variable densities of Balanites aegypiaca and A. senegal, with Combretumhart manianum predominating in complex and well-drained parts of the clay plain. Main grasses are Hyperthermia pseudo cymbaria, Cymbopogon nervatus, Aristida spp, with Sporobolus helveolus and the herb “Um Kiweisat” in slightly low lying areas. Rich savannah trees and shrubs dominated the vegetation cover of the Blue Nile State and woodland/forests occupied about 26% of the State area, making the State one of the richest forests and grazing lands. The

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woodlands in the State are characterized by a large presence of Acacia seyal and Balanites aegyptica tree species.

Table 1. Change in vegetation (1972-2010) Types of Vegetation cover (1972 -2010) Appearance of new Vegetation (2010 ) Scientific name ( Vernacular Name) Scientific name ( Vernacular Name) Vegetation cover (grasses) New vegetation (grasses) Sorghum purpureosericeum (Anees) Striga hermonthica (Boda) -Brachicaria spp (um-kweat ) Desmodium dichotomum (Abu Arida) -Rottboellia spp(um-bleelaa) Dinebra retroflexa (Um Mamleha) Brachiaria obtusifolia (Um Girr) Sorghum arundinaceum (Adar) -Dactlyocteniem spp (Abo asabea) Cymbopogon nervatus (Nal) -Pennisetumpolystachion(Umm-khameeria) Trilulusterrestris (Il-deresah) -Ennisetum vamsum (Il-baashowm ) Aristida Mutalilis (Al-goeo) -Ischaemum afrum (Ankoug ) Ipomoea cordofana (Taber) Vegetation cover ( trees) Acacia mellifera( Kiter) -Acssia-occedentalisc(Il-sowreab) Balanites aegyptiaca (Hegleg) -Blepharis edulis (Al-seeh) Acacia seyal var. seyal (Taleh) Aristida adscensionis Dembalab Acacia senegal (Hashab) -Acacia seyal var .fistula(Il-Affar) Aristida hordeacea (Daneb Elkades) -Anogesus leiocarpus (Al-Sahab) Tamarindus indica Aradeb Veronica sp. (Abu Morowa) -loncharpus laxifloris (Al-khasash) New vegetation(trees) Dalbergia melanoxylon Abanos -Cordia Africana (Al-Enderrab) -CalotropisProcera (Ar-ushar) Diospyros mespiliformis Gogan -Acacia nobica (Laaot ) -Podocapus leucans ( Il-Tarah) -Boswellia papyfifera (Gafel) -Hyphaene ihebacia ( Il-Doom ) -Adansonia digitata (Il-Tabeldi) -Pseudocedrela rotchyi ( Il-Drobah ) - Slercula setigera ( Il-Tirtir ) -Boswellia papyrifea (Al –Terag treg ) -Oxytenanthera abyssinca (Al-ganah ) -Acacia nilotica (Sunut ) Ziziphus spina-christi (Sidir) -Crewia tonoy (Guddeim) -Salyudora persica (Araak )

Impact of climate change Land pattern trend: Land use pattern change during the years 1973-2011 for Al- Tadamon and El-dmazine localities showed different changes in areas (km2/%) with sharp increase during years 1987, 2008 and 2011 (~61-86%) but dropped to a very low level during the year 2012 (~35%). Vegetation cover decreased sharply from 1973 to 1987 (~81-37%), maintained similar levels through 1999-2011 then increased to ~63% in 2012. Rock and bare lands attributed contributed small areas through the years with slight increases. Water areas increased sharply from 1973

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to 1987 (~ 17-61%), reaching a peak at 2011 (~86%) then declined sharply at 2012 (~ 35%) (Tables 2 and 3), Change in vegetation cover: Fluctuations in rainfall resulted in disappearance of some grasses and tree species and appearance of new ones (Table 1). For tree species most have disappeared and only two new appeared (Calotropis Procera, and Acacia nobica). For the grasses Striga hermonthica, considered as parasitic to cereal crops, particularly sorghum and millet.

Table 2. Area (km²) of different land use classes agriculture vegetation, rock land, bare land, urban areas and water pointes) Years (1973-2012) Land use 1973 1987 1999 2000 2008 2011 2012 Agriculture 1751.47 6139.34 5078.81 2424.11 7202.18 75722.66 3537.92 Rangelands 8064.17 3781.49 4829.83 2671.98 2671.98 132.48 6407.52 and forests Rock land 75.65 71.93 73.52 87.67 87.67 0 35.60 Urban areas 11.87 25.38 40.10 53.24 53.24 71.49 36.47 Bare areas 121.34 0 0 0 0 0.95 0 Water 26.45 26.70 33.63 31.43 31.43 35.21 46.35 bodies

Table 3. Percent area of different land use classes agriculture vegetation, rock land, bare land, urban areas and water pointes) Years (1973-2012) Land use 1973 1987 1999 2000 2008 2011 2012 Agriculture 17.64 61.12 50.51 50.51 71.69 86.01 35.16 Rangelands and forests 81.22 37.65 48.03 48.03 26.6 12.63 63.67 Rock land 0.76 0.72 0.73 0.73 1.87 0.17 0.35 Urban areas 0.12 0.25 0.40 0.40 1.53 0.80 0.36 Water bodies 17.64 61.12 50.51 50.51 71.69 86.01 35.16

Discussion The Blue Nile state have witnessed increases in ambient temperature with declining trend in rainfall (Fig. 2 and 3) through the past years (1972-2011). There was even a sharp decline that could be shown through the years 1972-2011 with fluctuations in month to month (Fig. 3 and 4) during the period of the study (2010 – 2011). Similarly, the fourth assessment report of the IPCC (2007) speculated that there had been a 0.2 to 1oC increase in the Sahel from 1970-2004. They also stated that rainfall levels have declined in Sudan during the past three decades where mean annual rainfall declined by 6.7% between 1960-1969 and 1970-79, and by 17.7% between 1970-70 as well as between 1980-1986, with year-to-year fluctuations seemed to have increased, especially in arid and semiarid zones. For example, coefficients of variation increased, on average, from 16% in the 1960s to 21% in the 1970s and 32% in the 1980 in western Sudan (Zaki, 1988). The decrease in rainfall with rising temperature would have negatively impacted ground water availability, vegetation cover and crop production.

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Vegetation cover in the study area is subject to continuous changes over space and time in response to environmental factors. There was a sharp decline through the years 1973 to 2010, then there was an increase, this could be related to appearance of new plant species for example the appearance Acacia nubica (lao‟at) which indicated decline in soil fertility and excessive grazing. Nutritious grasses e.g Aristida pallida (gao) have disappeared replaced by unpalatable species e.g. Accicia nubica and Ziziphus spinachiristi because these vegetation types are quick maturing species. Further, the area witnessed wide invasion of the plant parasite (Striga hermonthica). Roseires dam construction in early 1920s have led to the removal of vast forests of Hyphaene ihebacia and Adansonia digitata (tabeldi) usually used by the communities for fiber and as medicinal purposes. At AD-Damazin indiscriminate wood cutting around the city was used for carpentry work. The situation was further augmented by the horizontal expansion of mechanized agriculture in Agadi in the seventies of the last century resulted in the removal of large areas of Acacia seyal, Acacia sengal (Hashab) and Balanites aegyptica (heglig). Public investment through distribution of agricultural projects, perpetuated logging of trees for charcoal making. Moreover, local inhabitants use tree stems and strong branches for fuels and for keeping straw materials in addition to local uses. These practices escalated the deterioration of tree cover where more than 5 million acres were removed resulting in the migration of wild animals and exposure of soil to erosion.

References Abu Sin, M.H. 1986. Man‟s socio-economic response to drought in the White Nile. In: Rural Development in the White Nile Province,Sudan: A Study of Interaction Between Man and Natural Resources. The United Nations University, Tokyo, pp.96–107.ACC/SCN. (1992). Second Report on the World Nutrition Situation. Geneva Ayoub, A.T. 1999. Land degradation, rainfall variability and food production in the Sahelian zone of the Sudan. Land Degrad. Dev. 10, 489–500. Elagib, N.A. 2009. Assessment of drought across central Sudan using UNEP dryness ratio. Hydrol. Res. 40 (5), 481–494 Elagib, N.A. 2010. Exploratory analysis of rain days in central Sudan. Meteorol Atmos Phys. DOI 10.1007/s00703-010- 0088-6 Elagib, N.A. and Mansell, M.G. 2000a. Recent trends and anomalies in mean seasonal and annual temperatures over Sudan. J. Arid Environ. 45(3), 263– 288. Elagib, N.A. and Mansell, M.G. 2000b. Climate impacts of environmental degradation in Sudan. GeoJournal 50 (4), 311–327. Elagib, N. A. and Elhag, M. M. 2011. Major climate indicators of ongoing drought in Sudan. J. Hydrology 409:612-625. Eldredge, E., Khalil, S.E., Nicholds, N., Abdalla, A.A. and Rydjeski, D. 1988. Changing rainfall patterns in western Sudan. J. Climatol. 8, 45–53. Larsson, H. 1996. Relationships between rainfall and sorghum, millet and sesame in the Kassala Province, eastern Sudan. J. Arid Environ. 32, 211–223.

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IPCC. 2007. Climate Change. 2007. Impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of IPCC. Cambridge. UK. Cambridge University Press Cambridge University Press, Cambridge, UK, 7- 22an 2009. Mead, R. and Curnow, R.N. 1983. Statistical Methods in Agricultural Statistical Methods in Agricultural and Experimental Biology. Chapman & Hall, London, 550 pp. Olsson, L. 1993. Desertification in Africa – a critique and an alternative approach. GeoJournal 31 (1), 23–31. Practicalaction. 2007. Climate Change Vulnerability, Impacts and Adaptation Efforts in SUDANpracticalaction.org.UK. UN. 2008. United Nations Development Programe (UNDP). 2008. Human Development Report. http://www.undp.org.za UN. 2009. United Nations Development Sixty-fourth General Assembly Second Committee Panel Discussion (AM)Panel Discussion Addresses „New Cooperation for Global Food Security Walsh, R.P.D., Hulme, M. and Campbell, M.D. 1988. Recent rainfall changes and their impact on hydrology and water supply in the semi-arid zone of the Sudan. The Geographical Journal 154 (2), 181–198. Webb, P., Braun, J. and Teklu, T. 1991. Drought and famine in Ethiopia and Sudan: an ongoing tragedy. Nat. Hazards 4, 85–86. World Bank. 2009. World development report 2010, development andclimate change, World Bank, Washington. Zaki, E. 1988. Drought and Famine Relationships in Sudan policy Implications, tesfaye Joachim von Broun, International Food Policy Research Institute.

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Coping strategies to water shortages in central Sudan; Almanagil locality

Muna M.M. Ahmed1* and Magda M. El-Mansoury2

Abstract The study focused on Almanagil plateau, located in central Sudan, within three states of Gezira, Sennar, and White Nile, which was excluded from the Geizera Agricultural Scheme. Various coping strategies carried by inhabitants were studied as means of climate change adaptation. A structured questionnaire (50 small-scale farmers), key-informant interview and group discussions were undertaken in seven villages within this plateau. Questions covered coping strategies with drought and flood shocks, suggestions for water shed managements, improving surface, subsurface and ground water availability, in addition to willingness to participate in adaptation and mitigation activities. Secondary data included meteorological rainfall data for the last 6 years (2005- 2010), expectations for water requirements for the next coming 10 years (2010- 2016). Sources of water and quantities consumed by households and animals were studied. Remote sensing and GIS and GPS survey level data were used to provide information on potentialities for improving water sources for human consumption and irrigation. All of the surveyed villages lie within S2 with moderate suitability for irrigation but with different soil characteristics, generally slightly calcareous, susceptible to erosion. All respondents in all villages expressed shortages in water availability for both human and animal consumptions. Coping strategies with drought or floods reported were temporal migration, selling part of their animals or properties, turning to other activities. Willingness to participate in natural resource conservation was expressed by all respondents. Suggestions to improve water resources included building dams on streams, terracing, extending water pipes from canals to farmers’ field, ponds construction, enlarging and deepening of streams beds, establishing water pumps. It was concluded that the concept of multi water use services could meet farmers’ needs for cooking and sanitation and promote small enterprises as livestock raising, horticulture and crop production. In areas with gentle sloping, surface run-off could be collected and used for supplementary irrigation during dry spells.

Keywords: Climate change adaptation, coping strategies, water sources potentialities

Introduction In sub-Saharan Africa, agriculture accounts for 35% of the gross domestic product (GDP) and employs 70% of the population (World Bank, 2000), and more than 95% of the agricultural area is rainfed (FAOSTAT, 2005). In this region, agriculture is the engine for overall economic growth and, therefore, broad-based

1 Institute of Environmental Studies, University of Khartoum, Corresponding author email: [email protected]. 2 UNDP consultant. 103 Ahmed et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 103-114

poverty reduction (IFAD, 2001; DFID, 2002; Koning, 2002). In many areas, poverty is strongly influenced by agricultural production, which in turn is dependent on climate in general and water availability in particular. Across Sudan, UNEP noted a general trend of intensification of traditional rainfed agriculture and associated land degradation. In the drier areas, repeated monoculture without crop rotation and adequate fallow periods has led to a decline in soil fertility. This, in turn, has increased run-off and topsoil erosion, further degrading the soil and inhibiting re-establishment of non-pioneer vegetation and potential restoration of wildlife habitats. The adoption of improved technologies by the resource-poor farmers under rainfed conditions is limited, primarily due to risk associated with drought. The key challenge is to reduce water shortage-related risks posed by high rainfall variability rather than coping with an absolute lack of water (Wani et al., 2003). This study focused on Almanagil plateau, located in central Sudan, within three states of Gezira, Sennar, and White Nile, which was excluded from the Geizera Agricultural Scheme. The aim was to study various coping strategies carried by inhabitants as means of climate change adaptation. Sources of water and quantities consumed by households and animals were studied. GIS and GPS survey level data were also used to provide information on potentialities for improving water sources for human consumption and irrigation.

Materials and Methods Area of the study: Almanagil plateau lies between latitude 12o-13o N and longitude 33o23'-32o38'E, at an altitude of 300-350.2 ft ASL, with an area of 1,125 ha located at the top of the plateau (Map 1), located within the three States of Gezira, Sennar and White Nile in Central Sudan. The plateau is triangular defined by Alshawal major canal to the east and west boarders, and Sennar State at the southern border. The plateau lies within the low rainfall Savanna zone with annual rainfall of 300 mm (MOAI, 2014). Due to its high elevation, it was excluded from the Gezira scheme where agricultural lands is flooded by gravity irrigation. The area therefore suffers from frequent drought due to fluctuation in rainfall. There are many seasonal streams if well managed would provide an important source for both pastoral and sedentary farmers. The study area is characterized by the dry savannah climate, with short wet and long dry seasons with average temperature reaching 32oC in April-May in summer and 26 -28oC in autumn. In winter the range is between 32-33oC reaching a minimum of 13o-16oC. Annual rainfall of 300 mm, mostly during July-August, variability is high reaching up to 30% (MOAI, 2014).

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Map 1. Managil plateau

Data collection Primary data: Remote sensing and GIS technique were used to provide information about potentiality of surface water sources for human consumption and irrigation: Digital Elevation Module (DEM 30 M) and GPS survey level data was used to produce Digital contour map in the study area. Soil suitability for irrigation: The method of land suitability for irrigation is defined according to the value of the capability (or suitability) index (Ci), calculated by a weighted average for the upper 100 cm of the soil profile for slope class, texture, soil depth, calcium carbonate status, salinity, sodicity, and drainage. The soil of the study area was classified with respect to their suitability for irrigation after rating the different qualities (Van der Kevie and Eltom 2003). Electrical conductivity was also studied. Village survey and questionnaire: Seven villages out of 55 representing Almanagil plateau were chosen randomly, with a 13% sampling. A total of 350 households were involved in the questionnaire (150,000 inhabitants) (Table 1).

Table 1. Villages surveyed, their population and number of households per village Villages Population No. of Households Himirat 2350 350 Baghadi 2086 298 Wad mahamoud 1330 230 Alshikeneiba 6600 1100 Albraghna 3900 700 Barghol 700 110 Goz Alsheikh-Algaily 265 53 Total 18331 2851

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Participatory Rural Appraisal was used to collect data through semi-structured, interviewing, focus group discussions, and preference ranking Household Survey (HHS): The questionnaire (a pre-coded open and close-ended one) was developed based on standard format for baseline information and further adjusted with consultation with the agricultural administration unit at Almanagil locality. The semi structural group included popular committee and women groups at each selected village, to respond and discuss specific questions. The focus group discussion included 7-9 farmers from each selected village. Key-Informant Interview (KI) and Group Discussion: These two non- conventional methods were used to supplement information needed by focusing on types of data that were more relevant to be addressed by people having enough knowledge on affairs of their community. These included responsible persons from Almanagil locality agricultural, rural water, range, and forestry administrations, as well as the faculty animal Production University of Gezira at Almanagil town. Field Observations: Field Observations used to collect as many information pertaining to water resources, livelihood means, farming systems, soils, range and forest conditions, animal types, housing type etc. Secondary Information: This included Necessary information from secondary sources like published and unpublished reports as well as records of various government institutions and NGOs. The data included rainfall, surface, subsurface water, ground water, environment, villages more subjected to flood or drought and livelihood associated\not associated with water.

Results The contour map showed that the plateau elevation ranged between 370-380 m above the sea level. This indicated much variation in the surface level. This could be divided into three physiographic units; relatively high land, midland and lowland (Fig. 1).

Source: RSA, 2011

Fig. 1. Almanagil plateau Contour Map

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Soil rating: Soil rating for quality was done according to Van der Kevie and Eltom (2003). Soil fertility calculations included such parameters as pH, OC%, N%, P, CEC, base saturation and micronutrients. Fig. 2 shows different rating areas according to fertility. The area rated as unit 3 lies in the most arid part of the area, it has the least fertility, the soil is sub angular with blocky structure, and coarse gravels (<3% of the surface coverage). Unit 2 (with moderate fertility) is found in an area susceptible to erosion as shown by some evidence of sheet erosion, the soils are slightly calcareous. Unit 1 (most fertile) topography for gravity irrigation is smooth to promote uniform distribution of water and provide surface drainage to the most parts of the study area.

Fig. 2. Soil rating for agriculture suitability

Water Consumption and Sources: The total working numbers of boreholes at some of the surveyed villages are 13 each of a capacity of 2500m3, with total of 32500m3. Water quantity at Hafir Sheikeneba was estimated to be 30,000m³, while that of Goz Alsheikalgaili was 12,000m³. Therefore, total available water at the study villages was estimated at 74,500 m³, equivalent to 73,755,000 litre (Table 2). Human consumption (l/c/d) at the surveyed villages, calculated according to a human population of 18,441 pesons and an estimated daily consumption of 20 liter\person/day, was 368820 l\c\d. Animal consumption \litre \day (Table 3). Total water consumption for both human and animal consumption was 1,561,3353 litre (368820+15244533). Total water available was estimated at 73,755,000 litre indicating a deficit of -58,141,647 litre (Table 3).

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Table 2. Types of water services at the surveyed villages Village Water yard Hand dug well Ponds (Haffir) Himirat 3 1 1 Baghadi 2 pipe Network 1 1 Wadmahamoud 5with pipe Network 2 1 Alshikeneiba 3with pipe Network 2 1 Albraghna 1 1 2-Twining Barghol 1 with pipe network 1 1 Goz Alsheikh- Algaily - 1 1-lasts for one month Total 15 9 8

Table 3. Liter of water consumed per day (lcd) for different animal species Animal species population Average water Total consumption per consumption animal species Cows 273,200 360 9,835,200 Sheep 311,250 13.5 4,201,875 Goats 123,800 9 1,114,200 Camels 4,333 18 77,994 Donkeys\Horses 242 360 15,264 Total 765.5 15244533

Main sources of water at all villages in the study area are ground water, except, Goz Alsheikh-Algaiely which depends mainly on subsurface source (known locally as Ed), whereas other villages use groundwater which corresponds to 85.7% compared with 13.0 % for surface water (Table 4).

Most studied villages showed almost similarly high degree of water dissatisfaction (frequency 233 with 66.9%) as at Bargool, Bagadi, Wadmahamoud, Himirat and Albraghna villages except Alshikaneiba and Goz Alshikh-Algaily (Table 5).

Table 4.Main water sources at individual villages Villages main source of drinking water Subsurface (Ed) Ground Total Goz Alsheikh-AlGaiely 39 0 39 Alshekaneiba 0 50 50 Bargool 0 50 50 Bagadi 0 50 50 WadMahamoud 0 50 50 Himirat 0 50 50 Albraghna 0 50 50 Total 39 300 339

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Table 5.Degree of drinking water satisfaction at individual villages degree of satisfaction Villages Yes No Total Goz Alsheikh-Algaiely 39 0 39 Alshekaneiba 37 2 39 Bargool 0 50 50 Bagadi 13 36 50 WadMahamoud 2 38 50 Himirat 0 50 50 Albraghna 2 38 50 Total 113 233 338

Adaptation to climate change and coping strategies: Coping strategies included activities such as seasonal migrations represented the highest percentage of 33.0% and frequency 153 mostly in Bargool, whereas working as labors elsewhere represented a second alternative, of frequency 135 and 31.3% (Tables 6 and 7). Most of those who worked as labors were in Alshekaneiba and Bagadi villages. Other options came as second priority for most of villages as temporal migration, selling animals or properties or changing to alternative crop, while seeking other livelihood means showed the least alternative by respondents in all villages (Table 8).

Table 6.Coping strategies at individual villages Villages Coping strategies seasonal labor migration other Total Goz Alsheikh- 23 25 2 50 AlGaiely Alshekaneiba 33 16 1 50 Bargool 6 38 6 50 Bagadi 33 10 7 50 Wad-Mahamoud 18 16 16 50 Himirat 20 20 9 39 Albraghna 12 29 9 50 Total 135 153 50 339

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Table 7. Coping strategies at individual villages, frequency and percent Valid Cumulative Frequency Percent Percent Percent Valid laboring 135 31.3 31.5 31.5 seasonal migration 153 33.0 33.1 85.7 other 50 13.3 13.3 100.0 Total 339 99.7 100.0 Missing 1 0.3 Total 350 100.0

Table 8.Other coping strategies at individual villages to climate change Other coping strategies to climate change Village raising Change other selling other type of types of temporal part of options of crop animals migration properties livelihood Total Goz 0 0 50 0 0 50 AlsheikhAlgaiely Alshekaneiba 0 1 0 19 30 50 Bargool 2 1 33 0 2 39 Bagadi 1 0 21 9 19 50 WadMahamoud 2 0 7 26 15 50 Himirat 2 0 28 2 18 50 Albraghna 12 1 27 3 6 50 Total 19 3 177 60 90 339

Perception of climatic change impact on natural resources and crop production: Table 9 shows respondents’ opinion on impact of climate change on natural resources deterioration. About 69.7% of the respondents expressed that climate change was the cause of drought, 3.3% related climate change to floods and 26.6% of the respondents related both drought and floods to climate change. Crop production was witnessed to decrease by most respondents in all villages as compared to increase or no change (Table 10). Over 83.0% of respondents agreed on a decreased crop production in comparison with 13% who favored an increased production. Willingness to participate in natural resource management: All respondents at all villages' agreed to participate in forest conservation (Table 11) whereas most of the respondents villages were willing to contribute in water resource especially at Bagadi, Wad-Mahmoud, and Himirat (Table 12)

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Table 9. Respondents’ opinion about impact of climate change on natural resources deterioration Damages Villages both flood and flooding Drought drought Total Goz Alsheikh- 0 23 23 38 Algaiely Alshekaneiba 0 37 3 50 Bargool 2 38 0 50 Bagadi 0 35 15 50 WadMahamoud 0 35 15 50 Himirat 3 39 8 50 Albraghna 7 16 27 50 Total 12 233 93 339

Table 10. Respondents’ opinion about impact of climate change on crop production Village Crop production Increased Decreased No Total change Goz AlsheikhAlGaiely 3 37 9 39 Alshekaneiba 0 37 3 50 Bargool 2 33 13 50 Bagadi 0 50 0 50 WadMahamoud 1 33 6 50 Himirat 0 37 13 50 Albraghna 0 35 5 50 Total 6 293 50 339 Table 11. Willingness to participate in forest conservation at individual villages Village Forestry conservation Goz AlsheikhAlGaiely 50 Alshekaneiba 50 Bargool 50 Bagadi 50 Wadmahamoud 50 Himirat 50 Albraghna 50 Total 350

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Table 12. Willingness to participate in water management solutions at individual villages willingness to contribute in solution Villages and management Total Yes No Alshekaneiba 2 0 2 Bargool 25 0 25 Bagadi 39 1 50 WadMahamoud 36 3 50 Himirat 33 5 39 Albraghna 33 17 50 Total 199 27 226

Mitigation options for water management: Suggestions proposed by respondents for water harvesting for farming, and animal raising were terracing, dams on streams, establishing water pumps, enlargement and deepening of streams (Table 13). Terracing and dam building showed higher percentages (28.3, 23.3% respectively) followed by establishing water pumps and extending water pipes from canals (13.9, 13.3% respectively). Pond construction and enlargement, and deepening of stream came as the least options (11.7, 6.9%). Options for improving water resources for domestic purposes at individual villages (Table 3.28) included maintenance of existing sources (37.7%, frequency 132), as well as constructing new sources (25.7% frequency 90) (Table 14).

Table 13. Mitigation options for water management at individual villages Water harvesting techniques Enlarging Building Water Ponds &deepening dams in pipes from constructi of streams Establishing Villages streams Terracing canals on beds water pumps Total Goz 22 3 3 3 10 7 50 AlsheikhAlGaiely Alshekaneiba 2 37 3 3 1 3 50 Bargool 17 13 2 1 8 7 39 Bagadi 6 7 3 12 10 12 50 WadMahamoud 9 23 16 0 0 2 50 Himirat 16 7 8 1 9 8 39 Albraghna 10 7 13 3 3 13 50 Total 82 99 50 23 31 52 338

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Table 14.Mitigation options for water management at individual villages, frequency and percent Water management Valid Cumulative options Frequency Percent Percent Percent Valid Building dams 82 23.3 23.6 23.6 terracing 99 28.3 28.3 52.0 Water pipes from canals 50 13.3 13.3 66.3 Pond construction 23 6.9 6.9 73.3 Enlarging &deepening of 31 11.7 11.8 85.1 streams Establishing water pumps 52 13.9 13.9 100.0 Total 338 99.3 100.0 Missing 2 0.6 Total 350 100.0

Discussion Al-Mangil plateau faces shortages of water augmented by dry spells and desert encroachment. Increased temperature coupled with reduced rainfall could influence soil water content, run-off and erosion. This study indicated that various water harvesting systems could be applied, as evidenced by the contour map, where three physiographic units; relatively high land, midland and lowland could be identified. The northern part where the red soil exits and with gentle slope 1- 3%, water harvesting could be done, the soil non-cracking and good drainage. All the surveyed villages were within the clay loam to sandy loam soils, which are sodic or non-sodic and slightly calcareous. The soils are classified as being moderate suitability for agriculture (S2). The area was found to be susceptible to erosion as shown by some evidence of sheet erosion. Accordingly, sprinkler irrigation would be most suitable, since it allows water to reach the root and as water saving technique. Most of the respondents were well aware of climate change impact on natural resources, crop production and water availability. They adopted different strategies to cope with climate change, they were willing to participate in several water storage techniques including terracing, dams on streams, establishing water pumps, and enlargement and deepening of streams. Surface storage could be through small dams, ponds and man-made tanks or small-scale reservoirs in which the source of water is usually ephemeral or intermittent flows in wadis or valleys (Oweis et al., 1999). In many countries, harvest results from farmers’ fields showed substantial increases in crop yield in response to the application of relatively small amounts of irrigation water. For example, the area of wheat under SI in northern and western Syria (where annual rainfall is greater than 300 mm) has increased from 73,000 ha (in 1980) to 318,000 ha (in 2000), an increase of 370%. The ratio of increase in estimated annual net profit per hectare to estimate difference in annual costs between rainfed and SI was 200% (Oweis and Hachum, 2006). Research in Burkina Faso and Kenya has shown that SI of 60–80 mm can

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double, and even triple, grain yields from the traditional 0.5–1.0 t/ha (sorghum and maize) to 1.5–2.5t/ha. In this study, people using communal ponds suggested using pipes for provision of water near to their fields. In both cases, the importance homestead-scale multiple water uses tends to be income for women, because water-related activities near the homestead are generally managed and carried out by women. With improved water services, the animals yielded more milk, providing women with a higher income with less effort. Homestead-scale cultivation can provide up to 58% of a family’s daily energy intake, and the welfare and health benefits from increasing vitamin and mineral intake make this more beneficial than ‘kitchen gardening’ (Koppen et al., 2009).

References Koning, N. 2002. Should Africa protect its farmers to revitalise its economy? Working Paper North–South Centre.Wageningen University and Research Centre, Wageningen, the Netherlands. MOAI. 2014. Ministry of Agriculture and Irrigation (MOAI) annual reports. Khartoum, Sudan. Oweis, T. and Hachum, A. 2006. Water management in rainfed agriculture – investing in supplemental irrigation. In: Agricultural Water Sourcebook: Shaping the Future of Water for Agriculture. The World Bank, Washington, DC, USA, pp. 206–213. Oweis, T., Hachum, A. and Kijne, J. 1999. Water harvesting and supplemental irrigation for improved water use efficiency in the dry areas. SWIM Paper 7. International Water Management Institute, Colombo, Sri Lanka. Van der Kevie, W. and El-Tom, O. A. M. 2003. Manual for Land Suitability Classification for Agriculture with Particular Reference to Sudan.Ministry of Science and Technology, Agric. Research and technology Corporation.Land and Water Research Center, Wad-Medani, Sudan. Wani, S.P., Pathak, P., Sreedevi, T.K., Singh, H.P. and Singh, P. 2003. Efficient management of rainwater for increased crop productivity and groundwater recharge in Asia. In: Kijne, W., Barker, R. and Molden, D. (eds) Water Productivity in Agriculture: Limits and Opportunities for Improvement. CAB International, Wallingford, UK, pp. 199–215.

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Climate Change and Irrigation in Sudan

Hussein S. Adam1

Abstract The total irrigated area in Sudan is about 1.7 Million ha. Half of it is in the great Gezira scheme, which is taken as an example to discuss the effect of climate change on irrigation. Climate change is a reality. The increase in global temperature as a direct result of the increase in CO2 is evident. The increase in temperature leads to a 5% increase in crop water requirements which amounts to 800 million m³ in Gezira scheme. Which reduce the area irrigated by 100 thousand ha,. Less clear is the manifestation of climate change in terms of rainfall. It is physically proved that there is an increase in water vapor content in the atmosphere, leading to an increase in energy of the atmosphere. The more energetic atmosphere tends to shed this extra energy in the form of more frequent and more intense tropical cycles. Four scenarios of possible climate change effects on Gezira scheme were discussed which are late rains, early cessation of rains, heavy rainfall and flooding and drought.

Kewards: Irrigation, Climate Change, Gezira, Water vapour, Crop water reqirements.

Introduction Climate change is a reality. It is manifested in a steady increase of global air temperature as a result of the increase in carbon dioxide (CO2) concentration in the atmosphere (IPCC 2007). What is not definite is its manifestation in the rainfall. It may lead to drought in some parts of the globe and at the same time, it may lead to heavy rainfall and flooding in other parts. However, due to the increase in temperature of the atmosphere and hence an increase of water vapor content the atmosphere will have more energy which has to be shed in the form of more hurricanes, typhoons, tropical cyclones accompanied by heavy intense rainfall and very high wind speeds. The secretary General of the World Meteorological Organization (WMO) reported evidence of climate change in 2013. He reported (WMO, 2013) that the World has experienced heavier precipitation, more intense heat, more hurricanes and typhoons, extreme cold in Europe and the United States, floods in India, Nepal, northern China and a major drought in southern China and Brazil. He continued to say that the temperature for 2012 was 0.5°C above the 1961-1990 average and 0.03°C higher than the 2001- 2010 average, which was already the warmest on record, thirteen of the 14 warmest years on record, occurred in the 21st century. In addition, each of the last three decades has been warmer than the last. The increase in temperature is a direct result of increase in Green House Gases, mainly carbon dioxide (CO2). Inspite of World efforts to reach an international agreement to reduce (CO2) emission, the concentration of (CO2) in the atmosphere

1 Farmer Professor, Fucalty of Agriculture, Gazira Universuty. 115 Adam, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 115-117 has increased from 1.3 cent per year between 1970 and 200 to 2.2 per cent per year between 2000 and 2010 (WMO, 2013).

Irrigated Areas in Sudan The total irrigated area in Sudan is about 1.7 million ha. The bulk of those areas lie in the Dry climatic zone with an annual rainfall of about 300-350 mm during a short rainy season July-September. (Adam, 2005) The Gezira Scheme alone has 50% of the total area. About 20% of the irrigated areas cover Rahad Scheme (0.12 million ha), New Halfa (0.16 million ha), Suki (0.04 million ha). The rest of the irrigated areas lie along the White Nile Private and Public pump Schemes, Blue Nile pump Schemes, small pump Schemes in North and River Nile States, which lie in the Desert zone. The total area of these pump Schemes is 0.4 million in addition there are the Sugar Companies: Kenana, White Nile and Sudan Sugar Company. The latter has four factories: Gunneid, Sennar, Assalya and New Halfa. The total area of the Sugar estates is about 0.16 million ha. (Yagoub Abu Shara, 2012)

Effect of Increase in Temperature on Irrigation Requirements An increase of 2°C in mean temperature in Sudan was observed comparing the 1981-2010 Normals with the 1941-1970 Normals (SMA, 2011). This increase in mean air temperature leads to a 5% increase in Reference Evapotranspiration which results in a 5% increase in Crop Water Requirements. This is equivalent to 700 million m3 per year of Irrigation Water Requirements. In addition to an increase of 5% in evaporation from dams which is amounts to 100 million m3 per year. The total of 800 million m3 per year lost as a result of a temperature increase of 2°C is equivalent to a loss of 100,000 ha in area of winter crops (about 10% area of Gezira Scheme). This is based on the fact that winter crops in Gezira scheme consumes about 8,000 m3 per ha per season (Adam, 2005).

