MINISTRY Of ‘.'ifJfr.S AND ENERGY ETHIOPIAN ENERGY STUDIES AND RESEARCH CENTER
VOLUME III
A Strategic. Plan for the Sustainable Development of Woody Biomass Resources
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(Draft)
Prepared by the Woody Biomass Inventory and Strategic Planning Project (WBISPP) '
November 30, 1995
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MINISTRY o r MiNtS AND ENERGY MINISTRY Of- AGRICULTURE ETHIOPIAN ENERGY STUDIES AND RESEARCH CENTER
VOLUME III
A Strategic Plan for the Sustainable Development of Woody Biomass Resources
(Draft)
Prepared by the Woody Biomass Inventory and Strategic Planning Project fWBiSPP) "
November 30, 1995 \ WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT 1
CONTENTS
I. INTRODUCTION TO PLANNING OBJECTIVES
II. NATIONAL FRAMEWORK FOR PLANNING
2 1 General 2.2 The Natural Resource Base 4 2.3 The Natural Resource Sectors 5
THE PROJECT AREA
3 1 The Physical Environment ii 3.2 Land Use Systems ' 9 3.3 Socio-Cultural Aspects
PLANNING FOR SUSTAINABLE DEVELOPMENT AND MANAGMENT OF WOODY BIOMASS RESOURCES
4.1 Factors affecting the Production and Consumption c' Woody Biomass 3 ( 4.2 Planning Approach and Analytical Techniques 39
SUPPLY AND CONSUMPTION OF WOODY BIOMASS AND OTHER BIO FUELS
5.1 Terminology 54 5.2 Methodology Used to Obtain Estimates of Woody Biomass Stocks and Yields 54 5.3 Supply Patterns of Woody Biomass 56 5 4 Consumption Patterns of Woody Biomass 57 5.5 Supply and Consumption Patterns of other Bio Fuels 61 5.6 Woody Biomass Supp’y and Consumption Balance? 52
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VI. ACHIEVING THE SUSTAINABLE DEVELOPMENT AND MANAGEMENT OF WOODY BIOMASS RESOURCES IN THE PROJECT AREA
5 1 Analysis of Issues 64 6 2 The Potential for and Constraints to the Sustainable Development and Management of Woody Biomass Resources 80 Reducing the Demand for Woody Biomass 86
VII. STRATEGIC PLAN
1 A Multi Sectoral and Participatory Approach 88 Direct Strategies for the Sustainable Development and Conservation of Woody Biomass Resources 8S - Indirect Strategies for Sustainable Development of Woody Biomass Resources C",VO r 4 Reducing Demand for Woody Bjomass 97
REFERENCES 98
TABLES
Table 2 1 Wood Products 1992/93 6 Tabie 2 2 Energy Supply in Ethiopia: 1984 7 Table 2 3 Energy Consumption - Pattern 1984 7 Table 3 1 Location and area of industrial plantations 32 Table 3 2 National Parks and other conservation areas 33 Table 3 3 Rural and urban population estimates 1995 35 Table 5 1 Woody biomass stocks and yields by region 1995 57 Table 5 2 Weighted mean annual per caput wood fuel consumption rates by region r c i ao>e : o Total wood fuel consumption by region 1995 59 Table 5 4 Annual rates of high forest clearing - by area -for agriculture by region for 1995. 2005 and 2015 60
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Table 5 5 Annual rates of high forest clearing - by weight - for agriculture by region for 1995, 2005 and 2015 61 Table 5.6 Annual rates of woody biomass consumption by weight for rural house construction by region for 1995, 2005 and 2015 61 Table 5.7 Total weight of agri residues and dung used as fuel by region. 1995 62 Table 5.8 Woody biomass supply ana consumption balances by region 63 Table 6 1 Woody Biomass Development Zones 6^
FIGURES -
Figure 6.1 a Costs and revenues from European and North American forests 76 Figure 6.1 b Costs and revenues of tree oroduction strategies of peasant Farmers in Ethiopia 7 3 Figure 7 1 Nested rotation cycles for managing and harvesting trees on farms 9C Figure 7 2 Agricultural landscape and socio-ecological niches in the Kambata Zone of Souirern Ethiopia Peoples region
END MAPS
End map 1 Location of the project ares End map 2 Altitude End map 3 Mean annual rainfall End map 4 Temperature zones End map 5 Agro-Ecological zones End map 6 Land use and land cover End map 7 Farming and pastoral systems End map 8 National Forest Priority Areas End map 9 Crop suitability based on length of growing period End map 10 Crop risk based on length of growing period End map 11 Administrative boundaries End map 12 Population density End map 13 Rurai population support capacity End map 14 Livestock carrying capacity End map 15 Annual wood fuel consumption per caput: Rural population End map 16 Annual wood fuel consumption per caput: Urban population End map 17 Annual wood fuel consumption per caput: Total population End map 18 Woody biomass stocks: 1995
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End map 19 Sustainable yield of 1995 woody biomass stocks End map 20 Woody biomass supply-consumption balance: 1995 End map 21 Crop residues used as fuel End map 22 Dung used as fuel End map 23 Deforestation End map 24 Areas of environmental stress End map 25 Woody Biomass Development Zones
APPENDIX 1 National Forest Priority Areas
APPENDIX 2: Population Support Capacity Analysis
APPENDIX 3. Livestock Carrying Capacity Analysis
APPENDIX 4. Fuel Wood Supply Consumption Balances
APPENDIX 5: Woody Biomass Development Zone Analysis
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CHAPTER I INTRODUCTION TO PLANNING OBJECTIVES
The population of Ethiopia (1995) currently estimated at 56 9 million is increasing at a rate of 2.9 percent per annum. Urbanization is relatively low. some 85 percent of the population live n the rural areas While 80 percent of the population is located in the Highlands (defined as all land over 1,500 masl) as settled agriculturalists the remaining population live the semi arid and arid eastern and southern Lowlands as pastoralists and agro-pastoralists, or as shifting cultivators in the moist western Lowlands
Agriculture in the Highlands comprises mixed cropping and livestock production with cereals predominating in the Northern, Central and Eastern Highlands and enset and root crops in the Southern and Southwestern Highlands. With a rapidly increasing population, cultivation is expanding. More marginal and steep iands are increasingly being brought under cultivation, leading to accelerated soil erosion, and to declining and more variable crop yields. Expanding cultivation is at the expense of communal iands on which most woody biomass resources are located, leading to a decline in these resources Nationally, bio-fuels provide 93.5 percent of the total energy supplies with 77 percent derived from woody biomass, some 8.7 percent from crop residues and 7 7 percent from dung. However these national figures conceal considerable regional and local variations in both supply and consumption patterns, as well as temporal changes in these patterns in the face of declining stocks and yields of wood fuel, and the increasing opportunity and money costs in its collection or purchase.
Given the well integrated nature of agriculture in the Highlands these changes have important implications for both crop and livestock production, as well for the health and nutrition of the population. Increasing use of dung precludes its use as manure , whilst the use of residues as fuel precludes their use as either livestock feed or.manure This leads in turn to breaches in the cycling of soil nutrients, in particular nitrogen ana phosphorous, leading in turn to declining soil fertility and thus declining crop yields.
The key specific aim of the project1 is to "provide a means for dynamically monitoring and evaluating the physical changes in forested and treed ecosystems undergoing rapid change, providing feed back to planning and decision makers on the implementation of policy decisions towards, or indirectly influencing tree cover and the depletion of wood biomass.” The project was seen to provide a first opportunity for a detailed assessment of woody biomass resources in a selected area of some 250.000 km2
^Contract Agreement between Government of Ethiopia and the Canadian Consortium. April 30th, 1990
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The planning objectives are as follows:
(i) to inventory the above ground woody biomass stock resources and determine the sustainable yields,
(ii) to survey and gain an understanding of the consumption and use patterns of woody biomass and other bio-fuel substitutes, including an understanding of the agricultural production systems and rural economy which influence both the supply and consumption patterns,
(iii) to identify the problems and issues with respect to the sustainable supply of woody biomass resources, and
(iv) to formulate strategies and tactics for the sustainable development and conservation of woody biomass resources within the project area
The Strategic Plan first sets out the national framework, in terms of the main natural resource sectors of the economy, followed by an outline description of the project area. Chapter IV examines, in general terms, the factors affecting woody biomass production and consumption, and they inter-relate. Given the nature and complexity of these production-consumption factors, an explanation is given of the planning approach which the project adopted, and a description of the main planning and analytical procedures used. Chapter V describes the main patterns of production and consumption of woody biomass and substitute bio-fuels within the project area. This followed in chapter VI by an analysis of the main issues which have been identified in the planning analysis,' and examines in detail the potential and constraints to sustainably developing and managing woody biomass resources in the project area. Finally a strategic plan is described detailing the main strategic and tactical approaches to dealing with specific problems and with specific areas.
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II NATIONAL FRAMEWORK FOR PLANNING
2.1 General
The total land area of Ethiopia is 1.2 million km2 with an estimated population in 1995 of 56.88 million. About one third of the land area comprises a hilly and mountainous plateau between 1,500 and 3,500 masl. About 90 percent of the population is rural, and 80 percent of this population lives in the highlands. The densely populated highlands are surrounded by sparsely populated lowlands. The eastern, southeastern and southern lowlands are arid to semi arid and are inhabited by pastoralists and agro-pastoralists; whilst the moister southwestern and western lowlands, which are infested by tsetse fly, the vector of trypanosomiasis, are inhabited by bush fallowing cultivators with few or no cattle.
The Gross Domestic Product (GDP) in the decade before 1982/83 grew at about 2.2 percent per annum in real terms. It decreased during the 1980's due to drought and the low level of investment in agriculture. With population increasing at 2.9 percent per annum per capita GDP declined. Since 1992 the GDP has accelerated to 6.4 percent in 1992/1993 and 5.8 percent in 1993/1994. Agriculture comprises 47 percent of the GDP, the industrial sector 16 percent, distribution and trade 17 percent and the remainder 20 percent. As agriculture comprises such a large proportion of the GDP and given the close dependence of Ethiopian agricultural production on rainfall, the fluctuations in the total GDP have a strong correlation with those of annual rainfall. Agricultural products form 71 percent of the total value of exports in 1991/1992, with coffee contributing between 32 percent in 1975 to 71 percent in 1985/86. Thus Ethiopia’s foreign exchange earnings are highly dependant on a volatile internationally traded crop.
Since 1991 the government has been dismantling many of the instruments of the previous centralized Marxist oriented economy. Crop and wood price controls and marketing have been abandoned, and inter-regional trade liberated. Many state owned enterprises are in the process of being privatized, although the state farm sector is still largely intact. The new Forest Proclamation (Proclamation 94 of 1994) has provisions for state and private forests. Whilst land continues to be owned by the state, current peasant land user rights and crop and tree disposal rights have been guaranteed. The Investment Proclamation (Proclamation 15 of 1992) allows commercial investment in agriculture on lands which are not occupied by peasant farmers or pastoralists. In the past three years medium to large scale commercial agricultural development has commenced in two localities of the Project Area, in Sagen Valley in South Omo Zone of the Southern Ethiopian Peoples’ Region (SEPR), and in the Gibe Valley of the Jima Zone of the Oromiya Regional State.
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2.2 The Natural Resource Base
The Ethiopian highland plateau is divided by the Great African Rift Valley into the Eastern and Southeastern Highlands, and the Northern, Central and Southwestern Highlands. The Lowlands are found below 1,700 masl in the west and approximately 1,300 masl in the east. Rainfall generally increases with altitude upto about 3,500 masl where it decreases. Temperature is inversely related to altitude, with mean annual temperatures of 22°C to 27°C in the Lowlands and between 10° to 22°C in the Highlands upto about 3,000 masl. Above 2,600 masl frost occurs during the dry season in valley bottoms with increasing frequency with altitude.
Ethiopia's arable land (ie. areas with more than 90 days growing period and suitable soils - excluding Vertisols) has been estimated2 at 34 million hectares (or 27 percent of the total area), with an additional 7 million hectares of arable land (or 6 percent of total) if Vertisols are included. Arable land on steep slopes (ie over 30 percent) adds another 6 million hectares (or 5 percent of total) bringing the total area of potentially arable land to 47 million hectares (or 38 percent of total). There are an additional 16 million hectares (or 13 percent of total) of marginal arable land (ie. soils are suitable but the growing period is between 60 and 90 days).Relative biomass productivity has been estimated 3 using a climatic index of productivity based on radiation, temperature and moisture. The highest values are found in the Southwest Highlands and decrease towards the Lowlands (with increasing aridity) and the high mountains (with lower temperatures). Optimal biomass productivity is found at altitudes of between 2,000 to 2,700 masl.
The natural (ie. undisturbed) vegetation patterns are closely related to patterns of rainfall and temperature, with local variations due to soil and drainage factors. Dry coniferous (Juniper and Podocarpus) montane forest is found in the Northern, Central and Eastern Highlands with evergreen scrub or woodland on the steep slopes and shallow soils of the Eastern Escarpment. Where there are extensive areas of poorly drained soils, natural grassland occurs. In the wetter areas of the southern Bale Mountain Massif, and in the southwest Highlands a mixed broadleaf montane forest occurs, with increasing species diversity to the west. The woodlands can be divided into the Acacia-Commiphora woodlands of the drier eastern and southeastern Lowlands and a broadleaf Combretum- Terminalia woodland found in the wetter areas of the eastern and southeastern Lowlands and throughout the moist western Lowlands. Above about 3,200masl Afro-alpine and sub- afro-alpine vegetation occurs in a combination of giant herbs and shrubs, succulents and
2 Ministry of AgricultureAJNDP/FAO (1988). NB. These estimates include Eritrea.
3 National Meteorological Services Agency (1989)
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2.3 The Natural Resource Sectors
2.3.1 The Agricultural Sector
The main components of Ethiopian agriculture are food crops, industrial crops, export crops, livestock and livestock products. The main food crops are tef, wheat, maize, barley, sorghum, enset, root crops, pulses, oil crops, fruit and vegetables. The total area under food crops4 is 7.1 million hectares with a total production of 7.5 million tons. Coffee is the main export crop and cotton is the main industrial crop. Tea and tobacco are grown mainly for the domestic market. The total livestock population comprises 26 million cattle, 24 million sheep, 18 million goats, 7 million equines and 1 million camels. According to data collected by the Central Statistical Authority total livestock numbers have remained- relatively constant between 1981/82 and 1991/92 with year on year changes caused by and occilations in rainfall, thus livestock feed.
The largest sub sector is the smallholder (peasant) mixed farming systems of the Highlands with cereal, pulse and oil seed production in the northern, central and eastern highlands, and enset, root and cereal production in the southern and southwestern Highlands. The subsector cultivates some 5.8 million hectares ( 96 percent of the cultivated area) and accounts for some 6.7 million tons of crop production ( 95 percent of total). Two thirds of the total livestock population are located in the Highlands. Livestock are mainly kept for draught purposes in the cereal areas and milk production in the enset areas. Everywhere livestock are a store of wealth. The enset-root systems tend to be the most integrated in terms of inputs and outputs, with a high proportion of crop residues as livestock feed and as manure for the enset and root crops. Coffee is an important cash crop below 2,000 masl in the eastern, southern and southwestern Highlands. Chat is also an important cash crop in the eastern Highlands, and increasingly in the other coffee production areas.
In the tsetse infested western Lowlands where cattle production is largely precluded, a form of extensive bush fallowing cultivation, based on sorghum and maize is found. In the southern, southeastern and eastern Lowlands there are agro-pastoral and pastoral systems of extensive livestock production, Agro-pastoralism (ie. extensive livestock production with a major reliance on crop production) is practiced on the higher and wetter lowlands in southern Ethiopia (e.g. by the Hamer). With increasing population
4 Central Statistical Authority (1987) Statical Abstracts for 1988/1989
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In 1989 the State Farms cultivated some 201,000 hectares. This accounted for approximately 5 percent of the total crop production. They were also responsible for most of the cotton, tobacco and tea production.
2.3.2 Forestry Sector
The main components of the sector are industrial timber, poles, construction poles, fuel wood, charcoal and tree products, in particular gums and resins (incense and myrrh). Production estimates for 1992/19935 are as follows:
Table 2.T Wood Products 1992/1993 Type Unit Production
Industrial timber M2 43,405 Poles No 30.014 Construction poles M2 24,739 Fuel wood M2 70,796 Charcoal ton 3,238
Some 2,067 tons of gums and resins were harvested, 65 percent being consumed within the country, the remainder being exported. These official figures do not include timber'and poles produced and used outside the official marketing structures, in particular, for domestic use in rural areas.
The latest estimate of the remaining area of closed high forests6 is 4,120,000 hectares or 3.37 percent of Ethiopia. The extent of human-made forests has been estimated as 42,124 hectares of peri urban fuel wood plantation, 18,706 hectares of industrial timber plantation and 44,634 hectares of Community Woodlot.
5 Source: National Policy on the Resource Base, its Utilization and Planning for Sustainability (National Conservation Strategy) Volume I: May 1994.
6 Ethiopian Forestry Action Programme: Final Report (1994)
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2.3.3 Energy Sector
Table 2.2 indicates the disproportionate role played by biofuel resources in the national energy supply of Ethiopia, constituting over 92 percent of the total energy supply. Of this fuel wood provides 77 percent.
Table 2.2 Energy Supply in Ethiopia 1992/93.7 (a) Primary Supplies Fuel wood Dung Crop Bagasse Residues Teal 125,083 14,117 12,026 1,683 % Energy 75.2 8.5 7.2 1 b. Secondary Energy Charcoal Electricity Oil products Teals 1,805 2,662 8,854 % 1.1 1.6 5.3
The proportions of total energy consumption by sector is shown in table 2.3
Table 2.3 Energy Consumption Patterns 1992/93 Teals % Agriculture: • 204 0.1 Industry 8,395 5.1 Transport 5,732 3.5 Public & Commercial 6,406 3.9 Households 145,472 87.5 Total 163,072
Households clearly dominate the energy consumption patterns with 88 percent of the total, followed by industry with 5 percent, transport 4 percent and the remaining sectors of agriculture, public and commercial and other making up the remaining 3 percent. Within the households, traditional fuels (fuel wood, dung and residues) contribute a massive 99.6 percent of the total household energy consumed. This is divided between fuel wood (81 percent), dung (9 percent), crop residues (8 percent) with modern fuels contributing the remainder. Of the modern fuels, kerosene has the largest share (48 percent), electricity next with 36 percent, Ipg 10 percent and diesel oil 6 percent. Per capita consumption was estimated at 2.69 Gcals per year, or 756 kgs of fuel wood equivalent.
7 UNDP/ESMAP (1995) Ethiopia: Energy Assessment, joint UNDP/World Bank Energy Sector management Assistance Programme.
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In the industrial sector traditional fuels contribute 85 percent which reflects the relative importance of cottage industries. The breakdown of traditional fuels is similar to the household sector with a slightly higher proportion of fuel wood (88 percent) with dung at 6 percent and residues 6 percent. Modern fuels contribute 18 percent divided between fuel oil (58 percent), electricity (25 percent) and diesel oil (12 percent).
Examining consumption patterns between rural and urban settlements, households in rural settlements account for 95 percent of the total energy consumed with rural cottage industries making up the remaining 5 percent. Modern fuels contribute only 0.42 percent of energy consumption in rural settlements, compared with 45 percent in urban settlements. Although charcoal is rarely used in rural settlements, because of their very large number compared to urban settlements, consume 30 percent of total charcoal production. Despite the inroads made by modern fuels consumed by urban settlements, fuel wood still constitutes 47 percent, charcoal 6 percent and dung and residues 6 percent of energy consumed.
In terms of regional consumption patterns, the per caput consumption of total energy varies only by 15 percent above and below 2.99 Gcals per year (or 790 kgs of fuel wood equivalent). There are however marked regional differences in the consumption of modern fuels with 5 of the old kiflehager ("provinces) consuming 85 percent of the total and the remaining 11 kiflehager with 61 percent of the population consuming the remaining 15 percent. Addis Ababa alone accounts for 40 percent of the consumption of modern fuels.
2.3.4 Population and Food Supply
2.3.4.1 Population numbers, trends and patterns
A new population census was conducted in October 1994 but the results have not yet been published. Resource must therefore be made to the previous census conducted in 1984. The estimated 8 1995 population for Ethiopia (excluding Eritrea) is 56.88 million with 85 percent residing in rural areas. The present annual growth rate is estimated at 2.9 percent which if maintained means the population will double in 24 years. Some 46 percent of the population is under 14 years, so that even if birth rates start to fall there is an in-built capacity to maintain current growth rates for some time. The overall population density is approximately 45 persons per sq. km. Spatial patterns vary with 80 percent of the population concentrated on the Highlands - one third of the area. The highest population densities are found in the enset land use systems where densities can reach as high as 800 persons per km2 in individual Peasant Associations.
8 Population Estimates of Regions, Awrajas, Weredas and Towns - 1992. Statistical Bull. 101, September 1992: Central Statistical Authority, Addis Ababa.
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2.3.4.2 National Food Balances and Trends
A recent study of famine in Ethiopia9 has examined the food production trends and availability in Ethiopia over the past three decades. Per caput cereal production has been declining since about 1965 by some 4 kgs per year, although there has been inter-annual fluctuations, largely as a result of variations in rainfall. Similar trends have been shown for per caput cereal availability which has been declining at 3.3 kgs per year and the per caput availability of all foods (cereals, pulses and roots) which have been declining at 2.7 kgs per year. Because of food imports, food aid and stock draw downs, the inter annual fluctuations for food availability are much less than those for cereal production. During the 1980's and 1990's the gap between cereal production and cereal availability has widened, a clear indication of an increasing structural (ie. permanent) food deficit, which is increasingly being met by the imports mentioned above. By 1991 food aid had reached 1 million tons and remained just below that level in 1992.
The main deficit areas are located in the areas of low and highly variable rainfall. These are the northern Highlands and the lower altitudes of the eastern, southern, and southwest Highlands and their adjoining Lowlands. However only the high rainfall areas in the southwest Highlands might be said to be almost totally immune from drought.
2.4 Policy Framework and National Strategic Programmes
2.4.1 Policy Framework and National Strategic Programmes
The country’s long term economic development strategy is termed Agricultural Development-Led Industrialization (ADLI). The goal of the strategy is to achieve rapid and sustainable economic growth by improving the productivity of the agricultural sector and by building up an agriculturally based industrial sector, which is labour intensive and utilizes local raw materials. The ADLI strategy focuses primarily on agricultural development to be attained through improved productivity of peasant agriculture and the establishment of large scale commercial agriculture, particularly in the lowlands.
Three stages of peasant agricultural development is envisaged with stages 1 and 2 taking place in the short and medium term. Stage 1 involves the improvement of existing crop and land husbandry practices and techniques, whilst stage 2 comprises the development of agricultural infrastructure such as small scale irrigation, and the introduction of fertilizers and agro-chemicals. Stage 3 is a long term strategy which envisages increasing farm sizes which will occur as the population moves out of agriculture into non-agricultural activities.
9 Patrick Webb, Joachim von Braun and Yisehac Johannes (1992)
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The National Population Policy was issued in April 1993 and aims at closing the gap between high population growth and low economic productivity, through a planned reduction in population growth, combined with an increase in economic returns. With specific reference to natural resources, the Population Policy had the following specific objectives:
i. Making population and economic growth compatible and the over exploitation of natural resources unnecessary.
ii. Ensuring spatially balanced population distribution patterns, with a view to maintaining environmental security and extending the scope of development activities.
iii. Improving productivity of agriculture and introducing off-farm non-agricultural activities for the purpose of employment diversification.
iv. Maintaining and improving the carrying capacity of the environment by taking appropriate environmental protection and conservation measures
The National Policy o f Women was issued in March 1993 and stresses that all economic and social programmes and activities should ensure equal access of men and women to the country's resources and in the decision making process so that they can benefit equally from all activities carried out by the central and regional institutions.
The Constitution was approved by the Constituent Assembly in December 1994, and among the many items it addressed, the following of are relevance to this report:
i. Maintains land under the ownership of the Ethiopian people but protects the security of usufructuary tenure;
ii. Reinforces the devolution of power and local participation in planning, development and decision making.
iii. Ensures equality of women with men.
iv. Ensures the appropriate management as well as protection of the well-being of the environment.
v. Maintains an open economic policy.
The National Policy on Natural Resources and the Environment - the National
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Conservation Strategy - was presented in May 1994. It provides an umbrella strategy for the conservation and sustainable development of the country’s natural resources and environment. It comprises 11 cross-sectoral and 11 sectoral sets of policy objectives, principles and strategies. The following were the strategies for the development and conservation of biomass energy resources:
i. Ensure that energy plans adequately address fuelwood requirements;
ii. Link the implementation of energy policies and strategies more closely to the implementation of policies and strategies on agriculture and forestry, as well as on biomass and renewable resources;
iii. Focus extension programmes on farm and homestead tree planting to ensure that each homestead grows enough trees to satisfy its wood requirements;
iv. Set aside land for long-term leases for private sector woodlots, especially in peri-urban areas;
v. Boost technical and social research on the design of improved cooking stoves;
vi. Promote local manufacturing and distribution of improved charcoal and biomass stoves; and
vii. Locate, develop, adopt or adapt energy sources and technologies to replace biomass fuels.
The Ethiopian Forestry Action Programme was presented in December 1994 and contains 8 major Action Programmes each with its own set of sub-programmes. These are briefly outlined below:
TREE AND FOREST PRODUCTION PROGRAMME - Industrial Plantation Forestry - Peri-urban Plantation Development - Community Woodlot Development - Protection Forestry Development - Farm Forestry Development - Minor Forest Products Development
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FOREST RESOURCE AND ECOSYSTEM MANAGEMENT PROGRAMME - Natural Forest Management - Woodland Management - Ecosystem Management
FOREST INDUSTRIES DEVELOPMENT PROGRAMME
WOODFUEL ENERGY EFFICIENCY DEVELOPMENT PROGRAMME
TECHNOLOGY DEVELOPMENT AND DISSEMINATION PROGRAMME
SECTORAL INTEGRATION PROGRAMME
PLANNING AND MONITORING AND EVALUATION PROGRAMME
HUMAN RESOURCES DEVELOPMENT PROGRAMME
2.4.2 Institutional Framework
With the change in government in 1991 came a new administrative structure based on the different nationalities within Ethiopia. Some 14 Regional States have been established, although five of these formed themselves into the Southern Ethiopian Peoples’ Regional State. The Regions are also referred to by numbers, the full list of which is as follows:
Tigray Region (1) Afar Region (2) Amhara Region (3) Oromiya Region (4) Somali Region (5) Beni-Shangul Region (6) Southern Ethiopian Peoples Region (7,8,9,10 and 11) Gambela Region (12) Harer Region (13) Addis Ababa Region (14)
Most regions have been subdivided into Zones to facilitate administration, although these are not political entities. The main administrative unit within the region is the wereda, with the Farmer’s Association or kebelle as the lowest rural and urban unit of administration
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At the Regional level most central government ministries are mirrored as “Bureaus". The two key ministries of concern to the Project are the Ministry of Mines and Energy, and the Ministry of Agriculture and their respective Bureaux in the Regions
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CHAPTER III THE PROJECT AREA
3.1 The Physical Environment
3.1.1 Location and size
The Project Area is located in southwestern Ethiopia, to the west of longitude 42° east, and south of latitude 10° north. This gross “working” area of 443:000 Km2, includes 6,316 km2 of water, 18,588 km2 of National Parks and 2,614 krr? of State Farms. Some 40,482 km2 has not been surveyed by the project leaving a net area of approximately 375,000 km2
3.1.2 Relief and geology
The three main relief units in the Project Area are: - the highlands - the Rift Valley - the lowlands
The Great Rift Valley bisects the highland plateau. In the east are the highland plateaus of East Harerge, Arsi, Bale and Sidama lying between 1,800 and 2,600 masl. Rising above the plateaus to altitudes exceeding 4,100 masl are the mountain massifs of Mounts Chilalo, Kaka and Batu. To the east and south of the highlands are the dissected lowlands of the Wabe Shebelle, Genale and Dawa river basins; to the north are the Afar Lowlands whilst to the west is the Rift Valley.
To the west of the Rift Valley are the Central Highland plateaus of North and West Shewa and the Southwest Highlands lying between 1,700 and 2,600 masl. . Rising above these plateaus up to 4,000 masl are the Gurage Mountains in West Shewa, and the Chencha Mountains in North Omo. To the north the plateau is deeply dissected by the Abay River and its south bank tributaries. In the west the highlands fall steeply to the Western and Gambela Lowlands. In the central parts and southern the plateau is deeply dissected by the Omo river and its main tributaries of the Gibe and Gojeb.
The main blocks of highland are underlain by great thicknesses of Tertiary Trapp basalts, with localized areas covered by recent volcanic ashes and tuffs, particularly in the Rift Valley. In the Lowlands of the Wabe Shebelle, and Genale rivers, there are extensive outcrops of Cretaceous limestones and sandstones. In the west these formations
VOLUME III. STRATEGIC PLAN Page 14 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT are only found in the deep gorges of the Abay and its tributaries. In the western part of the highlands in Welega and the Western, Gambela and Southern Lowlands are extensive outcrops of the Basement Complex of igneous and metamorphic rocks. Extensive alluvial and colluvial deposits of recent origin occur In the lower Rift Valley and in the valleys of the Sagen, the Omo, the Baro and the Akobo rivers.
3.1.3 Agro-Climate
The pattern of mean annual rainfall in the Project Area closely mirrors the main relief units: with high rainfall (more than 750 mm) associated with the eastern, central and southwestern Highlands, and lower rainfall with the western, southern and southeastern Lowlands. The highest rainfall is found in the southwestern Highlands where it exceeds 2,000 mm, and the lowest in the lower valleys of the Omo, Dawa, Genale and Wabe Shebelle rivers where it falls below 300 mm.
The project area experiences three main rainfall regimes. In the southwest Highlands, and in the Gambela, western and Abay Lowlands, a uni-modal pattern prevails with a single rainy season varying in length from 3 to 8 months between March and October. The season is longest in the southwestern Highlands of lllubabor and Kefa, and shortest in the Abay Lowlands. A bi-modal rainfall pattern is found in the Rift Valley as far south as Arba Minch, extending north along the North Shewa Highlands and east along the Arsi and Herege Highlands. A highly variable and short rainy season (belg) occurs in March-April and the main rainy season (mehr) in June-September. A second bi-modal pattern is found across the southern and southeastern Lowlands and the Bale Highlands, with either two rainy seasons of equal length or, more generally, a longer and more secure season in March-May and a shorter and more variable season in October-November.