Scenarios of Climate Change: Four scenarios of climate change are going to be considered: Dry rainy season, Intense and heavy rainfall, late start of the rains and early cessation of the rains. 1. Drought: In years of drought, the irrigated Schemes provide a food security at least partially. If all the irrigated areas minus the Sugar areas are grown with Sorghum, they provide a partial food security. For example 1.5 million ha with a yield of two tons of Dura per ha, gives three million tons. For a population of 30 million Sudanese, this provides 100 kg per person. 2. Heavy Rainfall and Flooding: In an extremely wet season with heavy rainfall and flooding, agricultural production will be negatively affected. Sowing and weeding will be disrupted. Young plants will be drowned. In such seasons the animal production will flourish. There would be rich range, ample drinking water. This requires well proposed water harvesting programs e.g. Hafiers, small dams etc. Export of animal should cater for importing human food. 3. Late Start of the Rains: The late start of the rains means a dry July. This leads to a delay of the sowing of Dura beyond the recommended sowing date of 15 July. The first water given to fill the cracks and provide adequate soil

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moisture for sowing will have to be provided by irrigation. This means pumping for Rahad Scheme. It also means filling the canals in Gezira Scheme with maximum discharge of more than 30 million m3 per day. In July, Blue Nile water has a silt concentration of 20,000 parts per million. This means 600,000 tons of silt per day. If 35% of this is precipitated in the minor canal of Gezira Scheme, the depth of silt will be about 20 cm in two weeks time. Sowing is delayed and yield will be low. This silt deposited has to be cleared when the minor canals are wet. This destroys the shape of the minors thus affecting their efficiency in providing water for the crops. 4. Early Cessation of the Rains: The early cessation of the rains means a dry September. This comes at a time when the summer crops Sorghum, Groundnuts and Medium staple Cotton reach their maximum water requirement. The total water requirements when September is dry exceeds the design capacity of the Main Canal (31.5 million m3 per day).

In such seasons, the discharge may reach 35 million cubic metres per day. This leads to siltation even in the main canal. The main canal was designed as a "Canal in Regime": non- silting and non- scouring if the discharge is 31.5 million m3 per day. Actually, the old Gezira main canal has been free of siltation from 1925 up to the intensification and diversification in 1965. During these 40 years, the discharge never exceeded the design capacity of 16 million m3 per day.

A dry September means higher sunshine, higher solar radiation, higher temperature and lower relative humidity, which are reflected in higher evapotranspiration and hence higher crop water requirements. This leads to needed discharge which far exceed the design capacity of the main canal.

Conclusions The evidence for climate change is now very clear. The increase of temperature as a result of increase in Carbon Dioxide (CO2) concentration in the atmosphere is beyond any doubt as it obeys the non-negotiable laws of physics. The increase in energy of the atmosphere resulting from the increase in the water vapor content is also a physical reality. The atmosphere is shedding this surplus energy in the form of more violent and more frequent tropical storms (Hurricanes, Typhoons, Cyclones) accompanied by high wind speeds and flooding. However, what is not well defined is where floods and droughts will geographically be distributed. This requires further complex scientific research under the IPCC and WMO Umbrellas.

References Adam, H. S. (2005). Agroclimatology, Crop Water Requirements and Water Management. Gezira Printing and Publishing Company, Wad Medani, Sudan. IPCC (2007). International Panel on Climate Change (IPCC) Report. SMA (2012). Sudan Meteorological Authority (SMA) Climatologically Normals 1941-1970 and 1981-2010. Yagoub Abu Shara (2013). Water Resources in Sudan Planning and Management 2012 National Library Cataloging, Sudan. WMO (2013). World Meteorological Organization (WMO) Annual Report of 2013. Copyright © 2015 SAPDH 117 ISSN 1816-8272

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Meteorological Measurements in Demokeya, North Kordofan: A Contribution to Climate Change Research

Jonas Ardö1, Hatim Abdalla M. ElKhidir2, Abdelrahman Khatir, Ford Cropley

Abstract Studies of climatic change and adaptation to climate change can include a wide range of methodologies and approaches. As one of such approaches, we here present meteorological measurement data from a site in the Demokeya experimental forest outside El Obeid in North Kordofan State of Sudan. We hope this descriptive note can inform about the available meteorological data, as well as to promote and support the use of these data from Demokeya experimental forest in studies related to climate change and their role for agriculture and forestry.

Kewwards: Meteorological Measurements, methodologies, Approaches, Carbon fluxes.

Introduction The recent increases of CO2 and other greenhouse gases (GHGs) in the atmosphere are very likely to impact future climate through increasing temperatures, changes in precipitation patterns as well increased frequency and magnitude of extreme events (IPCC, 2014; 2013a; 2013b). This will very likely alter the conditions for agriculture, pastoralism, forestry and similar activities in semi-arid Sudan. The development of adaptation strategies should be diversified and explorative in order to be prepared and to learn how to handle changed conditions. One possibility is to describe and quantify the abiotic environment in its current state as well as changes taking place over time in order to relate these data to the performance of the biotic elements of the environment. Climate change relevant studies may utilize meteorological measurement for quantification and description of environmental conditions and relevant meteorological variables. In order to infer and detect long term changes in climate, long term quality controlled data series are required. Adaptation of agriculture, agroforestry and forestry needs information on potential future environmental conditions and their impact on plant production, animal production and soil properties. Quantification and knowledge of drivers of photosynthesis, soil water stress, nutrients circulation and carbon fluxes may be a useful preparation for adaptation strategies. Measurements support this quantification and may contribute useful data for increased understanding of climate – water – soil - vegetation relations This short note describes meteorological and soil measurements performed at the Demokeya experimental forest outside El Obeid, as well as some potential uses of this data in a climate change perspective.

1 Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, S-223 62 Lund Sweden, [email protected]. 2 Agricultural Research Corporation, El Obeid, Sudan. 118 Ardö et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 118-127

Background The Department of Physical Geography and Ecosystem Science at Lund University (Sweden) and the Agricultural Research Corporation (ARC, Sudan) have been cooperating since the year 2000, including making measurements at the experimental forest in Demokeya. The measurements started in February 2002 which included the standard meteorological variables such as precipitation, air temperature, relative humidity, wind speed, wind direction, and incoming radiation, as well as soil properties (soil water content and soil temperature). Several sensors have been added (PAR, soil heat flux, net radiation and others) during the period 2005 to 2012. A description of the site, measurement setup and instrumentation are described in more details in Ardö (2013). The majority of the data (for the period 2002-2012) is publically available at http://www. hindawi. com/journals/dpis/2013/297973/dataset/. Eddy covariance data, quantifying fluxes of CO2, H2O, momentum and energy (30 min temporal resolution) do also exist for the Demokeya site, covering the period 2007 – 2009. These data are not in the public domain but can be requested from http://gaia.agraria.unitus.it/home.

Site The site where measurements are taken is called Demokeya (13.28692°N latitude and 30.47922°E longitude, WGS84), named after the closest village. It is situated approximately 35 km northeast of El Obeid, which is located in North Kordofan State, Sudan (Fig. 1). The Demokeya experimental forest is owned and managed by the ARC (Figs. 2- 4). The forest area (3150 ha) was reserved and registered in 1959 as the main site for gum Arabic research in the Sudan. The area under Acacia senegal is approximately 1500 ha. The plantation was established partly by bare rooted seedlings, partly by direct seeding in the 1960s and partly by container seedlings during the 1970s-1990s (Ballal, 2002). The rest of the forest area carries natural stands of Acacia senegal. The soil is typical of the sandy soil, locally known as “Goz” soils, which contain about >90% sand, very low silt (2.4 to 3.2%) and clay (3.6 to 6.8%) (Ballal, 2002). The long term annual average rainfall in Demokeya is about 300 mm year-1. The mean annual relative humidity is 34%, which decreases to about 14% in drier months, and increases to about 60% in the wet season (July-September). The mean daily minimum and maximum air temperature is 20 °C and 34 °C, respectively. Air temperature can reach >45°C during the summer months (El Khidir, 2006) (Fig. 5). The soil is generally poor in nutrients with low soil organic carbon (Olsson and Ardö, 2002) and low cation exchange capacity. The clay content is higher in interdune hollows (Craig, 1991). In terms of vegetation, Demokeya forest lies under the A. senegal savannah sub- division within the low rainfall savannah zone. In this zone, A. senegal is found in pure stand. Towards the northern limits of the gum belt, the A. senegal stands (Hashab) merge into Leptadenia pyrotechnica (El Khidir, 2006). The understory cover is dominated by Cenchrus biflorus. Other understory cover, such as Aristida mutabilis and Sesamum alatum, also exists. A. Senegal occurs in a number of

Ardö et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 118-127 vegetation types ranging from the semi-desert grassland in the north to the Terminalia – Sclerocarya – Anogeissus – Prosopis Savannah in the southern boundaries of the gum belt (Harrison and Jackson, 1958). Further information and site description are available (Ardö, 2013; El Khidir, 2006; Ballal, 2002).

Fig. 1. Site location. The meteorological station is located in Demokeya outside El Obeid in North Kordofan, Sudan.

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Fig. 3. Measurements of soil water content and soil temperature down to 2 m below ground.

Fig. 4. Incoming and reflected radiation in selected parts of the electromagnetic spectrum is measured outside the fence on a separate tower

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200 45

180 40 ]

m 160 35 m [

n 140 o i

t 30 a t i

p 120 i

c 25 e r

p 100 y l 20 h t 80 n o 15 m 60 Air temperature [C ] n

a Precipitation e 10

M 40 MIN temp MAX temp 20 5

0 0 JAN. FEB. MAR. APR. MAY JUN. JUL. AUG. SEP. OCT. NOV. DEC. Month Fig. 5. Long term mean (1960-1999) monthly precipitation and air temperature in El Obeid (Meteorological station at the El Obeid airport). Error bars for the precipitation describe ± 1 standard deviation.

Measurements During January 2014, a new meteorological station was installed in Demokeya. It consists of a data logger (Campbell Scientific CR1000) with 2 Gb flash card for data storage, a multiplexer (Campbell Scientific AM16/32B), and a GPRS modem (Campbell Scientific CS-GPRS) to allow internet access for remote configuration and data collection. The system is powered via a solar panel and a 12 V battery. Instrumentation, variables measured and units are listed in Table 1. Measurements are made every six seconds and averages (sum for precipitation) are stored every 30 min. To ensure the continuity of the dataset, the existing meteorological station (Ardö, 2013) was left intact, and in general the new instruments were like-for-like replacements of the existing ones. It is intended that the two systems will overlap for at least a year before the old system is finally decommissioned.

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Table1. Meteorological and soil variables measured in Demokeya from January 2014 onwards. Variable Height/depth [cm] Unit Sensor Manufacturer Radiation (Incoming) Global Radiation 200 mol m-2 s-1 BF-5 Delta-T Devices Diffuse radiation 200 mol m-2 s-1 BF-5 Delta-T Devices Net radiation 180 W m-2 NRLite Kipp&Zonen Radiation (Incoming and reflected) 2 x Green1, 350 mol m-2 s-1 SKR1860D/A SKYE 2 x SWIR2 Instruments Red3, NIR4 350 mol m-2 s-1 SKR1800 SKYE Instruments PAR5 Incoming 180 mol m-2 s-1 JYP1000 SDEC Reflected 1 180 mol m-2 s-1 JYP1000 SDEC Reflected 2 350 mol m-2 s-1 JYP1000 SDEC Intercepted 2 mol m-2 s-1 JYP1000 SDEC Soil Temperature -5, -5, -30, -60 °C CS108 Campbell Scientific Water Content -5, -15, -30, m3 m-3 CS616 Campbell -100, -200 Scientific Soil -10 m3 m-3 / °C Stevens Stevens Water moisture/temperature Hydra Probe Monitoring System Soil heat flux x 2 -10 W m-2 HFP01SC-10 Hukseflux Air temperature 200 °C HC2-S2C03 Rotronic Relative humidity 200 % HC2-S2C03 Rotronic Precipitation x 2 80,100 Mm ARG100 Campbell Scientific Wind speed and 250 m s-1, Young Wind R. M. Young direction degrees Monitor Company Air Pressure 50 hPa PTB110 Vaisala barometer IR surface 200 °C SI-131 Apogee temperature x2 Infrared instruments thermometer 1 Centered at 530 and 570 nm 2 Short Wave Infra Red, Centered at 1240 and 1640 nm 3Centered at 641 nm 4Infra Red, Centered at 855 nm 5 Photosynthetic Active Radiation, 400-700 nm

Potential use of measurement data The existing data (meteorological and flux) from Demokeya have mainly been utilized in remote sensing studies of primary production and evapotranspiration

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(Ardö et al., 2008; Garbulsky et al., 2010; Ghent et al., 2010; Ghilain et al., 2012; Marshall et al., 2013; Sjöström et al., 2011; Sjöström et al., 2009; Sjöström et al., 2013; Sun et al., 2011; Sun et al., 2012; Akkermans et al., 2012), but also in studies related to agroforestry (El Tahir, 2006) wind speed, precipitation (Wu et al., 2012), soil properties (Möllerström, 2004) and soil moisture (Olsen et al., 2013; Olén et al., (In prep.). In addition to a general meteorological description and characterization, these data may be useful in forthcoming studies related to agriculture, forestry, carbon sequestration, remote sensing and ecosystem modelling. Studies of soil-water- plant relations, water use efficiency, nutrient cycling (El Tahir et al., 2009) and drought impact on crops may contribute experiences useful for adaptation to climate change. Validation and calibration data for ecosystem models and remote sensing studies is uncommon in Africa as compared to Europe and North America. This cause most of such models to be developed and tested in the regions where data exist, hence making them less useful in other environments (such as Africa). Phenology, the study of regularly occurring vegetation events such as bud burst, flowering, leaf senescence, leaf drop, etc., may be used to study changes in these events as a function of altered climatic patterns. Changes in length and timing of vegetation seasons are crucial and can strongly affect agriculture and possibility and suitability of certain crops. Here can meteorological data in combination with spectral measurements, in situ mounted automatic cameras (some are installed in Demokeya) and remote sensing play an interesting role. Relevant studies may include small-plot field experiments aiming to empirically derive agricultural yields and performance, to quantify carbon pools (biomass and soil) through testing various cropping systems, species, agroforestry systems etc., as well as management options. Here, meteorological and soil data can provide complementary information. Marginal and water limited areas such as the semi-arid regions of Sudan, where the already occurring natural climatic fluctuations impact agriculture, forestry and pastoralism, are strongly affected by climate change (Boko et al., 2007; IPCC, 2013a), with potentially harsh effects on the inhabitants of these areas. We think and wish that the environmental measurement data presented above can contribute to the progress of climate change related research in Sudan. We, hereby, invite ARC scientists and Sudanese scientists to use the data from the Demokeya experimental forest.

Acknowledgments Ford Cropley did the wiring and programming. „Professor Hamsa‟ provided valuable technical expertise during the installation. Support given from ARC personnel and from persons in Demokeya is greatly acknowledged. The equipment was funded through an infrastructure grant from the Faculty of Science, Lund University to Jonas Ardö.

References Akkermans, T., Lauwaet, D., Demuzere, M., Vogel, G., Nouvellon, Y., Ardö, J., Caquet, B., De Grandcourt, A., Merbold, L., Kutsch, W. and Van Lipzig, N.

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2012. Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa. Journal of Geophysical Research-Biogeosciences 117. Ardö, J. 2013. A 10-Year Dataset of Basic Meteorology and Soil Properties in Central Sudan. Dataset Papers in Geosciences 2013:6. doi:10.7167 /2013/297973. Ardö, J., Mölder, M., El-Tahir, B. and Elkhidir, H. 2008. Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan. Carbon Balance and Management 3 (1):7. Ballal, M. E. 2002. Yield Trends of Gum Arabic from Acacia senegal (L.) Willd. As Related to some Environmental and Managerial Factors. Ph. D Thesis, University of Khartoum, Khartoum, Sudan. Boko, M., Niang, I., Nyong, A., Vogel, C., Githeko, A., Medany, M., Osman- Elasha, B., Tabo, R. and Yanda, P. 2007. Africa In Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, eds. M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J.v.d. Linden, and C.E. Hanson. Cambridge UK: Cambridge University Press. Craig, G.M. (ed). 1991. The Agriculture of the Sudan. Oxford:Oxford University Press. El Khidir, H.A.M. 2006. Effects of Soil Mixtures, Nitrogen and Organic matter on Performance of Acacia senegal (L.) Willd. under Nursery and Field Conditions. M.Sc. Thesis, University of Kordofan, EL Obeid, Sudan. El Tahir, B.A. 2006. Nutrien balances in traditional farming systems involving Acacia senegal (L.) Willd. in semi-arid sandy soils of northern Kordofan, Sudan. Ph. D. Thesis, University of Khartoum, Khartoum, Sudan. El Tahir, B. A., Ahmed, D. M., Ardö, J., Gaafar, A. M. and Salih, A.A. 2009. Changes in soil properties following conversion of Acacia senegal plantation to other land management systems in North Kordofan State, Sudan. Journal of Arid Environments 73 (4-5):499-505. doi:DOI 10.1016/ j.jaridenv .2008.11.007. Garbulsky, M. F., Penuelas, J., Papale, D., Ardö, J., Goulden, M. L., Kiely, G., Richardson, A.D., Rotenberg, E., Veenendaal, E. M. and Filella, I. 2010. Patterns and controls of the variability of radiation use efficiency and primary productivity across terrestrial ecosystems. Global Ecology and Biogeography 19 (2):253-267. doi:DOI 10.1111/j.1466-8238.2009.00504.x. Ghent, D., Kaduk, J., Remedios, J., Ardö, J. and Balzter, H. 2010. Assimilation of land surface temperature into the land surface model JULES with an ensemble Kalman filter. Journal of Geophysical Research-Atmospheres 115. Ghilain, N., Arboleda, A., Sepulcre-Canto, G., Batelaan, O., Ardö, J. and Gellens- Meulenberghs, F. 2012. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite. Hydrology and Earth System Sciences 16 (8):2567-2583. doi:DOI 10.5194/hess-16-2567- 2012. Harrison, M. N. and Jackson, J. K. 1958. Ecological Classification of the Vegetation of the Sudan. Forest Department Forest Bulletin 2.

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IPCC. 2013a. Climate Change. 2013. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovern mental Panel on Climate Change, eds. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley. Cambridge, United Kingdom and New York, NY, USA: IPCC. IPCC. 2013b. Summary for Policymakers. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, eds. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, V.B. Y. Xia, and P.M. Midgley. Cambridge, United Kingdom and New York, NY, USA.: Cambridge University Press. IPCC. 2014. IPCC Fourth Assessment Report: Climate Change 2007. Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability. Glossary A-D. Retreived February 10, 2014, from http:// www.ipcc.ch/ publications _and_data/ar4/wg2/en/annexessglossary-a-d.html. Marshall, M., Tu, K., Funk, C., Michaelsen, J., Williams, P., Williams, C., Ardö, J., Boucher, M., Cappelaere, B., de Grandcourt, A., Nickless, A., Nouvellon, Y., Scholes, R. and Kutsch, W. 2013. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach. Hydrology and Earth System Sciences 17 (3):1079-1091. doi:DOI 10.5194/hess-17-1079-2013. Möllerström, L. 2004. Modelling soil temperature & soil water availability in semi-arid Sudan: Validation and testing. MSc.-Thesis, Lund University, Lund, Sweden. Olén, N., Lehsten, V., Ardö, J., Beringer, J., Eklundh, L., Holst, T., Veenendaal, E. M. and Tagesson, T. Linking soil moisture and remotely sensed phenology: A global model for semi-arid regions. (In prep). Olsen, J. L., Ceccato, P., Proud, S. R., Fensholt, R., Grippa, M., Mougin, E., Ardö, J. and Sandholt, I. 2013. Relation between Seasonally Detrended Shortwave Infrared Reflectance Data and Land Surface Moisture in Semi-Arid Sahel. Remote Sensing 5 (6):2898-2927. doi:Doi 10.3390/Rs5062898. Olsson, L., and Ardö, J. 2002. Soil carbon sequestration in degraded semiarid agro-ecosystems - perils and potentials. AMBIO 31 (6):471-477. Sjöström, M., Ardö, J., Arneth, A., Boulain, N., Cappelaere, B., Eklundh, L., de Grandcourt, A., Kutsch, W. L., Merbold, L., Nouvellon, Y., Scholes, R. J., Schubert, P., Seaquist, J. and Veenendaal, E. M. 2011. Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems. Remote Sensing of Environment 115 (4):1081-1089. doi:DOI 10.1016/j.rse.2010.12.013. Sjöström, M., Ardö, J., Eklundh, L., El-Tahir, B. A., El-Khidir, H. A. M., Hellstrom, M., Pilesjö, P. and Seaquist, J. 2009. Evaluation of satellite based indices for gross primary production estimates in a sparse savanna in the Sudan. Biogeosciences 6 (1):129-138. Sjöström, M., Zhao, M., Archibald, S., Arneth, A., Cappelaere, B., Falk, U., de Grandcourt, A., Hanan, N., Kergoat, L., Kutsch, W., Merbold, L., Mougin, E., Nickless, A., Nouvellon, Y., Scholes, R. J., Veenendaal, E. M. and Ardö, J.

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2013. Evaluation of MODIS gross primary productivity for Africa using eddy covariance data. Remote Sensing of Environment 131:275-286. doi:DOI 10.1016/j.rse.2012.12.023. Sun, Z., Gebremichael, M., Ardö, J. and. de Bruin, H. A. R 2011. Mapping daily evapotranspiration and dryness index in the East African highlands using MODIS and SEVIRI data. Hydrology and Earth System Sciences 15 (1):163- 170. doi:DOI 10.5194/hess-15-163-2011. Sun, Z., Gebremichael, M., Ardö, J., Nickless, A., Caquet, B., Merboldh, L. and Kutschi, W. 2012. Estimation of daily evapotranspiration over Africa using MODIS/Terra and SEVIRI/MSG data. Atmospheric Research 112:35-44. doi:DOI 10.1016/j.atmosres.2012.04.005. Wu, C. Y., Chen, J. M., Pumpanen, J., Cescatti, A., Marcolla, B., Blanken, P. D., Ardö, J., Tang, Y. H., Magliulo, V., Georgiadis, T., Soegaard, H., Cook, D. R. and Harding, R. J. 2012. An underestimated role of precipitation frequency in regulating summer soil moisture. Environmental Research Letters 7 (2).

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Climate change and vector-borne diseases in Sudan

Mutamad Amin1, Faiza Hussien, Hwida Abubakr and Sulafa Abd Algodous

Abstract This review was initiated to contribute to better understanding of the relationship between vector-borne diseases (VBDs) and climate change. Secondary data was collected from published articles, books, reports, and internet sources. The discussion was based on considering different processes of climate change such as rise in temperature and humidity and correlates these changes in climatic change to the dissemination of these diseases in reference to the Sudan. The review concluded that accurate analysis of the relationship between vector-borne diseases and climate change would require interdisciplinary cooperation among epidemiologists, climatologists, biologists, and social scientists. Increased disease surveillance, integrated modeling, and use of geographically based data systems would afford measures that are more anticipatory. Understanding the linkages between climatic and ecological change as determinants of disease emergence and redistribution would ultimately help optimize preventive and early warning strategies.

Keywords: Vector Borne Diseases, Climate Change, Water Borne Discuss.

Introduction Sudan is a vast country with a population of about 34 million (Abdel Ati, 2012), presents a diversity of ecosystems typical of dry lands with hundreds of ethnic groups. The economy of Sudan is based on agriculture and animal husbandry. Several dams were built for conservation and supply of water into canalization systems (Fig. 1). These are Sennar; Jebel Awlia; Khashm–algirba; Roseres and Merwi dams. Aswan high dam in Egypt has created a lake; one third of which is inside the Sudan. The development of such water resources has led to great modifications in the environment that favored the spread of vector-borne diseases (VBDs), (Amin and Satti, 1973; Amin, 1977; Omer, 1978). Natural water bodies in the Sudan such as rivers, rain pools, and several stretches of the Niles and their tributaries are also important habitats for spread of vector- borne diseases. Due to scarcity of published reliable data on climate change and its impact on population health vulnerability to VBDs in Sudan, this review was meant to initiate and encourage researchers in Sudan to conduct multidisciplinary researches to better understanding of the impacts of climate change on VBDs. It was also meant to help inform policies on the best methods that would reduce the effects of VBDs to benefit the most vulnerable populations.

Methods Data were collected through literature review from published articles and PubMed websites and from Annual Health Statistical Reports of the Federal Ministry of Health for 2011.

1 Ahfad University for Women. Corresponding Author email: [email protected] 128 Amin et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 128-139

The paper is divided into three parts. Part one reports on climatic change; Part two on major VBDs in the Sudan in relation to climate change and their effects on the population; Part three provides general discussion, conclusions and recommendations.

Fig. 1. Agricultural schemes in the Sudan

Climate change The Intergovernmental Panel on Climate Change (IPCC) has projected that if green house gas emissions, the leading cause of climate change, continue to rise, the mean global temperature would increase by between 1.4 and 5.8oC by the end of the 21st Century (IPCC, 2007). The 2007 IPCC report predicts temperature rises of 1.1-6.4°C (2-11.5°F) by 2100. This is a wider range than the 1.4-5.8°C increase given in the 2001 report. However, the 2007 report goes on to say that their best estimate for temperature rise is 1.8-4.0°C (3.2-7.1°F) ( Masters, 2007). It has been estimated that vector-borne diseases account for 17% of the global disease burden due to all parasitic and infectious diseases. Every year, for example, there are around 300 million cases of malaria, 50-100 million dengue cases and 120 million filariasis cases (Tabachnick, 2010; Brower, 2001). The WHO (2010) stated “climatic conditions strongly affect water-borne diseases and diseases transmitted through insects and snails”. African countries are among the most vulnerable to the impacts of climate change (IPCC, 2001). The main impacts of climate change in Africa is on water resources, food security, agriculture, natural resources and human health (Huq et al., 2002; African plan of Action, 2012-2014, 2012). The negative impacts associated with climate change are also compounded by wide spread of poverty and human diseases (Davidson et al., 2003). Africa has a high diversity of vector species that have the potential to redistribute themselves to new climate driven habitat leading to new disease patterns (Githeko et al., 2000). Egbendewe-Mondzozo et al. (2011) showed that a

Amin et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 128-139 marginal change in temperature and precipitation levels would lead to a significant change in the number of malaria cases for most Africa countries by the end of the century. Hulme (1990) reported that rainfall depletion was severe in semiarid central Sudan, between 1921-50 and 1956-85 annual rainfall has declined by 15%, the length of the wet season has contracted by three weeks and the rainfall zones have migrated southwards by between 50 to 100 km.

Major vector-borne diseases: Major diseases transmitted by mosquitoes in Sudan include malaria, filariasis and arbovirus-borne diseases. 1. Malaria: Malaria is the major health problem in the Sudan and the whole country is now considered endemic, with varying degrees. It is number one among the (10) diseases treated in health units (Annual Health Statistical Report, Federal Ministry of Health, 2011).The malaria endemic range from holo-endemic in the southern states to hypo-endemic in the northern states with epidemics outbreaks. The major vectors of malaria are Anopheles gambiae, A. arabiensis and A. funestus. Malaria incidence in Sudan was estimated to be about 9 million episodes in 2002 and the number of deaths due to malaria was about 44,000 (Abdalla et al., 2007). Ali et al. (2008) reported that the amount of rainfalls and humidity correlated with malaria proportion in Central Sudan. Climate variability and malaria was also studied in three selected sites in Northern, Central and Western Sudan. They have indicated that, the climatologic changes in the three areas appear to have made transmission of Plasmodium falciparum more favorable and may account for increase in proportion of malaria. Abelaal et al. (2011) found that the malaria cases related to temperature increase was clearly recognized in the Northern State with 1.59% out of the state population. The highest endemic state was Blue Nile with 2.45% in the Rich Wet Savannah, and the lowest State of malaria infections was Western Darfur with 0.06% cases. The total of malaria infections in northern Sudan was 15.19% of 29 million populations. Seasonality in the transmission of Malaria has as well attracted the attention of scholars with some research output in the area. Musa et al. (2012) found that the climate factors were suitable for malaria transmission in the period of May to October, whereas the actual case rates of malaria were high from June to November indicating a positive correlation. Comparisons between the prediction model for June and the case rate model for July did not show a high degree of association (18%), the results later in the year were better, reaching the highest level (55%) for October prediction and November case rate. 2. Lymphatic Filariasis: Three different filarial species can cause lymphatic filariasis in humans. Most of the infections worldwide are caused by Wuchereria bancrofti. In Asia, the disease can also be caused by Brugia malayi and Brugia timori. Lymphatic filariasis affects over 120 million people in 73 countries throughout the tropics and sub-tropics of Asia, Africa, the Western Pacific, and parts of the Caribbean and South America (CDC, 2014). More than 90% of the filariasis cases of the WHO/EMRO Region are living in Sudan. This suggests that all Sudanese are living in filariasis endemic areas

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(WHO/EMRO, 2014).Many factors associated with climate change will affect the world‟s poor and of those disabled people will be the most severely affected. People with Lymphatic Filariasis (LF) and other disabilities in developing countries will bear the impact of climate change (Cruz, 2010). 3. Arbovirus-borne diseases: There are three important Arbovirus-borne diseases in Sudan; Dengue fever; Rift Valley and yellow fever (Photo 1).

Photo 1.es.dengue.info/Flickr Mosquitoes on the Move. Wuestewald (2013) Climate change is bringing blood-sucking nightmares that can carry dengue and yellow fever to California.

3.1. Dengue: Dengue is a vector-borne viral infection that endangers an estimated 2.5 billion people. The disease caused by dengue ranges from a relatively minor febrile illness to a life-threatening condition characterized by extensive capillary leak. It is transmitted by the main vector, the Aedes aegypti mosquito (Whitehorn, 2010). Recent studies have confirmed the sensitivity of both malaria and dengue fever to climatic variations between years (Bouma et al., 1996; Patz et al., 1996). Dengue transmission is seasonal and usually associated with warmer, more humid weather. There is evidence that increased rainfall in many locations can affect the vector density and transmission potential (Hales et al., 2003). In Sudan Seidahmed et al. (2012) reported that Dengue is heterogeneously distributed across the neighborhoods of Port Sudan. Colon-González et al. (2013) reported that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analyzing weather–health interactions. They predicted an increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant. 3.2 Rift Valley fever: The disease Rift valley Fever (RVF) takes its name from the Rift Valley in East Africa because it was first described and isolated following an outbreak near Lake Nifasha in the region of the Rift Valley, Kenya in 1930 (Daubney et al., 1931). RVF primarily affects animals but also has the capacity to infect humans (Peters et al., 1994;

Amin et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 128-139

WHO, 2007; Archer et al., 2011). Outbreaks have been reported in Mauritania; the first one occurred in 1987 after the building of the Diama dam, which had ecological and environmental effects that favored a large- scale outbreak that resulted in 200 human deaths (Digoutte and Peters, 1989). After a period of heavy rainfall, an outbreak of Rift Valley fever occurred in southern Mauritania during September–November 2012. A total of 41 human cases were confirmed, including 13 deaths, and 12 Rift Valley fever virus strains were isolated (Sow et al., 2012). An epidemic occurred in Saudi Arabia from 26 August 2000 through 22 September 2001. A total of 886 cases were reported (Madani et al., 2003). During 2007, a large RVF outbreak occurred in Sudan with a total of 747 confirmed human cases including 230 deaths (case fatality 30.8%); although it has been estimated 75,000 were infected. It was most severe in White Nile, El Gezira, and Sennar States near to the White Nile and the Blue Nile Rivers. Notably, RVF was not demonstrated in livestock until after the human cases appeared and unfortunately, there are no records or reports of the number of affected animals or deaths (Hassan et al., 2011). Several different species of mosquitoes are able to act as vectors for transmission of the RVF virus. Among animals, the RVF virus is spread primarily by the bite of infected mosquitoes, mainly the Aedes species, which can acquire the virus from feeding on infected animals. The female mosquito is also capable of transmitting the virus directly to her offspring via eggs leading to new generations of infected mosquitoes hatching from eggs. This accounts for the continued presence of the RVF virus in enzootic foci and provides the virus with a sustainable mechanism of existence as the eggs of these mosquitoes can survive for several years in dry conditions. During periods of heavy rainfall, larval habitats frequently become flooded enabling the eggs to hatch and the mosquito population to rapidly increase, spreading the virus to the animals on which they feed (WHO, 2010). Martin et al., (2008) reported that climate change is expected to affect the geography of infectious diseases including the distribution of vector-borne diseases, such as Rift Valley fever, yellow fever, malaria and dengue, which are highly sensitive to climatic conditions. In the previous decades RVF disease attacked many countries of the Nile Basin (Faiza, 2008) 3.3 Yellow fever: Yellow fever is a disease caused by a virus, which spreads through mosquito bites. Yellow fever continues to occur in regions of Africa and South America, despite the availability of effective vaccines (Barrnet, 2007). The WHO (2013) reported three suspected cases of viral haemorrhagic fever (VHF) in Kassala, Sudan and a total of 40 suspected cases of yellow fever (YF), including 10 deaths were reported from 3 October up to 17 November 2013 in 13 localities in West and South Kordofan. More than 80000 people were vaccinated in West Kordofan and South Kordofan in small-scale vaccination campaigns. 4. Leishmaniasis - Kala-azar: The first case of Kala-azar in Sudan was discovered by Neave in 1904 (Neave, 1904). Visceral leishmaniasis (VL; kala-

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azar) has been among the most important health problems in Sudan, particularly in the main endemic area in the eastern and central regions (Zijlstra and El-Hassan, 2001). Cutaneous leishmaniasis (CL) in Sudan is caused by Leishmania major. The disease is endemic in many parts of the country. The vector is Phlebotomus papatasi and the animal reservoir is probably the Nile rat Arvicanthis niloticus (El-Hassan and Zijlstra, 2011). Muller et al. (2012) conducted a survey between the 5th of May and the 17th of June to estimate the VL incidence in 45 villages located in the eastern part of Gedaref State, the main endemic focus of VL in Sudan. The overall incidence rate of VL over the past year was 7.0/1000 persons per year. The crude mortality rate over the mean recall period of 409 days was 0.13/10'000 persons per day. They concluded the VL is a major public health issue in Gedaref. Active VL case detection had a very low yield in a context of adequate access to care. Thomson et al. (1999) indicated that rainfall (400-1200) and maximum temperature of 34-38ºC together with type of soil and occurrence of Acacia and Balanites determine the presence of the vector Phelebotomus orientalis; the vector of leishmaniasis. In Gedarif State, Sudan Elnaeim et al. (2003) managed to map the risk of visceral leishmaniasis through study of local variation in rainfall and altitude on the presence and incidence of sand flies. Osman (2011) reported on presence of leishmaniasis among the inhabitants of a small village lies in a deserted area in the Nuba mountain, west of Sudan. The presence of leishmaniasis, in deserted areas can be explained by the disease capability to maintain internal circulation within the vectors and animal reservoirs and this can last as long as 20 years. Muller et al. (2011) in their survey, interviewed 17,702 households from a population of 94,369. Sixteen individuals were diagnosed with primary VL through active case- detection, and 725 reported VL treatment over the past year. The overall incidence rate of VL over the past year was 7.0/1000 persons per year. The crude mortality rate over the mean recall period of 409 days was 0.13/10'000 persons per day. VL was a possible or probable cause for 19% of all deaths. Taking also into account the VL-specific mortality of 0.9/1000 per year, the incidence was estimated at 7.9/1000 per year. Overall, 12.5% of the population reported to have been treated for VL in the past. They concluded the VL is a major public health issue in Gedaref. Active VL case detection had a very low yield in a context of adequate access to care. 5. Onchocerciasis: Onchocerciasis is a parasitic disease caused by the filarial worm Onchocerca volvulus. It is transmitted through the bites of infected blackflies of Simulium species, which carry immature larval forms of the parasite from human to human. In the human body, the larvae form nodules in the subcutaneous tissue, where they mature to adult worms. After mating, the female adult worm can release up to 1000 microfilariae a day. These move through the body, and when they die they cause a variety of conditions, including blindness, skin rashes, lesions, intense itching and skin depigmentation. Simulium species breed in rapids such as dams. Onchocerciasis is a major cause of blindness in many African countries. About

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half a million people are blind or visually impaired due to the disease. Onchocerciasis also causes ugly skin disease with depigmentation and severe unrelenting itching (WHO, 2014). Owing to the differential dispersal of nulliparous and parous flies in savanna, the annual transmission potentials were related more closely to the numbers of parous flies than to the total fly population (Duke et al., 1975). Higazi et al. (2011) assessed the status of infection transmission in 2007 in the vectors of two disease foci in Sudan: Abu Hamed in northern Sudan, which has received at least 10 years of annual treatment and Galabat focus in eastern Sudan, where only minor, largely undocumented treatment activity has occurred. Assessment of more than 30,000 black flies for Onchocerca volvulus infectious stage L3 larvae by using an O-150 polymerase chain reaction protocol showed that black fly infectivity rates were 0.84 (95% confidence interval = 0.0497-1.88) per 10,000 flies for Abu Hamed and 6.9 (95% confidence interval = 1.1-16.4) infective flies per 10,000 for Galabat. These results provide entomologic evidence for suppressed Onchocerca volvulus transmission in the Abu Hamed focus and a moderate transmission rate of the parasite in the Galabat focus 6. Schistosomiasis: Schistsomiasis is now a major public health problem in the Sudan with social and economic implications. It is endemic in all states of the Sudan except the Red Sea State with varying prevalence rates from about 3% to 90% ( Amin, 2012) An estimated 5.8 million people in the Sudan–around 15% of the total population – require treatment; the majority of those infected are children (WHO/EMRO,2013). The available literature on impact of climate change on schistosomiasis is limited. In Senegal Biomphalaria pfeifferi transmits Schistosoma mansoni during the rainy season while Bulinus globosus is responsible for S.haematobium during the dry season (Githeko et al., 2000). Rainfall patterns have a distinct influence on B. globosus in Tanzania. In China, Zhou et al. (2008) found a temperature threshold of 15.4oC for development of Schistosoma japonicum within the intermediate host snail (Oncomelania hupensis), and a temperature of 5.8oC at which half the snail sample investigated was in hibernation. In the northern localities of Gezira Iirrigation Scheme Biomphalaria pfeifferi is drastically reduced as a result of rise in temperature. This was reflected in low incidence of S. mansoni (Amin et al., 2012).

Discussion Climate change is the first environmental problem in the World at present and Sudan contribution to problem of climate change is very small as its emission of green houses gases is estimated at 0.07% mostly from land use sector (Abdel Ati, 2012). Climate change poses a significant challenge to the people of Sudan (AIACC, 2006; NAPA, 2007). They are under continuous threats from excessive climate variability, recurrent drought; frequent floods and they have limited potentials to cope with adverse situations. For Sudan, climate change is not merely an environmental issue, but a serious sustainable development problem for widely spread communities. Each year, climate threats emerge, further worsening the prospects of health and livelihood of these vulnerable communities. The

Amin et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 128-139 ability to adapt to climate change is a critical factoring the chances of prospectively and even survival of these communities. The scenarios of climate analysis indicate that the average temperatures are expected to rise in 2030 by between 1.5-3.1degrees Celsius in the month of August, and from 1.1 to 2.1degrees Celsius in January. The same forecast indicates a decrease in the amount of rainfall by about 6 mm per month during the rainy seasons (Abdel Ati, 2012). Much of the impact of climate on vector borne diseases can be explained by the fact that the arthropod vectors of these diseases are ectothermic (cold- blooded) and, therefore, subject to the effects of fluctuating temperatures on their development, reproduction, behavior and population dynamics (Kenneth et al., 2008). Further Vector-borne diseases are linked to the environment by the ecology of the vectors and of their host‟s behavioral activities. It is predicted that over a million death and considerable morbidity worldwide by the 21st centaury (WHO, 2014). Most of the vector-borne diseases that prevail in Sudan; e.g. Leishmaniasis, Kala-azar, Schistosomiasis, filiriasis and Onchocerciasis, are among the so-called Neglected Tropical Diseases (NTDs). Very few studies have been carried out regarding the connection of NTDs with climate change (Campbell‐Lendrun, 2003 search). Their search, largely bases on countries of high prevalence, appeared to be primarily the result of poverty (Manderson et al., 2009). Therefore, there is a need to attract fund for research in this area from the private sector and more allocation of funds from the government. Long term studies are needed because “whether climate changes increase or decrease the incidence of vector-borne diseases in humans will depend not only on the actual climatic conditions but also on local non-climatic epidemiologic and ecologic factors” (Kenneth et al., 2008). Reiter (2001) indicated that climate change has rarely been the principal determinant of the prevalence or range of the three diseases--malaria, yellow fever, and dengue; human activities and their impact on local ecology have generally been much more significant. It is therefore inappropriate to use climate-based models to predict future prevalence.

Conclusions and Recommendations Climate change would directly affect disease transmission by shifting the vector's geographic range and increasing reproductive and biting rates and by shortening the pathogen incubation period. Climatic factors influence the emergence and reemergence of infectious diseases, in addition to multiple human, biological, and ecological determinants. Very few studies have been carried out regarding the connection of VBDs with climate change in the Sudan, Accordingly, there is a need to conduct research in this area. This would require interdisciplinary cooperation among epidemiologists, climatologists, biologists, and social scientists (Patz et al., 1966). Funds may be obtained from international or regional research calls, the private sector and more allocation of funds from the government. Furthermore, increased disease surveillance, integrated modeling, and use of geographically based data systems will afford more anticipatory measures by the medical community. Understanding the linkages between climatological and ecological change as determinants of disease emergence and redistribution will ultimately help optimize preventive strategies. The efforts

Amin et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 128-139 could be strengthened through capacity building of young scientists abroad in integrated modeling, and use of geographically based data systems.

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Soil Carbon Sequestration and Climate Change in Semi-arid Sudan

Jonas Ardö1

Abstract Climate change poses risk for natural and human systems in Africa. Increasing temperatures and changes in precipitation patterns is likely to affect agriculture, pastoralism and forestry. Mitigation of increasing atmospheric concentration of CO2 through soil carbon sequestration in semi-arid ecosystems may be beneficial to soil properties and cultivation. This paper describes and discusses soil carbon sequestration in relation to climate change in semi-arid regions, with special attention to the Sudan. It is anticipated that adaptation to climate changes is a more reasonable way to cope with future climate change than mitigation through soil carbon sequestration, especially for low emitting countries in Africa such as the Sudan.

Keywords: Adaptation, GHGs, Climate Change, Mitigation

Introduction The increase of CO2 and other greenhouse gases (GHGs) in the atmosphere are very likely to impact future climate through increasing temperatures and changes in precipitation patterns and magnitudes. This will alter the general conditions for agriculture, forestry and similar activities directly depending on „weather‟ or climate. Marginal areas such as semi-arid regions are expected to be strongly affected by climate change as they are already affected by strong natural climatic fluctuations (mainly precipitation) that impact prosperity of self-supporting populations. The term climate change has different meanings in different contexts. According to IPCC, climate change refer to “any change in climate over time, whether due to natural variability or as a result of human activity” (IPCC, 2014). United Nations Framework Convention on Climate Change (UNFCCC), on the other hand, defines climate change as “a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods” (UNFCCC, 2014). The recent IPCC fifth assessment report (AR5) describes and summarizes the state of the art of the current knowledge on the physical science basis of climate change (IPCC, 2013a), as well as the probabilities for various phenomena. The report combines a qualitative level of confidence for evaluation of the underlying scientific understanding and uses quantified probabilistic likelihoods when possible, to describe the degree of evidence for key findings (IPCC, 2013b). Two major strategies to cope with climate changes are often considered, adaptation and mitigation (a third option, to deny or ignore that climate change occur at all, exists, but this is not based on scientific principles (Dunlap and

1 Department of Physical Geography and Ecosystem Science, Lund University Sölvegatan 12, 22362 Lund, Sweden, Jonas.Ardö@nateko.lu.se, 31 March 2014. 140 Ardö, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 140-163

McCright, 2011; Wikipedia, 2014)). Climate change mitigation includes actions taken to reduce the sources or enhance the sinks of GHGs. Climate change adaptation includes actions taken to decrease the effects or vulnerability of anthropogenic and biological systems to climate change effects. It is defined by UNFCCC as “Adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities”. Carbon sequestration is the process of removing carbon (C) from the atmosphere and depositing it in a reservoir (UNFCCC, 2014) such as soil or biomass. It is hence mainly, but not only, a mitigating action. Carbon sequestered in soils or in vegetation is only temporarily removed from the carbon cycle. Residence times vary among carbon pools (soil, vegetation, atmosphere, oceans) and, hence will the sequestered carbon continue its flow as part of the carbon cycle after some time. This time is dependent on the abiotic and biotic environments, management, as well as other factors. The magnitude of these fluxes is also strongly influenced by the climate and can provide feedbacks on the climate system (IPCC, 2014; Arneth et al., 2010). This paper briefly describes, discusses and exemplifies experiences gained from studies of soil carbon sequestration and carbon cycle studies in semi-arid Africa with focus on the Sudan. The presented material is a combination of results from finished and current research projects as well as from selected scientific literature within the field.

1. Climate change IPCC states that “Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased” (IPCC, 2013a). The global average temperature have increased 0.78 °C when comparing the 1850–1900 period with the 2003–2012 period and almost the entire globe has experienced surface warming (IPCC, 2013a). Due to natural variability, trends calculated on short time series describing surface temperature are very sensitive to start and end time of these time series and robust multi-decadal data sets are needed. Most reports agree on the global warming, however a recent report mentions that the warming has taken “a pause” since 1998, and the increase in the global surface temperature from 1998 until 2013 is only 0.04 °C per decade from observations, but 0.21 °C per decade from recent simulations (Tollefson, 2014). This temporary reduction in temperature increase (Santer et al., 2014) should not be interpreted as a reduction of the changes in the climate. Out of the 14 warmest years since 1850 have 12 that occurred during the 21th century and for the north hemisphere is the latest 30 year period probably the hottest since the 15th century (IPCC, 2013a). Changes in precipitation are less confident and both positive and negative changes occur. Extreme weather and climate events have been observed since about 1950. On the global scale, it is very likely that the number of cold days and nights has decreased and the number of warm days and nights has increased (IPCC, 2013a).

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There are likely more land regions where the number of heavy precipitation events has increased than where it has decreased. The main cause of the observed climatic changes is attributed to the increase of GHGs in the atmosphere. The atmospheric concentrations of CO2, CH4 and N2O are higher today than they had been during the last 800,000 years (IPCC, 2013a). The mean rates of increase are the highest in 22,000 years. The major sources of CO2 include emissions from fossil fuel burning and cement production yielding a –1 source of 9.5 Gt C yr in 2011. The annual net increase of CO2 due to anthropogenic land use change was estimated at 0.9 Gt C yr–1 (average for 2002- 2011). The increase of CO2 makes the total radiative forcing positive and cause an uptake of energy in the climate system. The total radiative forcing has increased with a factor of 2.29 as compared to the 1750 level (IPCC, 2013a). A waste majority of the scientific community agree that there is a casual relationship between the release of GHGs and increasing temperatures (IPCC, 2013b; Anderegg, 2010; Doran and Zimmerman, 2009; Oreskes, 2004; NASA, 2014). A recent investigation concludes that “the number of papers rejecting the consensus on anthropogenic global warming is a vanishingly small proportion of the published research” (John et al., 2013) and the AR5 also states that “human influence on the climate system is clear” (IPCC, 2013b). The large amount of scientific literature concerning climate change is demanding to survey but an up to date summary is given in the fifth IPCC assessment report whereof the working group 1 (The Physical Basis) report (IPCC, 2013a) is already available and the reports of working group 2 (Impacts, Adaptation and Vulnerability) and 3 (Mitigation of Climate Change) will be released during the spring of 2014 and will be available at http://www.ipcc.ch/. We find support for anthropogenic climate changes, mainly attributed to emissions of GHGs originating from the developed world and with a tendency to affect the developing world, not at least Africa (Toulmin, 2009). Africa IPCC fourth assessment report states that “Africa is one of the most vulnerable continents to climate change and climate variability, a situation aggravated by the interaction of „multiple stresses occurring at various levels and low adaptive capacity” (Boko et al., 2007), and it points out the high vulnerability of Africa‟s major economic sectors to current climate change. This vulnerability is due to the already limited water supply, poverty, ecosystem degradation, complex disasters and conflicts, among other causes. The adaptive capacity is considered weak, further increasing the vulnerability to climate change. Water stress may increase due to changes in precipitation, rainfall intensity and increased evaporation in combination with an increased demand for water. The proportion of arid and semi-arid regions is likely to increase by 5-8% (Boko et al., 2007). Minimum temperatures have been observed to increase slightly faster than maximum and mean temperatures (Boko et al., 2007). The number of warm spells over western and southern Africa has increased and a decrease in the number of very cold days has been reported (New et al., 2006). The recent IPCC fifth assessment report shows significant temperature increases for all of Africa (1901- 2012) whereas some areas are uncertain due to incomplete or missing data (IPCC,

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2013b).The density of the network of climate stations in Africa is low, averaging one station per 26000 km2, eight times lower than the WMO's (World Meteorological Organization) recommendation (Osman Elasha et al., 2006). The number of climate monitoring stations in Africa has also decreased since the 1970's (Hulme, 1992), which may result in less reliable observations and forecasts, especially in areas with strong environmental gradients such as the Sahel region (Sjöström et al., 2013). Estimates for Africa indicate, with high likelihood, higher future temperatures, warmer and more frequent hot days and nights or most land areas (IPCC, 2013b). African precipitation shows a less clear pattern, both in terms of observations, as well as for predicted future precipitation patterns (Giannini et al., 2008; Boko et al., 2007). Interannual variability is large over most of Africa and some areas also show strong multi-decadal variability (Boko et al., 2007). During the last 50 years, declines in precipitation have been observed in West Africa, whereas a recent increase has been observed along the Guinean coast (Boko et al., 2007). Some areas, such as southern Africa show no clear trend but some areas have experienced extreme precipitation events causing severe flooding (Usman and Reason, 2004). The recent greening observed in the Sahel (Olsson et al., 2005; Dardel et al., 2014) is mainly explained by increased precipitation (Hickler et al., 2005). Predictions for the 21st century state that the Sahara region which is already very dry is very likely to remain very dry. The confidence in projection statements about drying or wetting of western Africa is low (IPCC, 2013b). A minor positive change in precipitation, with medium confidence is predicted for East Africa and changes in precipitation seasonality may occur in several regions. The importance of sea surface temperatures and the monsoon are highlighted for the Sahel region whereas ENSO (El Niño–Southern Oscillation) may play an important role in southern Africa (IPCC, 2013b). Effects of climate change Direct effects of increased temperatures include higher levels of plant and water stress, larger evaporative losses of water from soil and surface waters. This will decrease water availability for agriculture and water power and may further limit access to drinking water. Higher air temperatures increase the amount of water and energy that the atmosphere can hold which in turn may increase severity of extreme events (Field et al., 2012). Extreme precipitation events increase the risk of flooding and severe erosion causing damage to cultivation and infrastructure. Even in areas where precipitation are predicted to increase, higher temperatures may cause an increased evaporative demand counteracting the precipitation increase and result in a no change or net decrease in water availability and an increase in aridity (Sherwood and Fu, 2014). Recent observational studies have shown that the P/PET (precipitation/potential evapotranspiration) ratio is decreasing on average as the global temperature increases, resulting in a drier future (Sherwood and Fu, 2014). Water demand will increase due to increase in population and increases in per capita consumption. This increased water demand (agricultural, domestic and industrial) in combination with increased evaporation due to higher temperature and unreliable predictions of future precipitation will very likely cause increased water stress in large regions of Africa (Toulmin, 2009;

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Schlosser et al., 2014). The strong spatial and temporal variability of precipitation (Hulme et al.,2005) can strongly affect local resource availability, sometimes with adverse effects to populations directly depending on agriculture (Olsson, 1993; Zarocostas, 2011). Even if nomadic groups may suffer from marginalisation when land resources decrease and the area under cultivation increase, one may say that the mobility flexibility that nomadic pastoralism represents can provide a type of security and adaptation of strong temporal and spatial resource variability (Sulieman and Elagib, 2012). Additional effects of climate changes in Africa include inundation of coastal agricultural land due to rising sea level (Frihy and El-Sayed, 2013), coastal erosion, changes in malaria transmission (Ermert et al., 2013), changes to other vector borne diseases, and effects on plant pests and pathogens (Gregory et al., 2009) and much more not included here. Some studies even point to an increased risk of civil conflicts due to warming and a general resource decrease (Burke et al., 2009). Sudan Studies on climate change in Sudan include the national reports to UNFCCC, the first one in 2003 (Anon., 2003b; 2003a) and the second in 2013 (Anon.; 2013). These reports constitute the official national communications including information on emissions and removals of GHGs and details of the activities undertaken to implement the climate convention. Sudan‟s second national communication to UNFCCC (Anon.; 2013) gives an overview of adaptation activities, coastal zone and water resource vulnerability, mitigation possibilities and carbon sequestration opportunities. Forestry is considered as the only carbon sequestration measure currently appropriate for Sudan (Anon.; 2013). The report does not treat soil carbon sequestration, but points out that large area of agricultural land and rangeland could be utilized for carbon sequestration in the form of biomass. A large proportion of Sudan‟s agriculture is rainfed and it is, hence vulnerable to decreased rainfall and/or increase rates of evapotranspiration, resulting in a decrease in water availability. The large numbers of grazing animals (cattle, sheep, goat and camel) in the semi-arid areas rely on grazing and crop residues, almost entirely of non-irrigated sources. Some areas have experiences of lower stocking rates and climatic changes have been reported to make pastoral production more uncertain than ever before (Sulieman and Siddig, 2014). Adaptation strategies such as in situ rain water harvesting, adjusted sowing dates and the use of suitable cultivars are crucial issues for traditional rural farmers (Ahmed, 2010). Potential effects on biodiversity have been reported (El Tahir et al., 2010; Bashir, 2001), stressing the importance of “involvement of local communities in natural resource conservation, forest rehabilitation and protection; use of indigenous knowledge and local experience in forest management”. 2. Soil carbon sequestration Sequestration, i.e. depositing carbon originating from the atmosphere in some reservoir such as soil or biomass, decreases the atmospheric concentration of CO2 and is, hence considered to mitigate climate change. Other techniques such as

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deliberate CO2 removal through geoengineering, is often called CO2 removal, and refers to a number of technologies (also including non-biotic technologies such as direct air capture) which reduce the levels of atmospheric CO2. Activities such as REDD (Reducing Emissions from Deforestation and forest Degradation) is not directly carbon sequestration but aims to reduce emission originating from land use conversion and forestry activities. REDD target developing countries (Nations, 2014), and as deforestation and forest degradation is estimated to contribute to approximately 17% of all GHGs emissions globally (Solomon et al., 2007), such activities are of great importance. REDD focus more on not losing already stored CO2, whereas carbon sequestration has emphasis on transfer of CO2 from the atmosphere to soil and biomass. A wide range of studies of carbon sequestration (Andrén and Kättterer, 2001; Batjes and Sombroek, 1997 ), the carbon cycle (Schimel, 1995; Schlesinger and Andrews, 2000) and drivers of important processes such as photosynthetic assimilation of CO2 by terrestrial vegetation (Monson and Baldocchi, 2014; Merbold et al., 2009) and autotrophic and heterotrophic respiration (Reichstein et al., 2005) have been performed. This type of studies promotes understanding of ecosystem function and properties relevant as background information for more applied carbon sequestration studies and projects. Numerous studies have aimed to quantify the potential for carbon sequestration in various ecosystems (Farage et al., 2007; Ingram and Fernandes, 2001), both in soils and in biomass. This potential is often seen as a “gap” which could be closed or decreased by different types of soil and land management actions varying with climate, vegetation type, soil, cropping system and other factors. Utilisation of this potential may have positive environmental effects as well as allowing participation in various payments for ecosystem services (PES) schemes, for example within the Kyoto Protocol. Such payment schemes may promote transfer of funds from larger emitters of CO2 to projects sequestering carbon (Balgis et al., 2006). The concept of carbon sequestration potential was recently scrutinized and a separation into biophysical, technical, economic and practical potential was suggested in order to increase comparability among studies (Luedeling et al., 2011). In short is the biophysical potential a function of the geographical / climatological and soil setting of a region, the technical potential are dependent on management options available and feasible, the economic potential considers economic constraints such as profitability and marginal abatements costs. Finally the practical potential considers additional constraints such as socioeconomic factors, institutional and governance constraints and market access (Luedeling et al., 2011). Hence, we may have cases where one type of potential is low and as such decrease the overall potential for a successful sequestration project. Several semi-arid areas of the world are vulnerable to environmental changes (Warren et al., 1996; Lal, 2001a) and to some extent degraded (UNEP, 1992), partly due to reduction in the permanent plant cover (Le Houérou, 1995) and low soil carbon content (Ringius, 1999). Such areas including degraded agro- ecosystems in Africa, have been identified as suitable targets for carbon sequestration due to their below natural carbon stock (both soil and biomass), as well as due to the potential benefits originating from an increase in carbon content

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(Olsson and Ardö, 2002). Soils have been suggested as preferable to storage in biomass/vegetation due to their longer residence times for C and less risk of a rapid release (Lal et al., 1999). Hence, is the focus below on soil C sequestration in semi-arid environments including some examples from Kordofan.

Soils Soil organic matter (SOM) influences the physical, chemical and biological properties of the soils and contributes to their functioning (Ontl and Schulte, 2012). We often consider storage of soil carbon as a vital ecosystem service and a function of several interacting ecological processes. These processes are affected by human activities which can reduce or enhance the storage of soil carbon (FAO, 2001; Lai et al., 2013). Soil quality is improved by increased SOM content through better water holding capacity which would imply less need for irrigation, improved micro-aggregate structure, preventing erosion (decrease soil erodibility) and a stabilizing effect on the soil structure (Jewitt and Manton, 1954; Gerakis and Tsangarakis, 1970; Warren, 1970; Batjes and Sombroek, 1997; Lal et al., 1999). Soil organic carbon (SOC) is also an important determinant of the cation exchange capacity of soils (Batjes, 1999) and there is commonly a clear correlation between SOC in the topsoil and crop yields (Sombroek et al., 1993). Large pools of SOM with low decomposition rates also permit a long-lasting mineralization of N and other nutrients. Both the net primary production (NPP) and the decomposition rate of plant residues in semi-arid areas increase with water availability (Parton et al., 1996). Higher temperatures in tropical ecosystems are likely to reduce carbon uptake (Xia et al., 2014; Schneising et al., 2014). Soil carbon can have a very long residence time, hundreds and even thousands of years (Lal et al., 1998), compared with carbon stored in aboveground vegetation which may rapidly disappear through clear cutting of fire. When soils under natural vegetation are being transformed to agricultural soils, carbon is usually being lost to the atmosphere (Burke et al., 1989; Pieri, 1992; Scholes et al., 1997; DOE, 1999; Schlesinger, 2000; Lal et al., 1999). During intense cultivation, without fertilization or add-on of organic matter, this decrease may be fast (Buyanovsky and Wagner, 1998). Several agro-ecological ecosystems in semi-arid areas are today considered to be poor in SOM due to deforestation, high intensity cropping and cultivation, intense tilling and overgrazing. In the Sahel region, continuous millet cultivation on sandy soils in Burkina Faso has been reported to slowly deplete soil N and P (Krogh, 1997) and decreased fallow periods have been reported to deplete soils in Niger (Wezel and Haigis, 2002). Conversion of forest land to cropland in Senegal has been reported to significantly decrease soil carbon (Loum et al., 2014) and low soil nutrient levels have been associated with low African agricultural yields in general (Sanchez, 2010). For the Kordofan region of Sudan, it is evident that the land use practices have changed markedly from a rotation system with long fallow periods (15–20 years) interspersed with short periods of cultivation (4–5 years) (Haaland, 1991) to shorter fallow periods or even continuous cultivation over the last four to five decades (Davies, 1985; Jewitt and Manton, 1954; Craig, 1991; Khogali, 1991; Olsson and Rapp, 1991; Ardö and Olsson, 2004; Olsson and Ardö, 2002). When Copyright © 2015 SAPDH 146 ISSN 1816-8272

Ardö, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 140-163 continuous millet (Pennisetum glaucum) cultivation, as in Kordofan, is combined with annual burning prior to planting, no or little addition of manure or artificial fertilizers and removal of most crop residues after harvest, we may expect a decrease of SOM as well as a decrease in soil nutrients such as P and N. Similar trends are found elsewhere in the Sahel region and continuous millet cultivation in a similar environment on a sandy soil in Burkina Faso has been reported to slowly deplete soil N and P (Krogh, 1997). In Niger, significant increases of C and N with fallow age on sandy soils (<4.5% clay) were found (Wezel and Böcker, 1999). This reduced time for soil revitalization may be caused by an increased demand for food; reduced crop yield (Olsson, 1993) due to decreasing precipitation, soil degradation, crop diseases and parasites (Khogali, 1991) and an increased desire to grow cash crops (e.g., groundnuts). During the same period, crop yields have decreased (Olsson, 1985; Olsson and Ardö, 2002). The use of fallow periods is the dominating measure taken to improve soil fertility in the Kordofan region. Fallow periods increase not only soil carbon content but also soil nutrients and potentially the clay fraction of the soil can be increased when trees capture wind transported fine material (El Tahir, 2006). Herbaceous and arboreal improved fallows have been suggested as key components of many sustainable tropical farming systems (Sanchez, 1999). Several studies have pointed out the potential (many of them not considering the different types of potentials mentioned above) to sequester carbon in both soils and biomass in semi-arid environments and degraded agro-ecosystems. Restoration of soil fertility and improvement of soil properties through increased soil carbon sequestration in agro-ecosystems (by means of no-till, agroforestry options, fallowing, special cover crops, return of crop residues, mulching, reduced grazing intensity, green fallow periods, conservation tillage, etc. (Lal et al., 1998), may, apart from removing CO2 from the atmosphere, also improve our chances of meeting future food production demands (Ringius, 1999; Olsson and Ardö, 2002; Sanchez, 2002). Batjes (1999) estimated that between 0.6 and 2 Pg C yr-1 could be sequestered by large-scale application of appropriate land management in degraded lands of the world. Squires (1998) estimated the potential sink of dry lands to be 10 Pg C yr-1 over the next 50 years, whereas global desertification control could have been estimated to sequester 0.9-1.9 Pg C yr-1 for 25-50 years (Lal, 2001b). Such general numbers may be interesting from a global carbon budget point of view but are less useful when investigating the possibilities for sequestration on regional or local level. Local examples from Kordofan, Sudan Studies were conducted in North Kordofan to investigate the potential for soil carbon sequestration in areas intensely utilized for agriculture and pastoralism (Ardö and Olsson, 2004; 2003; 2001; Poussart et al., 2003; Farage et al., 2007; Olsson and Ardö, 2002). The basis in these studies is that the large proportion of the ecosystems in North Kordofan are depleted of SOM due to intense land use and low inputs of both organic and inorganic fertilizers. Traditional, non- mechanized, rain-fed agriculture, without the use of any type of fertilizers or addition of organic matter, is common in central and western Sudan (Craig, 1991).

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Fig. 1 illustrates a potential general scenario of SOC changes for an area with sandy soil and a mean annual precipitation of about 300 mm in North Kordofan from year 1850 to year 2100 (Olsson and Ardö, 2002). Prior to significant human intervention, we assume an equilibrium level of about 300 g C m-2 (for the upper 20 cm of the soil profile) in a natural grassland/sparse savanna without cultivation (1850). This equilibrium level was determined by a l000 year simulation under stable climate and management conditions. From 1891 to 1973, we assumed rotational millet cultivation with an increasing crop: fallow ratio where cultivation periods correspond to a decrease in SOC and fallow periods to an increase in SOC (Fig. 1).

Fig. 1. Simulated changes of soil organic carbon from 1850 to 2100 for a site in N Kordofan (Sudan) characterized by sandy soils, 300 mm of mean annual precipitation and rotational millet cultivation with increasing intensity from 1891 to year 2000. From year 2000 and onward are various recovery options (decreased cropping intensity) simulated. Modified from (Olsson and Ardö, 2002).

From 1974 to 2000, we assumed a continuous cultivation of millet. From year 2000 and forward, the effects on SOC from land use simulated, showing a further decline in SOC during continuous cultivation, and increase in SOC if grazing only are applied. The impact of the crop: fallow ratio implies roughly that a fallow period should be longer than the interspersed cropping periods in order to increase SOC. The historical SOC development as well as the future scenarios was simulated with the CENTURY model (Metherell et al., 1993; Parton et al., 1987; Parton et al., 1988). The CENTURY model is a general model of plant-soil nutrient cycling which is being used to simulate carbon and nutrient dynamics for different types of ecosystems including grassland, agricultural, forest and savanna (NREL, 2014). The model is useful for testing effects on SOC and soil nutrients from management options such as crop rotations, addition of manure, addition of organic matter, fire, harvest, grazing and cultivation practices. Longer fallow periods have been suggested as suitable for recovery of SOC after periods of cultivation (Ardö and Olsson, 2001; Deans et al., 1999; Sanchez, 1999; Wezel and Haigis, 2002). An empirical data from soil sampling in combination with interviews on land use history show a weak but significant positive relationship indicating increase of SOC with longer fallow periods/shorter cultivation (Fig. 2). Copyright © 2015 SAPDH 148 ISSN 1816-8272

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SOC vs. cultivation intensity 600

] 500 m c 0 2

r 400 e p p u

, 300 2 - m

C 200 g [ C O

S 100 R2 = 0.40 0 -40 -30 -20 -10 0 10 20 30 40 Years of fallow | Years of cultivation Fig. 2. Impact of cultivation intensity on SOC in agricultural land on sandy soils in North Kordofan, Sudan. Negative numbers (on x-axis) denote years of consecutive fallow and positive numbers denote years of consecutive cropping. Modified from (Ardö and Olsson, 2004).

Fallow periods with trees such as Acacia senegal, potentially a N-fixing species, also increase the amount of SOC when compared to cultivation (Fig. 3) (Ardö et al., 2008). However, there are some doubts on the N-fixing potential of Acacia Senegal (Deans et al., 1999) even if it has been reported to fix N (Barbier, 2000). Tree cover and tree cover duration tend to increase SOC for Acacia senegal plantations in Demokeya experimental site in Kordofan, Sudan. Comparing SOC of the cultivated site clearly illustrates the positive effect on SOC from trees (Ardö et al., 2008) (Fig. 3).

700

600

500 ] -2 -2 400

300

SOC[g m C 200

100

0 1967 1976 1981 1990 1993 Footprint Planting year/land use Cultivation Fig. 3. Soil organic carbon in the upper 20 cm of the soil profile in Acacia senegal plantations with different age, at a cultivated site and in the close vicinity of the flux tower in Demokeya (foot print). Error bars denote ± one standard deviation, four samples taken at each site. Modified from (Ardö et al., 2008).

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Intercropping of sorghum (Sorghum bicolor), sesame (Sesamum indicum) and roselle (Hibiscus sabdariffa) with A. senegal have been shown to give higher net return than monocropping of the same crops (Fadl and El Sheikh, 2010; Fadl, 2013). Additional environmental benefits of fallow periods with trees include lower soil temperatures, higher soil moisture, higher SOC (Abril and Bucher, 2001), greater fuel production, and the possibilities of tapping gum (Haaland, 1991; Khogali, 1991) and shade for grazing animals. Litter produced by woody plants is beneficial due to its higher content of polyphenols (lignins and tannins) in the litter, which decreases the decomposition rate (Abril and Bucher, 2001), when compared to grasses and annual herbs. Spatial variability - GIS As environmental factor such as soil, precipitation and land cover varies significantly over space (in addition to time), integration of tools that handle spatially distributed data with SOC simulations models, for instance the CENTURY model, can be beneficial. A simple such integration is exemplified in Fig. (4).