There is a strong correlation between temperature and altitude, and 10 temperature zones have been recognized10 based on altitude. These have been placed into five groups of agronomic importance:
Group Temperature Mean orowinq season Altitude Zone temperature (°C) (masl)
1 1 -3 more than 20° less than 1,700 2 4 - 5 17.6° -20.0° 1,700 -2,200 3 6 - 7 12.6° -17.5° 2,200 - 3,000 4 8 10.1° - 12.5° 3,000 - 3,400 5 9 - 10 less than 10.1 ° more than 3,400
10 MOA/UNDP/FAO (1986)
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Below 1,700 masl in temperature zones 1-3 temperate, cereals are not generally grown. Temperature zones 4-5 are an important temperature “window” for coffee and are the zones where maize and sorghum are the dominant cereals. In zones 6-7 barley, wheat and tef are the dominant cereals, whilst in zone 8 only barley is possible. Zones 9-10 are sub-afroalpine and afro-alpine zones where no cereals can be cultivated. Temperature and rainfall have been combined into a system of agro-climatic zones11 which have been used by the project to determine its forest inventory sampling pattern.
3.1.4 Soils
Soils types and patterns are largely influenced by the parent material, the weathering-leaching regime, local land forms, and human interference. The FAO classification 12 has been followed, as this system is in current use by the Ministry of Agriculture.
In the highlands, soils are derived from basalt parent material, the predominant thermal zones are 4 to 7 and mean annual rainfall generally exceeds 900 mm. This gives rise to a high weathering and leaching regime and high rates of organic matter accumulation. Soils are generally freely drained red clay loams of moderate fertility, though deficient in phosphorous. On less steep slopes Nitosols are the most prevalent, but these grade into shallower Luvisols and more leached Acrisols on steep slopes. Where slopes are gentle to flat, heavy black cracking clays (Vertisols) develop. At higher altitudes (above 2,600 masl) formation of the clay mineral allophane results in the formation of soils of great structural stability (humic andosols). A similar development of allophane in the Rift Valley leads to the development of soils of lower stability and which are often sodic (vitric Andosols). In the high rainfall (ie. above 1,500 mm) areas of the Southwest Highlands excessive leaching of bases occurs and acid soils of low fertility result (eutric Nitosols).
On the Basement Complex rocks of the western part of the highlands in Welega, and in the western, southern and southeastern Lowlands, there are red coarse acid soils of very low fertility. The temperature zones are 2 and 3, and mean annual rainfall varies between 600 to 1,000 mm. The weathering-leaching regimes are moderate, but when the organic cycle is interrupted, mineralization of organic matter can be very rapid. On the more gentle slopes dystric Nitosols occur, with Luvisols and Acrisols on the steeper slopes. Because textures are lighter, structural stability, poor and organic matter mineralization rates high, these soils are more prone to degradation and erosion that basalt derived soils in the highlands.
11 SCRP (1987)
12 Soil types in brackets refer to the FAO Soil Classification: see MOAAJNDP/FAO (1986)
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In the southeastern Lowlands the parent material is Cenozoic limestones, sandstones and evaporites and Basement Complex gneisses On the Cenozoic parent materials where rainfall is above 700 mm Nitosols are found grading into Cambisols towards the drier areas. Below 700 mm annual rainfall, and where slope gradients are low Xerosols and Yermosols are widespread. Weathering rates are very low, and soils, on even slightly increased gradients, are very shallow. Along the main rivers saline Fluvisols are found.
In the lower Omo and Gambela Lowlands where there are extensive areas of alluvium and colluvium on very shallow to flat slopes, black cracking clays (Vertisols) develop. Where there are sites which receive water and where evaporation rates are very high, saline and sodic soils (Solonchaks) occur.
3.1.5 Land Cover and Vegetation
Although much of the original vegetation or land cover of Ethiopia has been altered or destroyed, the project area has been less affected than the northern and eastern parts of the country. The following nine land cover types have a broad correlation with temperature and rainfall:
Afro-alpine and Sub-afro-alpine ii. High forest iii. Woodland iv. Bushland V. Shrub land vi. Grassland vii. Bamboo viii. Wetland ix. Bare land
Afro-alpine and Sub-afro-alpine: Four of Ethiopia’s eight mountains over 4,000 masl are located in the project area, together with four others over 3,500 masl. Sub-afro-alpine vegetation occurs with Erica woodland and scrub between about 3,300 and 4,000 masl. Afro-alpine vegetation commences at about 4,000 masl, and is represented by tussock grasslands, Helichrysum scrub and isolated Lobelia rhynchopetala.
High Forests: A forest is a closed stand pf trees with an interlaced canopy, rising to 40 m or more in height. Five types of natural forest occur in the Project Area: montane broadleaf (with more than 80 percent broadleaf species), montane coniferous (with more than 80 percent coniferous species), montane mixed, lowland semi-evergreen and riparian
VOLUME III. STRATEGIC PLAN Page 17 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT forest. Forests are basically evergreen or semi deciduous, only being leafless for a short period and then not simultaneously for all species. Where this occurs for long periods vegetation is classified as deciduous woodland. Detailed descriptions of the various forest types can be found in Annex 2.
Woodland: Woodland is a continuous stand of trees with a maximum height of not more than 20 meters, although emergents may exceed this, and a crown density of between 20 and 80 percent. Under the layer of mature trees there may layered understories of immature trees, bushes and forbs. Two major floristic types occur: Combretum-Terminalia woodland of broadleaf trees is usually found in the wetter areas of the southern, Gambela, western and Abay Lowlands, and Acacia-Commiphora woodland of small leaf trees in the drier areas. A degraded form of dry Juniperus forest occurs on steep slopes and shallow soils and might be more accurately described as woodland or even bushland
Bushland: a bush is defined as a one stemmed woody plant with low branching: ie. many branches starting from the stem within a height of 50 cms from the ground, and having no potential to become a tree. Bushland is a continuous stand of bushes with a crown density of between 20 and 100 percent. There may be an under storey of shrubs and grasses, and there may also be scattered individual trees with a crown cover of less than 20 percent or scattered clumps (ie. less than 0.5 hectare) of trees.
Shrubland: a shrub is a multi stemmed woody plant. Shrubland is a continuous stand of shrubs with a ground cover of more than 20 percent. There may be a grass/forb layer and also scattered bushes and/or trees or trees /bushes in scattered clumps (less than 0.5 hectare).
Grassland: Grassland is dominated by grasses and occasionally other herbs, with trees, bushes and/or shrubs.
Bamboo: There are two species: highland bamboo (Arundinana alpina) which occurs in the montane forests, and lowland bamboo (Oxytenanthera abyssinica) which occurs below 1,500 masl in the moist western Lowlands.
Wetland: Three types of wetland have been identified: open water, perennial swamp or marsh and seasonal swamp or marsh. The most extensive areas occur in the Gambela Lowlands and around some of the lakes in the Rift Valley
Bare Earth: Three types of bare earth have been identified, bare rock, salt flats and exposed soil or sand.
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Within the project area, the areas and proportions of the various land cover types (which excludes cultivated land - see foot note 1) are as follows:
Area (km2) % Afro-alpine and Sub-afroalpine 1,646 5 High forest 43,066 14 Woodland 104,929 35 Bushland 89,355 30 Shrub land 14,487 5 Grassland 40.476 13 Wetland, Lakes 6,316 2 Bare land 877 0.3
3.2 Land Use Systems
3.2.1 Term inology and Rationale
The Project uses the Land Use System as a basis for its analysis of the key strategic planning themes, in particular for its analysis of the supply and consumption of woody biomass. A Land Use System is identical in concept to a “farming system” or a "pastoral system” but is applied to all types of land use With respect to strategic planning: it is important that woody biomass be treated as an integral part of the land use system.
Land use systems can be defined and mapped on the basis of their agro-ecological conditions, their crop, livestock and tree production components, and their socio-cultural and economic characteristics. These systems may have developed over decades or even centuries, in response to the natural environmental conditions, as well as to socio-cultural and economic factors. The concept is sufficiently flexible to accommodate land use systems in the state sector such as National Forest Priority Areas, State Farms’ and National Parks. All land use systems are in the process of dynamic change in response changes in population, and their demands on natural resources, as well as in the natural, socio-cultural and economic environment.
The Land Use Systems of Ethiopia have been divided into two main sectors: the Communal Peasant/Pastoral Sector which is the largest, and the State Rural Sector. The Communal Peasant/Pastoral Sector has been sub-divided into the following major systems:
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1. Agricultural Systems: - Cereal Systems - Enset-root Systems - Shifting Cultivation or Bush Fallowing Systems without Livestock
2 Agro-Pastoral and Pastoral Systems
- Agro-pastoral Systems with Sedentary Cultivation - Agro-pastoral Systems with Shifting Cultivation - Pastoral Systems with little or no Cultivation
The State Sector has been sub-divided as follows: - National Forest Priority Areas (NFPA) - State Industrial Tree Plantation and Peri-Urban Fuel Wood Plantations - State Farms and Ranches - Wildlife Conservation Areas: National Parks and Wildlife Sanctuaries
In some cases there can be an overlap between two systems: e.g.. a National Park and an NFPA, and at least one State Farm has been converted to a State Industrial Wood Plantation. Except for the Awash National Park none of the six other National Park in the Project Area have been gazetted. At present not one of the NFPA’s has legal status under the new Forestry Proclamation.
3.2.2 The Communal Peasant/Pastoral (Private) Sector
3.2.2.1 Cereal Systems:
The main distinguishing feature of these systems is the production of nearly all crops from seed. The crops are mainly cereals and some pulses and oil seeds, with root crops of little or no importance. Perennial crops such as coffee and chat are important in some cereal systems (particularly in Welega and East Harerge). Most systems depend on draught power and the plough (maresha) although the hoe may still be found in South Omo, and in the wurch zone of the Sidama Highlands. Within the Project Area five main cereal systems have been identified:
i. Systems in the Arsi and Bale Highlands li. Systems in the Central Rift Valley iii. Systems on Vertisols in the central Highlands iv. Systems on Non Vertisols in the Central and Western Highlands v. Systems in the southeastern and southern Lowlands and the Southern Rift Valley
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The systems in the Arsi and Bale Highlands are on poorly drained Vertisols and Chernozem soils, except on the slopes of Mount Chilalo. They comprise are one of the three main surplus cereal producing areas in Ethiopia (with Central Shewa and Gojam). In Bale two crops are grown. The principle crops are wheat, tef and barley Cattle are an important component in the farming system. There is considerable movement of livestock between the Highland and Lowlands, with Highland cattle moving to the Lowlands during the rainy season and the Lowland cattle upto the Highlands in the dry season It is likely that the original natural vegetation on these poorly drained plains was grassland, and they remains largely treeless today.
In the Central Rift Valley the dominant cereal is maize with some tef The proportion of tef is influenced by the quality of the short {belg) rains: if they are on time the proportion of maize is high, but if they are late or poor then the proportion of maize drops and tef increases. Sorghum is not grown because of the heavy bird challenge: particularly from migrant birds passing through the Rift Valley southwards, when the sorghum would be heading. Cattle are still very important (decades ago the inhabitants were agro- pastoralists), particularly in the drier areas around the lakes. Elsewhere the livestock assets per household are declining because of the increasing shortage of grazing land. The natural woodland vegetation (still to be seen in the Arbonozer Ranch) is fast disappearing, although farmers retain scattered trees (though heavily pollarded) in their fields.
The cereal system farmers • on the Vertisol plains in the central Highlands of Central, West and Northwestern Shewa and in East Welega have adapted their cropping practices to these poorly drained and difficult to mange soils. These are now some of the highest cereal producing areas of Ethiopia. Tef is the main crop which can withstand waterlogged conditions. Other crops such as wheat, sorghum and horsebean are grown on narrow (about 10 cms wide) didaro ridges, and planted just before the end of the rains. Chickpea is planted just at the end of the rains in the furrows between the ridges. All Crops mature on the residual soil moisture. Along the floodplain of the Awash River a specialized form of flood retreat cultivation of chickpea and lentils on residual soil moisture is practiced. Livestock and cropping are well integrated, with crop residues comprising upto 80 percent of total livestock feed. The plains are largely treeless, although in some areas farmers have retained scattered trees in their fields, though these are heavily pollarded.
The cereal systems on the non-Vertisols in the central Highlands and the Highlands of East and West Welega are based on maize and tef up to about 2,600 masl, with wheat and barley dominating above this altitude. Below 2,000 masl coffee is an important cash crop. Valley bottoms are cultivated in the dry season for maize, potatoes and onions, using the watertable for moisture. Soil fertility is maintained on the low infertile granite soils of Welega by moving the night cattle byre over the croplands. In many areas there are still
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200 TLU’s per km2 Cattle are kept for manure and milk, but also as a store of wealth (from sales of coffee). There are many scattered trees from the original high forest, but these are not as dense as those in Kefa. Further north and into Welega these decrease markedly, indicating the much longer period of settled agriculture. In Welega forest remnant patches are very rare, and in the most densely populated areas scattered trees in the landscape are becoming very sparse.
3 2.2.3 Shifting Cultivation Systems
Below 1,700 masl in the Abay, Western, Gambela, North and South Omo Lowlands, and in the river valleys of the Gojeb, Gibe and Didessa rivers shifting cultivation is practiced with bush fallowing of varying periods. In the Gojeb, Gibe and Didessa river valleys, this may be adventitious cultivation by Highland farmers on a temporary basis The most widespread systems are in the Abay and western Lowlands practiced by the Gumuz people. Sorghum and finger millet are planted as a mix in the main fields, and undersown with beans, pumpkin, gourds and cabbage. Sesame, cotton and ginger are planted in separate fields. In the household garden, sorghum, cabbage, pumpkin, gourds, yam, maize, peas and beans are intercropped. Although the areas are infested with tsetse a few cattle are maintained for milk and meat, but working draught oxen is impossible. Land preparation is with a bamboo digging stick and the hoe.
West of the Dabus river the Beta people cultivate sorghum, tef and chickpea. On the Baro river plains the Anuak people cultivate the alluvial terraces, double cropping maize and beans with a single crop of sorghum. Below the Kefa Highlands the Mekan cultivate sorghum, beans and tobacco. In the high forest on the escarpment overlooking the Gambela Lowlands, the Majangir (Masongo) people practice a sophisticated system of weed mulching and bush fallowing. The use of the mulch to suppress weed growth extends the period of cultivation by some 2 to 4 years. The main crop is sorghum, with yams, pumpkin and gourds planted in suitable micro sites within the sorghum. On the oldest, and thus most infertile fields, sesame is cultivated, and on the most fertile sites along rivers and streams maize is cultivated in almost permanent fields.
Bush fallowing is required on the Basement Complex soils because of their inherent infertility, and the high mineralization rates of the organic matter which follow their cultivation. Fields are probably finally abandoned because of excessive weed infestation, rather than infertility - a problem which the Majangir appear to have partially solved. Hunting by extensive bush burning is practiced throughout these Lowlands These practices are adversely affecting the Lowland Evergreen Forest in the Gambela Lowlands, and the forest was reported to be retreating even thirty years ago. However it has been
VOLUME III. STRATEGIC PLAN Page 24 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT tubers (yam: taro and sweet potato), tobacco and fruit trees are grown in the household garden, or an enclosed in-field next to the homestead. In unenclosed outfields, cereals are cultivated: maize, tef and sorghum below and wheat and barley above 2,600 masl. Livestock densities are very high, but production is very intensive, with tethered grazing and stall feeding universally practiced. Communal grazing areas have been almost totally converted to cropland, except in parts of the Gurage Zone where extensive areas remain. A major distinguishing feature of these systems is the extensive system of hedges, and the planting of trees along field boundaries and in small woodlots. These pre-date the Land Reform of 1974, although the process of enclosure using live hedges has accelerated in the past four years. In Sidama a great many scattered trees from the original high forest remain in the farmland, particularly to the south and east of Dila.
Enset as a co-staple crop with cereals and tubers is found in Wollaita (in Sidama Zone), the Amaroo Mountains east of Lakes Abaya and Chamo, the North and South Omo Highlands, and throughout the Kefa Highlands (where it appears to have replaced Westphall's “Tuber Dominant” system). The tuber and cereal crops are the same as those in the previous systems. However cassava has spread through the area over the past 10 years, following its introduction after the 1984/845 drought In the Amaroo Mountains enset is sometimes irrigated, whilst in the Chencha Highlands manure slurry is directed straight into the enset garden from the cattle stall under gravity. In the North and South Omo Highlands, extensive stone terrace systems similar to those of the Konso are found Coffee is only important in the Kefa Highlands.
Cattle densities are high -125 to 215 TLU’s per Km2 - and husbandry very intensive with tethered grazing and stall feeding. Cattle are kept for manure and milk. In many areas the digging fork is still used, particularly for preparation of the enset garden and in-fields. In the out-fields the maresha plough is increasingly being adopted. In the very high rainfall areas of Kefa, bush fallowing is practiced with 4 to 5 years cropping followed by 2 or more years fallow. In Wollaita and the North and South Omo Highlands, the dense network of live hedges is either poorly developed or absent. Trees (mainly Eucalyptus) are planted along some field boundaries and in woodlots. Indigenous trees are sparsely scattered throughout the landscape. In Kefa many scattered trees from the original high forest remain in the fields. On the expanding edge of cultivation many scattered patches of high forest, some of considerable extent, are found on the steeper slopes and valleys.
The third major system where cereals are the dominant staple crop, with enset relatively minor and tubers hardly at all, occurs through lllubabor and into East Welega where it merges imperceptibly with the cereals systems on non-Vertisols of the Central Highlands. Maize and tef with some sorghum are the main crops, being replaced by wheat and barley above 2,6000 masl. Coffee is an extremely important cash crop below 2,200 masl. Land preparation is with the plough. Livestock densities are high - between 100 and
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scattered patches of woodland and bushland and even high forest, although in the heavily populated areas these are fast disappearing.
The cereal systems of the southeastern and southern Highland/Lowland edge and in the Southern Rift Valley, are based on sorghum with some maize. The systems in the southeastern and southern Lowlands are transitional between the agro-pastoral systems of the Lowland Oromo and the Borena. Cattle are still very important, and as in the Arsi and Bale Highlands, there is considerable cattle movement between the Highland and Lowlands. The consequence is that much of this area is overgrazed by both Highland and Lowland cattle. The systems in the Southern Rift Valley are distinguished by their intricate and massive stone terraces, the very efficient water harvesting structures and the use of simple but effective sorghum contour trash lines on the steeper slopes. A wide variety of sorghum varieties are cultivated. Livestock are not as important in these systems as they are in the Lowlands to the east of the Rift Valley.
3 2.2.2 Enset-roots Systems
These systems are found in the southern and southwest Highlands between 1,600 and 3,000 masl. Production of enset is from suckers, which are separated from a corm 1 to 3 years after it has been specially planted for the purpose. After separation, the suckers are transplanted and left for 1 to 2 years. They are then transplanted again into a permanent plot where maturation takes 3 to 5 years, depending on the altitude. Spacing is generally 2 to 3 meters apart. Harvesting occurs before the plant starts to flower. Manure is applied regularly throughout the year. At wide spacings coffee, chat and cabbage may be interplanted. The maximum altitude for enset is about 3,000 masl. The minimum altitude appears to be set more by rainfall than temperature, with a minimum annual rainfall of about 800 mm.
Three13 main enset systems have been identified
I. Enset as the main staple food ii. Enset as a co-staple with cereals and tubers iii. Cereals as the dominant staple, with enset and little or no tubers
Enset is the main staple in the Gurage, Hadiya, Kambata and Sidama Zones of the Southern Ethiopian Peoples’ Region. In the Gurage Zone enset is dominant to the almost total exclusion of any other crops (except coffee below 2,000 masl). In the other areas
i:\A/estphall (1976) identified a fourth “primitive” system where tubers were dominant over enset and said to be practiced by the Gimmira people in Kefa. Field work in the area failed to find it. Westphall's description dates from the 1940's.
VOLUME III. STRATEGIC PLAN Page 22 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT estimated14 that the current system of the Majangir is sustainable at the current population levels and cultivation-fallow periods and is not leading to a permanent destruction of the high forest. The impact of the other bush fallowing systems coupled with seasonal burning for hunting on the Lowland woodlands and on the extensive areas of lowland bamboo has not been studied.
3.2 2.4 Agro-Pastoral and Pastoral Systems of Extensive Livestock Production
Agro-pastoral and pastoral systems form a continuum defined by the relative reliance households place on cropping and livestock production as the main source of subsistence. In practice this is defined by the size of an individual household’s livestock assets. These may undergo marked fluctuations from year to year, due to the vagaries of rainfall Pastoralists and agro-pastoralists may be found in the same cultural group Thus the Dassenetch, the Nyangatom and the Borena who are generally referred to as :'pastoralists”,may have within their midst, quite a sizable group of households whose main source of subsistence is crop production. It is reported15 that since the 1960's the proportion of households engaging in crop production has been increasing due to declining household livestock assets. This is being caused by the steady increase in the human population, with a livestock population which has reached the long term ecological carrying capacity of a particular group's grazing territory. Small household livestock assets makes it more difficult to recover from the large number of mortalities caused by the periodic droughts, and the gradual breakdown of traditional livestock redistribution customs.
The agro-pastoral systems have been sub-divided into those systems in which cropping is sedentary: ie on permanent fields, and those systems in which shifting cultivation and bush fallowing are practiced. The former include the Dassenetch and Nyangatom who cultivate permanent fields along the lower Omo river, using flood retreat cultivation where planting of sorghum and beans follows the recession of the flood Water on residual moisture. Some fields are located on fossil meander channels and ox bow lakes using high watertables. The extension of the Omo delta in recent decades has allowed an extension of this type of cultivation. The Borena also cultivate permanent fields in va iey bottoms and other sites where soil water collects.
The Hamer and other people on the Hamer Uplands of South Omo practice shifting cultivation and bush fallowing in the Combretum-Terminalia woodlands. Sorghum, maize and beans are the main crops with tobacco grown on old cattle kraal sites. The Mursi and
14 Sutcliffe (1994) and Chaffey (1980)
15 See Turton (1977), Carr (1977), Coppock (1994), Webb et al (1994)
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Bode Me’en people live just to the north of the Nyangatom along the lower Omo river. They practice both flood retreat cultivation along the Omo river, and a form of shifting cultivation in the thickets and woodlands away from the river. The Abore in the Sagen valley also have permanent fields along the Sagen river in and near its delta at lake Chew Bahir, as well as shifting cultivation fields along the colluvial foot slopes of the Hamer Uplands.
3.2.3 The State Sector
3.2.3.1 State Farms
The state farm sector was established in 1975 when all large commercial farms were nationalized under the Land Reform proclamation. In the next decade the sector increased the area of its holding, so that by 1985 it held 182,120 hectares. Gradually problems of declining soil fertility and poor site selection (in terms of rainfall) led to some farms being abandoned or transferred to the peasant sector. The project estimated the area of state farms in the project area from LANDSAT TM imagery as 261,400 hectares. This apparent over estimation possibly results from the inclusion of previous state farms which have been abandoned or handed over to cooperatives or peasant farmers. The location of individual farms in the various administrative regions are as follows:
Region 3: East Shewa Zone: 3 South Shewa Zone: 1
Region 4: Arsi Zone: 5 Bale Zone: 5 East Welega: 7 lllubabor: 3
Southern Ethiopian Peoples’ Region Sidama Zone: 2 (rainfed maize seed; tobacco) North Omo Zone: 2 (irrigated cotton; rainfed maize and sorghum) Kefa Zone: 2 (coffee; tea)
The current status of these farms is not certain. The Government’s economic policy with respect to government commercial enterprises is to privatize or enter into joint public and private ventures.
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3.2.3.2 National Forest Priority Areas
Introduction
Prior to the publication of Proclamation 94 of 1994 ("Forest Conservation, Development and Utilization Proclamation") the high forests were divided into state forests (ie more than 200 hectares in extent) and "community" forests (i.e. less than 200 hectares) There were no private forests. The state forests were classified into 58 National Forest Priority Areas (NFPAs). These Forest Priority Areas have not yet been reclassified according to the new categories of the Proclamation. The term "National Forest Priority Area” is thus maintained in the present report (without prejudice to the eventual classification). Of the 58 NFPAs some 44 are located within the current project area These are located in eight geographical areas:
- the Borena Escarpment and Hills - the Arsi/Harerge Mountains - the Bale/Sidamo Mountains - the Rift Valley Escarpments - the Gamo Gofa Highlands - Kefa Highlands - Illubabor Highlands - Gambela Lowlands
A full list is provided in appendix table A1.1.
High Forest Types and Physical Environment
The high forests of Ethiopia have been classified by Chaffey and by Fnis and Mesfin Tadesse. The basic framework of Friis and Mesfin Tadesse is used but incorporates some of Chaffey's sub-divisions. These are listed below. Detailed descriptions can be found in Annex 2. i. Upland Dry Evergreen (Juniperus procera) Forests of Sidamo
These are found on the southern escarpments and hills of the Borena Zone of the Oromiya Region between 1,500 and 2,000 masl. The dominant species is Juniperus procera with other common species such as Barbeya oleo>des, Olea europaea cuspidata. Pistacia aethiopiica, Pittosporvan spp. and Schrebera alata. NFPA's which are included within this category are the following:
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32 Butajira South Shewa Zone, Region 4 37 Negele Borena Zone, Region 4 38 Yabello-Arero-Mega Borena Zone, Region 4
ii. Mixed Upland Evergreen Forest of Harerqe. Arsi, Bale, Sidamo. Shewa
These forests are found as dispersed patches of forest in Harerge, Arsi and Bale. They are found between 1,500 to 2,700 masl. The main canopy species are Juniperus procera and Podocarpus gracilor which grow between 20 and 30 meters in height, with a well developed stratum of small to medium trees. NFPA's which are included within this category are the following:
1 Chilalo Gallema Arsi Zone, Region 4 2 Arba Guga West Harerge Zone, Region 4 5 Gidole-Kemba North Omo Zone, SEP Region 27 Gedo W. Shoa/Region 14 28 Giba + Muta Gegenfo u n 29 Chilimo Gagi u n 33 Menegesha Suba Addis Ababa 46 Dodolas-Adaba-logo Bale Zone, Region 4 47. Aloshe-Batu-Dodola-Ababa Bale Zone, Region 4 49 Harena-Kojosa Bale Zone, Region 4 55 Menessa-Shashamene South Shewa Zone, Region 4
III. Humid Upland Broadleaved with Podocarpus
These forests are found on the southern and southwestern side of the Bale Mountain Massif between 1,500 and 2,600 masl. They are characterized by Podocarpus gracilior mixed with broadleaved species as dominants. NFPA's which are included within this category are the following:
34 Anfarara-Wadera Borena Zone, Region 4 35 Bore-Anfera Sidama Zone, SEP Region 36 Megada Borena Zone, Region 4 48 Goro-Bele Bale Zone, Region 4 50 Mena-Angetu Bale Zone, Region 4
iv. Humid Upland Broadleaved with Aninperia
These forests are found as scattered patches in the Chencha and Gofa Mountains but reach their greatest extent in the Kefa Zone of SEP Region and 11 lubsbor and Welega Zones of Region 4. They are found between 1,500 and 2,600 masl. These forests become more diverse, in terms of tree species, from east to west (ie with increasing rainfall) and with decreasing altitude (ie with increasing temperature). Forests in the Baro catchment are thus floristically richer than in the Omo or Weyto catchments. There is evidence of
VOLUME III. STRATEGIC PLAN Page 28 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT human disturbance throughout the area, and Chaffey considers that all the remaining high forest is in fact secondary. NFPA's which are included within this category are the follow ing:
3 Deme-Laha South Omo Zone, SEP Region 4 Bulki-Malakoza North Omo Zone, SEP Region 5 Gidole-Kemba North Omo Zone, SEP Region 14 Gebre Dima lllubabor (Region 4) 15 Sigma Geba lllubabor (Region 4) 16 Yayu u n 17 Abelti Gibe Kefa/SEP Region 18 Belete Gera n 19 Babiya Fola “ 20 Tiro Boter Becha “ 21 Gudere u 22 Sele Andeacha “ 23 Sibotole Kobo lllubabor (Region 4) 24 Bonga Kefa/SEP Region 25 Gura Ferda “ 26 Yeui “ 27 Gedo W.Shoa/Region 4 28 Gibat Muta Gegenfo u n 29 Chiiimo Gagi u 31 Yerer-Dire-Gerbicha -Zukuala East Shewa/Region 3 32 Butajira South Shewa/Region 3 33 Menegesha Suba Addis Ababa Region 34 Anferara-Wadera Borena/Region 3 35 Bore Sidama/SEP Region 36 Megada Borena/Region 3 37 Negele Borena/Region 3 38 Yabello-Arero-Mega Borena/Region 3 39 Gerafeda Gambela Region 40 Jongo Wato Welega/Region 4 41 Konchi u 42 Leucho Dale Gewi « 43 Chato Sengi Dengeb “ 44 Komto Waga Tsige u n 45 Gidame Asosa/Region 5
V The Transitional and the Lowland Semi-Everqreen Forests of Southwest Ethiopia.
These forests are found at the foot of and up the western escarpment overlooking the Gambella Lowlands. Mesfin Tadesse considers them as two separate types of forests.
The Transitional Forests occur between 500 to 1 500 masl usually in river valleys and other areas where there is, presumably, a high water table. The Lowland Forests are found between 450 and 600 masl. NFPA's which are included within this category are
VOLUME III. STRATEGIC PLAN Page 29 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT the following:
13 Abobo Gog Gambela Region 25 Gura Ferda vi. Riverain Forests
These are varied and have been little studied. Near Arba Minch town and within the Nechisar National Park there is an area of groundwater forest. Along the major streams and rivers there is generally a narrow band of gallery forest. No riverain forest is by itself classified as a NFPA (including the Arba Minch groundwater forest).
Land Cover and Vegetation within the NFPAs
All NFPA's enclose land which is covered by vegetation other than just high forests. Many enclose areas of cultivation and settlement, and/or are permanently or seasonally grazed which raise a number of issues:
- the percentage of ‘slightly disturbed forest' to be used as an indicator of a particular NFPA's value for protection or production
- the percentage of heavily disturbed forest to be used as a measure of the degree of degradation of the original forest
- the area of plantation and its potential for state production forest or conversion on lease as a private forest
-the area of "other land", which in most cases includes cultivated land to be used, as a measure of human encroachment and/or settlement within the current NFPA boundary
Current Legal Position
Proclamation 94 repealed all previous forestry legislation. The Proclamation provides for five types of forest as outlined below: i) State Forest: is forest and forest land designated, demarcated and registered by the Ministry of Natural Resource Development and Environmental Protection (MNRDEP) - now MoA - to develop forest resources, protect genetic resources and conserve ecosystems in a programme which will cover more than one region (own italics);
VOLUME III. STRATEGIC PLAN Page 30 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT i ii) Regional Forest: is forest and forest land designated, demarcated and registered by a Region and is not a state or protected forest, and is found within a specific region and developed by that region (own italics), lii) (State) Protected Forest: is forest or forest land designated, demarcated and register by MNRDEP (MOA) to make it free from human or animal interference for the protection of the environment and genetic resources;
iv) (Regional) Protected Forest: is forest or forest land designated, demarcated and register by a Region to make it free from human or animal interference for the protection of the environment and genetic resources; v) Private Forest: is a forest developed by any person and includes a Peasant Association or any other association of private individuals Regions will register private forests within their regional boundaries.
Thus the MOA is responsible for State Forests and State Protected Forests whilst the Regions are responsible for Regional Forests, Regional Protected Forests and Private Forests. It is not clear from the legislation what the distinction is between State and Regional Protected Forests.