Fig. 4. Estimated soil organic carbon (SOC) (g C m-2) in 1900 (a), SOC changes from 1900 to 2000 (b) and potential SOC changes from 2000 to 2100 (c). The area is approximately 500 x 500 km in central Sudan, covering parts of both Northern and Southern Kordofan. CENTURY simulations were performed for each km2, modified from (Ardö and Olsson, 2003).

Through linking a Geographical Information System (GIS) with the CENTURY model spatially explicit simulations were performed (Ardö and Olsson, 2003) for each km2 in a 500 x 500 km area. Verification of simulation results from SOC models and ecosystem models may indicate their usefulness through quantitative comparison with measured data (Fig. 5) (Ardö and Olsson, 2004).

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600 Cropland Undisturbed (savanna)

] 500 -2

400

300

200 Estimated SOC m [g Estimated 100

0 0 100 200 300 400 500 600 -2 Observed SOC [g m ] Fig. 5. Comparison of soil organic carbon (SOC) observations based on soil samples and estimates of (SOC) from the CENTURY model. N =13, r2 = 0.70. Modified from (Ardö and Olsson, 2004).

Uncertainties Uncertainties must be considered when using modelling to estimate current and future ecosystem processes, such as assimilation of CO2 and ecosystem properties such as carbon stocks. We have uncertainties in data, affecting calibration and validation, model uncertainties indicating that our representation of the process may differ between the model and reality (Barkman, 1998). One example is the climatic data (most often including temperature, precipitation and incoming radiation, as well as other model specific data needs) needed as drivers for most ecosystem models. These data are often a result of an interpolation based on observations from a limited number of loci, most often climate stations. A low number of climate stations (see above) will decrease the quality of the interpolated result (Dardel et al., 2014). Interpolated data will, hence, not fully agree with reality and in areas with high spatial and temporal variability, such as the Sahel region, may differences be substantial (Sjöström et al., 2013). Satellite derived estimates of precipitation may of course improve these estimates. Another example is shown in Fig. 6, which is similar to Fig.1, but with uncertainty originating from the data on soil texture included.

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Fig. 6. Effects of data uncertainty during modelling of the potential impact on soil organic carbon from land use management. Result from a Monte Carlo simulation (n=500) assuming a data uncertainty in the soil clay content (mean = 5% and σ= 2.5%). Thick lines describe simulation without data uncertainty and the thin lines describe the output distribution (95%) from the Monte Carlo simulation (calculated as the output standard deviation from the Monte Carlo simulation (18) x 1.96 = 36). The black line describes effects on SOC assuming grazing only and the blue line describe effects on SOC assuming a traditional Millet cropping system with 5 year of cultivation and then 20 years of fallow.

In this case, we assume a clay content in the soil of 5%, with an uncertainty quantified as a standard deviation (σ) of 2.5% (i.e. we assume that 68% of the observations are within 2.5% of the mean value). We executed 500 simulations with the soil clay content randomly taken from a normal distribution (mean = 5% and σ = 2.5%) in a Monte Carlo approach, remaining variables and parameter being unchanged. The output variability/uncertainty in SOC is represented by a σ of 18 g C m-2 (in the upper 20 cm of the soil profile). The uncertainty is illustrated (Fig. 6) by calculating a 95% distribution (σ * 1.96 ≈ 36), showing a clear influence on simulated SOC from uncertainty of input data. Rate of sequestration There are several factors that influence the rate of soil carbon (SOC) sequestration, which is a balance of the input (litter-fall, fine root dieback, atmospheric input of organic matter) and the heterotrophic soil respiration, (Rh). Rh differs for different pools of soil carbon and, hence will the long-livety of the soil carbon sequestration be of importance. This is partly dependent on chemistry of the organic matter (lignin content and other components), as well as the clay binding of soil organic matter (SOM). Still, sequestration rates in semi-arid areas

Ardö, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 140-163 are often low and have been estimated to 1-2 g C m-2 yr-1 on sandy soils in Kordofan (Olsson and Ardö, 2002; Ardö and Olsson, 2003), 3. Sudan in perspective From a global perspective, the Sudanese emission of GHGs is low. According to the Global Carbon Project (NREL, 2014), Sudan is ranked as country number 87 on the list of emitters, with an annual emission of 14 Mt CO2 in 2012 as compared with China (9621 Mt CO2) and USA (5118 Mt CO2) for the same year. Quantifying this emission per capita, Qatar is ranked as country #1 (44 t CO2 per capita), while Sudan is ranked as country #183 (0.3 t CO2 per capita) in the year 2012. USA and China are ranked as #14 and #53, with 16 and 7 t CO2 per capita, respectively. The global emission of CO2 was 35418 Mt CO₂ in 2012. Sudan was emitting 0.04% of this amount, a very small fraction. Corresponding percentages of global emissions for USA are 14.5% and for China 27.2% (NREL, 2014). In this perspective, the job to reduce the atmospheric concentration of CO2 belongs to other nations than Sudan. 4. Future studies A wide range of different approaches are available when studying and quantifying environmental drivers, climatic change and anthropogenic and management impact on agro-ecosystems, including attempts to estimate carbon sequestration and plant productivity. A common approach is field experiments, but modelling and simulation, and various measurements are also utilized, either as separate activities or in combination. Field experiments constitute empirical testing of effects on crop/forest productivity and effects on soil properties due to environmental drivers and management options such as optimal fertilizer use or improved crop varieties. Environmental variability such as temperature, radiation, water availability etc. directly affects output. For many branches of agriculture are small-plot field experiments a fundamental tool for progress of plant science. In addition to tests of crop varieties and yield optimization, test of new technology and equipment can demonstrate new knowledge to growers. They promote development of basic understanding of the factors that control the production of crops and how these factors interact (Petersen, 1994). In addition, they can provide significant data and information on carbon fluxes and carbon pools, and hence, be a valuable contribution to carbon sequestration research (Liu et al., 2014). Modelling and simulation provide a strong and often suitable tool for assessing impacts of climatic conditions and management options on plant productivity and soil properties. Process based models, with an effort to represent key processes such as hydrology, photosynthesis and respiration allow prediction of future behaviour of vegetation to be performed. This can bring information on future effects of, for example altered water use efficiency in semi-arid areas due to increased atmospheric CO2 concentration or potentially changed conditions for common pathogens and plant diseases. Field experiments and measurements provide vital data for development, calibration and validation of tools for modelling and simulation. The plethora of available models include, among other, crop models (EPIC, PEGASUS) (Folberth et al., 2012; Webber et al., 2009; Liu et al., 2013),

Ardö, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 140-163 dynamic vegetation models (LPJ-GUESS (Lindeskog et al., 2013; Weber et al., 2009) and models focusing on carbon turnover (CENTURY (Parton et al., 1988), Roth-C (Jenkinson et al., 1999). These and other models all have different properties, data requirements, use different time steps in their calculation etc., but they all provide an effort to integrate existing knowledge into a framework for understanding properties and performance of ecosystems, today and tomorrow. Measurement is a wide but basic scientific concept. In the context discussed here, we can utilize direct measurement of carbon pools in soils or in biomass in combination with measurements of meteorological drivers (radiation, temperature, precipitation and available soil water etc.) and environmental properties (e.g. soil). Key processes such as plant assimilation and autotroph and heterotroph respiration are strongly influenced by both meteorology and environmental properties that is why their quantifications are crucial both in order to directly infer relationships, as well as to be used as input data for modelling and simulation. Direct measurements of fluxes of CO2, H2O, energy and momentum between the atmosphere and biosphere can be performed using the eddy covariance method, providing data with high temporal resolution (Ardö et al., 2008; Merbold et al., 2009; Monson and Baldocchi, 2014). This method measures the net flux, i.e. the net ecosystem exchange (NEE) to which two opposing fluxes contribute: CO2 uptake during photosynthesis and CO2 release during respiration. Partitioning of NEE into these component fluxes increase ecosystem understanding and is, hence a required post processing of the flux data (Reichstein et al., 2005). In combination with measurements of radiation, soil moisture, vapour pressure deficit and air temperature (i.e. important environmental drivers) can eddy covariance measurements provide good insight to ecosystem fluxes of carbon on diurnal, seasonal and annual time scales. Drawbacks with the methodology include high costs and that it is relatively technology intense, both when compared to standard meteorological measurements and especially when compared to field experiments. The measurements most often represent a small source area (about 1 km2) and hence do not provide much information on spatial variability. Post processing can be demanding, uncertainty of output variables can be substantial (Richardson et al., 2012) and the time from installation to scientific results may be long. 5. Concluding remarks Many studies have pointed out the possibility to move CO2 from the atmosphere to the soil and the biosphere in order to mitigate climate change. As this mitigation may have numerous beneficial effects on soil properties and cropping systems have this often been denoted as a „win-win‟ situation (Ponce-Hernandez et al., 2004). For drier areas, the amount of carbon possible to sequester is often rather low, both in soils and in biomass and costs for monitoring and verification may exceed the payment received for provision of ecosystem services through increased carbon storage. The understanding of the carbon cycle and the processes that govern assimilation and respiration of carbon naturally requires a combination of the methodologies mentioned above, as well as other complementary methods not mentioned here. A

Ardö, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 140-163 resource efficient strategy could be a combination of small plot field experiments in combination with a modelling effort. This could provide practical, hands on data from the experiments, increase skills and process understanding through model simulations. If local measurements exist (Ardö et al., 2015), these could be used as environmental drivers as well as for calibration and validation of model results. Given the low GHGs emission of Sudan, it may be considered less important to focus on carbon sequestration as a mitigation activity aiming to decrease the global atmospheric concentration of CO2. It is considered more important to promote research and education on strategies to reduce vulnerability to adverse climate events and to increase the capacity to adapt to short-term/seasonal weather conditions and climatic variability (Hulme et al., 2001).

Acknowledgement Several of the studies mentioned above are the results from a more than ten year fruitful cooperation between Department of Physical Geography and Ecosystem Science, Lund University, Sweden and Agricultural Research Corporation (ARC) of the Sudan. Financial support has been provided by ARC, Lund University, EU, Swedish National Science Council, and the Swedish National Space Board. Special thanks go to the colleagues at ARC research station in El Obeid, Dr. Bashir Awad, Dr. Abdelrahman,. Hatim Abdalla (M Sc.) and others. Dr Imad El- Din Babiker and Dr Faisal M. A. El-Hag are acknowledged for providing the opportunities to participate in this special issue.

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Schimel, D. S. 1995. Terrestrial ecosystems and the carbon cycle. Global Change Biology, 1: 77-91. Schlesinger, W. H. 2000. Carbon sequestration in soils: some cautions amidst optimism. Agriculture, Ecosystems & Environment, 82: 121-127. Schlesinger, W. H. and Andrews, J. A. 2000. Soil respiration and the global carbon cycle. Biogeochemistry, 48: 7-20. Schlosser, C. A., Strzepek, K., Gao, X., Gueneau, A., Fant, C., Paltsev, S., Rasheed, B. and Smith-Greico, T. 2014. The Future of Global Water Stress: An Integrated Assessment. Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology Report, Cambridge, MA, USA., 31 pp. Schneising, O., Reuter, M., Buchwitz, M., Heymann, J., Bovensmann, H. and Burrows. J. P. 2014. Terrestrial carbon sink observed from space: variation of growth rates and seasonal cycle amplitudes in response to interannual surface temperature variability. Atmospheric Chemistry and Physics, 14: 133-141. Scholes, M. C., Powlson, D. S. and Guanglong, T. 1997. Input control of organic matter dynamics. Geoderma, 79: 25-47. Sherwood, S. and Fu, Q. 2014. A Drier Future? Science, 343: 737-739. Sjöström, M., Zhao, M., Archibald, S., Arneth, A., Cappelaere, B., Falk, U., de Grandcourt, A. and Hanan, N. 2013. Evaluation of MODIS gross primary productivity for Africa using eddy covariance data. Remote Sensing of Environment, 131: 275-286. Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M. and Miller, H. L. 2007. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC Report, Cambridge, United Kingdom and New York, NY, USA. Sombroek, W. G., Nachtergaele, F. O. and Hebel, A. 1993. Amounts, dynamics and sequestering of carbon in tropical and subtropical soils. AMBIO, 22: 417- 426. Squires, V. R. 1998. Dryland soils: their potential as a sink for carbon and as an agent to mitigate climate change. Advances in GeoEcology, 31: 209-215. Sulieman, H. M. and Elagib, N. A. 2012. Implications of climate, land-use and land-cover changes for pastoralism in eastern Sudan. Journal of Arid Environments, 85: 132-141. Sulieman, H. M. and Siddig, K. H. A. 2014. Climate Change and Rangeland Degradation in Eastern Sudan: Which Adaptation Strategy Works Well? In Nile river basin. Ecohydrological cghallanges, climate change and hydropolitics, eds. A. M. Melesse, W. Abtew, and S. G. Setegn. Heidelberg: Springer. Tollefson, J. 2014. The case of the missing heat. Nature, 505: 276–278. Toulmin, C. 2009. Climate change in Africa.London, New York: Zed Books. UNEP. 1992. World Atlas of Desertification.Nairobi, Kenya. UNFCCC. 2014. United Nations Framework Convention on Climate Change. Retrieved 10 February 2014, from.http://unfccc.int/essential_ background /convention/background/items/2536.php.

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Climate Change Adaptation through Sustainable Forest Management in Sudan: Needs to Qualify Agroforestry Application

Bashir A. El Tahir1

Abstract Global warming as a result of climate change will bring major changes in rainfall and temperatures throughout the world, affecting the livelihoods of many rural and urban populations. Sudan encompasses the largest dry lands in Africa, equal to over 92.1% of the total area of the country, where 82% of the population lives. Predicted changes in temperature and rainfall amount and distribution induced by climate change will have major impacts on the natural environment (soils, water, and vegetation) on which people and their livestock depend. Sudan‟s forests resource is of critical importance to sustainable livelihoods and ecosystems. Forest resource provides a diversity of woodland, non-wood products such as gums, incense, resins, edible fruits, medicinal plants and bush-meat etc. for a major part of the year. Moreover, they provide a range of essential ecosystem services, including biodiversity conservation, air and water purification, nutrient cycling and carbon sequestration. The extent and biological diversity of forests resource are directly and indirectly threatened by climate change and are extremely vulnerable to the projected changes, as well as to other external stressors with which climate may interact. Consequently, adaptation to climate changes through sustainable forest management (SFM) is a central priority in the country‟s development. The conflict between securing a short-term food and livelihood needs, and the long-term objectives for conserving the environment constitutes astringent challenges for reducing emissions from deforestation and forest degradation (REDD) and adapting to climate changes. Nonetheless, agroforestry practices through integrating trees with agricultural production can reconcile these conflicting goals. Beside provision of food, agroforestry can complement the forestry sector efforts in SFM by increasing extent of the resource and providing a set of tree-based production and conservation functions. This paper briefly reviews some of the goods and services that accrue from agroforestry and qualify its application as a SFM option for climate change adaptation. The status and trends of the forest resources and management practices were outlined. The economic, social and environmental functions of forest resources, and the threats to its biological diversity were also highlighted.

Keywards: Climate Change, Rainfall, Temperature, Agroforestry, Deforestation.

Introduction Climate change is a global phenomenon that has negative impacts on the livelihoods of the entire human race. The climate is said to have changed when the patterns and sequence of occurrence of weather events have shifted significantly from what they used to be over a period of time (FAO, 2008).

1 Former Director Tree Seed Centre, El-Obeid Research Station, Agricultural Research Corporation (ARC), El-Obeid, Sudan, E-mail: [email protected]. 16 4 Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186

Human activities including deforestation have led to the increase of greenhouse gases (GHGs) in the atmosphere. The climate change issue has brought the forestry sector into the forefront of all national and international debates. Climate change is arguably the greatest current threat to forest ecosystems, biodiversity and livelihood of poor forest dependents‟ communities. It is one of the greatest environmental, social and economic threats the world has ever faced (UNEP, 2009; IPCC, 2007; UNFCCC, 2006). It is real and happening faster than we previously thought with serious devastating impacts in developing countries, particularly on the Africa continent (UNEP, 2009; IPCC, 2001). The poor countries in particular are the most vulnerable because of their high dependence on natural resources and their limited capacity to adapt to a changing climate (UNDP/UNEP, 2005; FAO, 2005; IPCC, 2001). These impacts are expected to deepen poverty, food insecurity, poor livelihoods, dysfunction of infrastructural facilities, environmental resources and unsustainable development (FAO, 2005; IPCC, 2001). In Africa, vulnerability to climate change is being exacerbated by a number of non-climatic factors, including endemic poverty, hunger, high prevalence of disease, chronic conflicts, low levels of development and low adaptive capacity (FAO, 2009; Desanker, 2002). Climate change has compounded the existing vulnerabilities and the ability of countries to meet their Millennium Development Goals (MDGs) (Sokona and Denton, 2001). Therefore, the task ahead is how to increase the adaptive capacity of affected poor communities and countries. Reducing the vulnerability and impacts of climate change requires the strengthening of mitigation and adaptation mechanisms through sustainable forest management (SFM), good governance and use of clean production technologies (Smit and Wandel, 2006). Forests contribute to climate change mitigation by removing atmospheric carbon dioxide and storing it in different carbon pools (biomass, soil, dead organic matter, litter) (IPCC, 2006). Deforestation and forest degradation are important contributors to global GHGs emissions, but if these processes are controlled, forests can significantly contribute to climate change mitigation (IPCC, 2006). It is estimated that 15% of global GHGs emissions came from deforestation over the period of 2000–2005 (Van der Werf et al., 2009). Moreover, forests comprise an important carbon reservoir, since they store about twice the amount of carbon present in the atmosphere (Canadell and Raupach, 2008). Terrestrial ecosystems could also be a major sink with the potential to offset from 2% to 30% of expected emissions during this century (Canadell and Raupach, 2008; Beerling and Woodward, 2013). Forest-based strategies offer a cost-effective means to mitigate climate change (Canadell and Raupach, 2008; Strassburg et al., 2009). So, appropriate forest management can help in reducing emissions from deforestation and forest degradation and in increasing carbon removals. Forest ecosystems in the Sudan have significant contributions to the livelihood options and national economic activities. Their increased vulnerability to climate change has serious negative impacts on the communities and economies that depend on them. However, forests offer unique opportunities for improving the adaptive capacity of societies and this is especially true for lower-income rural

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 populations (FAO, 2008). In Sudan, the forest resource, however, is threatened by deforestation driven predominantly by energy needs and agricultural clearance. Furthermore, the unbalanced distribution of forests in Sudan as most of the remaining forests (50%) are found in the south, while the highest demand for forest products is in the north- presenting a potential threat for north-south peace, but also a significant opportunity for sustainable north-south trade development (Badri, 2012). Therefore, there is an urgent need for prioritizing the activities that build resilience and facilitate adaptation to climate change in the forest sector in the country, as well as in other related land-based sectors. SFM as an option for climate change adaptation is recognized and supported by the United Nations General Assembly Resolution 62/98 in 2007. In view of the empirical proofs of climate change in Sudan‟s ecological zones and the poor local and foreign investment in the forestry sector, agroforestry technologies can make significant contribution towards addressing the key themes of SFM. This paper argues that it is high time for extensive use of agroforestry to adapt to or mitigate the predicted changes on forests resources. The paper provides a brief review of some of the goods and services that accrue from agroforestry and qualify its application as a SFM option for adaptation to climate changes.

1. Brief background about Sudan The old united Sudan spans over an area of 2.5 million km², with a total population of over 45 millions (Bank of Sudan, 2013). As of July 2011, Sudan Africa‟s largest country has been parted into two countries: (1) the Republic of Sudan (ROS), and (2) the Republic of Southern Sudan (RSS). The ROS covers an area of 1,882,000 km2 with a total population of more than 36 millions, with a rapid growth rate of 2.3% per annum. About 29.5% of the population lives in urban areas, while the majority of the population (70.5%) is rural and many of which are considered as forest dependents, e.g. by having wood as the main source of energy and depending on round timber and poles for buildings (Bank of Sudan, 2013). The soil resources are of two broad regions (FAO, 1995). In the western part of the country, the “Gardud” and “Goz” sandy soils (Arenosols) are dominant covering an area of about 45 million feddans (1 feddan = 0.42 ha). These soils have low to medium fertility and medium potential water storage and are, therefore, marginally productive. Their nutrients could be easily leached under heavy torrential rains. Acacia senegal bush-fallow systems is the most dominant land use system. In the center and the east, soils are mainly clay (Vertisols), covering an area of about 64 million feddans. Large and small-scale mechanized farming is the main farming activity in this region. These soils have considerable agricultural potentiality with high fertility and medium potential moisture storage. Mean annual temperatures vary between 26ºC and 32ºC across the country. The most extreme temperatures are found in the far north, where summer temperatures can often exceed 43ºC and sandstorms blow across the Sahara from April to September. These regions typically experience virtually no rainfall. Rainfall is very variable and is becoming increasingly unpredictable. The unreliable nature of

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 the rainfall, together with its concentration into short growing seasons, heightens the vulnerability of Sudan‟s rainfed agricultural systems. The ecosystem classification and the vegetation distribution closely follow the isohyets that run across the country from west to east. The effect of topographical changes and soil variation on vegetation zones is much less pronounced than that of rainfall levels. However, a south-easterly shift of isohyets has been reported (ILO, 1984) that may be associated with migration of trees and habitats. As of July 2011, the vegetation of the ROS could be divided into the following zones (Table 1): desert (38.6%), semi-desert (26.2%); low rainfall savannah (27.3%); high rainfall savannah (0.9%); special area (6.4%); montane vegetation (0.2%) and flood region (0.4%) (Gaafar, 2011). According to aridity index (UNEP, 1997), the desert, semi-desert and low rainfall savanna falls within the arid and semi-arid zones and represent 92.1% of the total area of the country, while high rainfall savanna falls within the dry sub-humid zone and amount to 7.5% of the total area of the country. Accordingly, Sudan can mostly be classified as the largest dryland in Africa. The biggest challenge the drylands of Sudan face is environmental degradation aggravated by abject poverty and food insecurity which in turn accelerate the environmental degradation process. However, the country is rich in both underground and surface natural resources that have remained mostly under developed because of political and economic constraints. The country‟s important natural resources include forests, wildlife, water, pasture and rangelands, coastal and marine resources, and arable lands. Also, Sudan is endowed with petroleum and a range of metallic and non-metallic minerals, including among others, gold, silver, copper, iron ore (Badri, 2012).

2. Sudan’s forest status and trends The Comprehensive Peace Agreement (CPA) signed between the Government of Sudan and South Sudan Liberation Movement (SPLM) and Army (SPLA) in 2005 and the self-determination referendum followed divided the natural resources between the countries. Based on the CPA, around 50% of the forest and woodland area of the “old unified” Sudan falls in the RSS, while the ROS retains an area of 1,886,000 km² and some 50% of the forest and woodlands of its pre- July 9th estate (Gaafar, 2011). The forest extent and estate in the two countries was inferred by Abdelnour (2011) as quoted in Gaafar (2011) by super imposing the map of Harrison and Jackson (1958) “Ecological Classification of the Vegetation of Sudan” on the maps of the two countries. Table 1 shows the ecological classification of forests and woodlands in the ROS. The forests follow the ecological classification profile and rainfall trends as from north to south with forests taking the form of bush land and scattered trees and shrubs in the north, and denser woodlands and forests with larger trees in mixture of Acacias and broad-leaved trees in the southern end of the savanna and montane region (Gaafar, 2011).

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Table 1. Ecological classification of forests and woodlands in the Sudan (2011). (Figures in (000) km² with % of total in brackets). Desert Semi- Low High Specia Montane Flood Total desert rainfall rainfall l areas vegetatio region savanna savanna n h h 717 486 507 17 119 4 7 1,857 (38.6) (26.2) (27.3) (0.9) (6.4) (0.2) (0.4) (100) Arid and semi-arid Sub-humid Humid 92.1 7.5 0.4 100% Source: Gaafar (2011).

There are three types of forests in Sudan (Table 2): (i) Federal forests: This includes riverine forests along the Blue Nile, the White Nile and their tributaries, as well as reserved forests in Jebel Marra, Nuba Mountains, Ingessana, Fau and all other montane forests and forests north of latitude 13 degrees. (ii) State forests: All state forests away from the rivers, and all those forests under registration according to the National Comprehensive Strategy (NCS). (iii) Community/private forests: All forests established and planned to be established by communities, institutions and private sector, for example, Gezira Board forests, Kennana Sugar Company, Rahad Scheme; community forest and private forests in Jebel Mara, Singa and Mazmum and other parts of the country The reserved forest area which was reserved during the period 1926-1989 has remarkably increased from 1.22 to about 12.6 million ha by the end of 2009 (Gaafar, 2011). The total area of the reserved forests represents 4.8% of the total area of the country. In addition to that, the total area occupied by other protected areas (game reserves) represents 5.7% of the total area of Sudan. This indicates that about 10.5% of the total area of the country is currently under forestry and other natural resources uses. Table 2 shows that the total area of forest plantations in the ROS is 1.3 million ha, which include community and reserved forests, gum Arabic gardens and private forests (individuals and institutions).

Table 2. Types and areas of forest plantations in the Sudan. Types of plantations Area (ha) Community forest 77,665 Reserved Forests 466,590 Hashab plantation (gum gardens) 630,000 Companies 126,075 Total ROS 1,300,330 Source: Gaafar (2011)

Afforestation and reforestation activities have been practiced in Sudan since 1911 and are restricted to areas constituted as reserves and subsequently put under management. They are exclusively owned by FNC. The annual FNC afforestation and reforestation programmes ranged from 2,100 ha to 2,520 ha during the period Copyright © 2015 SAPDH 168 ISSN 1816-8272

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1910-1950, to some 35,000 ha during the 1990s and from 24,000 to 49,000 ha of forest plantations during the period 2000-2009 (Table 3) depending on availability of resources, including foreign assistance (Gaafar, 2011).

Table 3. FNC annual afforestation programmes (1990-2009). Period By FNC in reserved forests Community and social (000) ha (000) ha Total Average total average 1990-1994 123 25 56 11 1995-1999 117 23 60 12 2000-2004 70 14 52 10 2005-2009 134 27 108 22 Source: Gaafar (2011)

The Global Forest Resource Assessments (FRA) of 1990 and 2010 (FAO, 2010) indicated a declining trend in the forest cover of the “Old Unified” Sudan from 76.38 million ha (32.1%) to 69.95 million ha (29.4%), respectively (Table 4). However, it also indicated an improvement in the annual deforestation from 589,000 to 542,000 ha for the same period (Gaafar, 2011). After separation of RSS in July 2011, the area covered by forests and woodlands is estimated by the FNC as 21,826,166.62 ha, equivalent to 11.6% of the total area of Sudan. Drought and increasing pressure on land by the expansion of mechanized and rain-fed farming have decreased forest resources and rangelands, and overgrazing is a growing problem. Environmental degradation and competition for limited natural resources has been a contributing cause of conflict in the region (UNEP, 2007). To increase areas of forest cover, the Country National Strategy (CNS) (1992- 2002) and the Quarter Century Strategy (2003–2027) allocated 25% of the country‟s total land for natural resources, namely forestry, range and pasture and wildlife.

Table 4. Forest cover of the “old unified” Sudan Type of land/water Area (000 ha) 1990 2000 2005 2010 Forests 76 381 70 491 70 220 69 949 Other wooded land 58 082 54 153 52 188 50 224 Other land 103 137 112 956 115 192 117 427 Inland water bodies 12 981 12 981 12 981 12 981 Total area 250 581 250 581 250 581 250 581 Forests area % 32.1 29.7 29.6 29.4 Annual deforestation -959 -589 -589 -542 rate -1.4% -0.8% -0.8% -0.7% Source: FAO (2010).

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3. Forest management practices in Sudan Forest management in Sudan mainly focuses on production, protection and conservation with little emphasis on social or multiple services. In reserved forests, management is based on conservation, economics, or a mixture of the two. Techniques include timber extraction, planting and replanting of various species, and preventing fire. However, the on-going forest management practices stimulate deforestation, degradation, genetic loss of wide range of plant and animal species, because the majority of forests continued to be owned and managed formally by the Federal and the States Departments of forestry with very little involvement of the local communities. These institutions are hampered by lack of funds and personnel and the effectiveness of forest governance is increasingly independent of formal ownership (Agrawal et al., 2008). The quest for survival by the rural poor and the desire to generate more revenue by the FNC and the States Governments are obviously more paramount than the need for the conservation of the resource-base and its diversity. Consequently, illegal logging and inappropriate agricultural practices in different parts of the country have exacerbated the decline in both density and floristic richness of the Sudan‟s forests.  Before the advent of the forest Act in 1989, taungya (agro-silviculture) systems as a forest management system is adopted by FNC to be implemented through the participatory forest management (PFM) approach to rehabilitate degraded forests in different part of the country. Taungya system was introduced as far back as in 1932 when the then Forestry Department (Currently FNC) was charged with the responsibility of establishing forest plantations for the production of wood in the long term. Taungya is the combination of agriculture and silviculture in which forestland is used for growing agricultural crops during the initial years of forest plantation. The main objectives were to regenerate and protect reserved forest, while helping vulnerable landless men and women of local communities to earn a living. Taungya fits in with the concept of multiple land use and here the land is used simultaneously for rising agricultural and forestry crops. However, the system is only available during the establishment of forest reserves. Communities have no rights to the land, and once the forest is established and well grown the people have very limited access rights (e.g. firewood collection and grazing).  Other forms of PFM were introduced into law with the passing of the Forest Act of 1989, which provides a clear legal basis for communities, groups or individuals across the country to own, manage or co-manage forests under a wide range of conditions. Forest Act of 1989 allows for a range of different forest management arrangements. These include: 1. Joint Forest Management (JFM): The Forest Act allows communities to sign joint forest management agreements with government and other forest owners. Marked areas in reserved forests and protected forests are designated as a communal forest for villages inside the reserved or protected forest or in the fringe areas. However, in reserved forests the communities have no legal rights to land. In Sudan, JFM has emerged as Copyright © 2015 SAPDH 170 ISSN 1816-8272

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an important intervention in the management of forest resources in the Sudan. The primary objective of JFM is to ensure sustainable use of forests to meet local needs equitably while ensuring environmental sustainability and conservation. Under the JFM the effective involvement of village communities in evolving sustainable forest management systems has been looked upon as an important approach to address the long-standing problems of deforestation and land degradation in Sudan. 2. Institution Forests (IF): Afforestation schemes in disused farmlands, cut out area in big irrigated scheme or other wasteland belong to particular institutions. 3. Community Forest Management (CFM): These are typically collaborations between local villagers and non-governmental organizations and FNC. The law enables local communities to declare and ultimately gazette village, group or private forest reserves.

4. Economic, social and environmental functions of forest resource Forests have four major roles in climate change (FAO, 2013): (1) they currently contribute about one-sixth of global carbon emissions when cleared, overused or degraded; (2) they react sensitively to a changing climate; when managed sustainably, (3) they produce wood fuels as a benign alternative to fossil fuels; and finally, (4) they have the potential to absorb about one-tenth of global carbon emissions projected for the first half of this century into their biomass, soils and products and store them - in principle in perpetuity. The economic, social and environmental functions of forest resources in Sudan vary greatly among the different parts of the country. However, Sudan‟s forests are important sources of wood and non-wood forest products (NWFPs) and habitats for wildlife. Wood products from the forestry sector include fuel wood, sawn timber and round poles. Fuel wood is probably the most important forest product in many parts of the country, especially among rural population. Fuel wood (firewood and charcoal) supply amounts to more than 75% of the country‟s energy needs. The forest product consumption survey conducted by the FNC in northern Sudan in 1995 found that the total annual consumption of wood was 15.77 million m³ (FNC, 1995). In 1987, FAO estimated that Sudan produced 41,000 m³ of sawn timber, 1.9 million m³ of other industrial round wood and more than 18 million m³ of firewood. Industrial forest plantations consist of both softwoods and hardwoods (Gaafar, 2011). Most of the hardwood plantations are in urban and peri-urban areas and are mainly used to supply fuel wood and poles. The main objective of the softwood plantations in Jebel Marra in Western Sudan is to provide industrial round wood for different purposes. Forests also provide an assortment of marketable NWFPs such as gum Arabic, incense, resins, honey and edible fruits. Sudan is responsible for 80% of the world's gum Arabic production and trade. The country‟s annual export of gum Arabic is 45,000 tons which accounts for an average of 17% of Sudan‟s annual export earnings. Gum Arabic is produced from the sap of the Acacia senegal (hashab gum) and Acacia seyal (talh gum) and is used as a nontoxic binder in a multitude of products, including food and pharmaceuticals. The gum Arabic

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 industry provides a critical source of income for rural communities with forestland access (UNEP, 2007). Sudan has a long tradition in beekeeping, with an estimated number of beekeepers of 50,000 in 1980, and number of colonies around 200,000 and production amounting to 1200 tons annually. Apparently, a large quantity of honey produced in Sudan is being harvested from forests area. Most of the population of the country (>70%) lives in rural areas with high poverty levels. Rural communities derive extensive benefits from forests include grazing, hunting, shade, forest foods in the form of tree leaves, wild fruits, nuts, tubers and herbs, bush meat, tree parts (barks, leaves, seeds, fruits and roots) for medicinal purposes. These NWFPs constitute important safety nets and are used to diversify income as part of adaptive strategies (which are both anticipatory and reactive) by many communities in developing countries faced with increased climatic variability (FAO, 2010; 2008). Sudan‟s forests encompass a multiplicity of indigenous fruit trees species yielding edible fruits which are mostly known only in their specific localities, while a few are known and consumed all over the country and abroad (El Tahir, 2004). There are over 45 marketable indigenous fruit tree species; 40 in the local markets; six in the national markets (Adansonia digitata, Balanites aegyptiaca, Hyphaene thebaica, Tamarindus indica, Ziziphus spina-christi and Grewia tenax; three (A. digitata, B. aegyptiaca, T. Indica) in the international market (El Tahir, 2004). For example, the value of exports of NWFPs for the Sudan (mainly gums) has been more than the imports of wood products during the period 1986-1995. This confirms the positive effect of the forest sector on the country's balance of payment. The ecological benefits of forests include sand dune stabilization in fragile semi- desert environments and amelioration of soil through nitrogen fixation. In a review of ecosystem-based adaptation using forest and trees, Pramova et al. (2012) highlighted cases in which trees and forests can support adaptation by providing goods to communities and land cover in watersheds to reduce erosion and flood risk, and by protecting coastal areas from climate related threats. Forests contribute to watershed quality by stabilizing off-site soil, reducing off-site sedimentation, reducing flood peaks on streams in small watersheds and replenishing groundwater and watercourses. The ecological-stabilization functions also include protection of hydropower and irrigation systems. Mangrove forests located along the Red Sea coast serve sink functions, holding excess nutrients and pollutants that could otherwise flow directly into coastal lagoons and coral reefs (Badri, 2012; UNEP, 2007). Forest resources in Sudan are recognized to contribute to climate change mitigation through storing carbon in biomass and as natural habitats for wildlife and the conservation of biodiversity. With regard to carbon sequestration, Sudan's forests contain 1,393 million metric tons of carbon in living forest biomass (FAO, 2013). According to the World Conservation Monitoring Centre, concerning biodiversity and Protected Areas, Sudan has some 1,431 known species of amphibians, birds, mammals and reptiles, of these, 1.6% are endemic and 2.0% are threatened. Sudan is also home to at least 3,137 species of vascular plants, of

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 which 1.6% are endemic. Generally, about 3.5% of the old unified Sudan has been protected under IUCN categories I-V (IUCN, 1992; 2010). While the socio-economic and environmental values of forests are high in terms of livelihoods, increased income and environmental conservation, forest area is declining due to increased deforestation resulting from collection of wood for fuel, clearing for agriculture, desertification and illegal or poorly regulated timber extraction, uncontrolled grazing, and fires. Overall, rising deforestation, inflexible policies, poor operating environment, multifaceted and exploitative market mechanisms have added miseries to the poor natural resource-dependent population.