For State and Regional Forests the MOA or the region, as appropriate, are required to produce a development programme and monitor its implementation; take protective measures against fire, and forest diseases and pests; facilitate the construction of infrastructure; and ensure the forest inhabitants benefit from development and conservation activities.
Protected forests are to be developed and protected in order to conserve the soil; protect and improve water bodies, river sources and catchments; protect rare and/or endangered species of animal or plant and genetic resources in general; and conserve unique and representative habitats or natural resources.
In State and Regional Forests the management plan may cater for forest inhabitants to use forest products to satisfy their domestic needs by paying appropriate fees. In Protected Forests the collecting of forests products, grass and fruit, and the keeping of beehives may be allowed. If people are required to vacate any forest this can only be done with their consultation and consent
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3.2.3.3 State Industrial Forest Plantations and Peri-Urban Fuelwood Plantations
Industrial plantations cover a total area of about 95,000 hectares most of which are located in the NFPA.s. Within the Project Area there is approximately 57,700 hectares or over 60 percent of the total. The location of these by administrative Region and Zone is shown in table 3.1.
Table 3.1 Location and area of industrial plantations within the project area Region 4: hectares Arsi Zone: 10,900 (includes plantations in South Shewa and Sidama Zones) Bale Zone: 3,900 Borena: 2,000 lllubabor: 4,400 West Shewa: 1,800 East Shewa 1,700 South Shewa 1,600 Welega 5,600 S u b to ta l 31,700
Southern Ethiopian Peoples’ Region Kefa 15,300 North Omo . 1,700 Sidama ,100 S u b to ta l 2,100 Gambela Region 1,100 Addis Ababa Region 2,800 GRAND TOTAL 57,700
The present estimated production of this area (assuming mean national yields) is approximately 57,000 M 3 although large areas are still maturing. Only about 10 percent of the yield can be classed as industrial wood, with the remaining 90 percent only suitable for poles and fuel wood16.
3.2.3.4 W ildlife Conservation Areas: National Parks and Wildlife Sanctuaries
i he strictest categories of wildlife conservation areas are the National Park and the Wildlife Sanctuary. These are areas in which settlement and all other uses are precluded. The National Park encompasses a wide ranges of species of both fauna and flora, whilst
~ Ethiopian Forest Action Programme Volume II (1994)
VOLUME III. STRATEGIC PLAN Page 32 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT the Wildlife Sanctuary is designated for the protection of one or two faunal species and their specific habitat. Other categories of wildlife conservation areas are the Wildlife Reserve which is an area designated for the conservation of significant wildlife resources, but which do not warrant strict conservation; and the Controlled Hunting Area where limited hunting on licence is permitted Currently hunting is prohibited across the whole country.
The Project Area contains 7 of Ethiopia's 9 National Parks, 2 of its 3 Wildlife Sanctuaries, 3 of its 9 Wildlife Reserves and 13 of its 17 Controlled Hunting Areas These are listed in table 3.2 with their respective administrative regions and zones.
Table 3.2 National Parks and Wildlife Sanctuaries within the project area
(a) National Parks:
Awash 75,600 hectares Region 2/Region 4 East Shewa Zone Bale Mountains 247,100 hectares Region 4:Bale Zone Rift Valley Lakes 88,700 hectares Region 4:South Shewa Zone Nechisar 51,400 hectares S.E.P.Region:North Omo Zone Mago 321,100 hectares S.E.P.Region:South Omo Zone Omo 406,800 hectares S.E.P.Region:Kefa Zone Gambela 200,000 hectares Gambela Region
(b) Wildlife Sanctuaries
Sankelle 5,400 hectares Region 4:South Shewa Zone Yabello 250,000 hectares Region 4:Borena Zone
(c) Wildlife Reserves
Awash West Region 4:East Shewa Zone Bale Region 4:Bale Zone Chew Bahir S.E.P.Region:South Omo Zone Tama S.E.P.Region:South Omo Zone
(d) Controlled Hunting Areas Arsi Region 4:Arsi Zone Awash West Region 4:East Shewa Zone Bale Region 4:Bale Zone
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Borena Region 4: Borena Zone Boyo Swamp Region 4:South Shewa Zone Dabus Valley Region 4:West Welega Zone Sagen Region4:Borena Zone Maze S E P.Region:North Omo Zone Murle-Kenya Border S.E.P.Region:South Omo Zone Omo West S.E.P.Region:Kefa Zone Akobo Gambela Region Jokau Gambela Region/Beni Shangul Region Tedo Gambela Region
Of the National Parks only the Awash NP is legally gazetted Management plans have been prepared for the Awash and the Bale Mountain NP's, and planning is currently underway for the Nechisar, Mago and Omo NP's. All the parks have either been settled or are permanently grazed. The degree of encroachment is most acute in the Awash Rift Valley Lakes, Bale Mountains, Nechisar and Gambela NP’s In terms of tourist infrastructure the Awash and Bale Mountains NP's are the best endowed, although planning is currently underway for considerable investment in the Nechisar, Mago and Omo NP’s. The Sankele Sanctuary suffered considerable loss of its population of Swaynes Hartebeest during disturbances immediately after the fall of the previous government, whilst in the Yabello Sanctuary the dry Juniper forest is being cut down Only the Bale Mountain and Nechisar NP's and the Yabello Sanctuary contain any significant examples of forest. Currently there is no strict protection of any of the high forests in the southwest Highlands.
3.3 Socio-C ultural Factors
3.3.1 Population
The government undertook a new national population census in October 1994 but the results have not yet been published. Recourse had to be made to the 1984 Census which was enumerated according to the administrative structure prevailing at the time, and which has been twice replaced, and the updated 1995 population estimates undertaken by the Central Statistical Authority based on standard rates of population increase but adjusted in some areas to take account of the massive migrations that had taken place in the country. As maps of the new administrative Regions and their weredas have not yet been published it is not possible to produce population estimates for the new Regions and their weredas.
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The Project's “Working Area” has been defined on the basis of latitude and longitude and thus cuts across administrative boundaries. Within the Project :s “Net Area" only those 1984 weredas which lie completely within the project boundary have been included within the inventory, analysis and planning. The total population of this area is indicated in table 3.3 by the 1984 administrative regions.
Table 3.3 Rural and urban population estimates and rural population densities for 1995 Region Rural Urban Total Rural density (Persons/Km2)
Arsi1 2,020,320 265,829 2,286,149 89.5 Bale1 698,211 140,598 838,809 25.3 Gamo Gofa 1,782,901 156,998 1,939,899 44.1 lllubabor 1,317,201 152,798 1,334,969 54.1 Kefa 3,182,117 321,709 3,503,826 56.2 Shewa1 6,750,140 1,174,810 7,924,950 144.8 Sidamo 5,140,499 520,796 5,661,295 42.9 We ega 3,241,033 339,128 3,580,161 100.0 (NB:1 Indicates only a part of the Region is covered).
Within the regions the wereda densities vary widely from a maximum of 492 persons per km2 in Kedida Gamela wereda and 1.9 persons per km2 in Moyale wereda. In Kedida Gamela wereda densities in some individual Farmers’ Associations are between 700 and 800 persons per km2 These large variations in population densities reflect the great diversity of environment within the Project Area.
3.3.2 Socio-cultural features of the project area
There are over 80 ethnic groups represented in the Project Area, and nearly as many languages and cultural systems. Frequently these different cultural systems are associated with specific land use systems. This feature has been used in many cases to help define the land use systems which are described in detail in Annex 2.
3.3.3 Infrastructure
Ethiopia’s main road network extends radially from Addis Ababa with few inter connecting links. Large areas still lack an all-weather link to the capital or other economic and administrative centres. Addis Ababa is linked to the following centre within the Project Area by asphalt all-weather road: Awasa (the administrative capital of the S.E.P. Region) and on to the Kenya border at Moyale; Jima (capital of Jima Zone)and, on to Metu (capital
VOLUME III. STRATEGIC PLAN Page 35 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT of lllubabor Zone); Nekemte (Welega Zone); Nazerrete (East Shewa Zone); Assela (Arsi Zone); and the Abay river and onto Gojam. A gravel surfaced road connects Gambela (Gambela Region), Assosa (Bem-Shangul region), Mizen Teferi (Kefa Zone), Mocha (Mocha Zone), Jinka (South Omo Zone), Arba Minch and Soddo (North Omo Zone), Robe/Goba (Bale Zone) and Negelle (Borena Zone). A new gravel road links Nekemte with Gojam across the Abay river.
Leading off these mam roads are an increasing number of secondary feeder and farm to market roads. However away from the roads human porterage and donkeys are the only means of transport for goods and produce. A maximum daily outward distance of 5 to 8 kilometers for humans and 15 to 20 kilometers for donkey has been assumed when delineating market catchment areas for bio-fuels
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CHAPTER IV PLANNING FOR THE SUSTAINABLE DEVELOPMENT AND MANAGEMENT OF WOODY BIOMASS RESOURCES
4.1 Factors Affecting the Production and Consumption of Woody Biomass
This section examines, in very general terms, the factors which affect the production, collection, supply and consumption of woody biomass, particular for the supply of energy, but also covering its removal for agricultural expansion and the many other uses of trees, bushes and shrubs.
4.1.1 Natural environmental and ecological conditions
The main influences on the stock and yield of woody biomass are the effects of temperature and rainfall, and to a lesser extent, soils and relief In Ethiopia the influences of temperature and rainfall generally work against each other, as temperature decreases with altitude and rainfall generally increases. The optimum conditions for biomass production lie between 1,800 to 2,700 masl. Similarly, these factors also strongly influence the types and patters of land use. In terms of consumption, temperature may have a small effect on the proportion of energy used for heating, although other factors such as availability and income have much stronger influences.
4.1.2 Land use systems: Inter-relationships and dynamics
The outputs of land use systems provide the main supply of bio energy in the form of fuel wood, crop residues and animal dung. Fuel wood can be obtained from communal or individual farms, either as free growing or specially grown trees, bushes and shrubs. Crop residues and dung can also form inputs within land use systems: crop residues as livestock feed, whilst both residues and dung are important in soil nutrient cycles, especially the cycling of nitrogen and phosphorous. Trees can also be important in nutrient cycling, either as nutrient “pumps” bringing nutrients in the deep subsoil to the surface or through nitrogen fixation by the roots. The dynamics of change in these inter relationships are driven by increasing population and the need for cropland. Extension of cultivation occurs at the expense of communal grazing lands, woodlands, bushlands and forests. Decreased area of natural grazing results in an increased reliance on crop residues for livestock feed, and with decreasing woody biomass resources, an increasing reliance on residues and dung for fuel. Breaches in nutrient cycles, declining soil fertility and so declining crop yields, increase the pressure to expand cropland.
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4.1.3 Land and trees tenure systems
The lack of security of individual tree tenure prior to the changes in 1991 has been cited as an important factor in the lack of tree planting or good tree management in many areas of Ethiopia. Sustainable production of woody biomass on communal lands is dependant on the degree of control communities can exercise over the use of these lands. The increasing pressure to which many communal areas have been put has resulted in their becoming “open access” resources with little or no control over their use Much of this lack of control in the past could be blamed on the often undemocratic nature of the Peasant Association leaderships and by the usurping of local power over communal resources by the previous very centralized government. The current practice of allowing communal grazing on the croplands after harvest is an important factor in dissuading farmers to invest in land improvements such as soil conservation structures, planting trees on boundaries and bunds, and under sowing legumes.
4.1.4 Socio-cultural factors
An important socio-cultural matter concerns gender relationships with respect to the production, collection, distribution, purchase and final consumption of fuel wood and other bio- fuel substitutes. There may be important differences with respect to the household member who produces, collects, sells and finally uses woody biomass and trees products, crop residues and animal dung. These relationships can be complex and are important when analyzing wood fuel supply and consumption patterns given the socio-cultural variability in Ethiopia.
4.1.5 Economic Factors
At the micro economic level the relative costs of producing and collecting fuel wood their bio-fuels, and other energy substitutes (electricity, kerosene, etc), together with the other uses for wood (construction, etc), strongly influence the consumption rates of woody biomass. Two important dterminants are the household income and its labour supply. The level of household income is particularly influencial in dtermining urban energy consumption levels and the types of fuel or energy used. In rural areas household labour supply strongly influences the amount of fuel wood a household purchases or collects, and as a consequence the amount it burns.
Where trees and shrubs are produced, on the farm these relative costs will also influence harvest methods and rates. Thus for fuel wood, farmers will practice shon rotations (2-3 years) of trees that coppice well (e.g.. Eucalyptus spp.), longer rotations (4- 5 years) for short poles and the longest rotations (7-9 years) for telegraph poles. The relative proportions of each will vary, but can well be practiced within the same woodlot.
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This multi-purpose approach to tree production is very different from orthodox forest management. Indigenous trees in farmers fields will also be managed to obtain the maximum output of woody biomass through a flexible system of pollarding. Again when farmers are considering the pollarding frequency, there is a careful examination of the relative costs and benefits leaves for use as fodder, small branches and twigs for fuel, and large branches for construction.
At the macro level, government interventions in wood (fuel wood, charcoal and timber) marketing, such as controlling the price, can influence wood consumption rates. When prices are set below the costs of production, there will then be a tendency to over consume. Additionally if supplies can not meet demand, then a "parallel” and unofficial market will develop, as happened before timber prices were de-regulated in 1991. Where it is not possible for suppliers to produce their own trees and potential tree growers can not dispose of their own trees, would traders are likely to obtain their supplies from “open access” resources: ie. the communal woodlands, forests and grazing areas.
4.2 Planning Approach and Analytical Techniques
4.2.1 Introduction
A strategic plan for the management of Ethiopia's woody biomass resources must answer four basic questions: (i) what and where are the major problems, (ii) what are the interventions available to effectively address these problems, (iii) what are the priorities in terms of the required and available interventions, and (iv) what are the likely impacts of these interventions.
An essential principle of strategic planning for natural resources is that people must be at the centre of efforts to achieve their sustainable use and development. The different ways in which people use (and abuse) natural resources is determined by a complex web of relationships. These relationships link not only the natural but also the social, cultural and economic "environment". Thus in any natural resource planning it is necessary to integrate information on the physical and biological systems with that of the socio-cultural and economic systems in order to define the "total environment" in which people use and manage natural resources.
Given the variability of agro-ecological, socio-cultural and economic conditions in Ethiopia together with the size of the project area, some logical planning framework is required. In this way meaningful recommendations can be made for woody biomass development and management.
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The purpose of this section is to examine a number of technical issues with respect to strategic planning of woody biomass resources. The first and most important of these is the definition of the basic planning unit A planning unit in the present context can be defined as:
"a spatial unit which can be identified and delineated on the ground and which is sufficiently homogenous in biophysical, socio-cultural and economic characteristics, that meaningful recommendations can be made with respect to desired objectives."
The "objectives" referred to here will be those established in the overall policy and strategic framework of WBISPP.
Initially the project recommended (in the Inception Report) using the "land system” and this was later changed to the 30 Woody Biomass Strata which were condensed from the 419 land use/land cover units. Annex 2 examines in some detail the advantages and disadvantages of using the Woody Biomass Strata in comparison with the unit used hitherto in nearly all previous land use planning in Ethiopia, namely the farming/pastoral or land use system. The latter was adopted because of the considerable gain in the quantity and quality of planning information.
A second and related issue relates to the scales or levels of planning and recommendations. Three levels are identified, (i) the land use/land cover unit, (ii) the land use system, and (iii) the basic administrative unit: le the wereda.
Thirdly a number of issues are raised in the discussion on the thematic areas of the planning, in particular the estimation of the woody biomass balances, the food balances and the forage balances.
Finally the section briefly outlines how the land use systemswere identifier md used for planning.
4.2.2 Past and current approaches to the “ Planning Unit” within WBISPP
4.2.2.1 The Initial "Land System" Approach
The basic unit for strategic planning recommended in the WBISPP Inception Report was the "Land System".
"The ultimate objective of the project is planning. Knowledge of the types and distribution of woody biomass occurrences, and likewise o f land utilization systems, provides a base line evaluation of the status quo, but provides little basis for
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projections into the future - either land potential or the land response to certain forms of management. In order to make such assessments — to undertake "planning" - a much wider range of biophysical parameters must be assessed. At the current scale of investigation, it is suggested that a land systems approach provides an appropriate framework for the collection and evaluation of the necessary range of resource parameters." (WBISPP Inception Report, pg. A1.14)
In the main report the "land system" was described as regional patterns of repeating land forms comprising land components which were further subdivided into land facets (see figure 6.1 in the report). The land components and facets were to be evaluated for their suitability for broad classes of land use and management following FAO's "Framework for Land Evaluation". It should be noted that the above is an exceedingly "physical" and "hard systems" approach to planning with no reference to the socio-cultural and economic context in which woody biomass is used or managed.
4.2.2.2 The Approach Using Woody Biomass Strata
Later in “Strategic Planning for the Woody Biomass Sector in Ethiopia", WBISPP Occasional Paper #3, January, 1994 the Woody Biomass Strata replaced the land system as the basic planning unit.
"The project proposes to develop indicative management plans for representative models. For each of these strata, or for a subset of the most important strata, the project will develop representative models. A 'typical' situation can be defined, either by producing a block diagram from digitized contours, or by artist impression, showing physiography, soils, current land use/cover, and land potential." (WBISPP Occ. Paper #3, pg. 9)
Some 419 combinations of land use-land cover and related parameters of physiography and soil erosion were identified during a complete mapping of approximately 500 000 km2 (WBISPP Occ. Paper #4, February, 1994). The 419 "Land Cover Units" were subsequently aggregated to form 30 "Woody Biomass Strata" defined by the dominant land cover/vegetation type and the slope (< or > 8%). It was these 30 aggregated Strata that were proposed as the basic planning unit.
4.2 2.3. An examination of the use of the woody biomass strata as the basic planning unit
Advantages: There are two advantages using the 30 Woody Biomass strata:
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1. The number of strata are relatively few.
2. There is some integration of physiography through the division of the "pure" biomass strata into those below and above 8% slope.
Disadvantages: There are, however, a number of serious disadvantages with respect to using the Woody Biomass Strata, as it was defined, for strategic planning of woody biomass in the ecological, socio-cultural and economic context of Ethiopia
1. High Variability of Land Use and Land Cover Characteristics within the Woody Biomass Strata: The initial results of the forest inventory revealed unacceptably high variability of land use and land cover characteristics within the 30 aggregated woody biomass strata. As a result the 30 Woody Biomass Strata were replaced by the original 419 Land Use and Land Cover Units as the primary sampling units for the forest inventory.
2. Identical Woody Biomass Strata mapped in different locations within Ethiopia may have very marked differences in:
(I) geology, climate and soils: Thus whilst standing woody biomass per hectare may be the same in all units of the same type, the annual yield per hectare of woody biomass may be different because of differences in soils and/or climate. For example, the annual woody biomass yield in strata 3B "Open Woody Bushland" found in Gambella may differ from the yield in Ogaden, which may differ from that in north Welo. This has important implications for the estimating woody biomass supply/consumption balances.
The same problem applies to the yield potential for other types of bio-production including crops and forage which has similar implications for population/food and livestock/forage balances.
(ii) socio-cultural and economic conditions. Whilst the biomass conditions and even agro-ecological conditions may be identical in two units of the same biomass type, the socio-cultural and economic factors may be significantly different. Such factors as:
- population numbers and density
- livestock numbers and densities
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- accessibility to roads, markets and thus the price structure for crops, livestock, bio-fuels and wood products
(iii) farming, agro-pastoral and pastoral systems of production: As a result of differences in agro-ecological, socio-cultural and economic conditions, the woody biomass types will be located in or across different farming, agro-pastoral or pastoral systems, each with their different systems of and institutional approaches to natural resource management.
(iv) different types and degrees of natural resource pressure and competition As a result of all the differences outlined in (I), (ii) and (iii) above, there will be different types and degrees of pressure on and competition for natural resources (including woody biomass) as well as potentials for their conservation, and sustainable development and management.
(v) differences in policies and priorities of Regional Governments Finally, policies and priorities of Regional Governments may differ with important implications for strategic planning of specific woody biomass types.
4.2.2.4 An alternative basis for the planning unit: The land use system
Land use systems were defined by the Socio-Economic Section on the basis of agro-ecological zones, crop mix, the livestock production system and agro-forestry characteristics. Thus an agricultural land use system has a defined set of agro-ecological conditions and a defined set of agricultural management practices with respect to crops, livestock and trees. These have developed over many decades or even centuries in response natural environmental conditions as well as to socio-cultural and economic factors.
Pastoral land use systems are defined on the basis of recognized grazing territories occupied by a specific cultural group of people. In the same way as agricultural land use systems, they too have developed over long periods of time in response natural environmental conditions and socio-cultural and economic factors.
Both agricultural and pastoral systems are in a process of dynamic change in response to changes in the natural, socio-cultural and economic environment. For all these reasons they provide a sound basis and appropriate context for strategic planning
Much experience has been gained in Ethiopia in the use of farming and pastoral systems as a basis for land use planning at all levels and scales:
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National level Master land Use Plan 1.2 million (by LURD/MOA, 1987)
Sub National level Agricultural Assessment of SW,S,SE and W Ethiopia (by LPRD/MOA, 1986) 1:1 million
Regional level Southern Rangelands Project (by MOA and ILCA, 1993) 1:500,000
Land Use Plans for Menegesha, Haykoch & Butajira, and Yerer & Kereyu (by LUPRD/MOA, 1989) 1:250.000
Wereda level Land Use Plans for Bichena and Hosaina (by LEPRID/MOA, 1988) 1:50,000
Local level Village level Plans in Kambata and\ Dalocha awrajas (by Shewa PADEP, 1990) 1:10,000
Both national (including IAR in Ethiopia) and international research organizations now use farming and pastoral systems as a basis for problem diagnosis and adaptive research. In particular ICRAFF has developed its "Diagnosis and Design" system of surveys and research for agro-forestry in farming and pastoral systems.
The specific disadvantages and advantages of using farming and pastoral systems as a basis woody biomass strategic planning are considered in more detail below.
Disadvantages
1. Boundary definition: The delineation of clear boundaries of some agricultural land use systems can occasionally be difficult, particularly where there is a gradual change in cropping mix. However the experience gained is that the sharp changes in altitude which occur in Ethiopia often mean that farming system boundaries are relatively distinct.
Pastoral land use system boundaries can also be difficult to delineate. In some cases there are arrangements or agreements for one pastoral group or sub group to use the territory of another in cases of emergency or drought. In other cases there may even be disputes as to where the exact boundaries lie between
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sub-groups and groups. However surveys undertaken in Borena in southern Ethiopia have revealed quite distinctive territories of Borana pastoral sub-groups around the deep wells. Similarly Cossins (1974) was able to map the Afar clan boundaries.
2. Number of Units: Whilst there may less than 30 farming and pastoral systems defined in the initial project area, there will be more than this number in the whole of Ethiopia. However as this strategic planning framework will eventually be used by Regional administrations for more detailed planning, this should not prove a major obstacle.
Advantages
1. Many of the disadvantages of using the woody biomass strata as the planning unit, outlined above, are avoided These advantages may be summarized as follows:
(i) Physical environmental conditions are well defined: Each agricultural or pastoral land use system is well defined in terms of its landform-soil pattern, climate-altitude and thus agro-ecological zone(s).
(ii) Socio-cultural and economic conditions are well defined: Characteristics such as human population and livestock density, pressure on natural resources, natural resource dynamics in response to these pressures, accessibility to roads and markets and, consequently, commodity prices are all likely to be well defined within the farming/pastoral system boundaries.
This is not to say that there will not be differences in, for example, crop mixes and/or resource attributes between farmers within the same agricultural system. However in Ethiopia the land reform of 1975 resulted in a general "leveling" in terms of farmers production assets, most particularly with respect to land holding. Thus differences between farmers are not as great as are often found in other countries. All farmers will face to a large extent the same external natural, socio-cultural and economic variables.
(iii) Natural resource management systems, institutions and institutional arrangements are well defined: Within the boundaries of each agricultural or pastoral system there is a uniformity in the individual farmers' and the communities' systems of management of natural resources together with the systems of tenure (ie. access, use and non-use
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regulations) and the institutional arrangements to ensure adherence by the members of the communities. In this way the functional relationships between the different land use and vegetation types (or woody biomass strata) can be identified and specified at the macro or micro levels depending on the level of detail (or scale).
2. Analysis of vegetation and land use dynamics: Given that the natural, socio cultural, economic characteristics, the natural resource management systems and the functional relationships between the woody biomass units located within the agricultural/pastoral system are all well defined, it follows that a deeper understanding can be obtained of the dynamics of the vegetation and land use types in relation to the pressures being exerted upon them
4.2.5. Using the land use system as a basis for strategic planning of woody biomass resources
Agricultural Systems:
A 1st approximation was obtained using the farming/pastoral systems identified in the LEPRID/MNRDEP planning studies at the national (1:2 million), sub-national (1.1 million), regional (1:250 000) and wereda (1:50 000) levels together with the agro- ecological zones (AEZ) which have been mapped based on altitude and rainfall and an examination of the socio-economic-survey data. The latter will be used to identify the general mix of the major crops to see if either: (I) there are major changes in the mix within the AEZ or (ii) whether adjoining AEZ's have similar crop mixes and thus can be grouped. Further refinement was possible using the detailed land cover/vegetation map at 1:250,000, noting in particular the agro-forestry modifiers in the agricultural strata.
Cross checks were made using the forestry inventory sampling sheets, w hich’held information on slope, vegetation, land use and soil data; together with the field sketches, cross sections and photographs taken in the field. Final verification was undertaken during field inspections.
Pastoral and Agro-pastoral Systems:
In Borena the Southern Rangelands Development project have undertaken mapping of wells and the grazing territories of those pastoralists belonging to a particular well. In parts of Bale and Arsi the territories of some pastoral and agro-pastoral groups have been mapped by the CSA. In South Omo and Kefa the territories of the various pastoral, agro- pastoral and hunter gatherer groups have been mapped as part of an NCS Planning Case Study.
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Other Planning Units:
Protected Forest Areas: Some have been accurately surveyed whilst others only have tentative boundaries recorded on small scale maps. A preliminary evaluation of 44 of the 58 PFA's has already been undertaken by WBISPP
National Parks and Wildlife Sanctuaries: Boundaries of all National parks and Wildlife Sanctuaries have been recorded on maps at 1:250,000.
State Farms: All state farms have been mapped by WBISPP.
4.2.6 The "Agricultural Landscape" as a Framework for Problem Diagnosis and Strategic Planning for Woody Biomass Management
4 2.6.1 Introduction
The "agricultural landscape" has been used by ICRAFF in its "design and diagnosis" methodology for agro-forestry as a framework for analyzing agricultural and pastoral problems in the context of crops, pastures and trees. ICRAFF defines "landscape" in the present context as follows:
"An area of land, usually between 10 and 100 square kilometers, including vegetation, built structures and natural features, seen from a particular viewpoint." (Nair, 1993)
A farming system will have its own agricultural landscape, which is simply the visible expression of the various components of land use and vegetation (fields, hedges, grazing areas, woodlands and forests, etc) and built features (roads, houses, other buildings,’ etc) se: within the physical framework of land forms, soils, water and climate. These visible landscape components are set within a "hidden" socio-cultural, economic and technological framework of e.g. land tenure rules and institutions, markets and prices, demographic factors (numbers, densities, growth rates), resource management technologies and practices (soil conservation, agronomy, animal husbandry, tree husbandry, etc).
4.2.6 2 Focus of Analysis: Woody and Herbaceous Biomass Components
The immediate focus of analysis in the WBISPP are the woody and herbaceous components in the agricultural landscape. There are 8 characteristics of these components which are considered in the overall analysis. These are briefly outlined below.
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(i) Form:Form refers to the three dimensional shape of the component. Generally four types are recognized: point e.g.. wells, ponds, etc; patches which are relatively small areas (ie. less than 1000 hectares) of vegetation or iand cover which are distinct from adjoining patches, such as crop fields, grazing areas, small areas of woodland and forest, etc; linear features such a hedges, field boundaries, roads, streams, etc; and finally extensive features which are relatively large areas (ie. more than 1000 hectares) of vegetation within which point, patch and linear features may be found.
(ii) Structure and Arrangement: These characteristics refer to the components' horizontal, vertical and temporal location, arrangement and relationship with each other within the landscape and account for the landscape's visible character Thus crop fields and their boundaries of trees and shrubs may have a distinctive square pattern e.g.. in Kambata, or the fields may be long and narrow running down from the homesteads which are located on top on the ridge crest, as in the Gurage areas.
(iii) Species Composition: This refers to the species composition of the landscape components: e.g.. a field of wheat, a grazing area comprising a number of grass and sedge species, etc.
(iv) Functions: These refer to the products or services provided by the landscape component to the farmer, pastoralist or community. Thus a hedge of shrubs and bushes may perform a number of functions: - products: forage, fuelwood -services: livestock control (e.g.. night stalling, enclosure in grazing areas, exclusion from croplands), shade (for humans and/or livestock), wind breaks (around crop fields). Functions are clearly related to farmers' and pastoralists' production objectives.
(v) lnteractions:These may be positive or negative and are particularly important in agro-forestry. An example of a positive interaction is the effect of leguminous trees in improving soil fertility, whilst that of a negative interaction is soil moisture competition between Eucalyptus trees on field boundaries and field crops in semi arid areas.
(vi) Climate and the Landform-Soil Pattern: This refers to the basic physical framework of the agricultural landscape and which may influence the form, structure and species of the landscape components, as well as the resource management technologies and practices.
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(vii) Socio-Cultural Environment: This refers to such factors as demography (numbers, densities and growth rates), resource tenure systems (relating to resource allocations, rights to access, use and harvesting or prohibitions on access or use) and the related implementing institutions. Such rights of access and use may refer to specific components of the landscape at particularly periods in time and to specific sections of the community.
(viii) Economic Environment: This refers to such factors as market supply and demand, market prices for inputs and outputs, which are influenced by physical accessibility and transport costs.
4.2.7 The Concept of the Landscape "Niche" in Woody Biomass Planning
The concept of the landscape "niche" is borrowed from ecology. Essentially it is an element or part of an element in the landscape (e.g. a field edge, live hedge) which is currently not utilized, or under utilized or at least available to be used for a specific purpose. One example of such a niche might be the use of a field boundary for planting forage and/or fuelwood trees (but recognizing the need to change the socio-cultural context with regard to communal grazing of fields after harvest). A second example might be the use of stabilized gullies for micro-irrigation or for the production of bamboo. Yet another example could be the expanded use of the homestead garden for increased vegetable production and/or for fuelwood production.
4.2.8 Identification of the sensitivity themes for analysis and modeling
A number of key sensitivity themes were identified as measures of environmental stress with close linkages to bio-fuel supply and consumption patterns. The basic planning framework for the analysis was the Land Use System. A systems approach permitted an exploration of the linkages between the different production components such as crop, livestock and tree production in terms of inputs (e.g.. residues as livestock feed and as fuel; dung as fertilizer or fuel) and outputs (e.g.. crop yields, heat energy for cooking). It also permitted an exploration of the dynamics of change driven in particular by population growth, and the increasing pressure on the natural resource base, and the ways in which people (both rural and urban) cope with increasing shortages of natural resources, and the impacts on crop, livestock and tree production.
The main sensitivity themes selected for analysis were:
i. Woody Biomass Supply-Demand Balances ii. Human Food Supply-Consumption Balances iii. Livestock Grazing-Fodder Resource Balances
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iv. Land Use Systems and Population Pressure v. Socio-Economic Aspects of Bio Fuel Production, Collection and Consumption vi. Soil Erosion vii. Critical Forest and Woodland Development and Conservation Needs
Modeling of woody biomass supply and consumption balances, population support capacity, livestock carrying capacity and potential soil erosion was undertaken using a combination of spreadsheet models and the project’s GIS. The methods and assumptions used are briefly outlined below. The results, by wereda, are presented in Appendix 2
4.2 8.1 Woody biomass supply and consumption balances
Data on woody biomass stocks and yields were made available on a land use systems basis from the GIS. Data on biofuel consumption rates and patterns were also available on a land use systems basis, from the project’s socio-economic survey and from the original household data in the ENEC/CESEN study. The supply and consumption data were then aggregated by wereda, and an analysis undertaken of fuel wood consumption against yield over a twenty year period (1995--2015).
Where consumption exceeded yield then stocks were reduced pro rata in the following year, with a commensurate reduction in yield. In the absence of data on fuel wood supply-consumption elasticities-^.e. by how much consumption changes in response to declining stocks, and thus increases in collection times), the annual increase in total fuel wood consumption was assumed to be slightly less than the increase in population: 2.55 percent per annum. This implies a reduction in per caput consumption of about 0.35 per cent per annum. In areas of acute shortage this is clearly unrealistic. Further work on this aspect is required, possibly through surveys of historical use of fuel wood in these areas.
4.2.8.2 Cropland population support capacity analysis
To determine the degree of population pressure in terms of the land’s capacity to support the current and projected population, an analysis was undertaken of the cropland population support capacity. Given the reconnaissance level of some of the land resources data, and the provisional nature of some of the data on crop areas and yields, the analysis is only indicative. However the results broadly indicate where the main areas of population of pressure occur.
The analysis sought to establish - for each of the 68 land use systems - the minimum crop area required by an average farm family to:
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(i) maintain their minimum food energy needs,
(ii) obtain an annual cash income of approximately EB400 from the sale of crops (including cash crops such as coffee where this was possible),
(iii) meet the minimum area of fallow land required to sustain crop yields at current levels.
Where milk was an important part of the diet, the estimated per caput consumption rate was subtracted from the calorie requirement. The area of potential arable land for each land use system within each wereda was calculated using the crop suitability ratings established by MOA/UNDP/FAO17 for temperature, length of growing period and soil type These were calculated within the Project’s GIS, and exported to the population support capacity model. It was assumed that only 65 percent of the total arable area was available for cropping, the remainder being occupied by settlement, field boundaries, etc. Areas of "Undisturbed” and “Slightly Disturbed” High Forest, State Farms and National Parks were not included in the estimation of available arable land.
The analysis was conducted using the current population (1995) and the projected populations for the years 2005 and 2025. Weredas were then classified into the following 5 categories:
i. Critical: current population exceeds maximum support capacity by more than 120 percent ii. At Capacity: current population is between 100 and 120 percent of maximum support capacity. iii. Population will reach maximum support capacity within 10 years. iv. Population will reach maximum support capacity within 25 years. v. No Pressure: population will not reach maximum support capacity within 25 years.
4.2.8..3 Livestock feed balances
Given the importance of crop residues and dung as potential fuels, of residues as livestock feed, and communal grazing areas as a source of fuel wood, an analysis of the livestock feed supply balance was undertaken.
Potential production of three sources of livestock feed were estimated: grazing lands, crop residues, and the grazing on cropland stubble after harvest. The steps taken
17 MOA/UNDP/FAO (1986)
VOLUME III. STRATEGIC PLAN Page 51 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT in calculating potential forage production of natural grazing were as follows. The maximum potential climatic forage production was first calculated. This figure was then reduced according to:
- soil and relief type - degree of shading by trees and bushes - degree of access or availability where these limitations applied.
Potential climatic production was obtained by multiplying the length of growing period in days, by an estimated 15 kgs dry matter per growing day18. Above 1,500 masl a temperature reduction factor15 was incorporated into the estimate. Finally a utilization factor of 75 percent was applied. The potential climatic production estimate was reduced for certain soil and relief types: e.g. shallow soils and/or slopes in excess of 30 percent, and increased for other soil types which have a greater water holding capacity, e.g. Vertisols and valley bottoms. The resulting estimate was then reduced for woodland and bushland land cover classes to account of the effects of shading. Further reductions were made to account for the lack of accessibility in dense forest, woodland and bushland, and for cultivation in the moderately and sparsely cultivated land use classes. Crop residue production was estimated from land use system crop and yield models using reported grain-residue ratios, but applying a utilization factor of 50 percent to maize and sorghum residues. Forage production of grazing on cropland stubble were obtained from MOA/LEPRID estimates25.
Livestock feed requirements were estimated as 2 percent of live weight per day for maintenance only. The last detailed livestock census by wereda was the General Agricultural Survey (GAS) in 1983/4. However an examination of the annual livestock estimates of the CSAfrom 1980/81 to 1990/91 show a remarkable constancy in numbers, with cattle numbers fluctuating between 20.4 and 23.5 million head, sheep between 8.0 and 10.5 and goats between 5.1 and 6.4 million, but with no discernible trends either up or down over the ten years. This suggests that livestock numbers have probably reached the maximum carrying capacity of the land under the current livestock production systems, and that fluctuations about this figure have been caused by fluctuations in rainfall and thus feed supply. Livestock numbers for each wereda from the General Agricultural Survey
18 Cossins and Upton (1985)
19Radcliffe et al. (1988)
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Carrying capacity (CC) Stocking rate Status (%of estimated carrying capacity) Below Carrying Capacity <90 percent At Carrying Capacity 90 - 120 percent Above Carrying Capacity >120 percent
4.2.8..4 Physical and biological land degradation
The main type of physical degradation in the Project Area is soil erosion by water; and biological degradation involving the breaching of soil nutrient cycles (nitrogen and phosphorous) by the burning of dung and residues.
To determine the areas currently suffering from soil erosion, the Universal Soil Loss Equation (USLE) adapted for Ethiopia21 was used. The USLE uses five sets of factors to calculate soil loss in tons per hectare:
(i) erosivity of rainfall (ii) erodibility of soil (iii) slope (iv) slope length (v) land cover (vi) land management
The project obtained the values for these factors from data sets within the GIS. The rainfall erosivity factor of the USLE was applied to the 1:2 million map of mean annual rainfall; soil erodibility factors were applied to FAO soil units identified on' the MOA/UNDP/FAO 1:1 million soil geomorphology map; slopes percentages were derived from a digital terrain model created by the GIS from the 1:250,000 topographic maps of Ethiopian Mapping Agency; slope length was assumed to be related to slope angle; the land cover factors were based on the Project’s own land use and land cover map. To obtain a picture of the extent and severity of soil erosion which might result from the conversion of the present land cover (forests, woodland etc) to cultivated land, all land cover units were then set to the USLE value for cultivated land, with all other factor remaining the same.
20 Of 250 kgs live weight
21 Huni (1984)
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CHAPTER V SUPPLY AND CONSUMPTION OF WOODY BIOMASS AND OTHER BIOFUELS
5.1 Terminology
Three important terms used in this chapter require careful definition. A more detailed explanation of these terms is provided in Annex 1. They are stock, annual yield, and the sustainable harvesting rate.
Stock: the total weight per unit area of above-ground woody biomass from trees, bushes and shrubs excluding below ground roots.
Annual yield: the total annual increment per unit area of above-ground woody biomass from all trees, bushes and shrubs. This is a purely biological concept, and refers to the sum of the annual yield of individual woody plants of all ages and sizes, on a specific tract of land.
Annual sustainable harvesting rate: the annual woody biomass harvest (in tons) in one year, including trees which have died naturally, fallen twigs and branches and harvested live twigs and branches, which neither decreases the amount of standing stock nor impairs its future yield potential.
5.2 Methodology used to Obtain Estimates of Woody Biomass Stocks and Yields
A ” woody biomass” inventory differs in one fundamental respect from orthodox forest inventory ,in that an estimation of the total biomass was required including not only the stem, but also all main and subsidiary branches and twigs.
This entailed the destructive sampling of whole trees, bushes and shrubs. Given the large number of species involved (a total of 370 has been enumerated by the project), and the wide range in agro-climatic conditions and land use systems this was a task of some magnitude. Previous work in Ethiopia, as elsewhere has been confined mostly to an estimation of volume (not weight) of usable timber for a select group of “commerciar species which involves the measurement of only two parameters - diameter at breast height (DBH) and stem length.
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The two main issues in selecting a reasonably accurate and yet practical approach to such an inventory are the sampling methodology to be adopted, and the parameters to be measured. Statistically “pure” sampling methodology may not be the most practical, given the resources and time available. Thus there is need to consider the relationships between costs and benefits, accuracy and practicality.
After careful consideration and extensive fields trials of different methodologies, the project adopted the following approach. The project area was divided into a number sectors, each sector being representative in terms of agro-ecological zone (s) and land use system (e.g.. cereal crop, enset, agro-pastoral and pastoral systems). As the mam land use and land cover mapping units were found to be too variable in terms of homogeneity of land use/land cover, those units selected for detailed inventory were subject to more detailed survey using computerized digital analysis of the LANDSAT TM tapes to produce an unsupervised classification of between ten and twenty digital classes. These digital classes were checked in the field and assigned to land use/land cover types and entered into the GIS, and detailed area statistics produced. These were then used as a basis for determining the sampling pattern and intensity.
Because of the extreme spatial variability of land use/land cover types, even over very short distances (of tens of meters), two types of transect were adopted. In the denser vegetation types plots were sampled at intervals along the transect, whilst in open grassland and agricultural land a continuous line strip was used. The number of transects in each of the surveyed mapping units was a function of the total area of the mapping unit.
The location and direction of the transects were selected to cross as many land use/land cover types as possible, their lengths being a function of the relative proportions of the areas of each land use/land cover type. In the lowlands many transects had to be located along roads and tracks because of the difficulties of access. This was much less of a problem in the agricultural areas, although the presence of crops in the fields meant that agricultural areas could not be surveyed during the cropping season.
Felling (ie. destructive sampling) and weighing of all parts of trees, bushes and shrubs was undertaken to cover as many species, sizes, and agro-ecological zones as was possible. A relatively large number of plant parameters were measured. Although very time consuming, this has permitted an extremely thorough and detailed regression analysis to be undertaken to enable future field surveys to reduce considerably the number of parameters which will need to be measured. It will thus be possible to concentrate on only
VOLUME III. STRATEGIC PLAN Page 55 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT two or three key measurements, which will enable an accurate estimation of tree weight without the need to fell. This will allow future survey work to proceed at a much faster rate, with a considerable reduction in costs.
The land use/land cover mapping22 was undertaken using visual interpretation of hard copy LANDSAT Thematic Mapper (TM) false colour images, at a scale of 1:250.000. The interpretation was based on tones, patterns and textures as well as the false colour hues. The initial interpretation was extensively field checked, and the necessary revisions were made to the mapping units which had been delineated on clear acetate film. The mapping units were then digitized and incorporated into the GIS using PAMAP software. Some 10 major land use/land cover categories were recognized, which were further subdivided into 31 sub-categories. In agricultural areas the presence of trees, bushes and shrubs were described according to their pattern and density.
With regard to biomass consumption the project undertook a limited socio-economic survey using very limited resources. The recommendations of the Inception Report Workshop were that the project should utilize to the maximum existing data. Thus the project has supplemented its own data with the results of the very comprehensive rural and urban household survey undertaken by the Ethiopian National Energy Committee (ENEC, 1986)23 By way of comparison the ENEC Study covered some 7,617 households and 1,792 fuel wood carriers, compared with the project’s 350 households. However the project’s survey was more wide ranging, in that it encompassed the acquisition of data on other linked components of the farming/pastoral systems, such as crop and livestock production, in considerably more detail than the ENEC Study. Information on urban energy consumption patterns were obtained from the ENEC Study. The project’s data and the ENEC data were organized in relation to the land use systems identified by the project.
5.3 Supply Patterns of Woody Biomass
The project estimates for total biomass and annual yield in tons of air dy weight are shown in table 5.1 on a regional basis. They are presented by wereda in Appendix 1..
22 Note-A Land Use and Land Cover map is a “hybrid" in that it encompasses two different concepts: “land use" refers to the use to which the land is put: e.g. grazing, whilst “land cover refers to the vegetative and non-vegetative cover of the land: e.g. Woodland.
23ENEC -CESEN (1986)
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Table 5.1 Woody biomass stocks and yields by region: 1995
Region Supply (million tons air dry weight) Stock Total Yield Yield as % of Stock Arsi 22.68 0.70 3.1% Bale 40.58 1.46 3.6% Gamo Gofa 59.50 1.69 2.8% lllubabor 155.13 7.23 4.7% Kefa 138.39 6.29 4.5% Shewa 31.15 1.06 3.4% Sidamo 141.50 5.75 4.1% Welega 42.20 2.27 5.4% Total 635.63
There is a clear regional variation in both total standing stock and the annual yield, with Arsi lowest in both stock and yield and lllubabor highest in both stock and yield. Yield as a % of stock indicates the relative rate of growth of woody biomass Gamo Gofa has the lowest rate of growth: an indicator of its low rainfall, while Welega has the fastest rate of growth: a reflection of its high temperatures and relatively high rainfall. The yield is of importance when matched against consumption. Annual consumption which exceeds yield depletes the standing stock which in turn reduces yield.
5.4 Consumption Patterns of Woody Biomass
5.4.1 Consumption of woody biomass as fuel
The project amalgamated the results of its rural socio-economic household survey with those from the ENEC study, in order to obtain as complete a picture as possible of bio-fuel consumption patterns within the Project Area. The project did not undertake any urban fuel consumption surveys.24 Where both surveys were conducted in the same locality a comparison was made between data of the two surveys. The comparison indicated that little or no change could be discerned in either per caput rates or proportion of bio-fuels consumed over the past ten years, other than a slight increase in the use of crop residues. The ENEC Study had forecast a gradual decline (in national terms) in per caput consumption of bio-fuels of about 0.33 percent per annum, but with no changes in the woody biomass surplus areas of Kefa, lllubabor and Welega. An important change in the source of fuel wood for rural households’ appears to have occurred, with a large increase in the proportion of purchased fuel wood in rural areas. This is reviewed in the next section, and examined in more detail in the next chapter.
24 Following the recommendations of the Inception Report Workshop in 1992.
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Patterns of fuel wood consumption vary widely across the project area, mainly related to its availability. Availability also influences the total amount of household energy consumed from all sources There is a weak relationship between the increasing requirements for heat (for cooking and human comfort) with increasing altitude and lower temperatures. Socio-cultural differences and types of and times taken for cooking also affect total consumption patterns.
The highest per caput rates of fuel wood consumption are found in and around the high forest areas of the lllubabor Zone of Region 4 and the Kefa Zone of SEP Region where rates of between 1,800 to 2,200 kgs per annum were recorded. In areas where supplies are adequate the lowest consumption rates were in the agro-pastoral and pastoral areas of the southeastern and southern Lowlands, where annual per caput consumption rates are between 500 and 600 kgs , a reflection of the lower cooking requirements where milk and milk products form a large proportion of the diet. The highest rates of consumption in those areas where supplies are just adequate, are found in the western parts of Welega, and in the high altitude (Upper Dega and Wurch) areas of the Chilalo and Bale Mountains of Region 4. Per caput rates of between 1,600 and 1750 kgs were recorded in these areas. In the enset areas, which are relatively well endowed with on-farm tree resources, fuel wood consumption rates of between 1,120 and 1,400 kgs per annum are found. The lowest per caput rates of fuel wood consumption in the project area - between 120 and 350 kgs per annum - are found on the Vertisols plains of Arsi and northern Bale Zones of Region 4. On the Vertisols plains of East Shewa Zone, rates were slightly higher at 450-550 kgs per annum.
Rural per caput consumption rates of fuel wood and other bio-fuels are higher than urban rates. In the urban areas this is clearly a reflection of the higher prices which have to be paid (either in cash or time), the need for more care in fuel wood use, and the increasing use of modern fuels, particularly electricity and kerosene. Table 5.2 shows the weighted mean annual per caput rates of consumption for the old kiflehager in the Project Area. Per caput rates by wereda are presented in Appendix 1.
The annual per caput rates of fuel wood consumption in many parts of the Project Area are considerably higher than the average for Ethiopia which is approximately 700 kgs per caput. The weighted average for the whole of the Project Area is 1,170 kgs, reflecting the relatively better fuel wood endowment of many parts of the Project Area. By way of comparison annual per caput rates in South Africa are reported25 to be about 410 kgs and in Tanzania 540 kgs.
25 Quoted in Meyers and Leach (1989)
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Table 5.2 Weighted mean annual per caput consumption rates of fuel wood in the project area (kgs per annum)
Region Rural Urban Arsi 873 642 Bale 797 717 Gamo Gofa 998 546 lllubabor 1,695 792 Kefa 1,780 895 Shewa 1,209 911 Sidamo 894 496 Welega 1,486 856
The total consumption of woody biomass as fuel on a regional basis is shown in table 5.3, and on a wereda basis in Appendix 2.
Table 5.3 Total wood fuel consumption by region: 1995 (million tons of air dry wood)
Region Rural Urban Total Arsi 0.78 0.13 0 91 Bale 0.13 0.11 0.24 Gamo Gofa 1.57. 0.06 1.63 lllubabor 2.43 0.13 2.56 Kefa 6.42 0.23 6.65 Shewa 7.21 0.80 8.01 Sidamo 5.01 0.18 5.19 Welega 3.80 0.25 4.05 Total 27.35 1.89 29.24
Sources of fuel wood and other bio-fuels
The three main sources of bio-fuels are the household’s farm, the communal areas and by purchases. Other minor sources recorded by the project’s survey were, “community forest” and “state forest". There are distinct differences in the proportions of fuel obtained from the three sources in the cereal and the enset systems. Some two thirds of households in the enset systems obtain most of their fuel wood from the farm, whilst two thirds of households in the cereal systems obtain most of their fuel wood from the communal areas. This reflects the much higher rate of tree planting on farms in the enset systems, and the larger areas of communal lands in the cereal systems.
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The surprising figure to emerge from the project's household survey was the relatively high proportion of rural households who purchased fuel wood. In 1985 the ENEC Study reported that the proportion of fuel wood purchased by rural households rarely exceeded 5 percent, except in Tigray and Eritrea where it reached 30 percent. The project’s survey found that in the cereal land use systems 34 percent of all households were purchasing some fuel wood, with 18 percent purchasing more than 50 percent of their requirements. In the enset systems the figures were lower with 20 percent of all households purchasing some fuel wood, and 7 percent purchasing more than 50 percent of their requirements. This interesting phenomena is explored further in the next chapter
In the agro-pastoral and pastoral areas, some 95 percent of fuel wood is obtained from the communal areas with the remainder from the farms, as a product of the system of shifting cultivation.
5.4.2 Consumption of woody biomass for other uses
The major consumer of woody biomass is clearing for agriculture, particularly in the high forest areas of Bale, Sidamo, lllubabor, Kefa and Welega. An analysis was conducted in those weredas where there was high forest to determine the possible rate of deforestation caused by expanding population and its need for agricultural crop land. Farm families were assumed to increase at 2.9 percent per annum, and each family was assumed to dear the minimum area for cropping (as determined in the population support capacity analysis), and an equal amount for settlement and livestock grazing The annual area of forest cleared increase exponentially. The results by region are shown in table 5.4 and those for the relevant weredas in Appendix 2.
Table 5.4 Annual rates of high forest clearing for agriculture by region for 1995, 2005 and 2015 (hectares per annum)
Region 1995 2005 2015
Bale 13,260 17,830 27,770 Sidamo 10,570 14,690 22,880 lllubabor 31,100 41,800 65,120 Kefa 46,800 64,890 98,000 Welega 10,930 14,690 22,880 Total 112,660 153,900 236,650
Assuming the stocking rate for “disturbed” broadleaf forest of 50 tons dry wood per hectare, the annual weight of biomass cleared is shown in table 5.5. It must be noted that much of this wood will be used for fuel, construction of houses and other uses.
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Table 5.5 Annual Rates of Forest Clearing for Agriculture by Region for 1 9 9 5 , 2005 and 2015 (million tons of air dry wood)
Region 1995 2005 2015
Bale 0.66 0.89 1.39 lllubabor 1.56 2.09 3.26 Kefa 2.34 3.24 4.90 Sidamo 0.53 0.73 1.14 Welega 0.55 0.73 1.14 Total 5.64 7.68 11.83
Data at the wereda or regional level is not available for the consumption of woody biomass for other domestic uses (house and furniture construction, etc) and industrial uses The EFAP study assumed that new houses would be built at the same rate as popu ation growth (2.9 percent), and old houses replaced annual at a rate of 3 percent of total using 3m 3 of wood, or 2 tons of total air dried woody biomass (assuming unused twigs and branches used as fuel wood). These are shown in table 5.6.
Table 5.6 Annual rates of woody biomass consumption by weight for rural house construction by region for 1995, 2005 and 2015 (tons of air dry wood) Region 1995 2005 2015 Arsi 39,060 • 52,000 79,820 Bale 13,500 18,000 27,600 Gamo Gofa 34,480 45,890 70,460 lllubabor 25,480 33,900 52,100 Kefa 61,520 81,900 125,700 Shewa 130,500 173,700 2§6,700 Sidamo 99,380 132,300 203,100 Welega 62,660 83,400 128,000 Total 466,580 621,090 953,480
Current harvesting of timber from the high forests has been estimated by EFAP at 50,000 cu m or approximately 150,000 tons of total air dry woody biomass (includes branches and twigs).
5.5 Supply and Consumption Patterns of other Bio-Fuels
There appeared to be little or no use of other bio-fuels where per caput rates of fuel wood consumption exceed 1,000 kgs per annum, except in the lllubabor and Wellega
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Zones of Region 4, were residues rather than dung were used. Residues were also preferred to dung in those enset areas where fuel wood may be becoming scarce, e.g. in the Wollaita area of North Omo Zone of SEP Region Dung and residues appeared to be equally preferred as fuels in the Central Rift Valley cereal land use systems In the major fuel wood deficit areas of the Arsi, Bale and East Shewa Zones dung is used in preference to residues. This is probably due to the high value of wheat and tef residues as livestock feed, and their relatively poor value as fuel.
In all land use systems, the only source of residues is the farm. Although there is a small urban market for residues, none exists in the rural areas. Sources of dung differed between the two main land use systems. In the cereal systems two thirds is obtained from the communal areas and only one third from the farm, whilst in the enset systems, where total use was much lower, three quarters was obtained from the farm and only one quarter from the communal areas. The total consumption of residues and dung by region for 1995 is shown in table 5.7, and by wereda in Appendix 2.
Table 5.7 Total agri-residue and dung use as fuel by region: 1995 (million tons of air dry matter)
Agri-Residues Dung Region Rural Urban Total Rural Urban Total Arsi 0.188 0.002 0.190 1.209 0.008 1.217 Bale 0.040 0.000 0.040 0.522 0.008 0.530 Gamo Gofa 0.001 0.000 0.001 0.000 0.004 0.004 lllubabor 0.054 0.001 0.055 0.000 0.000 0.000 Kefa 0.246 0.004 0.250 0.000 0.002 0.002 Shewa 1.326 0.006 1.332 0.515 0.006 0.521 Sidamo 0.120 0.002 0.122 0.028 ,0.022 0.050 Welega 0.018 0.004 0.022 0.000 0.001 0/001 Total 1.993 0.019 2.012 2.274 0.051 2.325
5.6 Woody Biomass Supply-Consumption Balances
The woody biomass supply and consumption balances have been calculated for the twenty year period - 1995 to 2015 assuming that rates of consumption remain the same. This is clearly not correct as rates of consumption decline as the availability of fuel wood declines. However the analysis does provide a picture of how critical some weredas and regions are with respect to existing and impending deficits. The table 5.8 provides data on the percent of current annual yield which is being consumed - the greater the percent the more a region is “mining” its woody biomass resources. It also indicates the amount
VOLUME III. STRATEGIC PLAN Page 62 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT and percentage of woody biomass stocks which will remain if consumption continue at current rates. Finally the number of weredas in the region which are currently consuming more than their woody biomass yield is also indicated The data is provided at the wereda level in Appendix 2.
Table 5.8 Woody biomass balances: 1995 to 2015
Region Stocks remaining after 20 years No. of weredas million tons % of 1995 stocks exceeding yield in 1995 Arsi 6.89 30% 18 out 21 Bale 28.52 70% none Gamo Gofa 34.07 57% 11 out of 22 lllubabor 116.32 75% 13 out of 34 Kefa 53.38 39% 21 out of 39 Shewa 1.24 4% 57 out of 58 Sidamo 103.39 73% 19 out of 37 Welega 0.22 1% 38 out of 46 Total 343.03 65% 177 out of 260
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CHAPTER VI ACHIEVING THE SUSTAINABLE DEVELOPMENT AND MANAGEMENT OF WOODY BIOMASS RESOURCES
6.1 Analysis of Issues
Given the close links between bio-fuel supply and consumption, and with crop, livestock and tree production in the Ethiopian land use systems, an examination of these linkages in the project area is required. The first part of the chapter looks at a number of issues relating to bio-fuel production and consumption, with particular reference to woody biomass. This provides a basis for the examination of some of the potentials for and constraints to the sustainable development and management of the Project Area's woody biomass resources. In order to provide a framework within which the results of the analysis can be meaningfully described, and for which recommendations can subsequently be made, the land use systems of the project have been grouped into "w oody biomass development zones”. These are listed in table 6.1 with their attributes
Table 6.1 Woody Biomass Development Zones
1. Perennial Crop Systems: temperature and rainfall not limiting
1 .a. Enset land use systems: few indigenous trees in landscape 1 .b. Enset land use systems: many indigenous trees in landscape
2. Cereal Crop Systems: temperature and rainfall not limiting
2.a. Cereal land use systems on vertisols: few to no indigenous trees in landscape 2.b. Cereal land use systems in Central Rift Valley: moderately stocked with indigenous trees 2.c. Cereal land use systems in Central Rift Valley: lightly to very lightly stocked with indigenous trees 2.d. Cereal land use systems on non-vertisols in Central and Western Highlands: moderately to lightly stocked with indigenous trees
3. Cereal Crop Systems: temperature no constraint, but rainfall limiting
3.a. Cereal land use systems in Eastern and Southern Lowlands, and Southern Rift Valley: well to moderately stocked with indigenous trees 3.b. Cereal land use systems in Eastern and Southern Lowlands, and Southern Rift Valley: moderately to lightly stocked with indigenous trees
4. Shifting Cultivation Systems
4.a. Shifting cultivation land use systems: well to moderately stocked with indigenous trees 4.b. Shifting cultivation land use systems: moderately becoming lightly stocked with indigenous trees
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5. Agro-Pastoral Systems
5.a. Agro-pastoral land use systems with shift cultivation: currently moderately stocked with indigenous trees 5.b. Agro-pastoral land use systems with shifting cultivation: becoming lightly stocked with indigenous trees
6. Pastoral Systems
6.a. Pastoral land use systems: lightly stocked with indigenous trees 6.b. Pastoral land use systems: well to moderately stocked with indigenous trees
7. Areas of High Forest
8. State Farms
6.1.1 Woody biomass supply and consumption balances
In general the project area is relatively well endowed with woody biomass stock resources. However 177 out of the 260 weredas in the project area are harvesting well above the sustainable rate, and stocks are thus being depleted. The situation in each of the woody biomass development zone are outlined below.
1. Perennial Crop Systems: temperature and rainfall not limiting
1 .a. Enset land use systems: few indigenous trees in landscape
In these systems on-farm production of trees is at its greatest development, not only in the project area, but in the whole country. Trees and bushes are grown as hedges in and around the homestead and infields. Trees are also grown as woodlots. However under increasing population pressure nearly all areas are exceeding the sustainable yield of the present woody biomass stock.
1 .b. Enset land use systems: many indigenous trees in landscape
The major area of concern in these areas is the destruction of woody biomass stocks by farmers, who clear woodland and forests for agriculture. This is occurring in the high forest areas of Sidamo, lllubabor, Kefa and Welega. While there is no immediate concern in terms of energy supply given the large amount of scattered trees which remain in the landscape, there is considerable concern with regard to the loss of valuable timber, biodiversity, the negative impacts on the hydrological cycle and the great increase in soil erosion.
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2. Cereal Crop Systems: temperature and rainfall not limiting
2.a. Cereal land use systems on vertisols: few to no indigenous trees in landscape
These comprise two of Ethiopia’s three major cereal surplus producing areas. It is most likely that before these poorly drained areas were settled by man they were natural grasslands with few trees. The lack of woody biomass has resulted in a relatively lower use of all fuels, and an increase in the relative proportion of the two main other bio-fuels: dung and crop residues. Because of the high proportion of land which is under cultivation, these areas are generally deficient in natural grazing, and crop residues form a high proportion of the livestock feed. In addition, the main cereals grown - wheat and tef - are poor fuels compared with maize and sorghum stalks.
Dung thus provides a high proportion of the household energy supply - up to 70 percent in parts of Arsi, and 30 percent on the Vertisol plains of Central and Eastern Shewa. Soil fertility in these areas is maintained by the use of chemical fertilizers. These more or less replace the 30 to 40 kgs of nitrogen per hectare lost or foregone by burning dung. With the increasing cost of fertilizer, farmers are reducing the rates they apply. If the current dung burning rates continue, a gradual depletion of soil nutrients will result, and crop yields will decline. A farming systems study by the Institute for Agricultural Research 26 confirms that this is already occurring in Arsi.
2.b. Cereal land use systems in Central Rift Valley: moderately stocked with indigenous trees
These systems are around the Lakes and in the centre of the Rift Valley floor, in the driest part of the Central Rift Valley. The area is under active clearing for crop production, notwithstanding the high risk of drought. Along the main road, felling for charcoal production, has accelerated since 1991, and is severely reducing stocks.
2.c. Cereal land use systems in Central Rift Valley: lightly to very lightly stocked with indigenous trees
These areas of the Rift valley have been settled for agriculture longer than those in the centre. Areas of communal grazing, traditionally the source of fuel wood, are rapidly diminishing under the expansion of cropland. Trees remaining in the fields are heavily pollarded, and their reduced to a minimum. The EFAP Farm Forestry Study estimated production of pollarded trees (Croton machrostachyus) at about 0.13m3 per annum (or about 85 kgs). Assuming the average farm size in this area of 2 ha, then a family of six
26 See chapter 11 “Farming Systems of the Kulumsa Area” in Franzel and van Houtens (1993)
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2.d. Cereal land use systems on non-vertisols in Central and Western Highlands: moderately to lightly stocked with indigenous trees
Areas near to roads and densely populated areas are already only lightly stocked with trees. There is some on-farm production of trees, particularly around homesteads. The rates of rural consumption in these areas are boosted to some extent by the export of fuel wood to Addis Ababa, and to the large number of urban centres in these areas. However given the rapidly increasing demand for construction poles of Addis Ababa and these towns, and the recent deregulation of the market, the production of both fuel wood and poles by peasant farmers is becoming an economically viable enterprise.