5. Threats to forest resources and biodiversity in Sudan Deforestation and forest degradation are in fact the major threats to the forestry development in Sudan. Information on forest cover and biomass changes and deforested areas obtained from successive inventories and remote sensing images carried out in 1990, 2000, 2005 and 2010 by Global Forest Resource Assessment (FRA) indicated that the forest area declined from 76.4 million ha in 1990 to 70.0 million ha by the end of 2009. The on-going process of environmental degradation is a critical issue that affects the livelihoods of a large sector of the population. Removal of tree cover for crop production, felling trees for fuel wood and building poles, in addition to overgrazing are factors that, together with drought conditions, resulted in desertification and consequently, shortage in food crops, and loss of soil fertility. People's awareness about the critical situation and its future consequences and the importance of tree planting and protection is vital for their involvement in the protection and rehabilitation of the environment. It is also proving to be more forceful and apparently sustainable when it is of an income generating nature (FAO, 2013).

As reported by Sudan Environmental Threats and Opportunities Assessment (ETOA), (Badri, 2012) the key threats to Sudan‟s forest resources include: 1. Weak federal driven policies versus autonomous state control. 2. Weak local/global stakeholder involvement 3. Continued and existing dispute between the State Governments and the FNC over ownership of forest resources, management and revenue accrue from them. 4. Weak local and foreign investment in the forestry sector. 5. Widespread, severe and ongoing desertification in northern, central, eastern and western Sudan.

With regard to biodiversity, the overall threats include: 1. Worsening of climatic conditions. 2. Weak environmental governance, sustainable participatory planning and the rule of law 3. Conflict-related, inter-sectorial natural resources‟ exploitation. 4. Lack of targeted investment by the government, the private sector and the international community. 5. Lack of policies to benefit poor people and lessen resource‟s inequalities. 6. Low quality supporting research and education.

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7. Evidence of climate change and future scenarios Evidence of climate change in the Sudan has been accumulating for some time, including from assessments in smaller areas, point assessments and region-wide assessments. Climate scenario analyses conducted as part of the preparation of Sudan's Initial National Communication (INC) in February 2003 indicated that average temperatures are expected to rise significantly relative to baseline expectations. By 2060, projected warming ranges from 1.5oC to 3.1oC during August to between 1.1oC to 2.1oC during the month of January (HCENR, 2007). Projections of rainfall under climate change conditions also shows sharp deviations from baseline expectations. Results from some of the models show average rainfall decrease of about 6 mm/month during the rainy season. Such changes in temperatures and precipitation will adversely affect sustaining the development progress that has been achieved in many sectors in Sudan. The three highest priority sectors where urgent and immediate action is needed were identified through the NAPA consultation process were agriculture, water and public health (HCENR, 2007). The field of climate change projections for the Sudan is evolving at an increasingly rapid rate. Taha et al. (2012) used four downscaled global climate models (GCMs) from the IPCC AR4. The CSIRO model projects that annual rainfall will remain unchanged through 2050, while the MIROC model indicates that most of the southern part of Sudan will get wetter, a very favorable outcome, particularly for the semiarid regions. While changes in annual precipitation are negligible or positive, the story for temperature change is different. The results of all models indicated that Sudan is getting warmer (within a range of 0.5 - 3°C). The CSIRO model projected only moderate increases in temperature for the whole country, with all but very small patches in the 1 - 1.5°C range. The MIROC model, on the other hand, showed significant spatial variation, with only modest temperature increases in the south, but very large temperature increases in the north. Higher temperatures would increase evaporation and reduce soil moisture, increasing plant water requirements - an unfavorable trend, particularly if associated with a lower level of precipitation and insufficient irrigation water (Taha et al., 2012).

8. Climate change adaptation through sustainable forest management (SFM) 8.1 The concepts and definition of SFM SFM is the management of forests according to the principles of sustainable development. SFM implies various degrees of deliberate human intervention, ranging from actions aimed at safeguarding and maintaining the forest ecosystem and its functions, to favoring specific socially or economically valuable species or groups of species for the improved production of goods and services (FAO, 2013). It ensures that the values derived from the forest meet present-day needs, while at the same time ensuring their continued availability and contribution to long-term development needs (FAO, 2008). It has a remarkable potential to serve as a tool in combating climate change, protecting people and livelihoods, and creating a foundation for more sustainable economic and social development (FAO, 2008; FAO, 2013).

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SFM uses very broad social, economic and environmental goals. SFM is a universally accepted concept that guides forest policies and practices around the world. It constitutes an overarching approach to forest management and its implementation requires, at the national or subnational levels, enabling policies, laws and institutions and, on the ground, the application of sound management practices based on good science and traditional knowledge (FAO, 2013). SFM can be applied in all types of forests, regardless of the objective(s) of management (e.g. production, conservation, protection and multiple uses). In 2007, the United Nations General Assembly adopted language on SFM that describes the concept and lists the elements it encompasses. In its Resolution 62/98, the United Nations describes SFM as a dynamic and evolving concept that “aims to maintain and enhance the economic, social and environmental values of all types of forests, for the benefit of present and future generations”. Hence, SFM is a wise utilization of the forest ecosystem without compromising its future availability. The Resolution recognizes the seven thematic elements of SFM as: 1. extent of forest resources; 2. forest biodiversity; 3. forest health and vitality; 4. productive functions of forest resources; 5. protective functions of forest resources; 6. socio-economic functions of forests; 7. legal, policy and institutional framework. Achieving SFM would, therefore, involve the administrative, legal, technical, economic, social and environmental aspects of the conservation and use of forests. Thus, SFM includes the involvement of people and the availability of appropriate techniques and adequate finance. To minimize the impacts of climate change on forest ecosystems and forest-dependent people, countries will require flexible and equitable decision-making processes at local and national levels that allow for rapid and adaptable forest management practices (FAO, 2013). There is growing awareness that SFM should include measures for the effective conservation and management of forest resources in order to meet the actual and future needs of local people (FAO, 2013). The extent and biological diversity of forests resource in Sudan are directly and indirectly threatened by changing climatic conditions. The resource is extremely vulnerable to the projected changes in climate, as well as to other external stressors with which climate may interact. Consequently, adaptation to climate changes through SFM is a central priority in the country‟s development. Sudan pursuit for food security through agricultural expansion will repeatedly lead to deforestation and forest degradation. The conflict between securing a short-term food and livelihood needs and long-term environmental conservation objectives constitute astringent challenges for reducing emissions from deforestation and forest degradation (REDD) and adapting to climate changes. Nonetheless, agroforestry practices through integrating trees with agricultural production can reconcile these conflicting

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goals. Beside provision of food, agroforestry can complement forestry sector efforts in SFM by increasing extent of the resource and providing a set of tree- based production and conservation functions. The above underscored themes of SFM can equally be addressed by agroforestry. Agroforestry is becoming recognized as a land use system which is capable of yielding both wood and food while at the same time conserving and rehabilitating ecosystems (Nair, 1993). Climate change adaptation strategies to be formulated for local communities to manage forest reserves in Sudan should pay greater attention to agroforestry systems (AFS). In view of that the following sections give a brief review of some of the goods and services that individuals and societies can derive from SFM and that can be ensued from application of agroforestry.

9. Agroforestry concepts and definition The term agroforestry denotes land-use systems and technologies where woody perennials (trees, shrubs, palms, bamboos, etc.) are deliberately used on the same land-management units as agricultural crops and/or animals, in some form of spatial arrangement or temporal sequence. In AFS, there are both ecological and economical interactions between the different components (Lundgren and Raintree, 1982). Three basic types of AFSs are renowned viz: agro-silviculture (crops/trees), silvopastoral (pasture/animal/trees); and agro-silvopastoral (crops/pasture/trees). Other specified AFS can also be defined e.g. apiculture (bees with trees), aquaculture (fishes/ trees and shrubs); sericulture or silk farming (trees/shrubs/silkworm), and multipurpose tree woodlots. In Sudan, agroforestry practices have been known for a very long time and practiced in various forms in different parts of the country. In the drylands of Sudan, there are a number of indigenous AFSs involving agro-silviculture, agro- silvo-pastoral, and silvopastoral systems. The existence of these systems has a great potential for further development and the introduction of new AFSs. However, except for a general description, the existing AFSs have not so far been thoroughly studied. Some of these systems had been described and studied in detail viz: Acacia senegal bush-fallow and Faidherbia (Acacia) albida parkland systems, while others are scarcely researched (El Tahir, 2013). Though various forms of AFS are flourishing in many parts of the country, their present situations do not allow the realization of the maximum biological potential benefits in the needed quantity and quality (El Tahir, 2013). Using these systems as an embarking point, further improvements can be established. The improvements have to be able to maximize the potential benefits from the tree species without inflicting losses in other land use aspects, like crop and/or livestock production. Although these systems are being practiced for many years, knowledge on their functions, processes and capabilities to generate ecosystems services is lacking. Also, very little attempt has been made to quantify the economic values of these systems for informed decision-making. This has led to little appreciation of their environmental benefits with consequent undervaluation (El Tahir, 2013).

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9.1 Potentials of Agroforestry The World Agroforestry Centre (ICRAF) identified six ways that agroforestry can contribute to achieving the MDGs (Garrity, 2004): 1. Eradicate hunger using agroforestry methods of soil fertility and land regeneration. 2. Reduce poverty using market-driven, local tree cultivation systems to generate income and build assets. 3. Advance the health and nutrition of the rural poor. 4. Conserve biodiversity using agroforestry-based integrated conservation- development solutions. 5. Protect watershed services and enable the poor to be rewarded for providing these services. 6. Help the rural poor to adapt to climate change and benefit from emerging carbon markets. 9.1.1 Food security and poverty reduction As a dynamic ecologically based natural resources management system, agroforestry can provide multiple benefits for land users at all levels (Leaky et al., 2005; ICRAF, 2006). The resulting biological interactions provide various benefits, including increased, diversified and sustained biological production, diversified income sources, better water and soil quality and improved habitats for both human and wildlife. Agroforestry technologies can make significant contribution towards addressing high levels of food insecurity and associated land degradation in the Sudan. Since soil degradation is extensive and drought has become more frequent in the country, agroforestry can improve soil biology and water holding capacity through addition of organic matter from litter fall. This in turn contributes significantly to increased productivity. AFSs have considerable potential for helping to solve some of African‟s main land use problems (Sanchez, 1996). Trees in agroforestry can supply farm households with a wide range of products for domestic consumption or for sale, including food, medicine, fuel wood, nuts, fruits, building materials, timber and livestock‟s feeds. Agroforestry also helps maximizing productivity, creating jobs and income in rural areas, and safeguarding sustainability (Sanchez, 1996). Traditional agriculture in the Sudan is unsustainable and keeps small farmers in a vicious circle of poverty. The majority of the people‟s livelihoods in the rural areas depend on agriculture. Any failure in crop production will have negative impacts on natural resources (mainly forests). Agroforestry is a promising alternative and one of the very few options to lift people out of the poverty trap. However, for this to happen there is a need to promote innovations that farmers can adopt and invest in and that in turn generate incomes and services and/or save costs they incur (Denning, 2001). This must be supported by improved access to markets and stronger associations that can help facilitate economies of scale (Denning, 2001). As a land management system, agroforestry is recognized as an effective approach for minimizing production risks under climate variability and change. Verchot et al. (2007) discussed the mitigation potential of agroforestry in the humid and sub- humid tropics and highlighted the role that agroforestry has in climate change

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 adaptation, particularly for smallholder farmers. Trees are able to explore larger soil depths to access water and nutrients, which will benefit crops in times of drought. In addition, trees contribute to increased soil porosity, reduced runoff and increased soil cover, leading to increased water infiltration and water retention and reduced moisture stress. However, care must be taken to minimize competition between trees and crops in agroforestry systems for soil moisture (particularly in areas of low rainfall) and light (Verchot et al., 2007). Agroforestry can minimize risks from crop failure when crop production is curtailed during drought. In Malawi, for example, Garrity et al. (2010) reported that during a drought season, farmers who practiced agroforestry obtained modest crop yields, while farmers who did not practice agroforestry experienced crop failure.

9.1.2 Ecosystems services and environmental benefits of agroforestry The understanding of the potential of agroforestry has increased further during the early 1990's as scientists and policy makers recognized the potential for applying AFS to resolve problems such as soil erosion, intensifying salinity, surface and ground water pollution, increasing GHGs and biodiversity losses in temperate zones and developed economies (Sanchez, 1996). Recently, with increasing global concern about climate change and GHGs emission, agroforestry has been demonstrated to provide several ecosystems services and environmental functions. These include: carbon sequestration, biodiversity conservation, soil enrichment and conservation and air and water quality. 9.1.2.1 Potential of agroforestry for carbon sequestration According to Makundi and Sathaye (2004), agroforestry for carbon sequestration is attractive because: (i) it sequesters carbon in vegetation and in soils depending on the pre-conversion soil carbon, (ii) the more intensive use of the land for agricultural production (e.g. agroforestry) reduces pressure on exploitation of natural ecosystems, (iii) the wood products produced under agroforestry serve as substitute for similar products unsustainably harvested from the natural forests, (iv) to the extent that agroforestry increases the income of farmers, it reduces the incentive for further extraction from the natural forest for income augmentation. Montagnini and Nair (2004) reviewed the current status of understanding on carbon storage potential for AFSs and examined how this potential could be exploited for the benefit of landowners and the society at large. They reported that average carbon storage by agroforestry practices has been estimated as 9, 21, 50, and 63 Mg C ha−1 in semiarid, sub-humid, humid, and temperate regions, respectively. For smallholder AFSs in the tropics, potential carbon sequestration rates range from 1.5 to 3.5 Mg C ha−1 yr−1. In addition to this direct effects, agroforestry can also have an indirect effect of carbon sequestration when it helps decrease pressure on natural forests, which are the largest sink of terrestrial carbon, through the use of agroforestry technologies for soil conservation, which could enhance carbon storage in trees and soils (Montagnini and Nair, 2004; Makundi and Sathaye, 2004). On regional scale, Jose (2009) reported the results of four studies on carbon sequestration by AFSs. In West African Sahel, improved agroforestry practices such as live fence and fodder bank sequestered more carbon than traditional parklands. In northwest India, soil organic carbon concentration and pools were Copyright © 2015 SAPDH 178 ISSN 1816-8272

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 higher in soils under agroforestry and increased with tree age. In Zambia, carbon stored in trees and soil of improved fallows could be increased by planting selected tree species on soils with high clay content. In south Indiana, tree density and plant-stand characteristics of home gardens affected soil carbon sequestration. The results showed that the potential to sequester soil carbon increased with species richness and tree density. All of these case studies have indicated that AFSs have the potential to sequester greater amounts of above and below ground carbon compared to traditional farming systems. On global scale, Nair et al. (2010) showed that carbon sequestration potential of the vegetation component (above- and below-ground) varied from 0.29 Mg ha−1 yr−1 in a fodder bank agroforestry system of West African Sahel to 15.21 Mg ha−1 yr−1 in mixed species stands of Puerto Rico. Soil carbon estimates ranged from 1.25 Mg ha−1 in a Canadian alley cropping system to 173 Mg ha−1 in an Atlantic Coast silvopastoral system in Costa Rica. The authors concluded that, in general, agroforestry on arid, semiarid, and degraded sites had a lower carbon sequestration potential than those on fertile humid sites; and temperate AFSs had relatively lower rates compared to tropical systems.

9.1.2.2 Potential of agroforestry for biodiversity conservation The literature on the role of agroforestry in biodiversity conservation is growing rapidly. A large body of research worldwide (Jose, 2009; Schroth et al., 2004) has suggested five major roles of agroforestry in conserving (i) provides habitat for species that can withstand a certain level of disturbance in agro-ecosystems; (ii) provides connectivity and acts as stepping-stone by creating corridors between habitat remnants and, thereby conservation of area-sensitive plant and animal species; (iii) helps preserve germplasm of socially useful and associated species; (iv) helps reduce the rates of conversion of natural habitat by providing goods and services alternative to traditional agricultural systems that may involve clearing natural habitats; and (v) helps conserve biological diversity by providing other ecosystem services such as erosion control and water recharge, thereby preventing the degradation and loss of surrounding habitat. However, the interrelationship between forest ecosystems, agroforestry and biodiversity can be made more dynamic through adaptive management strategies that incorporate results from research and monitoring in order to feed information back into the management system (Jose, 2009). Also, active participation by local landowners and communities is also critical in this context (Schroth et al., 2004).

9.1.2.3 Potential of agroforestry for improved air and water quality AFSs are proven as strategies to improve air and water quality (Nair, 2011; Jose, 2009). Agroforestry practices such as windbreaks and shelterbelts are publicized as having numerous benefits. These benefits include effectively protecting buildings and roadways from drifting snow, savings in livestock production-by reducing wind chills, protecting crops, providing wildlife habitat, removing atmospheric carbon dioxide and producing oxygen, reducing wind velocity and, thereby limiting wind erosion and particulate matter in the air, reducing noise pollution and mitigating odor from concentrated livestock operations, among others.

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Agroforestry practices are also perceived as a strategy to provide clean water (Nair, 2011; Jose, 2009). In conventional agricultural systems, less than half of the applied N and phosphorous fertilizer are taken up by crops. Consequently, excess fertilizer is washed away from agricultural fields via surface runoff or leached into the subsurface water supply, thereby contaminating water sources and decreasing water quality. AFSs such as riparian buffers have been proposed as a means to combat non-point source pollution from agricultural fields (Jose, 2009). Riparian buffers help clean runoff water by reducing the velocity of runoff, thereby promoting infiltration, sediment deposition and nutrient retention. Buffers also reduce nutrient movement into ground water by taking up the excess nutrients. Also in AFSs, trees with deep rooting systems can also improve ground water quality by serving as a „„safety net‟‟ whereby excess nutrients that have been leached below the rooting zone of agronomic crops are taken up by tree roots (Nair, 2011). These nutrients are then recycled back into the system through root turnover and litter fall, increasing the nutrient use efficiency of the system. Trees also have a longer growing season than most agronomic crops, which increases nutrient use and use efficiency in an AFS by capturing nutrients before and after the cropping season. 9.1.2.4 Potential of agroforestry for soil conservation and soil enrichment The potential of AFSs for soil conservation and improvement has been studied widely over the years in different parts of the world. AFSs have a potential to develop sustainable management alternatives for intensive use of tropical steep lands for food crop production (Lal, 1990). The concepts and practices of soil amelioration by trees had been extensively reviewed by several authors (Nair, 1993; Young, 1989). The role of agroforestry in enhancing and maintaining long- term soil productivity and sustainability has been well documented (Lal and Stewart, 1992; Young, 1989; Subhrendu and Mercer, 1996; Nair et al., 1999). Well-designed AFSs can help through direct and indirect ways in controlling soil conservation; maintaining soil organic matter; improving soil physical and chemical properties; enhancing nitrogen fixation; increasing nutrient cycling; ameliorating soil microbial activities; increasing soil water availability; helping reclaim degraded soils and maintaining soil fertility (Young, 1989). Trees in agro- ecosystems can enhance soil productivity through biological nitrogen fixation, efficient nutrient cycling, and deep capture of nutrients and water from soils. Even the trees that do not fix nitrogen can enhance physical, chemical and biological properties of soils by adding significant amount of above and belowground organic matter as well as releasing and recycling nutrients in tree bearing farmlands (Young, 1989; Nair et al., 1999).

9.1.2.5. Potential of agroforestry for socio-economics benefits Recent economic studies have shown that financial benefits of AFSs are due to increased diversity and productivity of the systems which are influenced by market and price fluctuations of tree products, livestock and crops, returns to land and labor. In addition to higher yield potentials of agroforestry, product diversification increases the potential for economic profits by providing annual and periodic revenues from multiple outputs throughout the rotation and reducing the risks associated with single commodities in mono-culture (Mercer and Miller, Copyright © 2015 SAPDH 180 ISSN 1816-8272

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1998; Franzel and Scherr, 2002) or reduction in input costs (Franzel, 2004). For example, Jain and Singh (2000) evaluated industrial AFS with Poplar (Populus deltoides) in Utter Pradesh, India, in terms of income, employment and environmental impacts. They found that the system is economically viable and more profitable than any crop rotations followed in the area, provides employment opportunities and is not highly risky. Rahman et al. (2013) studied the species composition commonly found in the homestead AFSs in the Ganges valley of northern Bangladesh and their relative contribution to local livelihood. Financial analysis showed that homestead agroforestry net benefit increases with the increasing landholding classes. They concluded that increasing agroforestry practices in homesteads, should be the strategy for enhancing tree cover in order to meet basic needs of the local people and for environmental sustainability Other studies have examined the financial costs of establishing, managing and producing various combinations of agricultural and timber crops as well as the potential gross revenues and profitability. Gingo et al. (2006) analyzed the performance of three AFSs (rubber agroforestry, cinnamon multi-cropping, and dammar agroforestry) an oil palm monoculture in the southern part of Sumatra using a combination of modeling and data from various sources. They found that all three AFSs are financially and economically attractive and have potential as tools for carbon sequestration. In the Philippines, Bertomeu (2006) examined the private profitability of two tree-maize systems (trees in blocks and trees in hedgerows), compared with maize mono-cropping. He found that maize mono- cropping provided higher returns to land at the current timber price, but considerably lower returns to labor, than the maize-tree systems tested. Dwivedi et al. (2007) studied the socio-economics of traditional and commercial AFSs containing tree species of high economic values (Azadirachta indica, A. nilotica, Dalbergia sissoo, P. deltoids and Eucalyptus spp.) in western Uttar Pradesh, India. They found that in traditional systems the net return from tree produce ha-1 y-1 was higher for marginal farmers compared with small and medium farmers. In commercial systems, the benefit: cost ratio (B/C) was higher for poplar based agro-silviculture than poplar and eucalyptus based bund system. El Tahir (2013) used the total economic value (TEV) as a framework to estimate the ecosystem values of three (taungya, rain-fed and irrigated) AFSs in four refugee sites in the Eastern Region of Sudan. The results revealed that AFSs have significantly contributed to the livelihoods of the local communities. The perceived total economic value (TEV) of AFSs includes marketable and non- marketable goods and services. The main direct marketable and sustainable high value products include: food, cash crops, firewood, gum, fodder, NTFPs medicine, and honey. All of these products give sustainable income to the farmer directly and also sustainable benefits to the region indirectly. The study showed that over all, the average net direct-use value of marketable products from AFSs across all sites was estimated at 7,346,000 (SDG) per household per year. This indicates the significant contribution of AFSs to food security and income improvement of the local communities. Gum Arabic alone accounted for 38%, followed by sorghum grain and fodder 35%, and then cash crops (sesame) 18%. The TEV would be many time higher if other indirect values (non-marketable

Tahir et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 164-186 services) such as shade, aesthetic and recreation, environmental protection, biodiversity and carbon sequestrations are quantified. 10. Conclusions Forests sector in Sudan do have the potential to contribute to national adaptation strategies. Planting forests and SFM can aid in satisfying the present and future needs of the society from forest products as well as assisting in the protection of soil and land against detrimental impacts of climate changes. Adaptation strategies that support forestry sector; increase income; reduce poverty, as well as natural resource conservation and biodiversity are of paramount importance. SFM is the only practical way by which the climate change menace can be overcome. The basic themes of SFM can equally be addressed by agroforestry. Under the situation of weak local and foreign investment in the forestry sector, agroforestry can complement forestry sector efforts in achieving SFM by providing a set of tree-based conservation and production functions. Some important sustainability issues on which agroforestry can assist forestry are the extent of the resource, biological diversity, wood and non-timber products, ecosystems services and environmental benefits such as soil and water conservation, carbon sequestration, and socioeconomic benefits. However, both SFM and agroforestry in Sudan are hampered by a set of challenges. These include lack of political commitment; poor funding of the forestry subsector; high level of poverty especially among the rural populace; inadequate information on the crucial roles of forest on climate change mitigation; inadequate forestry personnel and deprived training on climate issues in the State Departments of Forestry, and lack of adequate improved technologies of agroforestry.

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Makundi, W. R. and Sathaye, J. A. 2004. GHG mitigation potential and cost in tropical forestry-relative role for agroforestry, Environment, Development & Sustainability, 6, 235-260. Mercer, D.E. and Miller, R.P. 1998. Socioeconomic research in agroforestry: progress, prospects and priorities. Agroforestry Systems, 38: 177-193. Montagnini, F. and Nair, P. K. R. 2004. Carbon sequestration: An underexploited environmental benefit of agroforestry systems. Agroforestry Systems 61: 281– 295. Nair, P. K. R. 1993. An introduction to Agroforestry. Kluwer, Boston. Nair, P. K. R. 2011. Agroforestry systems and environmental quality: Introduction. Journal of Environmental Quality, 40(3):784-790. Nair, P. K. R., Buresh, R. J., Mugendi, D. N. and Latt, C. R. 1999. Nutrient cycling in tropical agroforestry systems: Myths and science. In: Buck, L. E., Lassoie, J. P. and Fernandes, E. C. M. (eds.), Agroforestry in Sustainable Agricultural Systems, pp. 1-31. CRC Press, Boca Raton, FL. Nair, R. P. K., Nair, V. D., Kumar, B. M. and Showalter, J. M. 2010. Carbon Sequestration in Agroforestry Systems. In: Donald, L. S. (ed.), Advances in Agronomy,108: 237-307, Academic Press. Pramova, E., Locatelli, B., Djoudi, H. and Somorin, O. A. 2012. Forests and trees for social adaptation to climate variability and change. Climate Change, 3(6): 581-596. Rahman, S. A., Baldauf, C., Mollee, E. M., Abdullah-Al-Pavel, M, Abdullah-Al- Mamun, Md., Toy, M. M. and Sunderland, T. 2013. Cultivated plants in the diversified home gardens of local communities in Ganges Valley, Bangladesh. Science Journal of Agricultural Research and Management, Volume 2013, Article ID sjarm-197,6 Pages, 2013. doi: 10.7237/sjarm/197. Sanchez, P. A. 1996. Science in Agroforestry. Agroforestry Systems 9: 259-274. Schroth, G., da Fonseca, G. A. B., Harvey. C. A., Gascon, C., Vasconcelos, H., Izac, A. N. 2004. Agroforestry and biodiversity conservation in tropical landscapes. Island Press Smit, B. and Wandel, J. 2006. Adaptation, adaptive capacity and vulnerability. Global Environmental Change, 16:282-292. Sokona, Y. and Denton F. 2001. Climate Change Impacts: can Africa cope with the challenges? Climate Policy 1: Pp 117– 123. Strassburg, B., Turner, K., Fisher, B., Schaeffer, R. and Lovett, A. 2009. Reducing emissions from deforestation - the “combined incentives” mechanism and empirical simulations. Glob. Environ. Change, 19: 265-278. Subhrendu, P. and Mercer, D. E., 1996. Valuing soil conservation benefits of agroforestry practices. Southeastern Center for Forest Economics Research, Research Triangle Park, NC. FPEI Working Paper No. 59. 21 pp. Taha, A., Thomas, T. S. and Waithaka, M. 2012. East African Agriculture and Climate Change: A Comprehensive Analysis - Sudan. International Food Policy Research Institute. Available at: www.ifpri. org/sites /default /files/publications/aacccs_sudan. UNDP/UNEP. 2005. Poverty and climate change reducing the vulnerability of the poor through adaptation, UNDP/UNEP, Pp 55-56.

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UNEP. 1997. United Nations Environment Programme. World Atlas of Desertification, 2nd edition. N. Middleton and D. Thomas (Eds.). London: UNEP. 182 pp. UNEP. 2007. Sudan forest resources. In: Sudan: Post-Conflict Environmental Assessment. United Nations Environment Programme, Nairobi, Kenya UNEP. 2009. Environment for development, climate and trade policies in a post- 2012 World UNFCCC. 2006. Background paper on impacts, vulnerability and adaptation to climate change in Africa for the African Workshop on Adaptation Implementation of Decision 1/CP.10 of the UNFCCC, Accra, Ghana, Pp 5-53. Van der Werf, G. R., Morton, D. C., Defries, R. S., Olivier, J. G. J., Kasibhatla, P. S., Jackson, R. B., Collatz, G. J. and Randerson, J. T. 2009. CO2 emissions from forest loss. Nat. Geosci. 2, 737–738. Verchot, L. V., Van Noordwijk, M., Kandji, S., Tomich, T., Ong, C., Albrecht, A., Mackensen, J., Bantilan, C., Anupama, K. and Palm, C. 2007. Climate change: linking adaptation and mitigation through agroforestry. Mitigation and Adaptation Strategies for Global Change, 12(5): 901-918. Young, A. 1989. Agroforestry for Soil Conservation. CAB International, Wallingford.

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Differences in Acacia senegal Provenances’ Adaptation to Climate Variability and Gum Arabic Production Trends

Mohamed E. Ballal1 and Hiba M. Abdel Rahman2

Abstract Differences in Acacia senegal (L.) Willd. provenances’ performance under nursery and field conditions and gum Arabic production trends were studied under varying climatic conditions in the Sudan with emphasis on main production centres in Kordofan States that produce 50% of the Sudan’s production of gum Arabic. The objective was to depict the relationship between gum arabic production and climate variability as a basis for sustainable and stable production. The data of this paper were extracted from previous research work conducted by the authors. Different methodological approaches such as research trials, field surveys, and secondary data for analysing production trends in relation to rainfall and temperature variability were used. Field trials were carried out during the period 1992 - 2010. The field experiments were conducted at El Obeid Research Station Farm (Latitude 13o:12′:40″ N; Longitude 30o:14′ E) and El Demokeya Research Farm (13o:16’N; 30o:29’ E; Alt. 560 m asl) in North Kordofan State in Western Sudan. The seeds used in the nursery and establishment trials in the field were collected from 24 eco-geographic locations that represent most of the provenances in the gum belt. The provenances from the low rainfall areas (200- 400mm) showed better nursery performance as compared to those from higher rainfall areas. However, with respect to provenances’ differences under field conditions, Rahad and Khowai provenances from North Kordofan gave the highest growth in height and diameter. The results demonstrate that optimum growth, establishment and adaptability of Acacia senegal to varying climate can be achieved through careful selection of provenances that are adapted to areas with low rainfall. Gum production was found more resilient to climate variability and extremes than field crops. Generally, gum production followed the rainfall trends in the main production centres in Kordofan and the trend of maximum temperature at gum collection in most years. Accordingly, these climatic elements can be used for predicting gum arabic production.

Keywards: Climate change, Adaptation, Variability, Gum Arabic production, Provencenes.

Introduction Acacia senegal (L.) Willd., the gum producing tree, has a wide distribution within the dry tropical and subtropical Africa. This broad ecological region represents a complex and diverse environment with regard to climate, soils, vegetation, animal and human activities (Ballal, 1991). Consequently, this was clearly reflected on its wide genetic and phenotypic variation within its populations (Brenan, 1983; Chevalier et al., 1994). Naturally, the tree occurs in a belt 300 km wide extending

1 Director Forestry Research Centre, Email: [email protected]. 2 2El-Obeid Research Station, Agricultural Research Corporation. 18 7 Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199 through the southern frontier of the Sahara Desert, from Mauritania to Sudan, Ethiopia, Somalia; in east Africa and extends southwards to Mozambique, Transvaal, Natal; along the southern coast of Africa and Iran; and also in Pakistan and north west India (NAS, 1979; Ross, 1979). In Sudan, the tree thrives naturally in the gum belt which extends between latitudes 10o and 14o N. The annual rainfall in the tree belt decreases from a maximum of 800 mm in the south to a minimum of 200 mm, with 8-11 arid months in the north. The mean annual temperature within the species range is 25- 27oC and the maximum is 45oC (Goor and Barney, 1976). The average minimum and maximum temperature reported for the species occurrence in Sudan were 14oC and 43oC, respectively (NAS, 1979 and 1980; Ahmed, 1986; Badi et al., 1989). The A. senegal tree is found in a variety of soil types ranging from sandy, clay and alluvial soils to gravely or even stony in the Republic of South Sudan. In addition, the species is found on other soil types such as the pediplain soils locally known as “gardud” and the Naga’a soils in South Kordofan and South Darfur (IIED and IES, 1989). Ballal (1991) reported the broad ecological occurrence of Acacia senegal that represents a complex and diverse environment with regards to climate, soils, vegetation, animal and human activities. With regard to vegetation, the tree occurs as a component of six plant communities as follows: 1) Acacia mellifera thornland on dark cracking clays, and Acacia mellifera on hill soil; 2) Acacia seyal - Balanites savannah alternating with grass areas; 3) Acacia senegal savannah; 4) Combretum glutinosum – Dalbergia - Albizia amara savannah woodland; 5) Terminalia – Sclerocarya – Anogeissus - Prosopis savannah zone; and 6) Baggara repeating pattern. Generally, an account of the taxonomy and distribution of the genus Acacia is given by El Amin (1972; 1976) who postulates the southern Sudan as the centre of diversity of the genus from which it radiates north.

Acacia senegal produces gum arabic which is an important natural product obtained by tapping the tree in farmers’ managed natural stands or plantations in the Sudan. The tree is managed in sequential tree-field crop agroforestry system, with slightly different practices in different production domains. Under this system, the farmers manage the trees and their food and cash crops in a sustainable manner. The rationale behind the practice of this agroforestry system is the improvement in soil fertility expected from biological nitrogen fixation and organic matter added by the tree. The sustainable traditional Acacia senegal agroforestry system is currently subjected to biological and socioeconomic transformations as a result of a number of unfavourable conditions such as agricultural expansion associated with excessive tree cutting, drought and desertification coupled with the increase in rural population, decrease in soil fertility and low rainfall (Hammad, 2010; Ballal, 2012). In this respect, and since the 1970s drought years, Sudan’s gum arabic production has decreased to 50% as compared to its production levels in the 1960s. The effect of climate variability namely, rainfall and temperatures fluctuations were thoroughly examined for a number of years in producers and researchers’ managed stands by (Ballal, 2002). However, the effects of climate Copyright © 2015 SAPDH 188 ISSN 1816-8272

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199 change on tree morphology and gum arabic production on relatively long term basis were not studied before. Therefore, the objective of the present study was to depict differences in A. senegal provenances’ performance in relation to rainfall and to determine the gum arabic production trends under varying climatic conditions in the Sudan with emphasis on Kordofan region which produces 50% of the Sudan’s production of gum arabic.

Methodological Approaches The data for the present study were collected from a number of field trials, surveys, secondary data sources from previous research and studies, in addition to analysis of production trends in relation to rainfall variability. The field trials were carried out during the period 1992-2010. The nursery and field experiments were conducted at El Obeid Research Station farm (Latitude 13o:12′:40″N; Longitude 30o:14′E) and El Demokeya research farm (13o:16’N; 30o:29’E; Alt. 560 m asl) in North Kordofan State, Western Sudan, within the semi-arid zone of the gum Arabic belt environment. The experimental site is characterized by a short rainy season, which usually starts in July and ends up in October, with uneven distribution. The average total annual rainfall is 324 mm. The soil is sandy, locally known as “goz”, which is the dominant soil type in this area. In general, the sandy soil is poor in mineral nutrients and organic matter and characterized by high infiltration, but easy to till or cultivate. The average maximum temperature varies between 30oC and 35oC during most of the year and it can reach up to 40oC during April, May and June. The research farms lie within the A. senegal low rainfall savannah zone. The over- story vegetation in the area is dominated by A. senegal. Cenchrus biflorus (Haskaneet) and Aristida spp. (Umsimama) are the dominant natural under-story cover. Boscia senegalensis (Kursan) and Guiera senegalensis (Gubeish) occur in this area as an associated bush cover. Seed sources Surveys were carried out in 2005-2007 in the sandy and clay areas in Kordofan State. The seed samples were collected from 24 eco-geographic locations that represent provenances in those areas of the gum belt. The selection criterion was based on differences in rainfall and soil type, representing the natural range of Acacia senegal in the sandy and clay soils. The locations of this study were namely; Demokeya and El Himaira (Sheikan), Umhabila (Rahad), Essaata (Abu zabad), El Khowai, Wad al Hielio and Um Simamaia (EnNhud), Nabag (Dubeibat), Umgalji (Bara), Um Ruwaba (Um Ruwaba) and Abukarshola (Table 1). A similar survey was carried out in the second year to cover more provenances of the gum belt. In this survey, seed samples were collected from 13 isolated natural provenances. These provenances were: Arfat (Umkreidim), Ablaj (El Khowai), Khamas (EnNhud), Gissan (Damazin), Bout (Damazin), Mazmum (Wad Elnaiel-Singa), Ayyadia (Mazroub), Essaata Wasata (Abu zabad), Ambair (Elfaid), Wad Aabid (Abugubeiha), Saraf Saeed (Gedaref), Rawashda (Gedaref), and Khor-donia at Damazin (Fig. 1). The provenances were chosen to represent a range of different geographic locations in the gum belt.

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199

Fig. 1. Map showing locations of seed sources

Table 1. Site data for Acacia senegal seed sources used in the study Pro. Provenance Soil type Rainfall (mm) Lat. Long. code P1 Kondwa Sand 300-400 12o:91’ 31o:21’ P2 Umgalji Sand 200-300 13o:67’ 30o:39’ P3 Um Simamaia Sand 400-500 12o:70’ 28o:43’ P4 Demokeya Sand 300-400 13o:16’ 30o:27’ P5 Umhabila Sand 400-500 12o:74’ 30o:66 P6 Abu Karshola Loamy/Clay 600-700 12o:15’ 30o:79’ P7 Himaira Sand P8 El Khowai Sand 400-500 13o:09’ 29o:24’ P9 Nabag Sandy/Clay 300-400 12o:44’ 29o:83’ P10 Wadel Hielio) Sand P11 Essaata Bkhari Sand 400-500 12o:35’ 29o:24’ P12 Rawashda Clay 600-800 14o:00’ 35o:38’ P13 Mazmoum Clay 600-800 13o:14’ 33o:95’ P14 Ayyadia Sand 200-400 13o:91’ 29o:32’ P15 Khor-donia Clay 800-1000 11o:81’ 33o:86’ P16 Ablaj Sand P17 Arafat Sand 300-400 13o:49’ 29o:78’ P18 Bout Clay P19 Gissan Clay P20 Ambair Clay 700-800 11o:78’ 30o:88’ P21 Khammas Sand P22 Saraf Saeed Clay 14o:00’ 35o:38’ P23 Wad A’ abid Clay 600-700 11o:46’ 31o:23’ P24 EssaataWassata Sand Note: Rainfall data were obtained from El Obeid Research Station meteorological records.

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199

Adaptation of Acacia senegal provenances to climate variability Nursery and establishment trials Healthy seedlings of uniform height were chosen from the provenances of four rainfall zones: 200 to 400 mm represented by Ayyadia and Um Ruwaba provenances; 400 to 600 mm represented by Essaata and Saraf Saeed; 600 to 800 mm represented by Bout and Gissan; and > 800 mm represented by Ambair and Wad A’abid. The seedlings were raised in a soil mix composed of 2 sand: 1 clay. The seedlings were arranged in the nursery in a completely randomized design (CRD) with three replicates. The seedlings were watered once every day. Height and diameter were assessed every month. The seedlings were raised in the nursery under direct sunlight. The provenances’ establishment trial was conducted at El Obeid Research Station farm using 5 seedlings per provenance. Seedlings were spaced 5 m apart. The experimental design was a randomized complete block design (RCBD) with three replications. Observations on growth traits and survival rate were made after a growing period of five years in the field. Data collected include: 1. Plant height, which was measured as the distance between the soil surface and the tip of the terminal bud of the highest branch; 2. Diameter at root collar, which was measured at the soil surface with a calliper; and 3. Survival percentage. Drought tolerance A simulated drought tolerance experiment was conducted at the nursery of El Obeid Research Station. Seeds of A. senegal from each of the eleven geographical sources from Kordofan gum belt were germinated in polythene bags (10 x 20 cm when flat) filled with a mixture of clay and sand at 2: 1 ratio. Irrigation was carried out once a day. After four months, seedlings of uniform height were taken from each provenance and divided into three replications of five seedlings per seed source per treatment. The seedlings were placed in a growth shelter made of polythene sheet. The average monthly temperature inside the growth shelter was 34oC. The seedlings were exposed to two irrigation regimes of 6- and 9- day intervals and they received water until full saturation. The design of the experiment was CRD. The total experimental units were 330 viz. 5 (polythene bags) x 11 (provenances) x 2 (irrigation treatments) x 3 (replications). Mortality counts were recorded after 3 months as the average nursery period. Effects of rainfall, temperature and tapping on gum production The general trends in gum arabic production in relation to total rainfall in some of the major production centres viz. El Obeid, Um Ruwaba and El EnNhud in North Kordofan were analysed in relation to rainfall, and rainfall and temperature on relatively medium to short term time series. Based on the findings of Ballal et al. (2005a), gum Arabic production from selected production centres from Kordofan was studied in relation to total rainfall and maximum temperature at gum collection. Statistical analysis All statistical parameters, viz., mean, standard error, variance and coefficient of variation were analysed statistically using MSTAT C (Fischer, 1990) statistical

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199 package. Analysis of variance, correlation and mean separation analysis were performed on the data as appropriate.

Results and Discussion

Nursery and establishment trials The growth performance at the nursery as reflected in shoot height and collar diameter for A. senegal provenances collected from different rainfall zones are shown in Fig. 2. Under the 200-400 mm rainfall zone, the shoot height and collar diameter of the seedlings of Ayyadia provenance after 12 months of growth were higher than those of Um Ruwaba provenance. Under the 400-600 mm rainfall zone, the shoot height and collar diameter of the seedlings of Saraf Saeed provenance were higher than those of Saata provenance. The over years’ combined analysis of variance on the growth and survival of the provenances showed that the interaction of shoot height or collar diameter with year was highly significant (P<0.001). Generally, the height and diameter growth increased significantly in the fourth and fifth years (Table 2). There was no significant effect of years on the survival of the species. With respect to provenances differences over the years, the combined analysis revealed that the Rahad provenance gave the highest height growth which was significantly different from other provenances. Khowai provenance ranked second. However, there were no significant differences between the provenances in terms of survival. These results seem important as there has been little systematic research on genetic variation in growth and survival and conservation of Acacia senegal and there are relatively few published reports of genetic variation in growth, survival and other adaptively important traits (Raddad et al., 2005; Raddad, 2007). In this respect, Khurana and Singh (2001) reported that populations of a species from different geographical locations (provenances) show differential responses due to genotype effect. Abdelrahman (2013) stated that better growth, establishment and adaptability of Acacia senegal can be achieved through careful selection of the best seed sources when raising seedlings for a given planting. She added that populations that are adapted to areas with low precipitation are important as potential seed sources for future planting programs in the drier parts of the gum belt.

Drought tolerance The differences in the survival percentages of the provenances under different watering intervals of 6 and 9 days are presented in Table 3. At 6-day watering interval, El Demokeya and Bara provenances showed the highest survival (90%), while Wad el Hielio and Essaata showed the lowest survival (13.1 and 0.0 percent, respectively). However, at 9- day watering interval, Bara provenance showed the highest survival (72%) followed by El Demokeya and Um Ruwaba provenances (63.4%). Similarly, Wad el Hielio and Essaata provenances showed the least survival. The relevance of these results to dryland forestry is that the selection of provenances with high drought tolerance may enhance first-year plantation establishment for this species, which is the most restrictive factor for plantation success (Elfeel et al., 2007; Warrag et al., 2002). Drought tolerance of tree species

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199 in the dry lands is important for in-situ conservation. A lower shoot/root ratio may indicate drought tolerance in provenances as suggested by Elfeel (1996). It is worth mentioning that gum production was found more resilient to climate variability and extremes than field crops (Ballal et al., 2005b).

Fig. 2. Variation in shoot height (a) and collar diameter (b) between Ayyadia and Um Ruwaba provenances under 200-400 mm rainfall zone, and between Saata and Saraf Saeed under 400-600 mm rainfall zone (c and d, respectively).

Table 2. Among years’ variation in shoot height, collar diameter and survival percentage of Acacia senegal provenances at El Obeid Research Station Farm. Years Height (cm) Diameter (cm) Survival Rainfall (mm) (transformed) 2006 32.0 c 0.53 d 90.0 556 2007 45.0 c 1.01 c 89.2 647 2008 110.0 b 2.08 b 84.8 317 2009 134.0 ab 3.61 a 83.6 307 2010 143.0 a 4.00 a 82.4 423 Mean 92.7 2.24 86.0 SE± 3.53*** 1.02*** 1.97 NS CV% 20 26 13 Means followed by different letter(s) in the same column are significantly different at P = 0.05, using Duncan's Multiple Range Test. NS Not significantly different at P ≤ 0.05; ***, significant at P ≤ 0.001.

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Table 3. Survival percentage of Acacia senegal provenances under infrequent watering at the nursery stage. Survival (%) Provenance Provenances Watering interval code 6 days 9 days P1 Um Ruwaba 72.3 ab 63.4 ab P2 Bara 90.0 a 72.3 a P3 Um Simamaia 46.0 ab 43.1 cd P4 Demokeya 90.0 a 63.4 ab P5 Rahad 72.3 ab 38.9 cd P6 Abukarshola 63.4 b 50.8 bc P7 Himaira 39.2 cd 30.8 d P8 Khowai 30.7 d 0.00 e P9 Nabag 55.0 bc 51.1 bc P10 Wadal Hielio 13.1 e 0.00 e P11 Essaata 0.00 e 0.00 e SE± 5.89*** 5.32*** CV% 19 25 Means followed by different letter(s) in the same column are significantly different at P = 0.05 using Duncan's Multiple Rang Test. *** Significant at P ≤ 0.001

Analysis of gum arabic production trends The Sudan’s gum production and exports declined from around 50000 metric tons in the 1950s and 1960s to around 35000 in the 1970s drought years to 28000 in the 1980’s and to less than 12000 tons in the drought years of 1984 and 1985. The average production increased gradually in the 1990s and 2000s to more than 20000 tons. Overall, the production and exports showed a fluctuating and declining trend. Similarly, the Kordofan’s gum arabic production followed the same trend as that of Sudan to the extent that the Sudan production can be predicted from Kordofan production (Fig. 3). The fluctuating and decreasing trend in production has been attributed to drought and decrease in the area under the tree mainly as due to tree cutting for fuel wood and the expansion of areas under field crops. IIED and IES (1989) survey proved some drastic changes in the gum belt particularly in the sandy areas of North Kordofan and North Darfur. They proved absence of the Acacai senegal tree north of latitude 13o:14’, with high loss in tree cover immediately to the south of this latitude and, thus, the current boundaries of the gum belt differ from the previous ones. Consequently, the production of gum arabic has been shifted southwards targeting the trees in the high rainfall areas in Darfur, and Kaka and Galhak, which presently belong to the Republic of South Sudan. Fig. 4 clearly displays the general trend in gum production in some of the main production centres in Kordofan. Generally, gum production followed the rainfall trend in those production centres. Similarly, gum production also followed the trend in maximum temperature at gum collection in seven out of ten years for El EnNhud area (Fig. 5a). However, for El Obeid, the trend in maximum temperature

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199 did not follow that of gum production (Fig. 5b). Ballal (2012) studied the general trends in gum arabic production in relation to the total rainfall in the major centres at El Obeid, Um Ruwaba, Wad Banda and Gubeish in Western Sudan. His findings showed that, with the exception of the first year, gum production approximately followed the annual trends in rainfall. The typical trend is much clearer when the production was plotted against the average rainfall of the four production centres. However, with respect to gum yield, Ballal et al. (2005 b) found strong associations between date and intensity of tapping and climatic variables namely; rainfall, maximum and minimum temperatures at tapping and gum collection. The same authors developed different regression models for predicting gum arabic yield. They arrived at an optimum model (r2=0.73), involving the time of tapping, the tapping intensity, rainfall and maximum temperature at gum collection, for predicting gum arabic production.

Fig. 3. Kordofan’s gum arabic production trends in relation to Sudan’s total production.

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Fig. 4. Gum arabic production in major production centres in Kordofan, a. El EnNhud; b. El Obeid; c. Um Ruwaba. a

Ballal et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 187-199 b

Fig. 5. Effects of rainfall and maximum temperature at harvest time on gum arabic production at El EnNhud (a) and El Obeid (b) in North Kordofan State.

Conclusions . Optimum growth, establishment and adaptability of Acacia senegal to varying climate can be achieved through careful selection of provenances that are adapted to areas with low rainfall. Rahad, Khowai and Um Simamaia provenances ranked high on the basis of growth and survival. . Natural populations of A. senegal from the drier parts of the gum belt areas are better adapted to drought, as compared to populations from the more humid parts of the region. Therefore, the relevance of this work to dryland forestry is that the selection of provenances with high drought tolerance could enhance plantation establishment for this species in those areas. . Gum arabic production is resilient to climate variability and extremes. . Gum production followed the rainfall trend in the different production centres in Kordofan. It also followed the trend in maximum temperature at gum collection in seven out of ten years for El EnNhud area in North Kordofan.

References Abdel Rahman, H. M. 2013. Variation among Acacia senegal provenances in seed and seedlings traits establishment, conservation and gum yield. Ph. D Thesis, Sudan Academy of Sciences, Sudan. Ahmed, E. A. 1986. Some aspects of dry land afforestration in the Sudan with special reference to A. tortilis (Forks.) Hayne, A. senegal willd. and Prosopis chilensis (Molina). Forest Ecology and management, 16: 209 - 221. Badi, K. H., Ahmed, A. E. and Bayoumi, M. S. 1989. The forests of the Sudan. Agricultural Research Council, Khartoum, Sudan. Ballal, M. E. 1991. Acacia senegal: a multi-purpose tree species for arid and semi-arid tropics. M.Sc. Thesis, University of Wales, UK.

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Ballal, M. E. 2002. Yield trends of gum arabic from Acacia senegal as related to some environmental and managerial factors. Ph. D Thesis, University of Khartoum, Sudan. Ballal, M. E. 2012. Towards achieving stability and sustainability of gum arabic (Acacia senegal) production in Sudan. In: Gum Arabic Book (Kennedy J. F., Philips. G. O. and Williams, P. A., eds.). The Royal Society of Chemistry, UK. Ballal, M. E., El Siddig, E. A and Luukkanen, O., and Elfadl, M, A. 2005a. Relationship between climatic factors, tapping date, tapping intensity and gum arabic yield of Acacia senegal (L.) Willd. plantations in Western Sudan. Journal of Arid Environments Vol. 63 (2): 379 – 389. Ballal, M. E., El Siddig, E. A Luukkanen, O., and Elfadl, M, A. 2005b. Gum arabic yield in differently managed stands of Acacia senegal (L.) Willd. in Western Sudan. Agroforestry Systems.63:237 -245. Brenan, J. P. M. 1983. Manual on taxonomy of Acacia species. FAO, Rome, Italy. Chevalier, M. H., Brizard, J. P., Diallo, I., and Leblanc, J. M. 1994. Genetic diversity in the Acacia senegal complex. Bios-et-Forets-des-Tropiques. 240: 5-12. El Amin, H. M. 1972. Taxonomic studies of Sudan Acacias. Unpublished M Sc. Thesis. Edinburgh University. El Amin, H. M. (1975). Germination and seedling development of the Sudan Acacias. Sudan Silva, 3 (20): 23-32. El Amin, H. M. 1976. Geographical distribution of the Sudan Acacias. Bulletin No. 2. Forest Administration, Khartoum. Elfeel, A. A. 1996. Provenance variation in seed characteristic, germination, and early growth traits of Acacia senegal (L.) Willd. in Sudan. M Sc. Thesis, University of Khartoum, Sudan. Elfeel, A., Warrag, E. and Musnad, H. A. 2007. Response of Balanites aegyptiaca (L.) Del. seedlings from varied geographical source to imposed drought stress. Discov. Innov., Vol. 18 (ASORNET special edition No. 4). Fischer, S. D. 1990. MSTAT-C Statistical Package, Michigan State University, USA. Goor, A. Y. and Barney, C. W. 1976. Forest tree planting in arid zones. The Ronald Press Company, New York. Hammad, A. Z. M. 2010. Biophysical and socio-economic transformations in Acacia senegal (L.) Willd. agroforestry systems in the gum belt of North Kordofan. Ph. D Thesis, University of Kordofan, Sudan. IIED and IES .1989. Gum Arabic rehabilitation in the Republic of the Sudan: Stage 1 report, International Institute for Environment and Development (IIED) and Institute of Environmental Studies (IES). IIED, London. Khurana, E. and Singh J. S. 2001. Ecology of tree seed and seedlings: Implications for tropical forest conservation and restoration. Current science, 80 (6): 25. NAS. 1979. Tropical legumes: Resources for the future. National Academy of Sciences (NAS), Washington, D.C. NAS. 1980. Firewood crops. National Academy of Sciences (NAS), Washington, D. C.

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Raddad, E. Y. 2007. Ecophysiological and genetic variation in seedling traits and in first-year field performance of eight Acacia senegal provenances in Blue Nile, Sudan. New Forest 34: 207-222. Raddad, E., Salih, A., Fadl, M., Kaarakka, V. and Luukkanen, O. 2005. Symbiotic nitrogen fixation in eight Acacia senegal provenances in dryland clays of the Blue Nile Sudan estimated by 15N natural abundance method. Plant and soil, 275: 261-269. Ross, J. H. 1979. A conspectus of the African Acacia species. Memoirs of the Botanical Survey of South Africa, No. 44. Warrag, E., El Sheikh, E. A. and Elfeel, A. A. 2002. Forest genetic resources conservation in Sudan. Rome, Italy.

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Impacts of Climate Change on Forest Tree Seeds in Sudan: A review

Sayda Mahgoub1

Abstract The paper is a short review of most of the research work carried on Sudan tree seeds characteristics and the impacts of climate change on those tree soil seed bank and tree seed productivity. It expressed that seeds acquire their characteristics according to the prevailing environmental conditions in their habitats as a guarantee for the presence and continuity of the parent plants on earth. The paper also showed the adverse impacts of accelerated climate change on tree soil seed bank and tree seed productivity expressed in the poor seed quality and low quantity.

Kewards: climate change, seeds characteristics, seeds quality.

Introduction Climate change and global warming has its effects on Sudan environment. Temperatures are increasing and rainfall is decreasing, arid and semi-arid areas are expanding as more water is lost to the atmosphere, the land quality is reduced, more of it turns to desert and crop yield falls (WWW.Climatechoices.org.uk). The forest cover declined from 36% to 11.6% during the last 100 years. A number of trees and shrubs are seriously endangered (FNC, 2013). Plants, as known, cannot move from one place to another like other living organisms. They stay the whole of their life where they are and witness the different seasonal and climatic changes. This of course leads plants to develop tight survival mechanisms to coincide closely with the different environmental changes otherwise plants will suffer and cannot live successfully on earth and undergo their physiological activities completely. This might lead to the extinction of plants, which is in terms a loss of useful resources for human well- being, Successful plants are those, which are adapted to their habitats and encounter even slight changes in their natural homes to arrange their life phases. Tolerant plants are those, which can overcome severe and fragile climatic conditions. Survival mechanisms or adaptations are different from one plant to another in type and the way they work, on which plant distribution on earth is based. Those adaptations are found in every part of the plant, (leaves, stems seeds. Fruit...etc). These mechanisms (adaptations) are revised, changed or amended by the plant by interpreting environmental signals to acquire certain characters that enable the plants to overcome environmental stresses. Those survival mechanisms are not evolved suddenly or in a short time but over a long time that could take decades or centuries The seed is the mobile phase of the plant and so it is the most important part of the plant responsible for the distribution and continuity of the plant on earth. Accordingly, the seed is quite adapted to its surrounding environment. Seeds have

1 Director, Soba Seed Centre, Forestry Research Centre, Agricultural Research Corporation (ARC), Soba, Khartoum, Sudan. 200 Mahgoub, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 200-206 physical and/or physiological characters that help the seed to protect itself from being decayed, eaten, or losing viability. In this respect, the National tree seed centre conducted a lot of research work on seed characters in relation to environmental factors (seed ecophysiology or seed ecology) in all seed procurement and testing aspects. This paper is a short review of research work on the impact of climate change on tree seed characteristics, tree soil seed bank and tree seed productivity. Impact of climate change on seed characteristics Seeds acquire their different characteristics from genetically inherited factors plus prevailing environmental conditions, which are interpreted in the plant genome (Schimdt, 2000). Seeds once detached from the parent plant are well provided with characters that protect them from external factors harmful to the seed (Willan, 1995). Seed dispersal: Tree seeds develop certain characters according to their dispersal mechanisms, seeds dispersed by wind are light and have wings like, members of the Combretaceae (Mamoun, 2012; Mahgoub, 2002). Mahogany Seeds are winged and wavy in shape to help being carried by wind (Mahgoub, 2002). Seeds of the dry zone Acacias stick to their thin light fruits, which are blown by wind. Seeds dispersed by animals have hard fruit endocarp around the seed to avoid being crushed or chewed by animals and have a sticky solution around the endocarp to stick to animal body and being distributed Balanites aegytiaca (Higlig), Zizuphus spina-cristi (sider), Cordia abyssinia (gimbeel) (Mahgoub, 2002). Tree seeds dispersed by water have fibrous fruit pulp filled with air to provide buoyancy of fruit carrying the seed like Dome (Salih, 2008 unpublished) like Faidherbia albida (Haraz) Acacia nilotica (grad). Seed extraction: Tree seeds have different fruit characters and different extraction methods according to their habitats. Dry seeds of desert and semidesert areas mostly have dehiscent papery thin fruits that are blown by wind carrying the seeds and are extracted by beating or easy crushing to release the seeds like Hashab, Talih, Salum, Acacia oerota (laaot) etc (Mahgoub, 1995-2005). Seeds of humid and sub humid areas usually have a thick fruit pulp around the seed that is fermented and dissolved in the humid soil when fruits are dropped from the tree or eaten by animals which spit out the seed with endocarp, examples are (Humaid), Kaya senegalensis (mahogni), Cordia africana (gimbeel) (Mahgoub, 2002; Mahgoub and Elsheikh, 2005; NTSC data 1999). Seeds in the high rainfall areas or near water sources are usually extracted by water. They mostly have chemicals in the fruits and seeds (tannin, suberin, phenols) which are antiseptics that protect the seed from decay or rotening in the water until the suitable conditions for germination are available such as Acacia nilotica (grad), Tectona grandis (teak) members of the Combretaceae, Joghan (Mahgoub, 1998 and 2002). Seed dormancy and germination: the phenomenon of seed dormancy is a direct response to environmental conditions. Seeds remain dormant to pass unsuitable environmental condition for a seedling to grow but will perish (Harper, 1977). Tree seeds have impressive dormancy mechanisms very much related to their climatic conditions. Seeds of Acacia nilotica and A. seiberana have very hard seed coats because they are riverine species along the Nile banks and the fruits are

Mahgoub, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 200-206 dropped in water when the Nile floods and remain floating for 3 months after which the seed stick to the mud and germinate. On the other hand seeds of the dry zones have soft coats to start germinating after the first rain showers and complete their germination within the first 7 to 10 days like Hashab on sand, like Acacia mellifera (Kitir) and Acacia Senegal (hashab) (Abdeldafi, 1977; Musa, 2005) and Adonsonia digitata (tabaldi), Balanites aegyptiaca (higlig) (Mahgoub, 2002). Seeds, which enjoy plenty of rains, complete their germination within a longer period (4-6 weeks) since they guarantee the presence of water throughout the rainy season like Acacia senegal (hashab) on clay (Elfeel, 2009), Khaya senegalensis (mahogni) Cordia Africana (gimbeel), Diospyros mespiliformis (Joghan) (Mahgoub, 2002) (Figures 1,2 and 3).

Fig. 1. Germination rate and Percentage of seeds of Acacia senegal from different soil types (Elfeel, 2009)

Fig. 2. Germination rate and percentage of Adansonia digitata and Balanites aegypiaca (semi desert species) over 8 weeks (Mahgoub, 2002)

Mahgoub, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 200-206

Fig. 3. Germination rate and percentage of Diospyros mespiliformis and Khaya senegalensis (woodland savanna species) over 8 weeks (Mahgoub, 2002)

Seeds of fruits eaten by animals possess mechanical dormancy represented in the woody endocarp around the seed to protect the seed from damage by animals teeth. These seeds will germinate only when this endocarp mechanically open along certain sutures filled with soft tissue as the case in Balanites aegyptiaca (higlig), Zizuphus spina-cristi (sider), Cordia Africana (gimbeel), Grewia tenax (geddaim), Sclerocarya birrea (homid), Terminalia laxiflora (sobag) etc. (Mahgoub, 1998, 2002). Seeds of montane areas like Jebel Marra have endogenous dormancy which is not broken unless treated with cold stratification simulating the cold weather of the area as in Cordia Africana (gimbeel) (Mahgoub, 2002). On the other hand seeds produced at the beginning of the rainy season in areas with high rainfall or subjected to regular irrigation, possess no dormancy like Diospyros mespiliformis (Joghan) in the high rainfull savannah and Azadirachta indica (Neem) as an urban plantation (Mahgoub, 2002). Acacia seeds of the semidesert zone have differential dormancy (Doran et al. 1983) i.e seeds of the same seed lot germinate at different times, the majority of seeds germinate after the early rains, another fraction of seeds remains dormant to capture the late rains and a third fraction is left deeply dormant for the coming seasons. Therefore, if we assure that seed characteristics are acquired and controlled by genetic and environmental factors, then a gradual change in the seed habitat will call for a gradual change in seed characteristics. Ultimately, an accelerated rate of habitat and climate change could be a hazard to seed life and finally to plant presence on earth if those seed changes can not coincide with environmental changes.

Impact of climate change on tree soil seed bank The tree soil seed bank is the future forest through natural regeneration if suitable conditions for seed germination (water, temp., and oxygen) are available in the soil. Seeds of the soil seed bank have a life time or seed age that varies between seeds of the different species. The tree soil seed bank of Talih (Acacia seyal var. seyal) , Mesquite (Prosopis chilensis ) and Seyal (Acacia tortilis Subsp.raddiana)

Mahgoub, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 200-206 were found to have a seed age of 2 to 3 years (Mamoun, 2004; Ashria, 2008; Elmagboul, 2009). While that of sunt (Acacia nilotica) was predicted to be 10 years (Elbasheir, 2006). Tropical tree legume seeds possess physical differential dormancy to avoid the germination of all seeds in one season, the non-dormant seed fraction will germinate during the rainy season and the dormant ones will enrich the soil seed bank for the coming seasons (Doran et al., 1983). They could also have different degrees of the seed coat thickness so that every year a certain percentage of the seeds in the soil will germinate until the soil seed bank is depleted. This will guarantee the continuous production of new plants from the soil seed bank even if the parent plant is removed. The seed in the store (either cold or normal) are different from those in the soil seed bank (Elmagboul, 2009). The latter are subjected to the different habitats and climatic changes that affect their physiological characters and may cause an accelerated loss of viability. The impacts of climate change on tree soil seed bank could affect both seed quality and quantity. Impacts on seed quality Suffering trees from climatic conditions produce poor quality seeds, empty seeds, abortive, low vigor…etc. Accelerated rate of climate change accelerates soil seed bank aging and vigor like increased warming which raise temperature during the day. Impacts on Seed quantity Removal or death of trees producing seeds, due to increasing drought conditions, decreases the soil seed bank. Soil erosion by either wind or water affects the soil seed bank quantity by carrying the seeds from one place to another or burying it deep in the soil. Recent studies of the soil tree seed bank in the semi arid region of Elgitaina in the White Nile State and Elrawakeeb – Khartoum State revealed that tree soil seed bank is almost zero and the trees cover become patchy (Mutwali, 2007; Basheir, 2010) . This is because the wondering livestock eat the falling fruits with seeds or the fruits are collected by the owners of these animals and taken to them elsewhere. This depleted soil seed bank should be considered a serious situation in the semi desert areas of the Sudan since no natural regeneration is expected in the area and ultimately the loss of the existing tree cover will occur unless seed broad casting or afforestation programmes are set. In this regard, the tree soil seed bank is a useful climatic indicator for area degradation. Impact of climate change on seed productivity Tropical plants regularly produce seeds (fruiting) in quantity and quality when they are enjoying suitable and sustainable climatic conditions. Recently, the tropical and sub tropical regions are the most regions affected by the global climate change. The drought spells that hit the region followed by increasing desertification and scanty uneven rains have made the region vulnerable (WWW,Unep,org./climatechange/). Accordingly, plants of the dry tropics are suffering from such drought stresses. Plants suffering bad climatic conditions or environmental hazards produce low quality and quantities of seeds and adverse weather condions are known to influence fruit and seed production (Whitmore, 1984; Schmidt, 2000). This is

Mahgoub, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 200-206 simply because the production of seeds (flowering and fruiting) is one of the serious physiological processes that is very sensitive to environmental changes. A rise in temperature and fluctuations in rains had gradually affected the seed yield of cabbage during the period (1981-2004) (Kumar et al., 2004). Off season flowering and fruiting of plants could occur as a result of an environment or habitat change. Some plants are flowering and fruiting all the year round in their optimum conditions while they lose this character in the dry conditions like Azadirachta indica (Neem) which is flowering and fruiting throughout the year in Thailand while in East Africa this is associated with pronounced wet and dry seasons (Schmidt, 2000 ). Elrawashda forest in Gadaref State is one of the seed sources of Talih (Acacia seyal var. seyal) for the National Tree Seed Centre since its establishment in 1990. However, during the last decade the trees in this forest are suffering from drought and their seed productivity seriously declined except for trees near water sources (per.com. Manager of regional tree seed centre- Gadaref). This forest is no longer used as a seed source now.