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3. Cereal Crop Systems: temperature no constraint, but rainfall limiting
3.a Cereal land use systems in Eastern and Southern Lowlands, and Southern Rift Valley: well to moderately stocked with indigenous trees
In these areas fuel wood supply has not become a problem, except locally around urban centres. However cropland is expanding rapidly as agro-pastoraL families increasingly take to crop production in response to declining livestock assets.
3.b. Cereal land use systems in Eastern and Southern Lowlands, and Southern Rift Valley: moderately to lightly stocked with indigenous trees
The areas on the Southern Rift Valley floor, south of Soddo, have been increasingly settled by agriculturalists from the over populated areas of Chencha, Wollaita and Konso. over the past five decades. Although stocks are relatively high, in areas of settlement they have been largely depleted. Some areas have been totally cleared for state farms. On the long settled upland areas of Burji, Konso, and Gidole stocks are rapidly being depleted, and consumption rates are well above the sustainable yield. In the Konso area, there has been an increase in the planting of trees in farm land, particularly of the indigenous Juniperus. The cabbage tree (Moringa oleifera) is very common throughout the western side of the Southern Rift Valley, where the leaves are both human and livestock feed.
4. Shifting Cultivation Systems
4.a. Shifting cultivation land use systems: well to moderately stocked with indigenous trees
These systems are found in the southwestern, the Gambela, Western and Abay Lowlands. Low population densities have allowed the extensive system of shifting cultivation to be practiced, with long bush fallow periods enabling complete regeneration of the woody biomass stocks. However, the use of fire for hunting by local people and those from adjoining more densely populated areas, is causing a reduction in standing stocks.
4.b. Shifting cultivation land use systems: moderately becoming lightly stocked with indigenous trees
These areas are found mainly in the Western and Abay Lowlands, where population densities have increased, and fallow periods are insufficient to allow complete regeneration of woody biomass stocks. The increased amount of hunting with the use of
VOLUME III. STRATEGIC PLAN Page 68 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT fire is exacerbating the decline in stocks. The reduction in tree and bush cover has, however, reduced the tsetse challenge, and increasing numbers of cattle are being kept.
5. Agro-Pastoral Systems
5.a. Agro-pastoral land use systems with shift cultivation: currently moderately stocked with indigenous trees
These systems are found to the west of the lower Omo river, in Kefa, and in the Hamer Uplands in South Omo. West of the Omo, population densities are relatively low. However there has been an increase in the amount of cropping due to the loss of livestock assets over the past two decades. This is accelerating the decline in woody biomass stocks. In the Hamer Uplands increasing population pressure is leading to a reduction in bush fallow periods, and stocks in the most densely populated northern part of the area are now declining.
5.b. Agro-pastoral land use systems with shifting cultivation, lightly stocked with indigenous trees
These systems are found on the east bank of the lower Omo river, where rainfall is less than 600mm. Woody biomass stocks are naturally low. Burning, to initiate growth of grasses and to deliberately maintain low tree and bush stocks, also contributes to the low stock levels.
6. Pastoral Systems
6.a. Pastoral land use systems: lightly stocked with indigenous tree.s
These areas are found in western Gambela where there are large areas of seasonally inundated and poorly drained land. This maintains a naturally low stocking rate of trees and bushes.
6.b. Pastoral land use systems: well to moderately stocked with indigenous trees
These cover the Somali and Borana pastoral areas. In recent years bush encroachment has become a problem. The long term dynamics of herbaceous and woody biomass stocks is complex, and has been briefly described in Annex 2. Encroachment of woody biomass is the result of over grazing, and also two decades of a prohibition on burning by the government (rescinded in 1990).
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6.1.2 Cropland population support capacity analysis
To determine the degree of population pressure in terms of the land’s capacity to support the current and projected population, an analysis was undertaken of the cropland population support capacity. Given the reconnaissance level of some of the land resources data, and the provisional nature of some of the data on crop areas and yields, the analysis is only indicative. However the results broadly indicate where the main areas of population of pressure occur.
The results of the population support capacity analysis, assuming present technology levels are shown on end map 11. The main areas of. population pressure are as follows:
1. Perennial Crop Systems: temperature and rainfall not limiting
1 .a. Enset land use systems: few indigenous trees in landscape
2. Cereal Crop Systems: temperature and rainfall not limiting
2.a. Cereal land use systems on vertisols: few to no indigenous trees in landscape 2.b. Cereal land use systems in Central Rift Valley: moderately stocked with indigenous trees 2.d. Cereal land use systems on non-vertisols in Central and Western Highlands: moderately to lightly stocked with indigenous trees
Other smaller areas include the northern Bale Highlands, the immediate areas around the towns of Kibre Mengist, Mizen Teferi, Metu, Bedele and Dembi Dolo. These areas, together with the Bonga and Jimma Zones, are constrained by the high forest, which was excluded from the category “available” arable land. In fact the population is expanding into the high forest areas in their search for more arable land. The map shows the locations of these pressure points.
The areas with no apparent pressure are as follows:
5. Agro-Pastoral Systems
5.a. Agro-pastoral land use systems with shift cultivation: currently moderately stocked with indigenous trees 5.b. Agro-pastoral land use systems with shifting cultivation: becoming lightly stocked with indigenous trees
6. Pastoral Systems
6.b. Pastoral land use systems: well to moderately stocked with indigenous trees
However the analysis only focusses on the supply of energy derived from crops, and in these areas much of the energy requirements of the people in these areas are obtained
VOLUME III. STRATEGIC PLAN Page 70 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT from livestock products or grain purchased from the sale of livestock products. Only a relatively small proportion of the available cropland is being cropped, except in the lower Omo valley where all river bank cropping sites have been occupied. Negative food balances are caused by seasonal and yearly fluctuations in milk supply which is affected by rainfall and forage availability. As households' livestock assets decline, and cropping assumes a greater role in providing subsistence then pressure on suitable cropping sites will build-up, given their limited extent.
6.1.3 Livestock feed balances
Given the importance of crop residues and dung as potential fuels, of residues as livestock feed, and communal grazing areas as a source of fuel wood, an analysis of the livestock feed supply balance was undertaken.
The main cereal producing areas, which appear to be overstocked are in the Vertisols plains of the Arsi and north Bale Highlands, the Central Rift Valley from Shashamene to the Bilate river, and Lake Abaya. However this may be an over estimation, because cattle from the Arsi and Bale Highlands are taken to the Wabe Shebele Lowlands during the rainy season, thus relieving the livestock feed shortages when crops are in the ground at this time. The overstocking in the southern parts of the Central Rift Valley is evidenced by the visible signs of overgrazing and land degradation. Another area which is now showing signs of overgrazing, but does not appear to be overstocked in the analysis, is the area to the south of Agere Mariam. Here a large area of potential grazing has not been used recently, because of disputes between the Borena and the Guji Oromo cattle owners.
The enset areas of Hadiya, Kambata, Wollaita and Jimma Zones appear to be overstocked, but again this may be an over-estimation. In these land use systems on-farm production of fodder is quite common, and detailed data were not available from which to estimate the contribution made by enset leaves, which are known to be a significant part of the livestock feed supply. The Sagen Valley and the Teltele Plateau area of Borena appear to be overstocked, although this may be caused by an under estimation of forage production on the alluvial plains and the delta of the Sagen river.
The highest livestock densities in the Project Area are in all the mam enset producing areas, where they exceed 150 TLU’s per km2, compared to less than 90 TLU’s per km2 in many of the cereal land use systems. Livestock production in these systems is very intensive. The main areas of livestock concentration in the Arsi, Bale, East, West and South Shewa and Jimma Zones of Region 4, and the Hadiya, Kambata and North Omo Zones of SEP Region. These areas are at their ecological carrying capacity, and no
VOLUME III. STRATEGIC PLAN Page 71 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT further increase of livestock numbers is possible under the present livestock production systems. Parts of South and East Shewa have stocking rates of between 70 and 90 percent of their carrying capacity, which indicates that even here there is little or no potential for any major increase in numbers. In the Abay, Western and Gambela Lowlands tsetse infestation currently prevents any major expansion of the current low levels of livestock numbers.
An analysis was undertaken of the percent of residues consumed as livestock feed (assuming that only 50 percent of maize and sorghum residues are eaten). This showed that where stocking rates approached the potential carrying capacity of the grazing lands, the total proportion of crop residues consumed as livestock feed rose considerably. In the Vertisol plains of East and West Shewa, residues constitute up to 80 percent of livestock feed supplies. The analysis also indicated that on a wereda basis, not all grazing resources were apparently utilized. This could be explained by the fact that some Farmers Associations may be over endowed with grazing resources, in relations to their livestock numbers, and given the general rule in cultivated areas that prevents livestock from one Farmers Association grazing in another, this may mean that there are some underutilized resources.
6.1.4 Land use systems integration and dynamics
In many of the land use systems within the project area, there are clear linkages among the different components: crops, livestock, tree and bio-fuel production. The strength of these linkages varies among the systems. They are weak or even absent in the agro-pastoral and pastoral systems, and strongest in the enset systems, in particular in the very densely populated areas of Kambata, where population densities exceed 750 persons per km2. There is a clear relationship between population density and the degree of integration of the above main land use system components.
Two factors are responsible for changes in the direction and strength of these relationships: increasing population (in the absence of changes in production technology) and the need to increase the area of crop land. These changes result in competition for land among the different uses, and between inputs and outputs of crop and livestock production. Some of these dynamics are outlined below.
Expansion of cropland encroaches either onto the communal grazing land and woodlands, or into the forests, including the National Forest Priority Areas (NFPA’s) and National Parks. The reduction in the areas of grazing land and woodland also leads to encroachment of forests, and of other lands such as pastoralists’ reserve grazing areas, National Parks and State Farms. Two phenomena may occur when there is no more
VOLUME III. STRATEGIC PLAN Page 72 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT communal or other land on which to encroach: (I) an intensification of crop production through changes in technology (including crops) and/or practices, and/or (ii) an increase in the number of land less people. For the latter, the alternatives are selling labour to other farmers or pastoralists; engaging in non-farm activities e.g. fuel wood collecting, beer making, etc; or seasonal or permanent migration out of the area.
The decline in the area of natural grazing land results in increased pressure on livestock feed resources, and a greater use of crop residues as livestock feed. Residues thus attain an economic value, and may even be sold. Supplies of fuel wood are also reduced as more communal lands are converted to individual crop land. The ENEC survey and the Project’s household survey indicate that significant switches to residues and dung do not take place until the fuel wood situation becomes critical. Households tend to use fuel wood more and more efficiently, for some considerable time. The identification of this process is of importance when determining where and how to promote programmes of improved wood fuel stoves.
A major factor determining the proportion of residues consumed as fuel is their value as livestock feed. Where this value is high, then only the poorest livestock feed will be used for fuel: e.g. in the Arsi and Bale Highlands, and the Debre Zeit - Mojo Plains. In these areas dung is the main fuel. The depletion of soil nutrients caused by burning dung is replaced by chemical fertilizer. In those system where manure is extremely important for crop production: e.g. in the enset and root systems, then dung normally not used as fuel.
Any solutions or interventions to relieve the pressures on one particular component: e.g. crop production, must take into consideration the type, direction, and strength of the linkages with other components, and the dynamics of change in these relationships.
In the project area, integration between land use system components has gone furthest in the enset systems. In these systems individually held cropland has encroached almost entirely on to the communal lands. Only in the enset systems of the southwest highlands of Kefa, Mocha and South Omo Zones of SEP Region and lllubabor and Jimma Zones of Region 4 are there still extensive areas of high forest available in which to expand. Crop, livestock and tree production is extremely intensive: both on a per hectare and per labour unit basis. In the cereal systems the degree of integration is less strong. It varies from very strong integration between crop, livestock and bio-fuel production in the Arsi and Bale Highlands, to little or none in the shifting cultivation, agro-pastoral and pastoral systems in the Lowlands.
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6.1.5 Land and tree tenure issues
W hile the Constitution has settled the main issues of land tenure, there is an unresolved issue in the cereal areas. Here the crop land is not generally enclosed, and it is open to grazing by all members of the community. This discourages farmers' from planting trees along bunds and field boundaries, and from under sowing annual crops with legumes for fodder consumption in the dry season. The trampling of soil conservation structures by livestock, also discourages farmers from investing in these structures or in their maintenance.
The Constitution and policy statements by the government guarantee farmer’s rights to dispose of trees which they have planted as they wish While these rights are guaranteed, a potential issue could arise if government decided to place a sales tax on trees and /or tree products. Given the long history of insecurity of tenure of trees in Ethiopia, and the consequent lack of tree planting by farmers in many areas, this type of action could act as a strong disincentive to invest except for use on the farm.
6.1.6 Conservation of biodiversity in forests and woodlands
High forests have two functions: environmental and economic. The environmental functions are to;
i. Act as a repository of genetic resources, ii. Provide faunal and floral habitats, iii. Protect soil and water resources, and this control the discharge of water to streams and rivers, and iv. Act as a sink for C02. (in connection with global warming)'
conomic functions include providing:
i. A source of timber. ii. A source of forest products and other forest related activities (e.g. bee keeping). iii. A source of land for agriculture for anever increasing human population. Iv. A source of energy
There is a clear potential for conflict between these two sets of functions.
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A second issue has been the State's inability to exert control and exercise its use and management rights over the whole of the forest estate. The forests and forest lands of the NFPAs have come to be regarded as "open access" resources. This has been exacerbated in many cases by the absence of clearly demarcated and gazetted boundaries. With the increasing shortage of agricultural land around the NFPAs, encroachment for settlement, cultivation and grazing has occurred. A related issue has been the lack of consultation with local communities during the NFPA demarcation and management planning process.
Another issue has been the annual harvesting of 50 000 m 3 of timber (approximately 133,000 tons of air dry wood), together with the annual destruction of about 5.64 million tons of woody biomass from the high forest areas for agricultural expansion including coffee and tea estates.
In many NFPAs a very high proportion of the forest is heavily disturbed, and the remaining part of the forest land within the boundaries of the NFPA is classified as "other land". This mostly comprises settlement and cultivation. In nine of the NFPAs in the Study Area, the category of "other land" accounts for over 80 percent of the area of these NFPA’s. A first priority in implementing the new Forestry proclamation will be for the Central Government and Regional Administrations to identify and designate areas of forest and forest land as "Protected Forests". A second priority will then be to identify State and Regional Forests. The new Forestry Proclamation describes the function of Protected Forests as;
i. Conserving the soil from desiccation, erosion and degradation as well as maintaining and improving soil fertility,
ii. Protecting and improving the status of water bodies, sources of rivers and catchments,.
iii. Controlling floods.
iv. Protecting rare and endangered endemic plants, animals and birds species, and genetic resources in general, and
v. Conserving unique and representative habitats or natural resources.
The Proclamation makes provision for the declaration of land with little or no vegetation as a Protected Forest. There are thus two major sets of objectives: those related to what might be termed "catchment" protection, and the second related to protection of bio diversity. The two sets are, of course, complementary and mutually reinforcing.
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6.1.7 Physical and biological land degradation
The main type of physical degradation in the Project Area is soil erosion by water, and biological degradation involving the breaching of soil nutrient cycles (nitrogen and phosphorous) by the burning of dung and residues.
The analysis reveals that the Project Area is relatively free of soil erosion in view of its large areas of highland forest and lowland woodland when compared with northern Ethiopia. Given the lack of livestock in the western Lowlands there is generally of good grass cover where the woody vegetation becomes sparse. Critical areas for soil erosion under the present land cover pattern, are found along the western escarpment of the Central Rift Valley, the western escarpment of the Sidama highlands, and along the steeper cultivated slopes of the Central and Western Highlands overlooking the Abay, Didessa, Gojeb and Gibe Gorges. The analysis does not identify the sheet erosion occurring on the erodible granite derived soils on relatively gentle slopes in Western Welega Zone of Region 4, and the Asosa Zone of Region 6.
In the project area some 2.3 million tons of dung are burnt as fuel. In terms of soil nutrients lost this amounts to approximately 97,000 tons of DAP chemical fertilizer or 223,700 tons of cereal grain foregone.
6.1.8 Socio-Economic Issues
In developing strategies for farm forestry, it is important to note that it can form part of a broader package of inputs, with multiple social and economic benefits. The latter can include some or all of the following:
- production of fuel sticks and fuel wood, leading to decreased use of dung to fuel and its increased use as manure, thereby increasing crop production
- increased fodder production leading to increased livestock production
- production of poles for sale
- production of timber for sale
- production charcoal for sale
- creation of shade (for man and animals)
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- marking boundaries, corralling livestock
- creating wind breaks leading to increased crop production
- bee keeping and honey production for sale and home consumption
- low cost seedling production (when compared large centralized government nurseries)
- higher seedling survival rates
In any economic analysis of farm forestry, there is a need to think in terms of individual trees and not of an area of forest. In terms of yields and growth rates It is possible that growth of free standing trees is 3 to 6 times faster than that of trees in a plantation. It is known for example, that in the Sahel, scattered heavily lopped (i.e. po.larded) trees in agricultural land can yield 10 times more woody biomass than trees in natural woodland 27. In many of the enset areas, total biomass is planted at densities much higher than in a plantation using a standard 8-12 year rotation. The harvest strategies of small farmers growing Eucalyptus in these dense stands include a 2-3 year rotation (based on a coppicing regime) for the trees cut for fuel wood; with a 3-4 year rotation for much fewer trees cut for short poles. They retain the occasional scattered tree for long poles on 7-8 year rotation. Thus the area of woodlot required by a farm family is almost certainly much less than that projected using plantation production estimates.
Farmers and their wives and children are most interested in fuel “sticks” or twigs, fuel wood or light poles. They have little interest in the very thick stems usually produced in an industrial plantation. There is a fundamental difference in the economics of tree growing between the industrial plantation strategies developed in North America and Europe, and those developed by small peasant farmers in Sub-Saharan Africa. In Europe and North America revenue is maximized when the stem diameter is large because this gives economies of scale when processing the wood for industrial timber and pulp. The difference in costs and revenues between the Europe/North American strategy and that of the small farmer in Sub Saharan Africa is shown in the two diagrams below.
In Ethiopia however, revenue is maximized when the stem diameter is quite small because: the major end uses are (I) slender construction poles, (ii) fuel wood, twigs and leaves, (iii) fodder. In economic terms labour requirements are low because cutting is by hand (with a machete); benefits are realized relatively quickly; and there is a steady stream of benefits with coppicing annually for fuel sticks and leaves.
27 Dewees quote in Leach and Mearns (1988)
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Figure 6.1a Costs of and revenues from European/North American forests
rtem cfcamofcar «/ruU 16cm
Figure 6.1b Costs and revenues of the tree production strategy of small peasant farmers in Ethiopia
small terjfi
Surveys in an area of Kenya, very similar in terms of agro-ecology and land use in Kambata and Hadiya in Ethiopia, revealed that as population densities rose, so too did the standing stock of woody biomass. As population densities rise, farm sizes fall, so he percentage of the farm area planted to trees rises. There are a number of reasons for this
VOLUME III. STRATEGIC PLAN Page 78 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT apparent paradox:
although tree production and the sale of tree products give lower returns per hectare than cash crops (e.g. coffee) they do give higher returns per unit of labour.
small households often face a labour shortage.
tree management has lower start up costs than cash crops.
in any analysis, gender division is important: men often own trees and prefer to obtain cash for poles in contrast women’s' needs for wood for fuel.
Thus in any economic analysis of farm forestry strategies, there is a need to examine carefully the socio-economic variable at the individual farm level. Trees are also important in farmers’ strategies for minimizing risks as:
- trees can provide a continuous flow of products throughout the year, or at a time when there are no other sources of income.
- trees can be a form of saving: i.e. act as a store of wealth which can be liquidated as and when required.
All of these factors are assuming growing importance in the project area, now that it appears a rural market in fuel wood is emerging.
6.1.8 Poverty and woody biomass harvesting for income support
The Project’s household survey revealed the considerable extent to which rural households are now purchasing fuel wood: up to 37 percent of households in cereal land use systems, and 20 percent in the enset systems. This figures contrasts sharply with the results of the ENEC Study some ten years ago, suggesting that a rural, as distinct from a purely urban, market has developed. It appears that some households or household members, whose role it is to collect fuel wood, are finding that the costs involved (in time) exceed the benefits to be derived from alternative activities. These alternative activities could include crop and/or livestock production, beer making, or off farm employment.
^or some households or household members the reverse is true In many areas there are an increasing number of landless individuals and even households. The number of landless was swollen in the period immediately after the change in government by ex-soldiers and refugees returning to their home villages. It is possible that these landless households and individuals are forming the nucleus of the rural and urban-fuel
VOLUME III. STRATEGIC PLAN Page 79 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT wood collectors and sellers. There is evidence from Borena Zone of Region 428, that households who have lost most of their livestock assets are living on the edges of the main towns, subsisting on the sale of milk and fuel wood This is an important issue which needs to explored much more fully at the local level, in order to determine who are the fuel wood collectors, in order to ensure that any on-farm tree development programme for farmers with land does not marginalize those people without land.
6.1.9 Peoples participation: formal and non-formal institutions and organizations
A major finding of this project, and one which is confirmed from other studies in Sub-Saharan Africa, is that the fuel wood problem is one of considerable complexity and that it is inextricably linked to all the other parts of the rural economy. In Ethiopia, it is extremely diverse, and conditions are thus extremely “localized" in their characteristics. Strategies for the sustainable development of woody biomass must be sufficiently flexible to take account of this diversity, while the possible solutions proposal must address these local problems. The best people to determine the appropriateness of these are the local people. Participation of local people in any woody biomass programme by government or non-government agencies must, of necessity, be developed in close partnership with local people and communities: agricultural and non-agriculture, rural and urban.
6.2 The Potential for and Constraints to the Sustainable Development and Management of Woody Biomass Resources
A number of strategies have already been formulated by the Ethiopian Forestry Action Programme (EFAP). These, and other strategies formulated by the project are examined here, within the context of the woody biomass supply and consumption patterns, and other environmental and socio-economic conditions found in the Project Area.
6.2.1 Farm Forestry
A number of farm forestry “Tactics” are suitable for Ethiopian land use systems. Many of these are already in use in parts of the Project Area. They include:
- windbreaks - tree planting in homestead compound - on-farm woody legume planning (for fodder) - field tree planting - field boundary tree planting - tree planting in gullies
28 Coppock (1995)
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- roadside tree planting - woodlots (high density for poles) - woodlots (low density for wood and fodder)
The highest potential for farm forestry will be found in the cereal land use systems which are experiencing critical shortages of fuel wood: the Vertisol cereal systems in Arsi, Bale, West and East Shewa Zones of Region 4. The major problem with establishing trees in croplands is the practice of opening these lands to communal grazing after harvest. The major potential thus lies with homestead tree planting, where trees are beyond the reach of browsing animals. A previous constraint in the old villagized settlements was the shortage of land around the homestead. This has been removed now that many of these settlements have dispersed. Whether communities would agree to a change in the access rules for croplands and allow enclosure and exclusion of livestock after harvest is not known.
The second potential area for farm forestry development would be on the floor of the Central Rift Valley, where woody biomass deficits have or are emerging. On the eastern side of the valley (near Arsi Negele and Shashamene) there is already a tradition of tree planting. This is not as well developed on the western side (between Alaba Kulito, Dalocha and the Soddo Uplands). Towards the center of the Rift Valley floor, fuel wood deficits are not yet critical enough to encourage farmers to plant trees, except for forage purposes around homesteads. The depletion of woody biomass for charcoal production along the main road between Ziway and Negele may encourage charcoal burners to plant trees, but this unlikely given that cropland is still expanding and there are no landless people.
6.2.2 Community Forestry
This strategy has had an unfortunate history in Ethiopia, and is associated with’the centraliy directed campaigns of tree planting of the previous government. These were largely sited on scarce grazing land, and were instituted with little or no participation of local communities. Many of these plantings received little maintenance, and many of those which had survived, were destroyed in the disturbances following the change in government in 1991.
There may be a role for “Community Forestry" in the forested areas of the Bale, Sidama and Southwest Highlands where there are patches or even relatively large tracts of disturbed forest. These may have been left because they were not the best arable land Where haphazard and unplanned encroachment of high forest is taking place, there could be role for a participatory planned approach to agricultural expansion, leaving selected areas of forest as “Community Forests” for coffee production and for the protection of
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Ethiopia’s wild coffee gene stocks, timber, minor forest products (medicines etc) and bee keeping. The main constraint to this type of Community Forest development will be to evolve a genuine dialogue with concerned communities, taking sufficient account of their specific needs, and to allow these communities to retain total control over the use and management of these forests. There may also be a problem in finding a suitable mechanism to supply the very limited funds that such community resource management of initiatives would require.
6.2.3 intensification of crop production in areas of agricultural expansion and deforestation
The aims of this strategy would be to decelerate the expansion of agriculture into the high forest areas, through the intensification of crop production on existing cropland. The potential for this strategy is low given that crop production in these enset-root systems is already intensive in terms of production per hectare. However there may be some potential for increasing production of the main cereal crop, maize, with the introduction of higher yielding varieties currently being promoted by the MOA. Another tactic could be a programme of improved coffee production techniques, leading to higher cash incomes which may reduce the need for large areas of other crops. Possibly the best strategy is to replace the current haphazard encroachment of agriculture by the participatory planned approach to agricultural expansion and community forest development outlined in section 6.2.7.
6.2.4 Intensification of livestock production and development of fuel wood in areas of critical woody biomass deficits
The aims of this strategy would be to meet both the need of fuel wood and the need to help relieve the livestock feed deficits in the critical fuel wood deficit areas of the Arsi and northern Bale Highlands, and the Vertisol plains of East and West Shewa. The tactics would include the promotion of multi-purpose tree production The harvested leaves could be used to supplement crop residues and improve their digestibility as well as providing fuel wood supplies. Given the constraints outlined in the section on farm forestry with regard to community grazing on cropland in this area, such developments would have to start in and around the homestead. A point of entry for the forage component could be the use of the leaves as a supplement to crop residues for calf feeding to reduce the current high mortality rates and to work oxen before and during land preparation.
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6.2.5 Intensification of crop production in the shifting cultivation and agro-pastoral land use systems
Some areas of shifting cultivation in the Abay and Western Lowlands are already approaching the limit of their population support capacity under the present system of bush fallowing. This requires a total area of 18 to 20 hectares of fallow land per farm family, to maintain 2.5 to 3.0 hectares of land which is cropped each year. The strategy would be to improve soil fertility on cropland, and to assist in weed suppression, and so prolong the “life” of the land for cropping. Already there are some livestock in those areas where the tsetse challenge has been reduced following to the clearing of the dense woodland and bushland. The tactics would borrow from two traditional systems of soil fertility maintenance and weed suppression currently practiced in western Ethiopia. The shifting night corral system of Western Welega and Asosa could be adopted for use in these areas to increase the levels of soil fertility. The weed mulching methods of the Majangir to suppress weed growth, and increase soil organic matter, and therefore moisture holding capacity and fertility, could also be adapted.
The strategy would have the highest potential only in those areas which have reached or are approaching their population support capacity limit under the present system of bush fallowing, and where fallow periods are starting to decline. Its potential in other areas of low population pressure would be negligible.
6.2.6 Control of bush encroachment in the Ethiopian Rangelands
ILRI have studied the short and long term cycles of the range ecology in the Southern Lowlands29. In the short term, woody vegetation expansion and soil erosion occur when livestock numbers build-up during years of good rains. Following drought and the ensuing “crash” in livestock numbers, the subsequent recovery of herbaceous vegetation and cover depends on the rainfall patterns during the ensuing post drought phase. Thus low rainfall may lead to permanent bush encroachment and soil degradation, whilst good rains during the post drought phase may lead to full recovery. However in the absence of extensive burning of the range and the gradual increase in livestock numbers, the long term trend is for woody vegetation to increase at the expense of herbaceous vegetation.
With increasing town growth there will be an increased demand for fuel wood and charcoal. Trees around urban centers and along roads are increasingly being harvested by poorer pastoral households and urban dwellers to generate income The strategy is to rehabilitate the traditional fall back grazing reserves. These areas now being encroached
29 Coppock (1995)
VOLUME III. STRATEGIC PLAN Page 83 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT by Acacia thicket, thus restricting the ability of the Borena land use system to respond adequately to droughts and prolonged dry seasons. The aims of the strategy would be to:
reclaim areas of encroaching woody vegetation in the main rangeland areas, through bush control, prescribed burning regimes, and site restoration and regulated charcoal production
increase carrying capacity, through the provision of water and forage improvements in the cleaned fall back areas
reduce livestock numbers through sales and holding cattle in non-livestock form as saving accounts in local banks, and using funds generated to undertake development works
The main constraints to this strategy may be the transport costs to the main charcoal markets in Addis Ababa and South and East Shewa, as the markets for charcoal in the Southern Lowlands are very small.
6.2.7 Development and conservation of forests and woodlands
The major problem is how to integrate the potentially competing needs of: land for subsistence agriculture the sustainable supply forest products (wood and minor products) for subsistence the sustainable commercial supply of wood for timber and fuel the conservation of forest ecological, environmental and life support functions the conservation of bio-diversity
It is increasingly recognized30 that forests are reasonably robust in their ability to recover from localized and periodic disturbance (e.g. falls, fires, low intensity shifting cultivation). Selective harvesting constitutes a disturbance which may be compatible with conserving much of a forest's ecological and life support systems functions as well as much of its bio-diversity. Although it is not possible to protect all bio-diversity, it is possible to minimize loss with careful forest harvesting and management.
As with the integration of wildlife conservation with subsistence agriculture, the
30 McNeely etal (1990)
VOLUME III. STRATEGIC PLAN Page 84 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT I strategy is to establish an integrated system of protected areas, production forests and sustainably managed agricultural systems of production. The various categories of forest for protection, conservation, sustainable harvesting and temporary and permanent clearing for agriculture and settlement follow the principles outlined in Annex 2.
The strategy would be to identify and delineate areas of various categories of representative natural forest, for designation under the Forestry Proclamation. It is recommended that the topology of forests outlined by Friis and Mesfin Tadesse be used to define "representative" types of forest for conservation and protection. These are described in Annex 2. The strategy would be, that as a minimum, at least one NFPA or part thereof containing at least one of the representative types of forest, be set aside as a fully Protected Forest. Six of the seven representative forest types occur in the total Study Area. No riverain Forest has been designated as an NFPA. The Arba Minch Ground Water Forest is located within the Nechisar National Park and thus, in theory, is already protected. However it may be that this forest requires inclusion as a Protected Forest under the Forest Proclamation, given the current lack of legal status for the Nechisar National Park.