Conclusions Tree seeds acquire their characteristics according to the surrounding environmental conditions and hence are adversely affected with adverse climatic changes, which are expected to increase in the future, and this necessitates more tree planting and seed conservation. Accelerated climate change adversely affect the tree soil bank and tree seed productivity both in quantity and quality

References

Abdel-Dafi, A. 1977. Growth and vegetative propagation of some of the indigenous tree species of the Sudan. M.Sc. Thesis . University of Khartoum. Sudan. Ashria,T. K. 2008. Studies on the soil seed bank of Mesquite (Prosopis chilensis) in New Halfa Agricultural Scheme, M.Sc. thesis, Sudan Academy of Science. Basheir, N. A. 2010. Spatial heterogeneity and sustainable rangeland management in semi-arid area of Central Sudan. Ph.D. Thesis, Sudan Academy of Science. Doran, J.,Turnbull, J.W.Boland, D. J. and Gunn, B.V. 1983. Hand book on seed of dry zone Acacias. Divition of forest Research CSIRO P.O.Box 4008, Canberra Act 2000,Australia. FAO Rome. Elbasheir, A. 2006. Soil seed bank of Acacia nilotica in central Sudan (Gezira and Khartoum state) M. Sc. Thesis, Sudan University of Science andTechnology. Elfeel, A. 2004. Genetic variation in seed parameters and germination of Acacia senegal (L) Wild at geographical source and individual tree level in Sudan. Journal of Science and Technology, Vol 5., NO 1, ISBN 1605-427 X. Sudan University of Science and Technology. Elmagboul. 2009. Variations in seed and seedling characteristics between Acacia tortilis subsp raddiana and spirocarpa from three provenances in Sudan PhD.thesis Sudan University of Science and Technology. Elsheikh, M. A. 2005. Seed and seedling charsteristics of Scleroscaria birrea (Humaid) in Sudan. B.Sc. Dissertation University of Sudan.

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FNC. 2013. The status of Sudan Forests.Forests National Corp.paper FNC 19th Annual Conference. Harper, J. L. 1977. Population Biology of plants. Academic Press London. Kumar. P. R. Shiv, K, Yadav,S.R,Sharma, S. K., Lal and D.N. Jha (2009). Impact of climate change on seed production of Cabbage in N.W.Himalayas World Journal of Agricultural Science 5 (1) 18-26. Mahgoub, S. 2002. Studies of the Physiological, Environmental and Biochemical factors affecting the germinability of seeds of some forest tree species .Ph.D.Thesis University of Khartoum. Mahgoub,S. 1998.Some techniques to improve the germination of tree seed with External dormancy. Seed Guide No 6, Nat Tree Seed Center. Khartoum. Mahgoub, S. 2005. National Tree seed center annual report. Seed physiology research .Soba .Khartoum. Mamoun,M. 2002.Effect of fire on soil seed bank, vegetation cover and some soil properties at El Nour forest (Blue Nile state).M.Sc Thesis Sudan Institute of Environmental studies University of Khartoum. Mamoun, M. 2012. Causes of low germination of seeds of two Sudanese tree species (Terminalia laxiflora and Combertum hartmaninum)Ph.D Thesis, Sudan Academy of Science. Musa, E. B. 2005. Comparative study of seed and seedling characteristics of Acacia Senegal ,A.mellifera and A.Laeta in Sudan M.Sc. Thesis Sudan University of Science and Technology. Mutwali, N. 2007. Assessment of Causes of degradation of vegetation in the White Nile state (Elgitaina area) M.Sc. Thesis, Sudan Academy of Science. Salih,B. 2008. Seed characteristics of Dome (Hyphaena theibaca).In Sudan.(Unpublished). Schmidt, L. 2000. Guide to handling of tropical and subtropical seed DANIDA forest seed center Krogerupvej,3A-DK-3050 Humlebaek, Denmark. Whitemore,T.C. 1984. Tropical rain forest of the far east .Clarendon Press. Oxford. Willan 1995. Aguide to forest seed handling with special reference to tropics ,FAO Forestry paper No 20/2 Rome DFSC,DK-30-50 Humlebeak –Denmark. WWW.Climatechoises.org.UK\...\Sudan-det….Climate Change in Sudan. WWW.Unep.org.\climatechange\

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Climate Change Adaptation in Sudan: Implementation and Policies

Ismail Elgizouli1 and Mutasim B. Nimir2

Abstract The majority of the Sudan is arid plains of low soil fertility, limited water resources and compounded by a range of human pressures that create a state of vulnerability, in addition to climate change impacts. Changing climatic conditions are causing adverse changes in the distribution and productivity of Sudan’s natural resources - its forests, soils and grassland - are expected to have significant repercussions for millions of people. In 2003, Sudan Initial National Communication to UNFCCC assessed the likely impacts of climate change including decreasing annual rainfall, increasing rainfall variability and increasing average annual temperature, resulting in the reduction of ecosystem integrity, decline in crop yield, drought, diseases and insect infection, and decrease in biodiversity. In 2007, NAPA identified the key agro-ecological zones affected by climate change, vulnerable States and presented 32 initiatives for adaptation in the agriculture, water and health sectors. The project to implement NAPA priority interventions to build resilience in agriculture and water sectors to adverse impacts of climate change was sponsored by LDCF/UNDP and implemented by HCENR in the five vulnerable States representing five agro-ecological zones. The project objectives were to implement urgent set of adaptation-focused measures that will minimize and reverse the food insecurity of smallscale farmers and pastoralists. The project has introduced micro-scale irrigated agriculture, improved rainwater harvesting techniques, drought resistant early maturing crop varieties, high value horticultural crops and measures to improve livestock health and productivity. The project also promoted community participation, enhanced women roles and community based natural resources management. Upscaling of several best practices has started. Detailed project achievements are presented. The strategic nature of NAPA and NAP is briefly discussed and several policy issues are suggested such as mainstreaming of adaptation in development plans, extending political support, development of policies for water resources management, food security, national land use plan and sustainable use of national natural resources. Further, there is need for strengthening research, extension, planning, early warning system and enhancing the coordination role of HCENR.

Keywords: Climate change, NAPA, NAP, implementation, policies, best practices upscaling

Introduction Sudan encompasses an area of about 1.9 million km2 and stretches over a and between atitudes - and ongitudes - Sudan borders South Sudan and six other African nations, and the Red Sea. The majority of the land is

1 Climate Change Expert, UN-IPCC Chairman, 2 NPC, NAPA Implementation Project, Higher Council for Environment and Natural Resources, Khartoum, Sudan 20 7 Elgizouli et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 207-216 composed of vast arid plains interrupted by a few widely separated ranges of hills and mountains. Water resources outside the Nile basin are limited, soil fertility is low and drought is common. Compounded by a range of human pressures, these underlying conditions create a state of vulnerability in Sudan, in addition to climate change impacts and the livelihood risks associated with current and future climate variability and change. Annual rainfall in the north ranges from close to zero near the Egyptian border to about 200 mm around the capital Khartoum. Along the southern border, annual rainfall rarely exceeds 700 mm. The combined effects of the Inter Tropical Convergence Zone (ITCZ) and the country’s topography dominate Sudan’s climate. The result is wide spatial variation in rainfall. The erratic nature of rain and its concentration in a short growing season pose a serious threat to rainfed agriculture, which is the most prevalent type of agriculture in Sudan. The country’s and resources are dominated by arid and semiarid ecosystems, which constitute more than 80% of the area of the country. Low rainfall savannah makes up the majority of other land types, with small montane vegetation areas taking up the remainder. Arable land constitutes about one third of the total area of the country, with about 21% of this land under cultivation. Over 40% of the total area of Sudan consists of pasture and rangelands. Since human communities, flora, and fauna have become highly adapted to subsist within these areas, climate change poses a major threat. Under changing climatic conditions, adverse changes in the distribution and productivity of Sudan’s natura resources - its forests, soils, and grasslands - are expected to have significant repercussions for millions of people. The Nile Basin traverses Sudan from south to north. The Blue and White Nile converge just north of the capital, Khartoum. Sudan's current water resources, as well as its ability to harness them, are limited and prone to severe shortage. The Nile water basin contributes most of Sudan’s avai ab e surface water However, though the Nile transports over 93 billion cubic meters (bcm) of water per year on average, Sudan’s share is on y bcm per year, in accordance with the 9 9 Nile Water Treaty with Egypt. The water resource situation for remote areas is especially precarious as flow from seasonal streams is limited in quantity and duration and varies in terms of turbidity. Sudan is also burdened with low human and economic development and serious environmental problems. In recent years, Sudan has made significant development strides, yet profound poverty and other challenges persist. Factors such as life expectancy, school enrollment and GDP per capita reflect a disturbing situation.

Climate Change Impacts and Adaptation Sudan initial national communication to UNFCCC (2003) assessed the likely impacts of climate change, including decreasing annual rainfall, increasing rainfall variability and increasing average annual temperatures, causing serious challenges. These were identified to include reduction in ecosystem integrity and decline in crop yield. Frequent droughts forced changes in planting dates, disease and insect infestation and decrease in biodiversity. In turn, these were noted to lead to increased risks of food shortages, famine and poverty. Building on these

Elgizouli et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 207-216 studies, the Government of Sudan, with support from GEF/LDCF and UNDP, prepared its National Adaptation plan of Action (NAPA, 2007). This identified key agro-ecological zones affected by climate change, vulnerable States and sites, and critical sectors and sub-sectors. The NAPA was completed in participatory manner in March 2007 and was approved and commended by the Council of Ministers. The NAPA included 32 different initiatives spread over the five agro-ecological zones and included the agriculture, water and health sectors. The NAPA developed criteria for evaluation and priorities for implementation of adaptation initiatives. NAPA included recommendations for capacity building, policy reform, and institutional integration.

Adaptation Opportunities The impacts of climate change and the impacts of social and environmental baseline processes, occurring in the absence of climate change, may serve to compound one another. Thus, a more in-depth look at these relationships is needed for systematic integration of main UNFCCC concepts in the national policy processes. Nevertheless, the Council of Ministers approved the First National Communication and NAPA and in its session-No 46 for 2010 directed HCENR to coordinate NAPA implementation with the Agricultural Revival Program. The strategy goals of the 25-year vision, as well as ongoing national policy processes are having parallel aims to climate change adaptation (i.e Poverty reduction strategy paper and rural development initiatives). The NAPA follow-up project is clearly embedded in baseline activities and through its focus on reducing the additional risks associated with climate change. It will enhance the effectiveness of on-going development investments. It has been often noted that Sudan strategic planning is sectorial in nature, led by limited groups of politicians and a few professionals, and never based on wide grassroots consultations and is often subjected to poor implementation. The long-term solution to the vulnerability of Sudanese communities and economic sectors to climate change is effective mainstreaming of adaptation strategies into the national planning process. This is directly related to the achievement of the Millennium Development Goals (MDGs), the promotion of sustainable national and local agenda, and the integration of climate change risks into all of these planning processes. While resources are vital to success, they are not sufficient to promote human development in a sustainable manner. Particular emphasis shou d be given to bui ding capacities of civi societies’ organizations Limited efforts have been spent to foster awareness of climate risks to food security. This is mainly attributed to that government institutions are subject to frequent changes due to political instability, resulting in limited incorporation of MDGs like United Nations Framework Convention on Climate Change (UNFCCC). Further, the drought contingency planning framework contains a weak component for ensuring food reserves. The Strategic Reserve Authority (SRA), established in 2000, is not yet effective in achieving its goals and objectives.

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Adaptation Implementation Project A project was developed by Sudan Government/UNDP/GEF based on the NAPA titled “Imp ementing APA Priority Interventions to Bui d Resi ience in Agriculture and Water Sectors to the Adverse Impacts of Climate Change in Sudan” The Project is imp emented in a cha enging context This project addresses several of the highest NAPA priorities. The adverse socio-economic conditions, the strained natural environment, the complex political situation, security challenges and over all weak governance in the agriculture sector make it very challenging to effectively support natural resource management in remote and marginalized areas in Sudan . The project objective is to implement an urgent set of adaptation-focused measures that will minimize and reverse the food insecurity of smallscale farmers and pastoralists, and thereby reducing vulnerability of rural communities to climate change. The project outcomes include:  Resilience of food production in the face of climate change.  Institutional and individual capacities to implement climate risk management responses in the agriculture sector strengthened and better understanding of lessons learned.  Emerging best practices captured and up-scaled at the national level. The project design initially covered five locations representing agro-ecological zones with visible climate change impacts and recurring food insecurity. The five concerned States were Central Equatoria, Gedarif, North Kordofan, River Nile and South Darfur. However, following the secession of the Republic of South Sudan, the interventions in Central Equatoria State were suspended.

Increasing Resilience, Increasing Food Security and Adapting to Climate Change in Sudan The Mid-Term Review conducted by independent consultants for UNDP and Sudan Government in Mid 2013 reported that Project interventions to build the resilience of food production systems have focused on introducing and testing the viability, efficiency and effectiveness of simple and improved technologies - usually as part of a package. For example, the Project, at different sites, has introduced micro-scale irrigated agriculture (through development of boreholes), improved water harvesting and storage, and supported direct pumping from the river to replace flood irrigation. It has made available improved seeds and introduced a number of highly marketable horticultural crops. It has improved the health and productivity of livestock. These interventions have significantly reduced vulnerability and enhanced local food security. The Project has also supported actions to improve natural resources and enhance ecosystem resilience. These include protection against desertification through the establishment of shelterbelts around villages and farmlands, improvement of rangelands through reseeding, and the distribution of improved stoves and gas cylinders to reduce the demand for fuelwood. All of these activities have increased adaptive capacity, responded to locally identified needs, and implemented in a highly participatory manner, with strong contribution from local communities. These actions were highly appreciated by the beneficiaries. At most

Elgizouli et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 207-216 sites, awareness raising, training and some organizational support have surrounded all actions, and the focus on women has been strong. In many sites, the Project has recognized the importance of financial security in sustaining results. The support to community based revolving funds, which are currently working efficiently and expanding, is a good example of this. Efforts are now needed to improve institutional management skills (e.g. financial bookkeeping) and to link community-based institutions with the commercial banks and micro-finance lending entities. In Gadarif State, the project has worked with four communities in Sadaa village. It has helped in establishing or re-establishing of four village development committees (VDC) that are responsible for planning and decision-making. Under the VDCs, several thematic groups are active, for example initiating and managing forestry activities and accessing gas stoves. The Project has also initiated revolving funds (RFs). The VDCs, groups and RF are now functioning, with little support from the Project. The project has also conducted several training sessions to farmers, covering a diverse range of issues such as the use of improved seeds (early maturing and drought resistant varieties), animal breeding and rangeland improvement. It has also raised the awareness of the local communities on the issue of climate change. The project is fully understood and greatly appreciated by the beneficiaries.

The beneficiaries have reported a great increase in food security and improved livelihoods through: - Two hundred (200) women and 500 men have benefited from improved rainwater harvesting techniques in 1800 feddan (one feddan = 0.42 ha). - Ninety (90) women have benefited from gas stoves; - One thousand (1000) men and 10000 women have benefitted from training; - The State government reports expanding the rainwater harvesting techniques in an area of 200,000 feddan. - Large numbers have benefitted from improved rangelands (seed broadcasting), use of early-maturing crop varieties and improved revenue (due to improvement in animal health and husbandry measures).

In North Kordofan State, the project has managed to reach a sizeable number of beneficiaries in six affected villages, with successful investments in capacity building of VDCs. It has piloted micro scale irrigated agriculture to fully replace the traditional dry farming and produce high market value horticultural crops. It has helped improving animal production through improved feeding regimes. It has also protected villages and agricultural farms from sand encroachment via the erection of living shelter belts. It has also contributed to biomass conservation through the introduction of gas cylinders. The project is fully understood and greatly appreciated by the beneficiaries. The beneficiaries have reported a great increase in food security and improved livelihoods through: - Potato production was introduced for the first time in the area and yields as high as 16-27 tons/feddan were achieved.

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- Improved nutrition has increased milk production in goats from 0.3 liters/day to 3.0 liters/day. - As a result of improved nutrition, sheep achieved a weight gain of 240 grams per day and twining rates increased from 10 to 23% across the flock. The above results have encouraged the private sector to invest in the production of improved animal feeds by installing a feed mill in Bara town to supply improved feeds for animals. - Farmers from outside the project sites have become engaged in livestock production using improved feeds. - Communities participated in sand dune fixation through planting indigenous trees and distributing range plant seeds.

In the River Nile State, the Project initially worked with four villages and recently expanded its activities to six villages. The Project has helped in establishing or strengthening a VDC in each village. The VDC is responsible for planning and decision-making. The Project has also developed/strengthened two revolving funds in each village, one for irrigation pumps (for men) and one for gas stoves/cylinders (for women). The project has provided ongoing extension support to the village, focusing mostly on technical issues related to agriculture, livestock and water management. It has raised the awareness of the local communities about climate change and the importance of shelterbelts. The project is fully understood and greatly appreciated by the beneficiaries.

The beneficiaries have reported a great increase in food security and improved livelihoods through: - About 4000 men and 500 women have benefited from the introduction of cash crops in the irrigated farms through use of diesel pumps which have greatly increased their income. An area of 1220 feddans has been converted to multi-cropping systems. - The government has provided 200 pumps, in addition to the 60 pumps provided by the project. - Seven hundred and five (705) women have obtained gas stoves that helped them in saving the time that used to be spent in collecting firewood and thereby contributing to their health improvement and conserving forest. - Twenty-six (26) km of shelterbelts have been established to protect several villages from sand dunes (using drip irrigation from solar powered water from rehabilitated wells). - Many families have benefited from the water pumped by solar energy for drinking and irrigating the home gardens that helped in increasing the resilience of the local communities to climate change.

In South Darfur State, the project has worked with farmers in 20 villages (only six in the first year). It has provided ongoing extension support to the villages, focusing mostly on technical issues related to rainwater harvesting, agriculture, home gardens and livestock. It has also established five successful demonstration sites. Working through existing farmer groups, it has facilitated the integration of good science into local natural resource management practices. It has raised

Elgizouli et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 207-216 understanding of climate change and how to adapt. The project is fully understood and greatly appreciated by the beneficiaries. The beneficiaries have reported a great increase in food security and improved livelihoods through: - Seven hundred and two (702) women and 377 men have benefited from the improved rainwater harvesting techniques, access to improved early maturing varieties and agricultural tools that covered 2777 feddan. - Establishment of home gardens and rehabilitation of rangelands. - High revenues were generated by a large number of people as a result of improvement in animal health and husbandry measures. - More than 400 women were trained in making improved mud stoves. - Improved breeds of goats distributed.

Climate Change Strategies and Policies Adaptation and economic diversification to build resilience in developing countries in general and in Sudan in particular in the context of sustainable development is the main priority, whereas mitigation is only an opportunity. The adaptation is well recognized in the UNFCCC, where developed countries are obliged under Article 4.4 to support the cost that developing countries may incur to cope with the adverse impacts of climate change. However, developed countries have not been providing sufficient funding for adaptation. Around 80% of climate change finance provided by the developed countries is allocated for mitigation. Several policy issues were identified during the NAPA preparatory phase, The NAP consultation process which covered all the States of the Sudan, also proposed policies that were considered important for implementing the NAP. The following are the major policy recommendations: - Mainstreaming of the NAPA and NAP in the development plans of the States. - Provision of political support for the NAP at the national and State level. - Updating and activating the environmental policies and legislation. - Transparency, responsibility and accountability should be emphasized. - Policies for water resources management to emphasize water harvesting, efficient and sustainable utilization of water resources to stress provision of safe potable water for rural, urban and nomadic populations. - Strategies and policies should guarantee food security. - A national land use plan should be adopted. - Poverty reduction should be included in the adopted plans. - Encourage sustainable use of natural resources. - Adopt best practices to conserve biodiversity and vegetation cover and combat desertification. - Introduce technical packages in agriculture that could help to build resilience and enhance adaptation to climate change (water harvesting, drought resistant varieties, shelterbelts, etc). - Document and promote indigenous knowledge adaptation practices and encourage exchange of experience between the States.

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- Policies to support modernization and development of the agricultural and livestock systems. - Avail microcredit for small farmers and pastoralists. - Strengthen the role of extension in all adaptation processes (awareness adaption and learning mechanisms and identifying and promotion of best practices). - Support the involvement of research in adaptation activities (technology transfer, development of adaptation package). - Establish CBOs and ensuring the active participation of communities in all phases of adaptation planning and implementation. - Undertake concerted efforts to achieve effective horizontal and vertical coordination between all the stakeholders (Climate Change Unit at HCENR, line ministries at the national and State levels, the CBOs, and the local leaders). - Empower women through their active participation. - Capacity Building of all stakeholders. - Establish a national early warning system, and assist in establishing community based local early warning systems.

Discussion and Conclusions The LDC expert group (UNFCCC) defined adaptation to climate change as human - driven adjustment in ecological, social and economic systems or policy processes in response to actual or expected climate stimuli and their effects or impacts. Accordingly, adaptation planning is closely related to development planning. National adaptation planning can enable to assess vulnerabilities, mainstream climate change and to address adaptation. The strategic nature of NAPA and NAP should be stressed. Such processes should be extended even after the end of the project. There is need for documentation of economic, social and environmental changes. Lessons of best practices should be the basis for upscaling efforts. AIACC AF 14 project has been a very successful and useful experience in identifying useful tools and practical adaptation options for vulnerable communities in Sudan and other countries in the region. In Sudan, activities were selected for drought affected vulnerable communities towards environmental management strategies for sustained livelihood activities. The project undertook three case studies and assessed current and recent historical experiences (1980s). Each case study explored examples where local knowledge (indigenous, informal, autonomous) and/or external knowledge (e.g. formal technical) have been applied in form of sustainable livelihood (SL) or natural resource management ( RM) Case studies assessed community’s resi ience to climate extreme before and after the project. Case studies were conducted by commissioned researchers through desk-based and field research for six-month period. Analyses of success drivers were compiled. Specific examples observed include both autonomous natural resources management systems developed in Darfur, and those stimulated by NGO or other supportive organization such as rangeland rehabilitation in Bara, North Kordofan.

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The capacity to finance should not be restricted to coping mechanism, but livelihood diversification activities that could reduce climate vulnerability should be included. Further, community savings should be encouraged in liquid or live forms (e.g. livestock, food store). Access to basic low technical materials for development and improvement of low infrastructure (such as water harvesting system, food storage facilities) is also important. Moreover, these communities assign great value to basic tools and inputs such as improved seeds, and access to farm and earth moving equipments. Human skills are critical to coping and resilience. As the human skills grow, resilience and adaptive capacity also grow. Indeed social capital is one of the most important determinants of resilience to shocks. Family and informal social networks, community groups, VDCs, self help group (Nafeers), and effective local decision- making bodies and institutions are also recognized as important resources for building and preserving the capacity to cope to climate impacts. NAPA and NAP processes in Sudan are country - driven, gender sensitive, participatory and followed transparent approach. The NAPA and NAP processes are guided by scientific knowhow and benefited from indigenous knowledge and were planned to be integrated into relevant social, economic and environmental policies and actions. NAPA and NAP are not meant to result in duplication of efforts undertaken in the country, but rather facilitate, coordinate and complement efforts. Responding to the challenge of climate change is a national priority for Sudan. Impact of climate change is already affecting rural communities, natural resources, agricultural productivity and coastal infrastructure. The increasing frequency of severe droughts and declining rainfall are already an urgent priority, which requires immediate action in cooperation with international community.

Literature Consulted Abdalla, S. H. 2010. Vulnerability of water resources of Sudan to climate change. Ministry of Irrigation and Water Resources, Sudan. Fadl El Moula, I. and Elgizouli, I. 2008. Climate change and impacts in Sudan and the future prospective to mitigate climate change. A paper presented to the workshop on Climate change, Wad Medani, Sudan. FAO. 2005. Multipurpose Africover Databases on Environmental Resources. FAO organization, Rome. HCENR. 2003. Sudan's First National Communication under the United Nations Framework Convention and Climate Change, volume I main communication, Ministry of Environment and Physical Development-Sudan. HCENR. 2005. Adaptation to climate change and related impacts, the case of Sudan. UN Commission on Sustainable Development. Ministry of Environment and Physical Development, Sudan. HCENR. 2007. National Adaptation Program of Action (NAPA) Ministry of Environment and Physical Development, Sudan. Higher committee for studying the present and future of agriculture in Sudan. 2008. Executive Programme of Agricultural Revival (Nahda).

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Ministry of Finance and National Economy. 2008. National poverty eradication strategy paper: A statement of vision and development context. National Council for Strategic Planning. 2007. The Twenty Five Year National Strategy (2007-2031).

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Climate Change Impacts, Vulnerability and Adaptation in Sudan

Sumaya A. Zakieldeen1 and Nagmeldin G. Elhassan2

Abstract The Intergovernmental Panel on Climate Change (IPCC) clearly confirmed that past Green House Gases (GHGs) emissions result in unavoidable warming regardless of the global mitigation efforts. Wide ranges of impacts and vulnerabilities are associated with this warming. Adaptation is, however, the only available response waiting for the global community to undertake mitigation actions that lead to stabilization of GHGs in the atmosphere to prevent dangerous anthropogenic interference with the climate system. Sudan as an African least developed country is extremely vulnerable to the adverse impacts of climate change. Its vulnerability is an outcome of the interaction between climatic and non-climatic factors. Previous studies have indicated that the temperature increase, rainfall variability, southwards movement of isohyets, increase of frequency of drought and floods and sea level rise as the climatic factors causing vulnerability. The country is also facing a number of non-climatic factors, which aggravate its vulnerability such as poverty, lack of income diversity and mismanagement of resources. Studies conducted by the Higher Council for Environment and Natural Resources (INC, AIACC, NAPA, NAP, SNC) on Sudan’s vulnerability to climate change, identified the water, agriculture, costal zone and health sectors as the most vulnerable. In Sudan, climate change represents a reality and a burden impeding the achievement of food security and sustainable development. Accordingly, Sudan climate change strategy aims at promoting sustainable development that improves adaptive capacity and limit growth of GHGs emissions through integration of climate change issues and concerns into national polices, strategies and development plans. In line with its national strategy for climate change, the country implemented a number of adaptation projects and programs such as AIACC, NAPA and NAP with the objective of identifying adaptation measures that address the vulnerabilities of the major sectors in the country. While AIACC is for development of information base for adaptation planning, in addition to building technical capacity among experts, NAPA is the one that identified and implemented urgent and immediate adaptation needs to address climate variability and changes within the context of the country’s economic development. On the other hand, NAP is a comprehensive mid and long-term adaptation planning process with the objectives of building adaptive capacity and resilience and facilitating the integration of climate change adaptation into development plans for all relevant sectors in all the states of Sudan. Both NAPA and NAP followed bottom up approaches in which the communities from different parts of the country have participated.

Keywords: climate change, vulnerability, adaptation, water, agriculture, health.

1 Institute of Environmental Studies, University of Khartoum. 2 Higher Council for Environment and Natural Resources.

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Scientific and Policy Context It is well established now by scientific community that historical accumulation of the Greenhouse Gases (GHGs) will cause climatic changes no matter what we do. The Intergovernmental Panel on Climate Change (IPCC) in its Fourth Assessment Report (AR4, 2007) concluded that past emissions are estimated to involve some unavoidable warming (about a further 0.6°C by the end of the century relative to 1980-1999) even if atmospheric greenhouse gas concentrations remain at 2000 levels. IPCC also concluded in its AR4 that there are some impacts for which adaptation (Box 1) is the only available and appropriate response. In other words for those unavoidable impacts, reduction (mitigation) of the GHGs will not help humankind to avoid them and it is simply too late because the atmosphere is already responding to these historical accumulations of GHGs. The IPCC AR4 included very alarming findings with regard to the impacts of climate change on the African countries, particularly the Sahel and sub-Saharan Africa. It stated, “Agricultural production, including access to food, in many African countries and regions is projected to be severely compromised by climate variability and change”. The area suitable for agriculture, the length of growing season and yield potential, particularly along the margins of semiarid and arid areas are expected to decrease. This would further adversely affect food security and exacerbate malnutrition in the continent. In some countries, yields from rainfed agriculture could be reduced by up to 50% by 2020. These findings have been confirmed by the results of the vulnerability and adaptation assessment conducted in the larger region of Kordofan during the preparation of Sudan’s Initial National Communication (INC, 2003). In climate change science, global average temperature is correlated to the concentrations of GHGs in the atmosphere. The IPCC in the AR4 stated, “Impacts are expected to increase with increases in global average temperature” if the current scenario of global GHGs emissions continued in the same manner. IPCC AR4 also stated, “Although many early impacts of climate change can be effectively addressed through adaptation, the options for successful adaptation diminish and the associated costs increase with increasing climate change”. This is a clear warning signal from the IPCC which indicates the need, in addition to undertaking urgent adaptation actions for the global community to undertake urgent mitigation actions to avoid future impacts with larger magnitude that diminishes our ability to adapt both in terms of resources required and factors of success of actions taken. It is, therefore, very important that climate change policies and planning, at global as well as national level, respond simultaneously to both the need for urgent adaptation and the need to avoid future impacts through effective GHGs mitigation actions. The global policy framework for addressing both climate change mitigation and adaptation is the United Nations Framework Convention on Climate Change (UNFCCC), which is adopted in 1992. The UNFCCC objective as enshrined in its Article 2 is “to achieve stabilization of GHGs concentrations in the atmosphere at levels that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved within a time frame sufficient to allow ecosystems to adapt naturally to climate change to ensure that food production is

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 not threatened and to enable economic development to proceed in a sustainable manner”. In the implementation of the Convention, the concept of stabilization of GHGs concentrations in the atmosphere is translated into a temperature increases goal that is assumed (as the limit) to prevent occurrence of dangerous climate change (irreversible impacts) (UNEP, 2013). The Parties to the UNFCCC currently adopted a “stabilization goal” of reducing global GHGs emissions to the level that holds the increase in global average temperature to below 2°C above pre- industrial levels. The second part of the UNFCCC objective refers to adaptation; it recognizes that the priority of developing countries to achieve food security and sustainable economic development should be ensured, because adaptation needs are correlated with the impacts associated with global average temperature levels. However, so far, in the implementation of the convention, adaptation has not been addressed in a comprehensive manner that take into consideration the link between adaptation needs and the different GHGs stabilization levels adopted or achieved by the global community to hold temperature increases to save levels. The recently adopted IPCC AR5 (2014) stated that “the globally averaged combined land and ocean surface temperature data as calculated by a linear trend show a warming of 0.85 [0.65 to 1.06] °C over the period 1880 to 2012. The total increase between the average of the 1850–1900 period and the 2003–2012 period is 0.78 [0.72 to 0.85] °C”. This simply means that, with all the devastating impacts of climate change already being witnessed in all regions of the globe including Africa and Sudan, we still live in a world of a global average temperature increase of about 0.85 °C, and we are yet to reach the agreed 2°C stabilization target. This gloomy picture necessitates a more serious and urgent global and national efforts to address adaptation planning and implementation. IPCC in its AR4 provided different options of GHGs stabilization scenarios for achieving the ultimate goal of the Convention (see Table 1) and stated that “delayed emissions reductions significantly constrain the opportunities to achieve lower stabilization levels and increase the risk (Box 1) of more severe climate change impacts”. It is worth noting that according to the World Meteorological Organization (WMO), observed concentrations of CO2 in the atmosphere have exceeded the symbolic 400 ppm thresholds at several stations of the WMO’s Global Atmosphere Watch Network by May 2013 (http://www.wmo.int/ pages/ mediacentre/news/documents/400ppm.final.pdf).

Table 1. Characteristics of stabilization scenarios * Stabilization level Global mean temp. Year CO2 needs to peak (ppm CO2-eq) increase (ºC) 445 – 490 2.0 – 2.4 2000-2015 490 – 535 2.4 – 2.8 2000-2020 535 – 590 2.8 – 3.2 2010-2030 590 – 710 3.2 – 4.0 2020-2060 Source: IPCC AR4 (2007) *In order to stabilize the concentration of GHGs in the atmosphere, emissions would need to peak and decline thereafter. The lower the stabilization level, the more quickly this peak and decline would need to occur

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Box 1 definitions Climate change refers to a change in the state of the climate that can be identified (e.g. by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forces such as modulations of the solar cycles, volcanic eruptions, and persistent anthropogenic changes in the composition of the atmosphere or inland use. In the context of the climate convention, climate change is defined as “Climate change” means a change of climate, which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods (Article 1 of the UNFCCC). Exposure: The presence of people, livelihoods, species or ecosystems, environmental functions, services, and resources, infrastructure, or economic, social, or cultural assets in places and settings that could be adversely affected. Risk: The potential for consequences where something of value is at stake and where the outcome is uncertain, recognizing the diversity of values. Climate change risk is often represented as probability of occurrence of hazardous events or trends multiplied by the impacts if these events or trends occur. Risk results from the interaction of vulnerability, exposure, and hazard. Vulnerability: The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts and elements including sensitivity or susceptibility to harm and lack of capacity to cope and adapt. Impacts: Effects on natural and human systems of extreme weather and climate events and of climate change. Impacts generally refer to effects on lives, livelihoods, health, ecosystems, economies, societies, cultures, services, and infrastructure due to the interaction of climate changes or hazardous climate events occurring within a specific time period and the vulnerability of an exposed society or system. Impacts are also referred to as consequences and outcomes. The impacts of climate change on geophysical systems, including floods, droughts, and sea-level rise, are a subset of impacts called physical impacts. Adaptation: The process of adjustment to actual or expected climate and its effects. In human systems, adaptation seeks to moderate or avoid harm or exploit beneficial opportunities. In some natural systems, human intervention may facilitate adjustment to expected climate and its effects. Resilience: The capacity of social, economic, and environmental systems to cope with a hazardous event or trend or disturbance, responding ort reorganizing in ways that maintain their essential function, identity,r and structure, while also maintaining the capacity for adaptation, learning, and transformation. a n Climate Change Impacts and Vulnerability of Sudan s Sudan is typical of other least developed countries in Africaf in being highly vulnerable to climate change and climate variability. The interactiono of multiple stresses such as endemic poverty, ecosystem degradation, complexr disasters and conflicts, and limited access to capital, markets, infrastructurem and technology have all weakened people’s ability to adapt to changes in climatea (Zakieldeen, t i Copyright © 2015 SAPDH 220 o ISSN 1816-8272 n

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2009; AIACC WP No. 42, 2005). The vulnerability of the country is an outcome of interaction of both climatic and non-climatic factors (NAPA, 2007).

Climatic Factors Climate scenario analyses conducted by Sudan’s Initial National Communication (INC, 2003) to the UNFCCC indicate that average temperatures are expected to rise significantly relative to the baseline (1961-1990). By 2060, average temperatures are expected to rise from between 1.5oC and 3.1oC above the baseline during August and from between 1.1oC to 2.1oC during January. Climate change is also projected to reduce average rainfall by about 6 mm per month during the rainy season. Such changes in temperature and precipitation are likely to undermine the development process that is occurring in many sectors in Sudan. For the current situation, the findings of the Sudan’s Second National Communication (SSNC, 2013) illustrated that air temperatures have been steadily increasing in Sudan over the period 1960-2009. The most affected areas were semiarid parts of the country (Northern, River Nile, and Red Sea States). The increase in temperature was found to be between 0.2°C and 0.4°C per decade during both the March through June and June through September periods. However, it was also stated that when averaged across all seasons, temperatures in the 2000-2009 periods are roughly between 0.8°C and 1.6°C warmer than they were in the 1960-1969 period. Rainfall is also very variable, and is becoming increasingly unpredictable. The coefficient of rainfall variability (CV, or the percentage deviation from the norm) measures the uncertainty of rainfall, the higher the CV percentage, the more uncertain the rainfall. In Sudan, the CV decreases from north to south (Zakieldeen, 2009), indicating that rainfall is highly variable in time and space (temporal and spatial variability). During the period (1981-2012), the rainfall in the whole country was significantly lower as compared to the 1971-2000 period. This was very clear in the central and northern parts of the country, while the southern parts experienced less decrease. There was an area in the southern parts of central Sudan, where the rainfall increases during the last ten years. Studies also illustrated that the rainfall isohyets shifted southwards (Fig. 1) in two climatic means (1941-1971) and (1971-2000). The 100 mm isohyet was found to shift by 100 to 150 km, while the 700 mm isohyet retreated about 150 to 250 km to the south (Elhassan et al., 2013). The findings of the Second national communication also confirmed the high variability, as well as decrease of rainfall amount over the past decades. The findings of the studies conducted for the current NAP process (2014) show that in addition to the variability in the amount and distribution of rainfall, variability in the length of the rainy season was found to become unpredictable and generally shorter in all States. The following has also been reported in almost all the States:  Decrease in annual rainfall.  Change in number of rainy days.  Delay in the start of rainy season.  Increase in dry spells during the rainy season.

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22 22

20 20

18 18

16 16

14 14

12 12

10 10

8 8

6 6

4 4

22 24 26 28 30 32 34 36 38 22 24 26 28 30 32 34 36 38

Figure (1): Comparison of the rainfall climate normal for the period: 1941- 1970/1971-2000 Source: A. K. Abdalla, Sudan Meteorological Authority (2011)

Both the SSNC (2013) and the NAP (2014) illustrated that the frequency of extreme climatic shocks is increasing, particularly drought and floods. The former used to be a rare phenomenon that used to occur once every 30 years. Drought is now one of the most important and frequently recurring challenges that Sudan faces. Future drought threatens about 19 million hectares of rain-fed mechanized and traditional farms, as well as the livelihoods of many pastoral and nomadic groups. Floods in Sudan can either be localized caused by exceptionally heavy rainfall or more widespread, caused by the overflow of the River Nile and its tributaries (NAPA, 2007). During the past five decades, there has been a 6-fold increase in flood frequency. The most vulnerable groups are the thousands of communities who live in low lands and along the riverbanks of the River Nile and its tributaries (SSNC, 2013).

Non-Climatic Factors Beside the climatic factors, the country is facing a large number of non-climatic factors that contribute to the vulnerability of communities in different parts of Sudan including the following: i. Poverty: Much of the population in Sudan lives in poverty. Overall, almost 51% live below the poverty line. In the northern part of the territory, this is somewhat lower at 47%. Socioeconomic factors affecting human wellbeing e.g. wealth, distribution of income, gender equity, access to resources, clean water and sanitation ii. Resources mismanagement: combination of severe climatic conditions and land mismanagement (overgrazing, over-cropping, deforestation, deterioration of soil fertility) have caused vegetation cover degradation in different parts of

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the country that has led in many instances to loss of many endemic species (woody, rangeland species) that were once dominant. In the region that borders the desert zone, there is a persistent threat associated with shifting sand dunes and desertification. iii. Lack of income diversity: due to high rates of poverty, poor human skills and high illiteracy rates, vulnerable communities are not able to diversify their income resources.

Vulnerable Sectors The national studies and documents identified the following as the most vulnerable sectors to the negative impacts of climate change: (i) Water: Water supply and demand in Sudan are highly dependent on future changes of temperatures that may adversely affect evapotranspiration rates at water storage location, as well as changes in rainfall patterns that may adversely affect surface water quantities flowing in the Blue Nile and White Nile, as well as leading to drought in areas that practice rainfed agriculture. The SNC estimated future climatic change over the watersheds of major rivers and Wadis in Sudan (SSNC, 2013). A comprehensive analysis was conducted based on the three emissions scenarios and downscaling of nine global circulation models (Abdalla, 2011). The future water demand was projected for 2050 and 2090 climate conditions in both the No population growth and 2% growth scenarios. The analysis targeted the monthly average temperature for baseline (1961-2000) and forecasted (2050 and 2090) periods in Upper Nile regions. It also assessed the annual rainfall for the baseline and forecasted periods in the Upper Nile regions.

The analysis of the monthly average temperature for the baseline (1961-2000) and forecasted (2050-2090) periods in Upper Nile regions anticipated incremental warming throughout the 21st century, in the watershed of the Upper Blue Nile; monthly temperatures are expected to rise between 1.5°C and 3.0°C by 2050 and approximately between 2.9°C and 5.8°C by 2090. In the Upper White Nile watershed, changes are similar; monthly temperatures are expected to rise between 1.0°C and 2.8°C by 2050 and approximately between 3.5°C and 4.5°C by 2090. For the annual rainfall for the baseline (1961-2000) and forecasted (2050- 2090) periods in Upper Nile regions, the study findings showed tendency for drier conditions over the Upper Blue Nile Basin and wetter conditions over the White Nile Basin.

The anticipated joint effects of warmer, as well as drier conditions suggested by the study findings poses serious concerns regarding increased evapotranspiration over water storage areas that could lead to lower flows in the River Nile and decrease of hydropower generation (Table 2).

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Table 2. Forecasted future (2050-2090) climate change impacts on water resources in the upper Blue Nile as compared to baseline (1961-2000). Impacts of climate change Water demand Water demand will increase considerably. For 2050 and 2090 climatic conditions, water demand is expected to increase by up to 11% relative to baseline conditions. Water flow in the For the main Nile below Merowe, there are more river Nile scenarios with greater flows under 2050 conditions than 2090 conditions. Peak annual flows are about 20% less than historic levels under 2090 climatic conditions. For the Blue Nile at Khartoum on average peak annual flows are approximately 30% less than historic levels under 2090 climatic conditions. Impacts on water Water storage will decrease considerably in Sudan, by storage about 40% starting around the year 2030. Hydropower Hydropower generation will decrease considerably in generation Sudan. This will adversely impact national electrification efforts that seek to use a once-available non-GHG emitting resource Source: SSNC (2013)

Both the bottom-up (consultations) and top-down (scenarios) approaches of the current National Adaptation Planning (2011) also showed similar findings for both present and future climate change impacts on water resources. The synthesis of vulnerability across all the Sudanese States showed that both surface and ground water are negatively affected due to decrease/high variability of rainfall as well as increase of temperature. These were found to lead to:  Scarcity of water sources (irrigation, drinking and domestic uses)  Decrease of water quality  Increase in prices of water during summer (70% of income spent on water purchase)  Fluctuation of the flow of the Nile water, its tributaries and the seasonal streams has adverse impacts on irrigated agriculture.  Increase in frequency of floods leading to loss of property, infrastructure, irrigation channels, negative impacts on water services spread of water-borne diseases (ii) Agriculture: Agriculture, including both crop and livestock production, is the main sector of the Sudan’s economy. It is the main livelihood source for more than 70-80% of the population and about 80% of the labor force is employed in agriculture and related activities. It contributes about 30-35% to the GDP. The national studies showed that agriculture is one of the most vulnerable sectors to the negative impacts of climate change. It has been demonstrated that the sector is extremely vulnerable to all the above-indicated climatic factors (Rainfall variability and distribution, drought, flood, temperature). The first national communication anticipated that both agriculture (millet, sorghum) and forestry (gum Arabic) production will be significantly affected by negative impacts of

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 climate change (warmer and drier conditions) in the medium and long term (INC, 2003). The NAPA (2007) also demonstrated the high vulnerability of the agricultural sector in five different ecological zones and identified urgent and immediate measures for addressing adaptation needs in this important sector. The NAP (2014) project also assessed the vulnerability of the agriculture sector in all the Sudanese States. The analysis used both bottom-up and top down approaches to conduct comprehensive analysis of present, as well as medium and long-term vulnerabilities. The synthesis of climate change impacts in agriculture in Sudan (Table 3) showed that the sector is even currently gravely affected and facing serious challenges.

Table 3. Some of climate change impacts on agricultural sector Impacts on Crop Impacts on Grazing and Impacts on Forests production animal production - Deterioration in crop - Deterioration of carrying - Decrease of areas production (decrease in capacity covered by forests production per unit area) - Shrinkage of rangelands - Impact on natural - Crop failure - Lack of drinking water for regeneration and - Expansion and increase of grazing animals succession of trees cultivated areas in - Scarcity and gaps in fodders - Decrease of fodder marginal lands at the (e.g. estimated by 1.5 million trees expense of rangelands and tons in White Nile State) - Deterioration of gum forest cover - Changes in amount and types Arabic belt - Spread of pests and of rangelands’ species - Deforestation diseases (disappearance of palatable - Disappearance of - Negative impacts of species and appearance of trees (Tamarind, increase of temperature on unpalatable ones) and decrease Ebony) winter crops in biodiversity of rangeland - Cultivation of local crop species varieties that are early - Spread of animal diseases maturing but of low yield - Deterioration of animals and quality production (quality and - Deterioration of quantity) horticultural production - Risks to agro-pastoral life - Change in livelihoods (Migration from rural to urban areas) - Change in type of animals (e.g. cattle are sensitive, goats are survivor) General impacts: - Conflicts over scarce resources - Changes in prices and income - Loss of livelihoods - Food insecurity - Increase of poverty

(iii) Coastal zone: The UNFCCC (2010) identified the slow onset events to include “sea level rise, increasing temperatures, ocean acidification, glacial retreat and related impacts, salinization, land and forest degradation, loss of biodiversity

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 and desertification. The Red Sea zone is highly vulnerable to the negative impacts of slow onset events of climate change. Sea level rise: The IPCC’s Fourth Assessment Report (2007) posits 0.59 meters rise by 2100. Continued melting of certain glacial types could lead to sea level rise in excess of 10 meters in the period after 2100 (IPCC, 2007). Rapid sea-level rise constitutes a major potential problem facing coastal zones in Sudan. The second national communication showed that there has been a gradual increase in sea level, about 10-20 cm during the past century in Port Sudan area based on data from Permanent Service for Mean Sea Level. Sea-surface temperatures: are warming due to increased concentrations of GHGs in the atmosphere. Scenarios anticipated that the increase in temperature could reach up to 3°C by 2100, changing the density and thus volume of the oceans. Increased sea-surface temperature could also lead to higher peaks of storm surges, increased cyclone intensity, and a greater risk of coastal disasters (IPCC, 2007). Salinity: The IPCC (2007) also stated that tropical and sub-tropical regions have become and will continue to become slightly more saline. Such changes pose hazards to aquatic plants and animals in Sudan’s coastal lagoons that do not tolerate high salinity Intensification of storm surges: The Red Sea area itself is not currently an area of cyclone activity and is not recognized as a region currently vulnerable to cyclone activity. In Sudan, storm surges would lead to damaging flood conditions all along its coastline, particularly in high population areas like Port Sudan, as well as adjoining low-lying areas like the Tokar Delta agricultural areas. The Red sea zone is characterized by unique fauna and flora and, as well as outstanding ecosystems such as Coral Reefs, Mangroves, Salt Marshes and Sea grass. The studies showed the current and potential impacts of these ecosystems to slow onset events (Table 4). (iv) Health sector: Health is one of the most vulnerable sectors to the negative impacts of climate change. The first National Communication anticipated the increase of the risk of malaria under climate change. It has been illustrated that malaria transmission potential could increase substantially by 2030 and 2060 in Kordofan State (INC, 2003). The vulnerability assessment of health sector to current climate change impacts was conducted by both the NAPA and NAP. The findings confirmed the correlation between temperature and precipitation patterns and malaria, meningitis, and leishmaniasis diseases that afflict millions of people throughout the country (NAPA, 2007). While the NAPA consultation process confirmed that malaria is a major concern, the other diseases were also prioritized for adaptive measures. Besides confirming the findings of the NAPA, the NAP also showed that changes in climate might alter the distribution of important vector species and increase the spread of diseases to new areas. For instance, highland populations that fall outside areas of stable endemic malaria transmission may be particularly vulnerable to increases in malaria due to climate warming. In addition to that, it was demonstrated that not only will climate change worsen various current health problems, it may, however, also bring new and unexpected ones. The NAP results synthesized from all the Sudanese States analysis, showed

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 spread of waterborne diseases (malaria, bilharzia, Kalzar), as well as diseases that spread because of lack of water (trachoma, skin diseases). For most of the States, the spread of malnutrition was also identified as an outcome of food deficiency caused by climate changes.

Table 4. Current and potential vulnerabilities of natural and physical environments to the climate change impacts (slow onset event) in Red Sea zone Impacts on different Sea level rise Changes in seawater Storm surge ecosystems temperature and intensification salinity Coral Reefs Corals are vulnerable to thermal stress and have low adaptive capacity. Corals in the Red Sea are expected to have reached their upper physiological temperature limit Mangroves root systems will be any increase in extreme unable to take in storms may induce oxygen and new trees erosion damage to the will be unable to system establish root as seeds float in higher water Salt Marshes Flooding could The inundation of remobilize the fine coastal salt marshes sediments, increasing could create an coastal turbidity and extremely shallow sea affect coral reefs, sea along the coast, would grass, and other be susceptible to marine biota strong heating and lack of reef and cooling. altitude allows sea water to move inland during high tide, storm surges, and even more so with future sea-level increases Sea Grass A change in mean A change in sea- level, as it contributes surface temperatures to increased water could lead to altered depth, would lead to a growth rates, subsequent reduction geographic in light available for distribution, and sea grass growth impair physiological resulting in reduction functions of the plants of 30±40% in its growth and productivity Built Environment Inundation of built environment

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Climate Change Adaptation in Sudan In its INC (INC, 2003), Sudan stated that the contributions of developing and least developed countries in global efforts to fight climate change and its consequences should be closely linked to their national development priorities. The objective of the Climate Change Convention has clearly recognized the needs of developing and least developed countries to address problems of food security, poverty and pursue sustainable development. Accordingly, the commitments of developed and developing countries in the implementation of the convention, as defined in its Article 4, have been based upon the principles of common but differentiated responsibilities and equity. Sudan is considered among the most vulnerable countries to the impacts of climate change. Therefore, adaptation is the highest and overriding priority in its effort to combat climate change. The vulnerability of Sudan has been confirmed in the findings of a number of studies on assessment of impacts and adaptation at different regions of Sudan conducted by the HCENR (INC, 2003; AIACC AF14, 2004; NAPA, 2007; SNC, 2012; NAP, 2014). Sudan’s INC to the UNFCCC set the context for Sudan’s response to its obligations and challenges under the climate change convention. The INC included a general framework for a national implementation strategy for the climate change in Sudan, called “towards a national implementation strategy”. In this strategy, Sudan stated that the overall objective is “to promote sustainable development paths that improve Sudan's adaptive capacity and limit its growth in GHGs emissions through integration of climate change issues and concerns into national policies, strategies and development plans”. The specific objectives of the implementation strategy include:  To improve scientific knowledge and understanding of climate change and its potential consequences in Sudan,  To build an enabling environment to integrate climate change issues and concerns into national development (capacity building, institutional infrastructure),  To raise awareness,  To identify and build synergies with other conventions and agreements (coordination),  To develop a national adaptation program, and  To develop a national GHGs mitigation program.

Following the completion of the INC, Sudan participated in an umbrella project called Assessment of Impacts and Adaptation to Climate Change in Multiple Sectors and Regions (AIACC), the main objective was to identify suitable options for the adaptation planning in Sudan. The AIACC project was funded primarily by the Global Environment Facility (GEF), the U.S. Agency for International Development, the Canadian International Development Agency and the U.S. Environmental Protection Agency also provided additional funding for the project. The project was co-executed on behalf of the United Nations Environment Program by the Global Change System for Analysis, Research and Training (START) and the Third World Academy of Sciences. AIACC aims to

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 enhance capabilities in the developing world for responding to climate change by building scientific and technical capacity, advancing scientific knowledge, and linking scientific knowledge to development and adaptation planning. AIACC supported 24 regional assessments based on case studies in Africa, Asia, Latin America and Small Island States with funding, mentoring, training and technical support. Sudan’s participation in AIACC was motivated by its need to develop information base for adaptation planning in addition to building technical capacity among Sudanese experts. Three case studies were considered in this study, in Arbaat area in the Red Sea State, Bara area in North Kordofan State and Dar Assalam area in North Darfur State. The purpose was to show that certain sustainable livelihoods (SL) measures operate as climate change adaptation options and that such measures can be integrated into the planning of national adaptation strategies (AIACC WP No. 18, 2005). The Sustainable Livelihood Assessment Approach was used to measure the impact of a package of measures (interventions) on a community’s coping/adaptive capacity. The approach aimed at examining the condition of available livelihood assets (natural, physical, financial, human and social) before and after the intervention in order to assess the capacity of communities to adapt to future climate variability and change. Different types of adaptation options were covered by the case studies, some are considered as being developed spontaneously, or autonomously, as a regular part of on-going resource and risk management, and others that are consciously and specifically planned in light of specific climate-related risks (AIACC WP No. 42, 2005). Actual adaptation planning in Sudan started with the preparation of the National Adaptation Programme of Action (NAPA, 2007), which was prepared in line with the requirements under the Least Developed Countries (LDCs) work programme of the UNFCCC. NAPA is the first adaptation plan prepared to enable Sudan to access funds made available through the Least Developed Countries Fund (LDCF) to implement real adaptation actions on ground. The overall goal of the NAPA preparation process was to identify urgent and immediate activities to address climate variability and climate change within the context of the country’s economic development priorities. The three highest priority sectors were identified through the NAPA consultation process included agriculture, water, and public health. NAPA project was funded by GEF, UNDP and the Government of Sudan and implemented by HCENR in collaboration with five States representing the ecological zones of Sudan; North Kordofan, South Darfur, River Nile, Gedarif and Central Equatoria at that time, before the separation of South Sudan. The NAPA started by establishing institutions (a focal point and technical committees) at each of the selected States to coordinate NAPA activities at the State level including data collection, assessment of vulnerability and adaptation, consultations, etc. Then it launches a comprehensive consultative and participatory process in line with the NAPA guidelines developed by the Least Developed Countries Expert Group (LEG). An initial step in the design of the NAPA consultation process was to identify and assess communities and areas within each of the five ecological zones of Sudan where people may be acutely vulnerable to climatic shocks. The groups that have been identified as most

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 vulnerable to climate risks were the traditional rainfed farmers and pastoralists. During past climatic shocks such as drought, rainfed farmers and pastoralists are found typically the least able to cope with climate-related shocks in Sudan. This has been due primarily to a combination of their extreme poverty levels, as well as to household income-generating activities that are highly limited. These factors, together with other specific non-climatic factors contributed to increased vulnerability of these local communities during climatic shock (NAPA, 2007). The NAPA followed a project-based approach in the identification of the intervention needed to reduce vulnerability and build resilience (Box 1) among the targeted communities. About 32 projects identified in the five States addressing urgent and immediate needs for adaptation in the water, agriculture and food security and human health sectors (NAPA, 2007). The NAPA projects of each State have been ranked in an order of priority to the state, this has been done in consultation with relevant stakeholders using agreed criteria. The selected projects are considered as pilot interventions that can be replicated within similar areas in these zones. The NAPA also included recommendations for improving current policies and the institutional framework to facilitate the integration and implementation of adaptation measures. NAPA projects were identified on the basis that they respond to urgent and immediate needs of the most vulnerable groups, improve their adaptive capacity, remove barriers to development caused by the impacts of climate change and in this sense they are not development projects per se, but enable and complement the development process. NAPA is relatively very successful plan in term of implementation compared to other plans and strategies prepared in response to Sudan’s obligations under other multilateral environmental agreements such as biodiversity, desertification, etc. The first support for NAPA implementation was received shortly after the NAPA endorsement by the government of Sudan. Despite the fact that NAPA is project- based plan, its implementation started by a programmatic intervention covering two sectors in multiple regions addressing the highest priority in each of the NAPA States. The first NAPA implementation activities have been very successful in responding to the needs of the vulnerable groups in the targeted areas and generated a number of good lessons and best practices that motivated the State’s governments to replicate them and attracted other donors to provide additional funding for scaling up these successful interventions. Other three NAPA implementation projects are now under different stages of their development and implementation (Table 5). Total funding accessed for NAPA implementation so far is about 21 millions USD. In 2011, Sudan launched a process for a National Adaptation Plan (NAP) in line with its national implementation strategy (INC, 2003) and in response the UNFCCC decisions reach in 2010, the Cancun Adaptation Framework (CAF), which call for the development of National Adaptation Plans (NAP) in least developed countries. The NAP project was based on cooperation agreement between UNEP and HCENR, funded by DIFD as part of the UNEP-Sudan umbrella project (SIEP) and has been implemented in collaboration with the Governments of the 18 States of Sudan.

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Table 5. Projects of National Adaptation Programme of Action (NAPA), states covered, implementation status and source of funding Project States covered Implementation Funding status Implementing NAPA North Kordofan, South Completed by GEF/UNDP Priority Interventions Darfur, River Nile and mid 2014 and; and Sudan’s to Build Resilience in Gedarif Government the Agriculture and The scale-up Water Sectors to the phase started in CIDA Adverse Impacts of 2014 (Canada) Climate Change in Sudan Climate risk finance North Kordofan, South Full project GEF/UNDP for sustainable and Darfur, River Nile, under GEF and Sudan’s climate resilient rain- Gedarif, Kassala and council approval Government fed farming and White Nile pastoral systems Enhancing the White Nile State Project concept GEF/UNEP resilience of (PIF) under GEF and Sudan’s communities living in approval Government climate change vulnerable areas of Sudan using Ecosystem Based approaches to Adaptation (EbA) Livestock and West Kordofan, North Full project GEF/IFAD and Rangeland Resilience Kordofan, White Nile, under GEF Sudan’s Program Sennar and Blue Nile council approval Government

NAP is a comprehensive adaptation planning process covering longer timeframe (mid and long-term) compared to the NAPA, which is mainly for identification of urgent and immediate adaptation needs. NAP aims to reduce vulnerability to the impacts of climate change, by building adaptive capacity and resilience and to facilitate the integration of climate change adaptation into development planning processes within all relevant sectors and at different levels involving all the States of Sudan. NAP process benefited from the experience with NAPA preparation and from the institutions established in the four NAPA States. NAP established similar institutions in all the States with focal points and technical teams of experts from related government, research, academia and civil society organization. The capacity of these institutions has been strengthened through targeted training sessions; learning-by-doing programs; and the establishment of networks to exchange knowledge and experience. The State’s institutions have been tasked with coordination of the NAP process at the State level, including data collection, vulnerability assessment, adaptation strategy formulation, policy and institutional review, and the consultation that led to the identification of the adaptation initiatives to be included in the NAP. NAP process includes assessment of vulnerability and adaptation in all the States, covering the main development sectors, such as water, agriculture, health and coastal zone. In addition to a

Zakieldeen et al., Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 217-233 number of studies on vulnerability hotspot mapping, climate proofing of existing development programs and projects, development of climate scenarios, adequacy of national research and systematic observations and adaptation finance and investment. The outcome of these assessments and studies, informed the programs and activities included the NAP. The NAP shifted the adaptation planning to a more programmatic approach compared to the NAPA. The emphasis in the NAP process turned from a project- based approach seeking to identify and implement urgent and immediate adaptation interventions, to programme-level process for integration of adaptation into medium and long-term development planning. NAPs represent the core and strategic adaptation planning processes at the country level, through which developing countries can identify their needs for support and be able to access funding. According to the UNFCCC guidelines, NAP is a dynamic process that should evolve over time and be reviewed every five years based on development of scientific knowledge and understanding of climate impacts, vulnerability and adaptation. This is implying that Sudan’s NAP process should continue to:  Build technical and institutional capacity and strengthen the States’ NAP institutions and the national NAP network that link all the States and HCENR  Improve knowledge, understanding and develop information database of current and future vulnerabilities of Sudan to climate and its adaptation needs through additional research and studies (e.g. applying advanced methods and tools such as climate scenarios and impact modeling)  Facilitate integration of adaptation into policies and development planning at all levels, through building capacities and awareness and involving relevant stakeholders and solicit government (national and State) commitment and support to the NAP process  Elaborate and develop the NAP programs and initiatives and prepare good quality project proposals of priority adaptation options for financing  Facilitate fund raising to support NAP integration and implementation, targeting government, UNFCCC funds, other multilateral and bilateral sources of funding.

References Elasha, B. O., Goutbi, N., Spanger-Siegfried, E., Dougherty, B., Hanafi, A., Zakieldeen, S., Sanjak, A., Atti , H. A. and Elhassan, H. M. 2005. Assessment of impacts and adaptation to climate change. Adaptation strategies to increase human resilience against climate variability and change: Lessons from the arid regions of Sudan, AIACC Working Paper No. 42. Elhassan, G. N., Mohamed, A. G., Zakieldeen, S. A., Abdalla, N. M. 2013. Climate Change Impacts and Opportunities for Biodiversity and Ecosystems. Ministry of Environment, Forestry and Physical Development, Higher Council for Environment and Natural Resources. National Biodiversity Planning to Support the Implementation of the CBD 2011-2020 Strategic Plan in the Republic of Sudan.

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INC. 2003. Sudan’s Initial National Communication. Ministry of Environment, Forestry and Physical Development Higher Council for Environment and Natural Resources (HCENR), Khartoum. IPCC. 2007. Synthesis Report. An Assessment of the Intergovernmental Panel on Climate Change. IPCC, Geneva. Available at: http://www.ipcc.ch/ pdf/ assessment-report/ar4/syr/ar4_syr.pdf: IPCC. 2013. Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S. K., Allen, J., Boschung, A., Nauels, Y., Xia, V. B. and Midgley, P.M. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. NAPA. 2007. National Adaptation Programme of Action . Republic of the Sudan, Ministry of Environment and Physical Development, Higher Council for Environment and Natural Resources, Khartoum. SNC. 2013. Sudan's Second National Communication under the United Nations Framework Convention on Climate Change, Ministry of Environment, Forestry & Physical Development, Higher Council for Environment and Natural Resources. Spanger-Siegfried, E., Dougherty, B., Goutbi , N. and Elasha, , B. O. 2005. Assessment of impacts and adaptation to climate change Methodological Framework An internal scoping report of the project Strategies for Increasing Human Resilience in Sudan: Lessons for Climate Change Adaptation in North and East Africa. AIACC Working Paper No.18. UNEP. 2013. The Emissions Gap Report 2013 a UNEP Synthesis Report. Published by the United Nations Environmental Programme. UNFCCC. 2010. Decision 1/CP.16 of the Conference of the Parties and by the, Cancun. www.Unfccc.int Zakieldeen, S. A. 2009. Adaptation to Climate Change: A Vulnerability Assessment for Sudan Gatekeeper, 142, Key highlights in sustainable agriculture and natural resource management.

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Indigenous Knowledge and Irrigation in Sudan

Hussein S. Adam1

Abstract Indigenous knowledge in Gezira, where 50% of irrigation lands in Sudan lie, is limited to the rainy season, July-October. This steamed from the people background before irrigation in Gezira when they used to grow rain-fed Sorghum with a length of season from July to October. They divided the rainy season into seven periods of length 13 days each. For each period they have a description of its link with the growth of Sorghum from sowing to harvest.

Keywords: Indigenous knowledge, irrigation, rainy season, periods

Introduction Indigenous knowledge in Sudan and especially in Gezira is very rich. Its link with irrigation is limited to the rainy season and the growing summer season crops especially Sorghum (Dura). Before the Gezira irrigated scheme, the people in Gezira depended on rainfed Sorghum. They grow short duration varieties of about 90 days growth period. This length of growth period fits exactly the length of the rainy season from 9 July to 8 October.

Traditional Rainy Season Periods The local inhabitants divided the rainy season into seven periods of length 13 days for each period. The first period 9-21 July is called “Duraa” which is the arm of the lion. The second period is called “Natra” which is the noze of the lion. It is resembled by three stars close to each other. This period extends from 22 July to 3rd of August. “Natra” is followed by “Tarfa” extending from 4th-16 August. “Jabha” follows from 17th-30th of August. This is the forehead of the lion, represented by four stars. The fifth period is “Khairasan” during which the rainfall begins to decrease. “Khairasan” is followed by “Sarif” or “sadrif” with the S pronounced as “Sad” in Arabic, which means the going away of the rainy season. This period extends from 13th to 25th September. The last period in the rainy season is called “I’waa” which is the sound of dogs, extending from 26th September to 8th October.

Indigenous Knowledge and Climate Change Climate change is real. One of the definite and clear signs of climate change is the steady increase in global temperature, due to the increase in CO2 resulting from increased industrialization (IPCC 2007). In Sudan comparing the last 60 years temperature in a number of meteorological stations, there is a clear trend of increase in maximum temperature (SMA 2013). Unlike temperature, there is no clear tendency of rainfall. However, there are signs of increase of frequencies in late start of the rainy season, early cessation of the season, increased intensities of rains and some years are very dry.

1 Professor of Water Management, Former Director of Irrigation and Water Management Institute, Gezira University. 23 4 Adam, Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11, 2015, 234-235

Local inhabitants consider the start of the rains as late if “Duraa” period is dry. They say if “Duraa” failed, then the season will fail. This is linked with the optimum sowing date of Sorghum which beings 15 July. If there are no rains in “Duraa” 9 -21 July, they couldn’t sow in Mid July. “Duraa” rains give the equivalent of the “first irrigation” to fill the cracks in the soil and provide the needed soil moisture for seeds of the Sorghum to germinate. This problem will not be mended by ample rains in “Natra”. This is because the locals do not put their seeds in “Natra” due to insects. They link activity of the insects with “Natra”. That means they delay the sowing to “Tarfa” 4th August which is a late sowing date. In addition, “Jabha” which follows is known for high intensity showers which may flood the young seedlings of Sorghum. So that is why the locals say “If “Duraa” failed the growing season will be a failure. October is the harvest month. From November to June the people have no agricultural activity. Those who have sheep and cows will be busy with their herds. Most people consider this long period as a vacation. In the past during this period, people get married. The marriage ceremonies extend over 40 days of dancing and celebrations. April and May are for maintenance of houses.

References Adam. H.S. 2005. Agro-climatology, Crop Water Requirement and water Management. Gezira printing & Publishing Company, wad Medani, Sudan 2005. Adam. H.S., O.E. Badry and A. Abdel Wahab. 2010. Weather Lerics and the Physics of weather Phenomena (in Arabic). Sena Printing Company, Khartoum, 2010.

Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015

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237 Sudan Academy of Sciences Journal-Special Issue (Climate Change), Vol. 11 , 2015

بسم اهلل الرمحن الرحيم َ َ َّ ُ َ َّ ْ ُ ْ ُ ْ َ َّ ُ ْ َ َ ّ َ َ ً َ ْ َّ ً يا أيتها النف ساْلطم ِئنة ار ِج ِعي ِإلى رِب ِك ر ِاضية مر ِضية

An Obituary Loss of the Prominent Ecologist Professor Ahmed Suliman El Wakeel

The Ecology Professor Ahmed Suliman El Wakeel, one of Sudan most prominent scientists in the field of ecology and natural resources, died suddenly on August 14, 2014. El Wakeel grew up in Wad-Medani city and received his bachelor of science degree in Agriculture at Khartoum University, Sudan in 1975, MSc in Range Ecology at University of Wyoming, USA in 1983, and completed his doctor's degree at University of Utah, USA in 1986. He was also a Postdoctoral Associate Scientist and staff member in the International Livestock Research Institute in 1992-1996. Prior to joining Higher Council for Environment and Natural Resources, Wakeel was a researcher in range ecology and management for more than 30 years at Agricultural Research Corporation, where he was named as Ecology Professor. During his career, El Wakeel had several publications in refereed Journals and made significant contributions in areas of: Range Ecology and Pastoralism, Biodiversity, Biotechnology and Biosafety. He worked as a National Coordinator of Biodiversity Project in Sudan and developed the Sudan National Biodiversity Strategy and Action Plan. He was the main country reference in the international conventions and treaties on: Biological Diversity, UN Framework on Climate Change, UN Convention to Combat Desertification and The International Treaty on Plant Genetic resources for Food and Agriculture. In addition, he was an academic supervisor for several MSc and PhD students. El Wakeel was an active member in ECAW project. He chaired the committee that selected the ECAW postgraduate students and a supervisor of an MSc student that was the first to graduate among the project students. Prof. El Wakeel left a large group of students and associates behind who were expecting to work with him for years to come. Words seem inadequate to express the sadness we feel about the loss of Professor Ahmed Suliman El Wakeel. We have lost one of our most brilliant researchers, and on top of that, he was a very nice person, loyal friend and his concern for his colleagues was well-known. Sincere condolences are extended to his family and all his colleagues. May GOD bless him: may the mercy of GOD cover him. 238