The NFPAs have been categorized into the five representative forest types which are found in the project area and rank ordered, firstly in terms of their area of "slightly disturbed" forest, and secondly in terms of their area of "heavily disturbed” forest. Additional information on endemic tree species would be required.
For each of the five representative forests in the project area, and using the categories outlined in Annex 2 as a basis, the gross area of the NFPA or NFPAs selected, would be divided into a number of conservation and development zones. Criteria for the definition of the various conservation and development categories would be based, as far as possible, on existing uses and users. General criteria would include:
degree of disturbance: there will be a need to clearly define this term in order to easily identify such areas, and survey them in the field; - proximity to existing settlement and agricultural areas; existing uses and users: this will include traditional rights of access, to use, to gather, to settle, etc.
Specific criteria for area selection would include:
bio-diversity representativeness: in particular of genetic strains (e.g. wild coffee), of species (trees, shrubs, herbs, etc), of communities (tree and shrub associations), and of habitats for flora and fauna, degree of impact of continued existing uses
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danger, risk, or probability of increasing intensity of existing uses, with negative impacts in the future degree of ability to manage and protect
The categories could include the following:
i. Scientific Reserves ii. State and Regional Protected Forests iii. State and Regional Forests iv. Wetland Reserves v. Multi-Purpose Land Use Zones
The potential for this strategy will depend on surveys of bio-diversity in the high forests, in order that representative areas can be properly identified for conservation However this would only be required for delineating the Scientific Reserves, as sufficient information is known about the broad distribution of species. The main constraint will be obtaining the participation of large numbers of communities, in order that a comprehensive and coordinated plan of conservation activities can be instituted. Inter-regional cooperation will be required in the southwest forests, where Regions 4, SEP Region and the Gambella Region all share areas of contiguous forest.
6.3. Reducing the Demand for Woody Biomass Resources
This section briefly examines strategies for reducing the demand for woody biomass resources in the context of energy supply. Two main strategies are reviewed: an increase in the efficiency of use of fuel wood, and switching to alternative energy sources.
6.3.1 Increasing efficiency of use
Studies in Ethiopia and elsewhere indicate that households start to increase efficiency in using fuel wood as soon as collection costs increase. Traditional stoves can be made more efficient with care, however the main advantages of the improved stoves which are now being promoted is their consistency in efficiency. A major stove review from the users’ perspective31 listed the following characteristics that an improved stove should have:
- closely match present cooking patterns, including functions (e.g. mitad baking, wot cooking), size, space, range of fuels and cooking utensils (pots, plates, etc)
31 S. Joseph in Leach and Mearns (1988)
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save time spent collecting fuel (linked with fuel-efficiency), cleaning pots and kitchens (linked to smoke reduction)
more fuel efficient
reduce smoke, eye and lung disease
in rural areas, use local materials, reduced maintenance
be aesthetically pleasing, providing prestige without resentment
act as a vehicle for giving women greater confidence in their ability to improve their life.
Whilst fuel efficiency and time saving are important, other factors are also of importance when considering the adoption potential for an improved stove. Whilst the needs of stove adopters are now recognized, the mam constraint now appears to be organizing a sustainable programme for their construction and marketing.
It is difficult to forecast with certainty which areas are likely to prove most receptive to improved stoves. Taking into consideration the costs and supply of wood fuel ,it is likely that urban users are more likely to adopt them than rural users, most particularly the improved charcoal stoves. However.the picture is complex, given the competition from other fuels such as kerosene and electricity. In the rural areas it may be that fuel wood deficit areas are more likely to have more potential than the wood surplus areas. Thus the Arsi and northern Bale Highlands, and the Vertisols plains of East and West Shewa may have the greatest potential. Within these areas, households which are now purchasing fuel wood may be more likely to adopt such stoves than others.
6.3.2 Alternative Energy Sources
In urban areas there is clear evidence of the in-roads made by kerosene which is replacing fuel wood for cooking. In Addis Ababa electricity is replacing fuel wood for mitad baking, whilst in the rural areas kerosene and diesel are replacing fuel wood for lighting. As woody biomass fuels become more scarce these alternative fuels will have an increasing potential to replace fuel wood. A major constraint will be the transport and distribution of kerosene to many rural areas, given the poor road infrastructure.
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CHAPTER VII STRATEGIES AND PRIORITIES
7.1 A Multi-Sectoral and Participatory Approach
The Project’s woody biomass inventory and household surveys have revealed the complexity of both the supply and consumption of woody biomass fuels. The project area is extremely diverse in terms of its environmental, ecological, socio-cultural and economic characteristics. The supply and consumption of woody biomass and other bio-fuels are closely linked with other components of the rural economy: crop and livestock production and other off-farm activities. Outputs from one component can, and do, act as inputs to one or more other components. Within this complex system, there are defined roles for men, women and children with regard to these production and consumption activities. Given the wide range of objectives of rural and urban families which are specific to Ethiopia, the economics of these activities do not conform to models developed in Europe and North America. Finally the rapidly increasing rural and urban populations, and their demands on natural resources in general, and woody biomass in particular are increasingly having an impact on the complex web of relationships between the different components in the rural- urban economies.
The implications of these findings on the approach to be adopted to strategic planning for the sustainable development of the project area’s woody biomass resources are outlined below.
1. The complexity of woody biomass supply and consumption patterns in the project area is such that simple and global statements of what should be done, can not be made. Each situation in an particular area has its own unique set of characteristics. Any analysis and prescription should be based on a local approach, made in close participation and collaboration with the communities in the area. The lack of such an approach to woody biomass planning and implementation in the past has led to failure.
2. The complexity of the linkages among the different rural and rural-urban production, supply, marketing and consumption activities in the Project Area, means that a land use systems approach to planning should be adopted, in which the various activities can be analyzed in a holistic way. The approach seeks to understand how the farm or pastoral household, and the communities to which they belong, and their crop, livestock and woody biomass resources (trees, bushes and shrubs), all interact with each other and with the wider natural, socio-cultural and economic environment.
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3. The different roles played by men, women and children in these various production, supply, marketing and consumption activities require that they should each be intimately involved in the planning, design, implementation and monitoring of projects and programmes for woody biomass development and conservation.
4. The great range of indigenous technologies for crop, livestock and woody biomass production and use within the project area, should be built upon in any development or introduction of new technologies.
5 The planning for the conservation, protection and development of the remaining high forest and woodland areas of the project area, should be based on the active participation and cooperation between the central, regional and local governments and the communities likely to be affected. The roles, responsibilities and needs of all the levels of government and of communities must be recognized and respected.
6. Given the close linkages between agriculture and bio-energy production and consumption, an inter-sectoral approach to both should be followed. In institutional terms, this will involve closer collaboration between the central Ministries and the Regional Bureaus of Agriculture on the one hand, and Mines and Energy on the other.
7.2 Direct Strategies for Sustainable Development and Conservation of Woody Biomass Resources
These strategies seek, in a direct way, to conserve and increase the supplies of woody biomass. Their potentials and constraints have been examined in the previous chapter.
7.2.1 Farm Forestry
The various farm forestry practices proposed under this strategy have been outlined in section 6.2.1, and in many parts of the Project Area some of them form part of a set of existing local practices. The objective would be to pursue a flexible approach, which could suit the needs of individual households, and would also fit into the local agricultural landscape. Two examples illustrate the principles involved. The flexible approach in terms of woody biomass products is best illustrated by the graph in Fig. 7.1.
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Figure 7.1 Nested rotation cycles for the management and harvesting of trees on farms32
rotation period (years)
Fig. 5
This shows a set of nested rotation cycles for the management and harvesting of trees and wood products on the farm, which closely resembles current practices in the Kambata Zone of the SEP Region.
The approach to be adopted for designing interventions within an agricultural landscape using vacant socio-ecological niches33 is illustrated below with the complex agricultural landscape of Kambata Zone in the SEP Region. It indicates a number of approaches which might be adopted.
22 Van Gelder (1987)
33 A socio-ecological niche is an element of the agricultural landscape (e.g. a live hedge, homestead garden) which has an actual or potential use and which is subject to specific rules of tenure.
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Figure 7.2 Agricultural landscape of the Kambata Zone of the Southern Ethiopian Peoples’ Region showing socio-ecological niches for potential interventions for increasing woody biomass
Previous attempts to quantitify farm forestry interventions have generally been given in area terms: i.e. hectares, following commercial “plantation” models. If the agricultural landscape and the socio-ecological niche model is followed then the terminology and the concepts change. The terminology is now cast in that used by farmers: i.e, trees in fields, trees and bushes in hedges, trees along field boundaries, trees in spare patches of land in field corners.
This concept has been followed in the present plan to quantify the farm forestry strategies being proposed for the project area. From the woody biomass balance model, estimates were obtained for each wereda by Woody Biomass Development Zone, of the difference between the current total (i.e. rural and urban) woody biomass consumption and
VOLUME III. STRATEGIC PLAN Page 91 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT the sustainable yield of current stocks. For those weredas which were exceeding the sustainable yield, the weight of woody biomass deficit was calculated per farm family. Three potential farm forestry strategies wewre assessed:
- single row hedging (trees planted 30-50 cms apart in single rows, harvested every four years, producing 16.5 kgs per meter length per annum34)
- double row hedging (as single row spacing, producing 33 kgs per meter length)
- annual pollarding of Croton machrostachyus trees in fields or in hedges, (producing 90 kgs per tree per annum)
The per farmer estimates of single and double row hedging, and pollarded trees per fasrm and per hectare (at current farm sizes) are presented in table 8.1 for each of the Woody Biomass Development Zones, where consumption is currently exceeding sustainable yield.
Table 7.1 Tree planting estimates required per farm to meet current woody biomass deficits: agrgregated by Woody Biomass Development Zone:1995
Woody Biomass Single Double Total No. Trees/ha Development Zone hedge hedge of trees in in fields Fields (Meters) (Meters) Zone 1a:Enset:few trees 305 153 56 80 Zone 1 b:Enset:many trees 388 194 71 51 Zone 2a:Cereal:vertisols 117 59 117 59 Zone 2b:Cereal:C.Rift (mod. stocks) 179 89 33 15 Zone 2c:Cereal:C.Rift (light stocks) 329 164 ' 60 32 Zone 2d:Cereal:W.&C.Highlands 192 96 35 18 Zone 3a:Cereal:E & S Lowlands 88 44 16 8
The high deficits in Zone 1b may be partially a result of the analsysis deliberately excluding areas of “high forest”, when calculating the available woody biomass. It is possible that farmers are, in fact, obtaining some of their supplies from this source. It is also a reflection of the very high consumption rates by rural people in a situation of very high stocks. Harvcesting in excess of sustainable yield is difficult to perceive in this situation.
34 Estimates from EFAP Farm Forestry Consultant Group 1 Report: Volume 1, 1992
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A most Zones a mix of strategies will be prefered. In the cereal zones, planting (or leaving) trees in fields will be easier than in the enset zones because of the larger farm area in the former zones Thus hedges, even triple or quadruple planted, are an easier strategy in the enst zones. In the cereal zones of the southern and eastern lowlands, relatively few trees left in the fields are sufficient to make up deficits.
7.2.2 Community Forestry
This would differ from previous strategies and would focus on the areas in the Bale and lllubabor Highlands of Region 4, and the Sidama, Mocha and Kefa Highlands of the SEP Region. It would seek, through the active participation of concerned communities, to set aside areas of intact (though disturbed) high forest, in areas of active agricultural encroachment. The specific purposes for each community forest, their management and exploitation practices would be worked out between the communities and the relevant agricultural bureau staff. Such Community Forests could form a sub-set of initiatives recommended in the more comprehensive strategy for forest and woodland conservation and development set out in section 7.2.3.
7.2.3 Development and conservation of the current areas of forest, designated as National Forest Priority Areas (NFPAs)
The strategy for the development and conservation of the NFPAs has been set out in outline in the previous chapter. Details are given here of the different land use categories into which these forest lands would be placed during a number of comprehensive and participatory planning and development programmes. Annex 2 provides details on each of the individual NFPAs in the Project Area, and an indication of their bio-diversity and production values, their degree of disturbance, and the existing levels of encroachment by agriculture.
The categories are detailed below indicating how they may be used: i. Scientific Reserves
These will be relatively small areas,of primary or secondary forest, which represent prime examples of different highland and lowland forest and bamboo communities. They will constitute "core" or total preservation areas, reserved for scientific study and as in situ gene banks, with all human activities excluded. The size of these scientific reserves will be as large as possible within the prevailing socio-economic constraints. The perimeter to area ratios will be minimized, to maximize the regeneration of the maximum number of species.
VOLUME III. STRATEGIC PLAN Page 93 WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT I ii. Wetland Reserves:
Within the designated forest areas there are a number of wetland sites which would receive special conservation status because of their hydrological importance. iii. State and Regional Protected Forests
These will be relatively large areas of primary or secondary forest which will represent prime examples of a range of forest types (e.g. down an attitudinal topo- sequence), and/or which constitute a refuge area for wildlife. In Annex 2 an attempt has been made to make a preliminary selection of those NFPA’s which should receive priority treatment. Human activities would be limited to existing uses, such as gathering (fruits, etc) and apiculture. They would provide the first buffer zone around the Scientific Reserves. The problem of destruction of the Lowland Forest by the burning of both Anuak and Majangir, needs to be addressed through negotiated agreement as to where burning and hunting would not be permitted, and by the setting aside of areas where burning and hunting could take place. iv. The Majangir Forest Reserve
This would comprise the current territory of the Majangir. All existing land use and management practices would be permitted, as these are still within the forest's capacity to sustainably support them. No other agricultural or forestry activities would be permitted within the reserve. Scientific Reserves could be established in consultation with local Majangir communities. v. State and Regional Forests
These areas could be set aside for sustainable harvesting of timber. Specific harvesting practices would be established to ensure the maximum conservation of biodiversity and catchment protection. These may include:
selective felling of designated species
clear felling of selected areas and/or sites
leaving forest corridors to link Scientific Reserves, and Protected, State and Regional Forests, thus ensuring that habitats at known major resting sites, and known ends of migration routes are retained. vi. Multi-purpose Land Use Zones:
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These would constitute the main agricultural and settlement areas. They would also include areas of forest reserve, set aside for future clearing for permanent or shifting agriculture; or for community forest areas for gathering forest products, apiculture, fuelwood, etc.
7.2.4 Industrial and fuel wood plantations
The government’s Investment Proclamation and the new Forestry Proclamation both provide for private investment in forestry. There are a number of existing forestry plantations in the project area, which are now under the control of the Regional administrations. It is not possible in a report of this nature to make policy or strategic proposals regarding the mix of public and private (including small farmer) investments in this sector. The Project has prepared within its GIS, suitability classifications for all the main industrial and fuel wood species, and can on request advise central and regional governments on areas which are environmentally suitable (in terms of soils and climate) for this type of development. EFAP has undertaken a detailed study on the future demand projections for industrial and construction timber. These could form the basis for further detailed planning.
7.3 Indirect Strategies for Sustainable Development and Conservation of Woody Biomass Resources
Indirect strategies refer to those initiatives which indirectly affect the amount of forest and woodland, which might be destroyed for agriculture or which can assist in increasing the production or supply of woody biomass.
7.3.1 Intensification of crop production in areas of agricultural expansion and deforestation
This strategy aims to slow the expansion of agriculture into areas of undisturbed or slightly disturbed forest, by increasing production per hectare of existing crops, or by increasing farm incomes from existing farm land. It will be focussed on the forested areas in the Arsi, Bale, Borena and lllubabor Zones of Region 4; those of the Kefa and Mocha Zones of SEP Region, and of the Gambela Region. Two tactics are proposed; increasing maize yields through the promotion of higher yielding varieties and promoting improved coffee management practices to increase yields.
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7.3.2 Intensification of livestock production and the development of fuel wood
This agro-forestry strategy aims to meet the needs for fuel wood and at the same time reduce the livestock feed deficits. The tactics would be to promote the use of multi purpose leguminous trees to produce both fodder and fuel wood as part of the farm forestry strategy. The strategy would be focussed on the critically fuel wood deficit areas of the Arsi and northern Bale Highlands, and the Vertisol plains of East and West Shewa, where there are also livestock feed deficits. The strategy would also be promoted in the enset areas where non-forage species of trees and bushes could be replaced by multi purpose trees thus intensifying production in these areas.
Leguminous trees can be important suppliers of nitrogen, which enables them to contribute to the nitrogen pool in the homestead garden. It is unlikely that farmers in the cereal land use systems would plant such trees within their croplands, given the current practice of communally grazing croplands after harvest. In the enclosed fields of the enset land use systems these trees could be planted as hedgerows or in woodlots.
7.3.3 Intensification of crop production in the shifting cultivation and agro-pastoral land use systems
The aim of this strategy is to prolong the cropping cycle in these areas, thus slowing down the rate of bush clearing which is currently accelerating under increasing population pressure. This in turn would decrease the amount of total land required per household, yet maintain and even improve current crop yields. The tactics would be to promote two traditional systems of crop and land husbandry found in western Ethiopia. The first is the weed mulching system of the Majangir to suppress the build-up of weed growth which accompanies continual cropping in these areas. The second would promote the moving cattle corral system practiced in highland Welega, as a means of maintaining soil fertility. The priority areas would be where fallow cycles are already being reduced due to population pressure, particularly in the Konso and Hamer areas of South Omo Zone in the SEP Region, and the Western and Abay Lowlands of Regions 4 and 6.
7.3.4 Control of bush encroachment in the Ethiopia Rangelands
This strategy would adopt, on a pilot basis, the proposals set out by the Southern Rangelands Project and ILRI for the Borena area. It would promote the clearing of bush encroached land by private entrepreneurs, and the production of charcoal from the woody biomass. A detailed investigation of the costs and benefits would be required. The target population would be households who have suffered critical losses in their livestock assets and the target areas the bush encroached areas nearest to access roads..
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7.4 Reducing the Demand for Woody Biomass
The two strategies outlined in this section seek to reduce the demand on woody biomass resources by increasing efficiency in use of woody biomass, and promote alternatives to bio-fuels.
7.4.1 Increasing efficiency in use
The elements of the strategy have been set in section 6.3.1 and involve the promotion of improved charcoal or wood stoves. The strategy would also meet other identified needs of traditional stove users - women and children - such as reducing smoke and thus smoke induced eye and lung diseases; saving time used to collect fuels, as well as to clean utensils and kitchens (caused by excessive smoke); and increasing the empowerment of women to improve their own well-being and that of their families.
The target areas and populations are difficult to determine in a reconnaissance study of this nature; but suggestions have been made to target criticality fuel wood deficit areas, and households which have started to purchase fuels. There is a clear need for detailed local studies and consultations with local communities and particularly women, before embarking on such a programme. There is also a need to determine the type of stove production and marketing system that will be required. This will also require detailed consultations with potential entrepreneurs.
7.4.2 Alternative Energy Sources
The main alternative energy sources to bio-fuels are kerosene and electricity (and perhaps diesel oil in rural areas for lighting). There are complex issues involved here, which the Project had neither the mandate nor the resources to investigate. These issues invo've pricing policies; the type, scale and locations of any expansion of electricity supplies (national grid and isolated sites); and the potential role of the private sector in the supply and distribution of kerosene and diesel, in the generation of electricity, and in the manufacture of electrical and kerosene lighting, heating and cooking appliances.
The remarkable speed with which energy switches can be made has been observed in Addis Ababa over the past ten years. Thus this strategy has tremendous potential for relieving the increasing pressures on the nation’s woody biomass resources, crop residues for livestock feed, and animal dung for maintaining soil nutrient supplies
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REFERENCES
Carr, C (1977) “Pastoralism in Crisis: the Dassenetch and Ethiopian Lands”, Dept. Of Geography, Univ. Of Chicago.
Central Statistical Authority (1987) statistical Abstracts for 1988/1989, CSA, Addis Ababa.
Central Statistical Authority (1992) Population Estimates of Regions, Awrajas, Weredas and towns: 1992. Statistical Bulletin 101, Addis Ababa.
Chaffey, D.R. (1979) Southwest Ethiopia Forest Inventory Project: A Reconnaissance Inventory of the Forests in Southwest Ethiopia: Report 31, ETH10-04-6/REP-31/79, Land Resources Development Centre, United Kingdom.
Chilot Yirga et al (1993) “Farming Systems of the Kulumsa Area, Arsi”, ch. 11 in Research with Farmers: Developing Technologies and Policies for Agriculture in Ethiopia. (Ed) by S. Franzel and Helen van Houters.
Coppock, L (1995) The Borana Plateau of Southern Ethiopia: Synthesis of pastoral research, development, and change, 1980-1991. ILCA Systems Study 5, Addis Ababa.
Cossin, N and M. Upton (1987) “The Borana Pastoral System of production”, Agricultural Systems, 25:199-218.
Dewees, P (1987) “The Woodfuel Crisis Reconsidered”, draft paper (Oxford Forestry Institute, Oxford.
ENEC-Cesen (1986) Main Report, Ethiopian National Energy Commission, Addis Ababa
ENEC-Cesen (1986) Technical Report 1: Biomass Energy Resources, Ethiopian National Energy Commission, Addis Ababa.
ENEC-Cesen (1986) Main Report, Ethiopian National Energy Commission, Addis Ababa.
ENEC-Cesen (1986) Technical Report 7: Rural/Urban Household Energy Study - Part 1: Design, Organisation, and Basic Report, and Part 2: Compendium of Survey Results. Ethiopian National Energy Commission, Addis Ababa.
ENEC-Cesen (1986) Technical Report 8: The Energy Forecasting Model, Ethiopian
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National Energy Commission, Addis Ababa.
ENEC-Cesen (1986) Technical Report 12: New and Renewable Energy Technologies Ethiopian National Energy Commission, Addis Ababa.
Friis i and Mesfin Tadesse (1990) “The Evergreen Forests of Tropical Northeast Africa, in Ihlenfeldt, H-D, ed. Proceedings of the Twelfth Plenary meeting of AETFAT, Miit. Inst. Allg. Bot. Hamburg, Band 23a, 249-263.
Government of Ethiopia (1994) National Policy on the Resource Base, its Utilization, and Planning for Sustainability (NCS) Volume I, Addis Ababa.
Government of Ethiopia (1994) Ethiopian Forestry Action Programme, Addis Ababa.
Huni, H (1983) “Soil Erosion and Soil Formation in Agricultural Ecosystems in Ethiopia and Northern Thailand, Mountain Research and Development, 3, 2: 131-142.
Joseph, S (1987) “An Appraisal of the Impact of Improved Wood Stove Programmes: Synthesis of Experience", in Stoves for People: Proceedings of International Workshop. Guatemala., Utrech.
Kidane Mengistu (1994) “Forest Management Systems of Ethiopia: Overview and Options for the Future Development”, presented at conference on Participatory Forest Management held at Addis Ababa, 17-18 March, 1994.
Leach, G and R. Mearns (1988) Beyond the Woodfuel Crisis: People. Land and Tress in Africa. Earthscan Publications, London.
MOA/UNDP/FAO (1987) Assistance to Land Use Planning Project: Phase I, FAO/UNDP- ETH/78/003, Rome.
MOA/UNDP/FAO (1988) Master land Use Plan, MOA, Addis Ababa.
McNeely, J et al (1990) Conserving the World’s Biodiversity. IUCN, Gland, WRI, Cl, WWF-US and the World Bank.
National Meteorological Service Agency (1989) Climatic and Agro-Climatic Resources of Ethiopia, NMSA, Addis Ababa.
Radcliffe et al (1998) Land Evaluation of the Hosaina Area, AG:DP/ETH/82/010: Field Document 22, Addis Ababa.
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Refsdal, R (1987) "Small is Beautiful: the Local Markets should be Studies", paper for Workshop on Practical methods for Community Land Management in African Drylands (Hurdalsjoen, Norway: CARE/NORAGRIC).
Soil Conservation Researc Project (SCRP) (1986) Soil Conservation in Ethiopia., MOA, Addis Ababa.
Sutcliffe, J.P. (1992) Peoples and Natural Resources in the North and South Omo and Kefa Administrative Regions of Southwest Ethiopia, MPED, Addis Ababa.
Turton, D (1977) “Looking for a Cool Place: 1890-1990's” in The Ecology of Survival Case Studies from Northeastern African History, ed. By Johnson D.H. and Anderson, D M Westview Press.
Webb, Patrick, Joachim von Braun and Yisehac Yohannes (1992) Famine in Ethiopia Policy Implications of Coping Failure at National and Household Levels, Research Report 92, International Food Policy Research Institute, Washington DC.
Westphall, E (1975) Agricultural Systems of Ethiopia, Centre for Agricultural Publications and Documentation, Wageningen.
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APPENDIX 1.
Table A1.1 National Forest Priority Areas Located within the Current Project Area
SFCDD NAME OF FOREST NO (NFPA) Ha TOTAL Zone/Region
1 Chillalo-Galema 22,000 Arsi/Region 3 2 Arba Guga 21,000 Arsi/Harerge/Region 3 3 Deme-Laha 30,000 North Omo/SEP Region 4 Bulki-Malakoza 11,000 North Omo/SEP Region 5 Gidole-Kamba 16,000 North Omo/SEP Region 13 Abobo Gog 218,000 Gambela Region (12) 14 Gebre Dima 165,000 lllubabor (Region 4) 15 Sigma Geba 280,000 lllubabor (Region 4) 16 Yayu 150,000 u n 17 Abelti Gibe 10,000 Kefa/SEP Region 18 Belete Gera 174,000 u n 19 Babiya Fola 74,000 u 20 Tiro Boter Becha 85,000 u n 21 Gudere 160,000 u 22 Sele Andeacha 225,000 u 23 Sibotole Kobo 100,000 lllubabor (Region 4) 24 Bonga 52,000 Kefa/SEP Region 25 Gura Ferda 140,000 u « 26 Yeki 122,000 u n 27 Gedo 10,000 W.Shoa/Region 4 28 Gibat Muta Gegenfo 121,000 u n 29 Chilimo Gagi 22,000 u n 31 Yerer-Dire-Gerbicha -Zukuala 12,000 East Shewa/Region 3 32 Butajira 15,000 South Shewa/Region 3 33 Menegesha Suba 15,000 Addis Ababa Region 34 Anferara-Wadera 50,000 Borena/Region 3 35 Bore 50,000 Sidama/SEP Region 36 Megada 20,800 Borena/Region 3 37 Negele 10,000 Borena/Region 3 38 Yabello-Arero-Mega 40,000 Borena/Region 3 39 Gerfeda 70,000 Gambela Region 40 Jongo Wato 20,000 Welega/Region 4 41 Konchi 13,000 u n 42 Leucho Dale Gewi 50,000 u 43 Chato Sengi Dengeb 63,000 u 44 Komto Waga Tsige 37,000 u 45 Gidame 22,000 Asosa/Region 5 46 Dodola-Adaba-Lago 59,000 Bale/Region 3 47 Aloshe-Batu 40,000 Bale/Region 3
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SFCDD NAME OF FOREST NO (NFPA) Ha TOTAL Zone/Region
48 Goro-Bele 100,000 Bale/Region 3 49 Harena-Kokossa 182,000 Bale/Region 3 50 Mena-Angetu 190,000 Bale/Region 3 51 Kubayo 60,000 Bale/Region 3 55 Munessa-Sashamene 98,200 South Shewa/Region 3
Total 3,425,170
Source: Kidane Mengistu (1994)
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APPENDIX 2
POPULATION SUPPORT CAPACITY ANALYSIS
VOLUME III. STRATEGIC PLAN Page 103 PRENDIX 2: TABLE A2.1 UMMARY OF POPULATION SUPPORT CAPACITY ANALYSIS: ARSI EGlON/wereda RURAL POPULATION SUPPORT CAPACITY RSI Potential current/ yr 10/ yr 25/ Code wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
.01.01 Merti 60483 133,849 45% 61% 95% No Pressure .01.02 Aseko 56711 107,760 53% 71% 110% At Capacity within 25 yrs .01.03 Guna 56525 101,937 55% 75% 116% At Capacity within 25 yrs .01.04 Chole 63390 54,265 117% 157% 245% Critical .01.05 Golelcha 122347 134,403 91% 122% 191% At Capacity within 10 yrs .01.06 Jeju 100747 125,686 80% 108% 168% At Capacity within 10 yrs .01.07 Sirie 98040 109,483 90% 120% 187% At Capacity within 10 yrs .02.08 Dodota 54137 75,498 72% 96% 150% At Capacity within 25 yrs .02.09 Hitosa 114846 148,611 77% 104% 162% At Capacity within 10 yrs .02.10 Zuway & Dugda 84520 80,969 104% 140% 219% At Capacity .02.11 Tiyo 78246 88,655 88% 119% 185% At Capacity within 10 yrs .02.12 Digelu na Tiyo 97708 173,956 56% 75% 118% At Capacity within 25 yrs .02.13 Munesa 142374 257,958 55% 74% 116% At Capacity within 25 yrs .02.14 Limu & Bilbilo 113872 277,910 41% 55% 86% No Pressure .02.15 Gedeb 101123 223,815 45% 61% 95% No Pressure .02.16 Kofele 148541 305,357 49% 65% 102% At Capacity within 25 yrs .02.17 Shirka 149885 174,573 86% 115% 180% At Capacity within 10 yrs .03.18 Tena 96100 96,441 100% 134% 209% At Capacity within 10 yrs .03.19 Robi 99465 181,455 55% 74% 115% At Capacity within 25 yrs .03.20 Suda 123938 176,883 70% 94% 147% At Capacity within 25 yrs .03.21 Amigna 57322 102,901 56% 75% 117% At Capacity within 25 yrs 2,020,320 3,132,366 64% 87% 135% At Capacity within 25 yrs APPENDIX 2: TABLE A2.2 SUMMARY OF POPULATION SUPPORT CAPACITY ANALYSIS: BALE REGION/wereda RURAL POPULATION SUPPORT CAPACITY BALE Potential current/ yr 10/ yr 25/ Code # wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
32.06.12 Mida Walabo 35,147 280,773 13% 17% 26% No Pressure J2.06.13 Mena 28,530 215,505 13% 18% 28% No Pressure 02.06.14 Berbere 27,378 74,808 37% 49% 77% No Pressure 02.06.15 Erena Bulk 21,398 118,845 18% 24% 38% No Pressure 02.07.16 Nensebo 48,183 33,363 144% 194% 302% Critical 02.07.17 Kokosa 62,818 78,372 80% 108% 168% At Capacity within 10 yrs 12.07.18 Dodola 116,068 206,449 56% 76% 118% At Capacity within 25 yrs 32.07.19 Adaba 65,161 113,071 58% 77% 121% At Capacity within 25 yrs 02.08.20 Dinsho 58,036 83,183 70% 94% 146% At Capacity within 25 yrs 02.08.21 Agarfa 58,547 143,439 41% 55% 85% No Pressure 02.08.22 Gasera 48,953 130,659 37% 50% 78% No Pressure 02.08.23 Sinana 93,834 197,574 47% 64% 99% No Pressure 02.08.24 Goba 34,158 62,610 55% 73% 114% At Capacity within 25 yrs 698,211 1,738,651 40% 54% 84% No Pressure DPENDIX 2: TABLE A2.3 JMMARY OF POPULATION SUPPORT CAPACITY ANALYSIS: GAMO GOFA l/wereda RURAL POPULATION SUPPORT CAPACITY ^MO GOFA Potential current/ yr 10/ yr 25/ "ode 't wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
.18.01 Melekoza 96,208 109,984 87% 118% 183% At Capacity within 10 yrs .18.02 Basketo 88,561 89,267 99% 133%o 208% At Capacity within 10 yrs .18.03 Gofa Zuriya 156,237 144,652 108% 145%) 226% At Capacity .18.04 Zala 63,859 70,299 91% 122% 190% At Capacity within 10 yrs .18.05 Umamale 58,206 ' 108,325 54% 72% 113% At Capacity within 25 yrs .19.06 Kucha 109,110 115,933 94% 1-26% 197% At Capacity within 10 yrs .19.07 Boreda 62,018 105,318 59% 79%) 123% At Capacity within 25 yrs .19.08 Mirab Abaya 55,491 139,354 40% 54% 83% No Pressure .19.09 Chencha Zuriya 105,884 64,441 164% 221% 344% Critical .19.10 Dita 85,718 131,710 65% 87% 136% At Capacity within 25 yrs .19.11 Dera Malo 59,145 40,477 146% 196%) 306% Critical .19.12 Arba Minch Zuriya 110,185 223,771 49% 66% 103% At Capacity within 25 yrs .20.13 Bonke 125,308 262,456 48% 64%) 100% No Pressure .20.14 Kemba 112,047 149,835 75% 100%) 157% At Capacity within 10 yrs .20.15 Gardula 93,738 200,355 47% 63%) 98% No Pressure .20.16 Gumaide 22,762 127,538 18% 24%) 37% No Pressure .20.17 Konso 118,733 128,807 ' 92% 124% 193% At Capacity within 10 yrs .21.18 Bako Gazer 149,476 299,954 50% 67% 104% At Capacity within 25 yrs .21.19 Mursi Bode 9,291 68,875 13% 18% 28% No Pressure .21.20 Bena Kule 21,513 63,126 34% 46% 71% No Pressure .21.21 Hamer 29,800 33,164 90% 121% 188% At Capacity within 10 yrs .21.22 Geleb 49,611 2,116 2345% 3151% 4910% Critical 1,782,901 2,679,759 67% 89% 139% At Capacity within 25 yrs 'PENDIX 2: TABLE A2.4 IMMARY OF POPULATION SUPPORT CAPACITY ANALYSIS: ILLUBABOR GION/wereda RURAL POPULATION SUPPORT CAPACITY .UBABOR Potential current/ yr 10/ yr 25/ :ode U wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
49.01 Borecha 40,236 38,190 105% 142% 221% At Capacity 49.02 Dedesa 64,734 127,490 51% 68% 106% At Capacity within 25 yrs 49.03 Gechi 51,687 76,942 67% 90% 141% At Capacity within 25 yrs 49.04 Gumay 49,584 69,191 72% 96% 150% At Capacity within 25 yrs 49.05 Setema 86,681 236,828 37% 49% 77% No Pressure 49.06 Bedele 58,697 82,239 71% 96% 149% At Capacity within 25 yrs 49.07 Chora 72,691 103,188 70% 95% 147% At Capacity within 25 yrs 49.08 Dega 32,043 64,458 50% 67% 104% At Capacity within 25 yrs 49.09 Sigimo 70,942 224,449 32% 42% 66% No Pressure 50.10 Yayu 39,639 115,517 34% 46% 72% No Pressure 50.11 Dureni 31,307 39,950 78% 105% 164% At Capacity within 10 yrs 50.12 Supe & Sodo 53,503 98,083 55% 73% 114% At Capacity within 25 yrs 50.13 Darimu 75,238 90,077 84% 112% 175% At Capacity within 10 yrs 50.14 Bilo 24,961 22,524 111 % 149% 232% C ritical 50.15 Metu 56,572 57,957 98% 131% 204% At Capacity within 10 yrs 50.16 Hurumu 37,355 53,525 70% 94% 146% At Capacity within 25 yrs 50.17 Becho 20,170 30,566 66% 89% 138% At Capacity within 25 yrs 51.18 Bure 44,046 53,477 82% 111% 172% At Capacity within 10 yrs 51.19 Halu 19,000 58,087 33% 44% 68% No Pressure 51.20 Ale 46,285 117,505 39% 53% 82% No Pressure 51.21 Didu Lalo 32,532 147,881 22% 30% 46% No Pressure 51.22 Sylem 22,659 224,695 10% 14% 21% No Pressure 52.23 Masha 27.645 119,666 23% 31% 48% No Pressure 52.24 Nono 13,429 141,603 9% 13% 20% No Pressure 52.25 Sele 14,598 252,763 6% 8% 12% No Pressure 52.26 Anderacha 21,333 112,423 19% 26% 40% No Pressure 52.27 Yeki 64,638 63,788 101% 136% 212% At Capacity 52.28 Godere 23,498 133,013 18% 24% 37% No Pressure 53.33 Jikwao 19,513 391,642 5% 7% 10% No Pressure 53.32 Itang 11,611 48,072 24% 32% 51% No Pressure 53.31 Gambela 17,625 502,496 4% 5% 7% No Pressure 53.30 Abobo 32,573 35,824 91% 122% 190% At Capacity within 10 yrs 53.29 G.og & Jor 22,940 44,419 52% 69% 108% At Capacity within 25 yrs 53.34 Akob.o 17,236 33,803 51% 69% 107% At Capacity within 25 yrs 1,317,201 4,012,328 33% 44% 69% No Pressure APPENDIX 2: TABLE A2.5 SUMMARY OF POPULATION SUPPORT CAPACITY ANALYSIS: KEFFA REGION/wereda RURAL POPULATION SUPPORT CAPACITY KEFFA Potential current/ yr 10/ yr 25/ Code # wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
09.54.01 Limu Seka 151,207 238,557 63% 85% 133% At Capacity within 25 yrs 09.54.02 Limu Kosa 186,735 465,960 40% 54% 84% No Pressure 09.54.03 Gomma 207,003 117,529 176% 237% 369% Critical 09.54.04 Gera 75,418 187,948 40% 54% 84% No Pressure 09.55.05 Seka Chekorsa 254,768 192,924 132% 177% 276% Critical 09.55.06 Mana 145,146 70,794 205% 276% 429% Critical 09.55.07 Kersa 141,736 191,477 74% 99% 155% At Capacity within 25 yrs 09.55.08 Tiro Afeta 89,805 129,438 69% 93% 145% At Capacity within 25 yrs 09.55.09 Sekoru 139,723 150,708 93% 125% 194% At Capacity within 10 yrs 09.55.10 Janjero 39,980 61,602 65% 87% 136% At Capacity within 25 yrs 09.55.11 Omo Nada 179,408 279,757 64% 86% 134% At Capacity within 25 yrs 09.55.12 Dedo 224,543 185,891 121% 162% 253% Critical 09.55.39 Jima Town 0 0 0% 0% 0% No Pressure 09.56.13 Ela ' 60,121 103,105 58% 78% 122% At Capacity within 25 yrs 09.56.14 Tocha 67,667 59,658 113% 152% 237% Critical 09.56.15 Wushaye 42,231 79,099 53% 72% 112% At Capacity within 25 yrs 09.56.16 Mareko 71,010 41,599 171% 229% 357% Critical 09.56.17 Lume 72,752 34,019 214% 287% 448% Critical 09.56.18 Gena Bosa 54,319 29,961 181% 244% 380% Critical 09.57.19 Menjio 105,295 87,944 120% 161% 251% Critical 09.57.20 Gimbo 49,894 143,647 35% 47% 73% No Pressure 09.57.21 Gewata 51,906 94,946 55% 73% 114% At Capacity within 25 yrs 09.57.22 Tiliku Gesha 76,165 72,730 105% 141% 219% At Capacity 09.57.23 Tinshu Gesha 38,822 46,353 84% 113% 175% At Capacity within 10 yrs 09.57.24 Chena 103,522 63,184 164% 220% 343% Critical 09.57.25 Shewa Gimira 97,047 129,053 75% 101% 157% At Capacity within 10 yrs 09.57.26 Decha 105,922 196,732 54% 72% 113% At Capacity within 25 yrs 09.57.27 Cheta 29,934 45,782 65% 88% 137% At Capacity within 25 yrs 09.57.28 Telo 59,547 58r265 102% 137% 214% At Capacity 09.58.29 Goldiya 15,377 147,969 10% 14% 22% No Pressure 09.58.30 Gesha 9,121 60,742 15% 20% 31% No Pressure 09.58.31 Kurit 4,864 105,519 5% 6% 10% No Pressure 09.58.32 Shasha 10,047 64,630 16% 21% 33% No Pressure 09 58.33 Mehel Maji 13,717 132,154 10% 14% 22% No Pressure 09.58.34 Tirma Tid 20,056 490,379 4% 5% 9% No Pressure 09.58.35 Biro 8,717 84,695 ' 10% 14% 22% No Pressure 09.59.36 Gura Ferda 22,516 127,557 18% 24% 37% No Pressure 09.59.37 Temenja Yaz 136,345 95,459 143% 192% 299% Critical 09 59.38 Sheko 19,731 13,141 150% 202% 314% Critical 3,182,117 4,880,907 65% 88% 137% At Capacity within 25 yrs APPLNDIX 2: TABLE A2.6 SUMMARY OF RURAL POPULATION SUPPORT CAPACITY ANALYSIS: SHEWA pEGION/wereda RURAL POPULATION SUPPORT CAPACITY HEW A Potential current/ yr 10/ yr 25/ Code U wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
10.64.30 Jeldu 141,612 80,979 175% 235% 366% Critical 10 64 31 Dendi 171,386 179,128 96% 129%) 200% At Capacity within 10 yrs 10.64 32 Ambo Akababi 168,826 182,692 92%) 124% 193% At Capacity within 10 yrs 10.64 33 Tikur Enchet 42,267 100,220 42% 57%) 88% No Pressure 10.( 4.34 Cheliya 166,672 144,829 115% 155% 241% Critical 10.64 35 Bako Tibe 83,849 122,962 68% 92%) 143% At Capacity within 25 yrs 10.64.3 £ Dano 60,571 118,830 51% 69% 107% At Capacity within 25 yrs 10.64.3/ Nono 96,718 205,207 47%) 63%) 99% No Pressure 10.65.38 Ameya 89,760 213,025 42% 57% 88% No Pressure 10.65./9 Wenchi 88,690 166,897 53% 71% 111 % At Capacity within 25 yrs 10.65.-J Weliso 151,200 407,929 37% 50% 78% No Pressure 10.65 '1 Dawa 70,240 93,696 75%) 101% 157% At Capacity within 10 yrs 10.65 !? llu 44,813 48,145 93%) 125% 195% At Capacity within 10 yrs 10.65 i i Bechjo 47,230 53,766 88% 118% 184% At Capacity within 10 yrs 10,65 >4 Tole 49,947 72,740 69% 92%) 144% At Capacity within 25 yrs 10.65 .)5 Kokir Gedebano 70,237 368,335 19%) 26% 40% No Pressure 10.65.46 Goro 123,264 230,958 53%) 72% 112% At Capacity within 25 yrs 10.65. 47 Cheha 133,381 269,849 49% 66% 103% At Capacity within 25 yrs 10.65 48 Eza & Welene 217,536 503,807 43% 58% 90% No Pressure 10.65.49 Enemor & Ener 191,692 381,106 50% 68% 105% At Capacity within 25 yrs 10.65.50 Gumer 268,114 472,592 57% 76% 119% At Capacity within 25 yrs 10.60 31 Konteb 319,656 521,759 61%) 82% 128% At Capacity within 25 yrs 10.66 >2 Limu 287,982 313,551 92% 123% 192% At Capacity within 10 yrs 10.66. >3 Kedida Gamela 148,064 151,911 97% 131% 204% At Capacity within 10 yrs 10.66.54 Angaacha 145,039 155,035 94% 126% 196% At Capacity within 10 yrs 10.66.55 Timbaro 247,233 445,083 56% 75% 116% At Capacity within 25 yrs 10.66.56 Omo Sheleko 136,407 206,444 66% 89% 138% At Capacity within 25 yrs 10.66.57 Kacha Bira 123,010 115,106 107% 144% 224% At Capacity APPENDIX 2: TABLE A2.6 SUMMARY OF RURAL POPULATION SUPPORT CAPACITY ANALYSIS: SHEWA REGION/wereda RURAL POPULATION SUPPORT CAPACITY SHEWA Potential current/ yr 10/ yr 25/ Code # wereda Total rural potential potential potential Catagory rural pop population (%) (%) (%)
10.66.58 Sike 161,289 136,930 118% 158% 247% Critical 10.67,59 Siraro 162,713 95,538 170% 229% 357% Critical 10.67.60 Shashamene 188,088 126,770 148% 199% 311% Critical 10.67.61 Arsi Negele 105,315 87,113 121% 162% 253% Critical 10.67.62 Alaba 161,915 132,675 122% 164% 256% Critical 10.67.63 Dalocha 134,490 142,384 94% 127% 198% At Capacity within 10 yrs 10.67.64 Silti 119,007 159,419 75% 100% 156% At Capacity within 10 yrs 10.67.65 Lanfero 93,982 107,773 87% 117% 183% At Capacity within 10 yrs 10.67.66 Ziway Akakbabi 63,955 102,953 62% 83% 130% At Capacity within 25 yrs 10.67.67 Meska & Mareko 218,509 298,980 73% 98% 153% At Capacity within 25 yrs 10.67.68 Dugda 80,854 77,918 104% 139% 217% At Capacity 10.67.69 Sodo 105,887 354,705 30% 40% 63% No Pressure 10.67.70 Kondaltiti 81,657 273,000 30% 40% 63% No Pressure 10.67.71 Bora 35,984 63,874 56% 76% 118% At Capacity within 25 yrs 10.68.72 Liben Zikwala 57,173 65,159 88% 118% 184% At Capacity within 10 yrs 10.68.73 Adaa 104,136 106,702 98% 131% 204% At Capacity within 10 yrs 10.68.74 Lume 68,102 148,768 46% 62% 96% No Pressure 10.68.75 Adama 92,245 115,018 80% 108% 168% At Capacity within 10 yrs 10.68.79 Minjar 54,536 59,598 92% 123% 192% At Capacity within 10 yrs 10.68.80 Shenkora 34,771 23,505 148% 199% 310% Critical 10.68.81 Gimbichu 49,428 80,653 61% 82% 128% At Capacity within 25 yrs 10.69.82 Akaki 74,030 134,372 55% 74% 115% At Capacity within 25 yrs 10.69.83 Alem Gena 116,569 189,313 62% 83% 129% At Capacity within 25 yrs 10.69.84 Kersa & Malimo 34,573 77,454 45% 60% 93% No Pressure 10.69.85 Welmera 75,579 52,412 144% 194% 302% Critical 10.69.86 Addis Alem 65,605 82,440 80% 107% 167% At Capacity within 10 yrs 10.69.90 Sululta 95,071 54,448 175% 235% 366% Critical 10.69.91 Mulo 28,487 40,466 70% 95% 147% At Capacity within 25 yrs 10.69.92 Adaberga 94,908 59,095 161% 216% 336% Critical 10.69.93 Meta Robi 105,886 42,701 248% 333% 519% Critical 6,750,140 9,818,718 69% 92% 144% At Capacity within 25 yrs APPENDIX 2: TABLE A2.7 SUMMARY OF RURAL POPULATION SUPPORT CAPACITY ANALYSIS: SIDAMO REGION/wereda RURAL POPULATION SUPPORT CAPACITY SIDAMO Potential current/ yr 10/ yr 25/ Code # wereda Total rural potential potential potential Category rural pop population (%) (%) (%)
11.71.01 Boloso Sore 314,766 97,141 324% 435% 678% Critical 11.71.02 Koyisha 157,843 108,978 145% 195% 303% Critical 11.71.03 Ofa 128,002 80,110 160% 215% 335% Critical 11.71.04 Sodo Zuriya 207,214 131,435 158% 212% 330% Critical 11.71.05 Humbo 117,672 108,769 108% 145% 227% At Capacity 11.71.06 Damot Gale 240,966 94,439 255% 343% 534% Critical 11.71.07 Damot Weyide 184,853 114,366 162% 217% 338% Critical 11.72.08 Shebedino 429,922 333,506 129% 173% 270% Critical 11.72.09 Awasa Zuriya 252,538 248,985 101% 136% 212% At Capacity 11.72.10 Dale 329,297 404,292 81% 109% 171% At Capacity within 10 yrs 11.72.11 Aleta Wendo 346,887 238,385 146% 196% 305% Critical 11.72.12 Arbi Gona 137,491 370,500 37% 50% 78% No Pressure 11.72.13 Hagere Salem 210,126 188,309 112% 150% 234% Critical 11.72.14 Bensa 177,697 280,367 63% 85% 133% At Capacity within 25 yrs 11.72.15 Aroresa 34,351 175,667 20% 26% 41% No Pressure 11.73.16 Buie 122,060 438,320 28% 37% 58% No Pressure 11.73.17 Wenago 279,717 135,226 207% 278% 433% Critical 11.73.18 Yirge Chefe 208,210 152,862 136% 183% 285% Critical 11.73.19 Fiseha Genet 144,585 160,161 90% 121% 189% 11.73.20 Amaro At Capacity within 10 yrs 83,250 256,537 32% 44% 68% No Pressure 11.74.21 Uraga 128,868 612,015 21% 28% 44% No Pressure 11.74.22 Bore 82,568 381,959 22% 29% 45% No Pressure 11.74.23 Odo Shakiso 50,584 297,911 17% 23% 36% No Pressure 1 1.74.24 Adola 59,487 88,675 67% 90% 140% At Capacity within 25 yrs 1 1.74.25 Wadera 20,116 60,472 33% 45% 70% No Pressure 11.75.26 Hagere Mariam 280,573 933,541 30% 40% 63% No Pressure 1 I 75.27 Burji 38,244 200,618 19% 26% 40% No Pressure 11.75.28 Yabelo 50,226 593,991 8% 11% 18% No Pressure 11.75.29 Teltele 37,526 619,972 6% 8% 13% No Pressure 11.75.30 Arero 31,467 524,230 6% 8% 13% No Pressure 11.75.31 Dire 86,275 1,297,484 ' 7% 9% 14% No Pressure 11.75.32 Moyale 31,652 184,457 17% 23% 36% No Pressure 11.76.33 Liben 103,337 1,419,404 7% 10% 15% No Pressure 5,108,370 11,333,083 45% 61% 94% No Pressure APPENDIX 2: TABLE A2.8 SUMMARY OF RURAL POPULATION SUPPORT CAPACITY ANALYSIS: WELLEGA REGION/wereda RURAL POPULATION SUPPORT CAPACITY WELLEGA Potential current/ yr 10/ yr 25/ Code# wereda Total rural potential potential potential Category rural pop population (%) (%) (%)
13.85.01 Limu 91,516 175,220 52% 70% 109% At Capacity within 25 yrs 13.85.03 Gida Kiremu 107,003 107,440 100% 134% 209% At Capacity within 10 yrs 13.85.04 Abe Dengoro 41,189 47,382 87% 117% 182% At Capacity within 10 yrs 13.85.05 Horo 62,222 111,086 56% 75% 117% At Capacity within 25 yrs 13.85.06 Jardega Jarte 36,824 49,983 74% 99% 154% At Capacity within 25 yrs 13.85.08 Abay Chomen 25,656 55,912 46% 62% 96% No Pressure 13.85.09 Guduru 111,483 130,099 86% 115% 179% At Capacity within 10 yrs 13.85.10 Jima Genet 93,776 79,166 118% 159% 248% Critical 13.86.11 Gudeya Bila 34,823 24,330 143% 192% 300% Critical 13.86.12 Sibu Sire 73,362 129,240 57% 76% 119% At Capacity within 25 yrs 13.86.13 Gobu Seya 30,480 67,843 45% 60% 94% No Pressure 13.86.14 Boneya Boshe 39,193 51,527 76% 102% 159% At Capacity within 10 yrs 13.86.15 Wama Hagelo 39,949 68,560 58% 78% 122% At Capacity within 25 yrs 13.86.16 Wayu Tuka 58,594 41,696 141% 189% 294% Critical 13.86.17 Guto Gida 53,510 65,592 82% 110% 171% At Capacity within 10 yrs 13.86.18 Sasiga 60,676 61,558 99% 132% 206% At Capacity within 10 yrs 13.86.19 Diga 50,557 48,684 104% 140% 217% At Capacity 13.87.20 Meko 20,655 56,496 37% 49% 77% No Pressure 13.87.21 Dabo Hana 37,931 54,271 70% 94% 146% At Capacity within 25 yrs 13.87.22 Leka Dulecha 63,295 57,428 110% 148% 231% Critical 13.87.23 Jima Arjo 74,315 74,830 99% 133% 208% At Capacity within 10 yrs 13.87.24 Nunu Kumba 47,557 82,838 57% 77% 120% At Capacity within 25 yrs 13.87.25 Sachi 9,640 17,669 55% 73% 114% At Capacity within 25 yrs 13.87.26 Noli Kaba 157,537 183,449 86% 115% 180% At Capacity within 10 yrs 13.88.27 Yubdo 80,727 ■ 96,229 84% 113% 176% At Capacity within 10 yrs 13.88.28 Gimbi 109,476 108,874 101% 135% 211% At Capacity 13.88.29 Lalo Asabi 70,728 65,083 109% 146% 228% At Capacity 13.88.31 Boji Chekorsa 47,374 42,943 110% 148% 231% Critical APPENDIX 2: TABLE A2.8 SUMMARY OF RURAL POPULATION SUPPORT CAPACITY ANALYSIS: WELLEGA REGION/wereda RURAL POPULATION SUPPORT CAPACITY WELLEGA Potential current/ yr 10/ yr 25/ Code # wereda Total rural potential potential potential Category rural pop population (%) (%) (%)
13.88.30 Boji Dermeji 67,248 29,630 227% 305% 475% Critical 13.88.32 Ayera Guliso 68,684 85,306 81% 108% 169% At Capacity within 10 yrs 13.88.33 Nejo 130,923 173,109 76% 102% 158% At Capacity within 10 yrs 13.88.34 Jarso 86,254 128,946 67% 90% 140% At Capacity within 25 yrs 13.88.35 Menesibu 169,254 244,141 69% 93% 145% At Capacity within 25 yrs 13.88.36 Hanj 64,263 46,828 137% 184% 287% Critical 13.89.39 Asosa 130,295 114,366 114% 153% 239% Critical 13.89.40 Begi 167,681 198,103 85% 114% 177% At Capacity within 10 yrs 13.89.41 Gidami 63,948 92,939 69% 92% 144% At Capacity within 25 yrs 13.90.42 Jima Haro 34,199 32,373 106% 142% 221% At Capacity 13.90.43 Gawokebe 45,970 75,318 61% 82% 128% At Capacity within 25 yrs 13.90.44 Dale Wabera 93,516 104,651 89% 120% 187% At Capacity within 10 yrs 13.90.45 Dale Sedi 69,906 83,652 84% 112% 175% At Capacity within 10 yrs 13.90.46 Lalo Kile 54,784 142,537 38% 52% 80% No Pressure 13.90.47 Yemalogi Welel 38,307 69,381 55% 74% 116% At Capacity within 25 yrs 13.90.48 Anfilo 63,673 64,099 99% 133% 208% At Capacity within 10 yrs 13.90.49 Seya 106,531 87,351 122% 164% 255% Critical 13.90.50 Hawa Gelan 55,549 46,650 119% 160% 249% Critical 3,241,033 3,974,809 82% 110% 171% At Capacity within 10 yrs WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT
APPENDIX 3
LIVESTOCK CARRYING CAPACITY ANALYSIS
VOLUME III. STRATEGIC PLAN Page 114 APPENDIX 3: TABLE A3.1 SUMMARY OF LIVESTOCK CARRYING : a p a c it y REGION/wereda ARSI Carrying Stocking Stock rate Code # wereda capacity rate /CC (TLU's) (TLU's) (%)
01.01.01 Merti 62,747 29,100 46% 01.01.02 Aseko 47,995 33,191 69% 01.01.03 Guna 39,160 34,500 88% 01.01.04 Chole 30,618 50,438 165% 01.01.05 Golelcha 80,502 58,521 73% 01.01.06 Jeju 61,668 79,996 130% 01.02.07 Sirie 52,412 59,654 114% 01.02.08 Dodota 31,104 34,114 110% 01.02.09 Hitosa 61,654 62,520 101% 01.02.10 Zuway & D 39,466 72,992 185% 01.02.11 Tiyo 38,408 53,293 139% 01.02.12 Digelu na Ti 60,189 92,390 153% 01.02.13 Munesa 95,091 92,818 98% 01.02.14 Limu & Bilbi 82,251 101,820 124% 01.02.15 Gedeb 64,512 80,503 125% 01.02.16 Kofele 134,527 96,690 72% 01.02.17 Shirka 96,844 101,117 104% 01.03.18 Tena 54,740 42,465 78% 01.03.19 Robi 119,357 72,412 61% 01.03.20 Suda 97,032 100,803 104% 01.03.21 Amigna 43,537 59,599 137% tOTAL 1,393,813 1,408,934 101% APPENDIX 3: TABLE A3.2 SUMMARY OF LIVESTOCK CARRYING CAPACIT REGION/wereda BALE Carrying Stocking Stock rate Code # wereda capacity rate ICC (TLU’s) (TLU's) (%)
02.06.12 Mida Walab 222,195 23,253 10% 02.06.13 Mena 162,042 29,370 18% 02.06.14 Berbere 93,631 15,817 17% 02.06.15 Erena Bulk 47,668 20,918 44% 02.07.16 Nensebo 60,577 11,468 19% 02.07.17 Kokosa 44,624 50,525 113% 02.07.18 Dodola 72,968 85,628 117% 02.07.19 Adaba 59,364 88,818 150% 02.08.20 Dinsho 55,878 75,032 134% 02.08.21 Agarfa 47,114 49,933 106% 02.08.22 Gasera 63,429 52,166 82% 02.08.23 Sinana 70,204 58,571 83% 02.08.24 Goba 51,118 16,335 32% 1,050,813 577,834 55% A P P tN D IX 3: TABLE A3.3 SUMMARY OF LIVESTOCK CARRYING CAPACIT REGION/wereda GAMO GOFA Carrying Stocking Stock rate Code # wereda capacity rate /CC (TLU's) (TLU's) (%)
04.18.01 Melekoza 88,337 9,233 10% 04.18.02 Basketo 113,490 12,713 11% 04.18.03 Gofa Zuriya 88,803 34,337 39% 04.18.04 Zala 41,923 25,352 60% 04.18.05 Umamale 60,214 38,133 63% 04.19.06 Kucha 38,197 31,379 82% 04.19.07 Boreda 28,419 33,890 119% 04.19.08 Mirab Abay 21,480 12,689 59% 04.19.09 Chencha Z 35,535 17,407 49% 04.19.10 Dita 28,640 15,475 54% 04.19.11 Dera Malo 30,871 14,250 46% 04.19.12 Arba Minch 40,225 24,762 62% 04.20.13 Bonke 55,334 57,732 104% 04.20.14 Kemba 45,113 29,325 65% 04.20.15 Gardula 62,237 13,725 22% 04.20.16 Gumaide 10,836 5,280 49% 04.20.17 Konso 95,910 11,301 12% 04.21.18 Bako Gazer 305,489 21,763 7% 04.21.19 Mursi Bode 43,405 6,842 16% 04.21.20 Bena Kule 76,252 17,255 23% 04.21.21 Hamer 35,361 17,235 49% 04.21.22 Geleb 66,747 79,543 119% 1,412,817 529,621 37% APPENDIX 3: TABLE A3.4 SUMMARY OF LIVESTOCK CARRYING CAPACITY ANALY REGION/wereda _____ ILLUBABOR Carrying Stocking Stock rate Code # wereda capacity rate 1C C (TLU's) (TLU's) (%)
08.49.01 Borecha 80,291 10,762 13% 08.49.02 Dedesa 58,271 23,325 40%) 08.49.03 Gechi 23,128 25,250 109%, 08.49.04 Gumay 29,603 14,196 48% 08.49.05 Setema 69,358 48,121 69%o 08.49.06 Bedele 42,248 24,536 58% 08.49.07 Chora 39,404 24,954 63%o 08.49.08 Dega 17,932 14,838 83% 08.49.09 Sigimo 87,695 29,750 34% 08.50.10 Yayu 48,277 12,334 26% 08.50.11 Dureni 19,965 15,997 80% 08.50.12 Supe & Sod 29,234 12,088 41% 08.50.13 Darimu 45,503 21,728 48% 08.50.14 Bilo 33,023 4,482 14%, 08.50.15 Metu 63,231 11,675 18% 08.50.16 Hurumu 37,778 9,686 26% 08.50.17 Becho 11,119 8,453 76% 08.51.18 Bure 86,893 9,216 11% 08.51.19 Halu 25,390 7,635 30% 08.51.20 Ale 61,304 17,187 28% 08.51.21 Didu Lalo 59,618 9,264 16% 08.51.22 Sylem 80,483 8,478 11% 08.52.23 Masha 50,714 14,947 29% 08.52.24 Nono 74,548 4,370 6% 08.52.25 Sele 69,317 4,540 7% 08.52.26 Anderacha 40,058 10,436 26% 08.52.27 Yeki 42,643 8,320 20% 08.52.28 Godere 43,908 1,946 4%, 08.53.29 Gog & Jor 640,056 1,360 0% 08.53.30 Abobo 240,608 0 0%) 08.53.31 Gambela 290,923 0 0% 08.53.32 Itang 202,559 2,768 1%, 08.53.33 Jikwao 250,929 18,073 7% 08.53.34 Akobo 459,675 5,547 1%) 3,455,685 436,262 13%, APPENDIX 3: TABLE A3.5 SUMMARY OF LIVESTOCK CARRYING CAPACIT REGION/wereda , KEFA Carrying Stocking Stock rate Code # wereda capacity rate /CC (TLU's) (TLU's) (%)
09.54.01 Limu Seka 177,745 91,481 51% 09.54.02 Limu Kosa 190,964 79,879 42% 09.54.03 Gomma 90,455 31,057 34% 09.54.04 Gera 82,414 24,725 30% 09.55.05 Seka Chek 117,508 68,385 58% 09.55.06 Mana 57,307 117,480 205% 09.55.07 Kersa 64,306 66,131 103% 09.55.08 Tiro Afeta 40,540 36,420 90% 09.55.09 Sekoru 66,953 43,906 66% 09.55.10 Janjero 15,792 12,078 76% 09.55.11 Omo Nada 88,478 89,537 101% 09.55.12 Dedo 96,250 120,363 125% 09.55.39 Jima Town 0 0 0% 09.56.13 Ela 112,596 88,639 79% 09.56.14 Tocha 60,666 26,084 43% 09.56.15 Wushaye 75,690 12,171 16% 09.56.16 Mareko 41,037 17,442 43% 09.56.17 Lume 45,060 18,954 42% 09.56.18 Gena Bosa 31,663 26,619 84% 09.57.19 Menjio 92,845 27,182 29% 09.57.20 Gimbo 96,073 14,749 15% 09.57.21 Gewata 78,463 12,801 16% 09.57.22 Tiliku Gesh 70,895 30,066 42% 09.57.23 Tinshu Ges 34,015 0 0% 09.57.24 Chena 76,949 25,673 33% 09.57.25 Shewa Gimi 72,879 14,975 21% 09.57.26 Decha 120,549 27,512 23% 09.57.27 Cheta 52,715 15,342 29% 09.57.28 Telo 43,799 12,644 29% 09.58.29 Goldiya 59,221 213 0% 09.58.30 Gesha 71,827 1,176 2% 09.58.31 Kurit 195,176 3,284 2% 09.58.32 Shasha 34,253 0 0% 09.58.33 Mehel Maji 113,885 10,581 9% 09.58.34 Tirma Tid 271,403 0 0% 09.58.35 Biro 207,406 4,200 2% 09.59.36 Gura Ferda 247,274 70 0% 09.59.37 Temenja Ya 93,475 27,263 29% 09.59.38 Sheko 28,016 2,546 9% 3,516,543 1,201,628 34% APPENDIX 3: TABLE A3.6 SUMMARY OF LIVESTOCK CARRYING CAPACIT REGION/wereda SHEWA Carrying Stocking Stock rate Code # wereda capacity rate ICC (TLU’s) (TLU’s) (%)
10.64.30 Jeldu 91,404 80,939 89% 10.64.31 Dendi 83,046 97,956 118% 10.64.32 Ambo Akab 111,822 96,493 86% 10.64.33 Tikur Enche 38,738 24,158 62% 10.64.34 Cheliya 154,205 95,262 62% 10.64.35 Bako Tibe 83,146 47,924 58% 10.64.36 Dano 65,352 34,620 53% 10.64.37 Nono 75,238 55,279 73% 10.65.38 Ameya 60,786 51,303 84% 10.65.39 Wenchi 30,593 50,691 166% 10.65.40 Weliso 67,160 86,419 129% 10.65.41 Dawa 41,116 40,146 98% 10.65.42 llu 22,708 25,613 113% 10.65.43 Bechjo 21,749 26,994 124% 10.65.44 Tole 25,241 28,547 113% 10.65.45 Kokir Gede 34,241 40,144 117% 10.65.46 Goro 85,794 70,452 82% 10.65.47 Cheha 73,388 76,234 104% 10.65.48 Eza & Wele 112,143 124,333 111% 10.65.49 Enemor & 120,201 109,562 91% 10.65.50 Gumer 137,955 153,241 111% 10.66.51 Konteb 110,999 182,700 165% 10.66.52 Limu 100,481 164,597 164% 10.66.53 Kedida Ga 59,455 84,626 142% 10.66.54 Angaacha 61,463 82,897 135% 10.66.55 Timbaro 105,509 141,307 134% 10.66.56 Omo Shele 48,727 77,964 160% 10.66.57 Kacha Bira 37,261 70,307 189%, 10.66.58 Sike 55,880 92,185 165%, 10.67.59 Siraro 99,157 92,999 94% 10.67.60 Shashamen 92,103 127,928 139%, 10.67.61 Arsi Negele ' 85,156 60,193 71% 10.67.62 Alaba 94,880 92,543 98% 10.67.63 Dalocha 77,091 76,868 100% 10.67.64 Silti 67,525 68,019 101% 10.67.65 Lanfero 81,888 53,716 66% 10.67.66 Ziway Akak 83,784 36,554 44% 10.67.67 Meska & M 113,939 124,889 110% 10.67.68 Dugda 65,820 46,212 70% 10.67.69 Sodo 62,453 60,520 97%, 10.67.70 Kondaltiti 78,418 46,671 60% 10.67.71 Bora 25,239 20,567 81% 10.68.72 Liben Zikwa 46,295 32,677 71% 10.68.73 Adaa 57,684 59,519 103%, 10.68.74 Lume 47,645 38,924 82% A H p rn p CA AAC CO “7^0 070/ 1U.68.79 Minjar 64,748 31,170 48% 10.68.80 Shenkora 1Q 77.^ 1Q A nno/. APPENDIX 3: TABLE A3.6 SUMMARY OF LIVESTOCK CARRYING CAPACIT REGION/wereda SHEWA Carrying Stocking Stock rate Code # wereda capacity rate ICC (TLU's) (TLU’s) (%)
10.68.81 Gimbichu 32,700 28,251 86% 10.69.82 Akaki 53,408 42,312 79% 10.69.83 Alem Gena 64,884 66,625 103% 10.69.84 Kersa & Ma 24,280 19,760 81% 10.69.85 Welmera 34,950 43,197 124% 10.69.86 Addis Alem 33,466 37,497 112% 10.69.90 Sululta 62,671 54,338 87% 10.69.91 Mulo 21,099 16,282 77% 10.69.92 Adaberga 44,157 54,245 123% 10.69.93 Meta Robi 42,624 60,519 142% 3,848,085 3,878,487 101% APPENDIX 3: TABLE A3.7 SUMMARY OF LIVESTOCK CARRYING CAPACITY REGION/wereda SIDAMO Carrying Stocking Stock rate Code # wereda capacity rate ICC (TLU's) (TLU's) (%)
11.71.01 Boloso Sor 101,680 85,068 84% 11.71.02 Koyisha 57,835 51,889 90% 11.71.03 Ofa 45,610 38,856 85% 11.71.04 Sodo Zuriya 73,280 117,468 160% 11.71.05 Humbo 56,665 100,389 177% 11.71.06 Damot Gale 79,370 77,247 97% 11.71.07 Damot Wey 77,642 110,942 143% 11.72.08 Shebedino 164,859 244,511 148% 11.72.09 Awasa Zuri 114,956 157,399 137% 11.72.10 Dale 129,784 138,480 107% 11.72.11 Aleta Wend 112,437 178,251 159% 11.72.12 Arbi Gona 99,167 10,938 11% 11.72.13 Hagere Sal 91,133 116,759 128% 11.72.14 Bensa 95,879 3,095 3% 11.72.15 Aroresa 57,730 77,863 135% 11.73.16 Buie 96,517 73,039 76% 11.73.17 Wenago 92,063 35,452 39% 11.73.18 Yirge Chefe 83,390 24,114 29% 11.73.19 Fiseha Gen 59,682 9,773 16% 11.73.20 Amaro 51,200 38,142 74% 11.74.21 Uraga 84,564 92,969 110% 11.74.22 Bore 89,248 68,836 77% 11.74.23 Odo Shakis 186,062 128,454 69% 11.74.24 Adola 81,835 43,174 53% 11.74.25 Wadera 73,425 20,213 28% 11.75.26 Hagere Mar 269,262 82,778 - 31% 11.75.27 Burji 86,098 17,390 20% 11.75.28 Yabelo 223,773 77,301 35% 11.75.29 Teltele 62,872 82,024 130% 11.75.30 Arero 238,998 24,996 10% 11.75.31 Dire 524,594 251,587 48% 11.75.32 Moyale 371,747 83,917 23% 11.76.33 Liben 700,632 300,325 43% 4,733,987 2,963,639 63% APPENDIX 3: TABLE A3.8 SUMMARY OF LIVESTOCK CARRYING CAPACITY REGION/wereda WELLEGA Carrying Stocking Stock rate Code # wereda capacity rate ICC (TLU's) (TLU's) (%)
13.85.01 Limu 302,429 53,387 18% 13.85.03 Gida Kirem 152,669 47,278 31% 13.85.04 Abe Dengor 77,160 14,606 19% 13.85.05 Horo 45,499 49,865 110% 13.85.06 Jardega Jar 26,466 24,385 92% 13.85.08 Abay Chom 37,372 17,813 48% 13.85.09 Guduru 150,209 56,423 38% 13.85.10 Jima Genet 40,170 51,653 129% 13.86.11 Gudeya Bila 60,515 24,046 40% 13.86.12 Sibu Sire 105,860 35,853 34% 13.86.13 Gobu Seya 27,838 29,513 106% 13.86.14 Boneya Bos 31,344 23,086 74% 13.86.15 Wama Hag 30,335 11,178 37% 13.86.16 Wayu Tuka 29,028 35,901 124% 13.86.17 Guto Gida 53,546 19,099 36% 13.86.18 Sasiga 174,815 19,959 11% 13.86.19 Diga 63,210 22,265 35% 13.87.20 Meko 57,545 16,498 29% 13.87.21 Dabo Hana 100,792 23,349 23% 13.87.22 Leka Dulec 69,922 17,073 24% 13.87.23 Jima Arjo 70,422 29,610 42% 13.87.24 Nunu Kumb 52,395 24,378 47% 13.87.25 Sachi 6,210 11,054 178% 13.87.26 Noli Kaba 134,358 94,874 71% 13.88.27 Yubdo 37,395 58,625 157% 13.88.28 Gimbi 134,415 40,838 * 30% 13.88.29 Lalo Asabi 35,892 23,478 65% 13.88.30 Boji Dirmeji 143,108 27,033 19% 13.88.31 Boji Chekor 75,414 30,112 40% 13.88.32 Ayera Gulis 74,200 40,855 55% 13.88.33 Nejo 214,925 71,378 33% 13.88.34 Jarso 88,699 56,060 63% 13.88.35 Menesibu 203,024 101,471 50% 13.88.36 Haru 30,994 36,311 117% 13.89.39 Asosa 277,848 125,400 45% 13.89.40 Begi 266,211 278,870 105% 13.89.41 Gidami 203,027 24,945 12% 13.90.42 Jima Haro 28,315 19,757 70% 13.90.43 Gawokebe 93,206 31,452 34% 13.90.44 Dale Waber 57,865 22,895 40% 13.90.45 Dale Sedi 34,467 23,206 67% 13.90.46 Lalo Kile 60,441 22,895 38% 13.90.47 Yemalogi W 34,071 14,894 44% 13.90.48 Anfilo 98,780 6,182 6% 13.90.49 Seya 84,616 29,114 34% APPENDIX 4
FUEL WOOD SUPPLY/CONSUMPTION BALANCE SHEETS Pi ’ i 'JDIX 4: TABLE A4.1 FUELWOOD BALANCES: 1995 Rol Annual Rate of Increase in Consumption = 1.026 1995 EC 1C \J/Wereda Total Consumtion Total Supply Balance ode i Area fuelwood twigs Total Total Stock Annual Total Stock Yield (^a) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) 1.01 .C 1 Merti 109,500 11,324 5,935 17,258 70 238 0.64 > 4% 2,809 73,364 (14,449) .01.( Aseko 57,100 8,580 4,061 12,640 1,289,587 22.58 3% 38,161 1,281,007 25,520 .01.( 5 Guna 70,900 16,450 1,617 18,067 1,398,202 19.72 3% 39,449 1,381,751 21,382 .01 .( I Chole 183,000 19,629 2,882 22,511 1,280,985 7.00 3% 37,074 1,261,356 14,562 .01.c 5 Golelcha 49,800 32,649 9,558 42,206 4,115,368 82.64 4% 149,146 4,082,719 106,939 .01.c 3 Jeju 62,800 11,787 7,203 18,990 88,530 1.41 3% 2,735 92,998 (16,255) 02.C 7 Serie 67,344 17,789 5,635 23,423 80,058 1.19 2% 1,936 83,756 (21,487) .02. C 3 Dodota 116,500 34,889 22,366 57,255 266,181 2.28 3% 7,404 281,143 (49,850) .02.C ) Hitosa 101,732 111,975 24,122 136,097 475,526 4.67 3% 13,060 486,589 (123,038) .02.1 ) Zuway & Dugda 63,700 1,179 8,594 9,772 824,797 12.95 2% 20,472 823,618 10,699 .02.1 Tiyo 109,100 63,024 17,170 80,194 341,008 3.13 3% 9,219 348,959 (70,975) .02.1 Digelu na Tiyo 158,276 90,770 11,415 102,185 542,331 3.43 2% 12,883 540,863 (89,302) .02.1 Munesa 144,600 21,857 14,374 36,232 2,679,362 18.53 3% 78,900 2,657,505 42,669 .02.1 Limu & Bilbilo 106,600 62,540 13,340 75,880 501,224 4.70 2% 10,051 504,513 (65,829) 02.1 Gedeb 123,100 30,178 11,218 41,396 441,452 3.59 1% 5,612 447,058 (35,784) 02.1 Kofele 177,600 35,927 13,970 49,898 1,280,722 7.21 3% 37,944 1,256,749 (11,954) 02.1 Shirka 64,500 30,083 12,180 42,262 1,112,576 17.25 4% 41,754 1,083,001 (508) 03.1 Tena 128,900 28,984 3,787 32,771 299,518 2.32 3% 8,543 294,761 (24,227) 03.1 Robi 141,000 37,339 2,610 39,949 447,086 3.17 4% 20,063 429,634 (19,887) 03.2 Suda 129,960 36,237 3,360 39,597 565,509 4.35 4% 23,499 545,370 (16,098) 03.2 Amigna 200,872 19,931 2,039 21,969 842,844 4.20 4% 34,584 822,913 12,614 :al 2,366,884 723,120 197,434 920,554 18,943,105 8.00 3% 595,297 18,779,628 (325,257) PPENDIX 4: TABLE A4.2 FUELWOOD BALANCES: 4LE Annual Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consumtion Total Supply Balance >de # Area fuelwood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) .06.12 Mida Walabo 740,580 8,704 7,519 16,222 8,929,765 12.06 4% 327,254 8,921,061 311,032 .06.13 Mena 443,000 10,842 6,338 17,179 6,605,994 14.91 4% 248,328 6,595,153 231,149 .06.14 Berbere 158,800 7,180 5,882 13,061 3,609,098 22.73 5% 179,781 3,601,919 166,720 .06.15 Erena Bulk 255,600 5,300 4,578 9,878 2,031,256 7.95 6% 125,220 2,025,955 115,342 .07.16 Nensebo 150,708 12,742 10,358 23,100 2,769,446 18.38 5% 151,269 2,756,703 ~ 128,169 .07.17 Kokosa 44,000 2,739 3,653 6,392 413,640 9.40 5% 21,026 410,901 14,633 .07.18 Dodola 118,900 15,340 12,225 27,565 ‘ 3,219,673 27.08 2% 74,917 3,204,333 47,352 .07.19 Adaba 152,700 16,386 8,504 24,889 3,878,117 25.40 2% 77,791 3,861,731 52,902 .08.20 Dinsho 147,600 6,131 7,838 13,969 2,697,164 18.27 2% 53,819 2,691,033 39,849 .08.21 Agarfa 110,400 7,388 7,099 14,486 719,740 6.52 3% 23,526 712,352 9,040 .08.22 Gasera 106,700 2,759 4,796 7,554 493,627 4.63 5% 24,454 490,868 16,900 .08.23 Sinana 109,700 14,132 8,986 23,117 763,550 6.96 3% 21,689 749,418 (1,428) .08.24 Goba 216,700 36,002 4,327 40,329 3,707,110 17.11 3% 116,077 3,671,108 75,748 TOTAL 2,755,388 145,643 92,101 237,744 39,838,179 14.46 4% 1,445,151 39,692,535 1,207,407 PPENDIX 4: TABLE A4.3 FUELWOOD BALANCES: 1995 AMO GOFA Annual Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consumtion Total Supply Balance Dde # Area fuelwood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) 1.18.01 Melekoza 171,500 115,617 1,344 116,961 5,154,816 30.06 5% 235,062 5,039,198 118,100 -.18.02 Basketo 123,300 97,438 2,663 100,101 1,891,761 15.34 5% 97,126 1,794,323 (2,975) •.18 03 Gofa Zuriya 159,800 163,900 16,879 180,779 4,835,802 30.26 4% 188,578 4,671,902 7,799 •.18 04 Zala 82,600 20,532 25,422 45,954 531,178 6.43 7% 39,062 510,646 (6,891) •.18.05 Umamale 99,200 73,999 226 74,224 1,888,481 19.04 4% 80,823 1,814,482 6,599 -.19.06 Kucha 140,200 68,821 29,152 97,973 1,517,366 10.82 5% 79,568 1,448,545 (18,405) -.19.07 Boreda 51,200 43,158 10,717 53,875 1,554,750 30.37 4% 56,846 1,511,592 2,971 .19.08 Mirab Abaya 75,512 37,621 10,360 47,982 1,769,880 23.44 4% 69,390 1,732,258 21,408 .19.09 Chencha Zuriya 20,500 83,311 13,982 97,293 1,217,854 59.41 3% 30,540 1,134,543 (66,753: .19.10 Dita 41,900 65,999 11,087 77,086 2,374,064 56.66 3% 64,407 2,308,066 (12,678) .19.11 Dera Malo 31,600 30,276 16,395 46,671 486,218 15.39 5% 26,415 455,942 (20,256) .19.12 Arba Minch Zuriya 102,520 91,971 14,555 106,525 2,817,858 27.49 4% 101,465 2,725,887 - (5,061) .20.13 Bonke 87,600 154,728 1,771 156,499 4,328,587 49.41 3% 125,103 4,173,858 (31,397) .20.14 Kemba 116,800 72,374 22,186 94,561 1,995,543 17.09 4% 76,729 1,923,169 (17,831) .20.15 Gardula 172,748 57,814 16,976 74,790 3,797,335 21.98 4% 133,682 3,739,521 58,892 .20.16 Gumaide 124,864 11,005 3,370 14,375 666,086 5.33 10% 66,433 655,081 52,058 .20.17 Konso 183,500 52,335 16,590 68,925 3,459,215 18.85 3% 107,438 3,406,880 38,513 .21.18 Bako Gazer 415,300 68,602 51,211 119,813 7,223,099 17.39 4% 282,945 7,154,497 163,132 .21.19 Mursi Bode 414,900 3,912 1,262 5,174 6,590,348 15.88 3% 209,035 6,586,437 203,861 .21.20 Bena Kule 259,900 9,468 3,003' 12,470 4,027,078 15.49 4% 146,580 4,017,611 134,109 .21.21 Hamer 678,988 12,780 4,094 16,875 6,432,781 9.47 4% 225,297 6,420,001 208,422 .21.22 Geleb 407,264 20,972 6,757 27,729 1,703,491 4.18 5% 85,964 1,682,519 58,236 3,961,696 1,356,632 280,002 1,636,634 66,263,589 16.73 4% 2,528,488 64,906,957 891,854 PPENDIX 4: TABLE A4.4 FUELWOOD BALANCES: 1995 .LUBABOR A n n u a l Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consum tion Total Supply Balance Dde # area fuelwood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) 5 49.01 Borecha 85,100 69,810 7,327 77,137 754,239 8.86 6% 48,027 684,429 (29,111) ! 49.02 Dedesa 105,500 132,982 17,061 150,043 1,940,584 18.39 5% 103,800 1,807,602 (46,243) $.49.03 Gechi 43,800 109,879 14,611 124,489 747,225 17.06 6% 45,679 637,346 (78,810) 1.49.04 Gumay 42,100 105,292 14,027 119,319 1,059,313 25.16 5% 53,810 954,021 (65,509) 1.49.05 Setema 144,000 171,689 21,083 192,772 5,643,974 39.19 4% 251,935 5,472,285 59,163 1.49.06 Bedele 63,000 130,585 18,326 148,911 1,366,125 21.68 5% 72,672 1,235,541 (76,240) ;.49.07 Chora 78,700 152,379 19,985 172,364 2,436,486 30.96 5% 119,111 2,284,107 (53,253) ,49.08 Dega 45,500 67,490 8,879 76,369 1,339,436 29.44 5% 65,486 1,271,946 (10,884) .49 09 Sigimo 144,600 110,804 9,462 120,267 7,521,930 52.02 4% 310,959 7,411,126 190,692 .50.10 Yayu 108,700 81,456 10,503 91,958 5,359,329 49.30 4% 235,697 5,277,873 143,738 .50.11 Dureni 52,700 65,028 8,422 73,450 2,392,503 45.40 5% 113,285 2,327,476 39,835 .50.12 Supe & So 58,900 110,571 14,294 124,866 1,365,755 23.19 5% 74,227 1,255,183 (50,638) .50.13 Darimu 62,300 154,929 19,869 174,798 1,042,949 16.74 6% 67,467 888,020 (107,331) .50.14 Bilo 41,100 48,335 5,808 54,144 769,601 18.73 6% 46,476 721,266 (7,667) .50.15 Metu 66,900 115,705 15,257 130,962 1,520,186 22.72 5% 83,066 1,404,482 (47,896) .50.16 Hurumu 35,000 79,959 10,742 90,701 943,748 26.96 5% 45,655 863,789 (45,046) .50.17 Becho 17,400 42,565 5,610 48,175 191,554 11.01 6% 10,627 148,989 (37,548) .51.18 Bure 109,900 49,439 850 50,289 1,222,902 11.13 6% 76,043 1,173,464 25,754 .51.19 Halu 40,800 21,307 518 21,825 1,674,410 41.04 4% 73,354 1,653,103 ~ 51^529 51.20 Ale 72,100 105,283 15,100 120,383 3,351,068 46.48 4% 137,046 3,245,785 16,663 .51.21 Didu Lalo 96,400 52,792 5,074 57,866 5,667,054 58.79 4% 242,247 5,614,263 184,381 5' 22 Sylem 148,900 24,912 285 25,196 7,490,890 50.31 4% 322,918 7,465,979 297,721 52 23 Masha 79,300 32,662 1,011 33,673 4,250,253 53.60 4% 174,807 4.217,591 141,134 52.24 Nono 120,100 14,816 394 15,210 6,565,407 54.67 5% 297,515 6.550,592 282,305 52.25 Sele 167,500 15,763 213 ■ 15,976 17,266,029 103.08 4% 754,555 17,250,267 738,579 52.26 Anderacha 74,500 23,288 220 23,508 6,909,551 92.75 4% 285,645 6,886,263 262,137 52.27 Yeki 54,800 74,771 1,897 76,668 3,303,137 60.28 4% 144,721 3,228,366 68,053 52.28 Godere 101,500 25,790 282 26,072 5,708,071 56.24 5% 299,137 5,682,282 273,065 53.29 Jikwao 232,536 20,888 172 21,060 25,014.917 107.57 5% 1,264,856 24,994,028 1,243,796 =PENDIX 4: TABLE A4.4 FUELWOOD BALANCES: 1995 LUBABOR Annual Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consumtion Total Supply Balance — ^ >de # area fuelwood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) .53.30 Itang 186,792 13,282 297 13,579 24,563,019 131.50 5% 1,163,587 24,549,737 1,150,008 .53.31 Gambela 345,496 24,817 1,813 26,630 6,275,922 18.16 5% 308,617 6,251,105 281,986 .53.32 Abobo 410,656 35,274 252 35,526 1,044,523 2.54 6% 65,059 1,009,249 29,533 .53.33 Gog & Jor 928,136 24,409 109 24,518 1,300,319 1.40 6% 81,079 1,275,910 56,561 .53 34 Akobo 410,656 18,490 176 18,667 2,296,349 5.59 6% 143,185 2.277.859 124.518 Total 4,775,372 2,327,441 249,931 2,577,372 160,298,761 33.57 5% 7,582,345 157,971,321 5,004,973 PPENDIX 4: TABLE A4.5 FUELWOOD BALANCES: 1995 EFA Annual Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consumtion Total Supply Balance )de # Area fuelwood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) '.54.01 Limu Seka 255,400 130,136 35,881 166,017 2,134,867 8.36 6% 129,531 2,004,731 (36,486) '.54.02 Limu Kosa 286,000 375,712 51,267 426,979 6,279,085 21.95 4% 248,990 5,903,373 (177,990) ’.54.03 Gomma 72,200 453,126 58,371 511,496 1,670,145 23.13 5% 87,715 1,217,019 (423,782) .54.04 Gera 134,400 158,473 20,385 178,857 6,613,211 49.21 4% 277,323 6,454,738 98,466 .55.05 Seka Chek 160,800 483,247 68,918 552,165 7,042,739 43.80 4% 269,824 6,559,492 (282,341) .55.06 Mana 40,300 304,892 39,218 344,110 971,133 24.10 5% 49,341 666,241 (294,769) .55.07 Kersa 109,000 296,469 38,130 334,599 6,965,394 63.90 4% 248,630 6,668,925 (85,968) .55.08 Tiro Afeta 83,500 186,759 24,015 210,773 4,164,879 49.88 3% 138,774 3,978,121 (71,999; .55.09 Sekoru 131,200 285,935 38,550 324,484 5,218,514 39.78 3% 162,704 4,932,579 (161,781) .55.10 Janjero 32,700 53,420 25,503 78,923 1,577,453 48.24 3% 44,196 1,524,033 (34,727) .55.11 Omo Nada 180,600 378,380 48,678 427,057 9,476,133 52.47 3% 273,676 •9,097,753 (153,381) .55.12 Dedo 164,800 458,475 60,365 518,840 8,000,713 48.55 3% 271,897 7,542,237 (246,943) .55.39 Jima Town 0 45,751 6,545 52,296 0 ERR 0% 0 (45,751) (52,296) .56.13 Ela 201,200 73,966 33,430 107,396 3,620,638 18.00 6% 200,362 3,546,672 92,966 .56.14 Tocha 80,500 86,132 40,511 126,642 950,403 11.81 7% 69,493 864,271 (57,149) .56.15 Wushaye 107,300 56,561 26,957 83,518 984,966 9.18 7% 73,264 928,404 (10,254) .56.16 Mareko 49,500 98,488 45,777 144,265 573,963 11.60 7% 38,516 475,474 (105,749) .56.17 Lume 123,800 93,873 44,620 138,493 780,298 6.30 7% 52,189 686,424 (86,304) .56.18 Gena Bosa 94,300 70,271 33,339 103,610 414,595 4.40 6% 23,777 344,324 (79,833) .57.19 Menjio 129,900 145,299 44,060 189,359 3,196,694 24.61 5% 152,546 3,051,396 (36,812) .57.20 Gimbo 123,600 93,317 11,857 ' 105,174 4,655,254 37.66 4% 206,510 4,561,937 101,336 .57.21 Gewata 76,500 96,182 16,409 112,592 3,186,680 41.66 4% 136,098 3,090,498 23,507 .57.22 Tiliku Gesh 58,600 124,181 37,267 161,448 2,045,354 34.90 4% 90,840 1,921,173 (70,608) 57.23 Tinshu Ges 52,400 55,233 20,049 75,282 2,966,925 56.62 4% 122,896 2,911,692 47,614 .57.24 Chena 67,300 166,652 23,098 189,750 2,583,835 38.39 4% 102,934 2,417,183 (86,816) 57.25 Shewa Gim 112,700 154,410 21,735 176,145 6,738,158 59.79 3% 229,918 6,583,748 53,773 57.26 Decha 286,200 157,900 27,747 185,647 5,347,379 18.68 6% 305,127 5,189,479 119,480 57.27 Cheta 83,500 45,252 6,077 51,329 952,442 11.41 7% 71,264 907,190 19,935 57.28 Telo 48,000 93,059 17,156 110,215 743,638 15.49 6% 43,750 650,579 (66,465) ,PPE IDIX4: TABLE A4.5 ' FUELWOOD BALANCES: 1995 EF A Annual Rate of Increase in Consumption = 1.025 1995 EGIO JAA/ereda Total Consumtion Total Supply Balance ode 1 Area fuelwood twigs Total Total Stock Annual Total (ha) Stock Yield wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) ).58.; Goldiya 131.000 23,717 7,821 31,538 5,152,839 39.33 4% 213,356 5,129,122 ).58.: Gesha 102.000 11,357 5,439 181,818 16,796 3,088,675 30.28 4% 124,914 >.58.: Kurit 196,100 3,077,318 108,118 9,531 3,506 13,037 2,803,483 14.30 5% '.58.2 136,072 2,793,952 123,035 Shasha 97,100 13,628 6,126 19,754 3,401,913 35.04 4% 150,481 3,388,286 130,727 '.58.? Mehel Maji 312,188 11,071 3,559 14,630 2,516,015 8.06 5% 121,325 2,504,944 106,695 58.2 Tirma Tid 452,680 16,188 5,203 21,391 4,622,595 10.21 4% 164,682 4,606,408 143,292 .58.2 Biro 136,416 8,937. 2,514 11,451 . 727,089 5.33 6% 42,245 718,152 30,794 .59.2 Gura Ferda 305,648 23,440 5,920 29,359 19,712,768 64.50 5% 920,260 19,689,329 890,900 .59.2 Temenja Y 124,700 187,913 80,071 267,985 5,121,417 41.07 4% 228,201 4,933,504 (39,784) .59.3. Sheko 34,800 29,093 10,138 39,231 728,272 20.93 6% 46,793 699,179 7,562 Total 5,238,832 5,556,422 1,096,213 6,652,635 147,730,553 28.20 4% 6,270,414 142,174,131 (382,221) PP zNDIX 4: TABLE A4.6 FUELWOOD BALANCES: 1995 HEWA Annual Rate of Increase in Consumption
EGION/Wereda Total Consumtion )de # Area fuelw ood tw igs Total (ha) wood (tons) (tons) (tons) .64.30 Jeldu 155,400 121,052 37,638 158,690 .64.31 Dendi 153,700 194,983 63,095 258,078 .64.32 Ambo Akababi 178,700 212,870 60,676 273,546 .64.33 Tikur Enchet 41,900 62,621 19,434 82,055 .64.34 Cheliya 162,600 150,240 45,792 196,033 .64.35 Bako Tibe 88,800 81,858 22,982 104,840 .64.36 Dano 69,600 66,751 21,602 88,353 .64 37 Nono 112,300 149,256 12,618 161,873 .65.38 Ameya 102,400 145,199 45,074 190,274 .65.39 Wenchi 64,100 140,343 1,070 141,412 .6^ .40 Weliso 102,800 236,813 42,381 279,194 .61.41 Dawa 54,200 40,246 25,358 65,604 .6' .42 llu 44,813 16,076 14,380 30,457 ,6t 43 Bechjo 30,100 32,087 11,885 43,971 6 i 44 Tole 30,600 18,447 14,522 32,969 ,6f 45 Kokir Gedebano 65,900 82,218 3,423 85,641 .61 46 Goro 102,600 187,158 32,537 219,694 .6.' 47 Cheha 56,400 179,088 1,099 180,186 .61 48 Eza & Welene 101,500 285,963 408 286,371 ,6‘ 49 Enemor & Ener 99,700 252,242 518 252,761 .65.50 Gumer 86,200 352,271 391 352,661 .66.51 Konteb 133,100 401,891 993' 402,883 .66 52 Limu 81,100 368,120 5,614 373,734 .66 53 Kedida Gamela 42,300 170,959 5,423 176,382 .66.54 Angaacha 39,200 175,860 3,550 179,411 66 55 Timbaro 117,000 313,912 572 314,484 66 56 Omo Sheleko 55,200 171,513 432 171,945 6C.57 Kacha Bira 21,800 166,707 1,684" 168,391 66 58 Sike 40,900 180,104 7,760 187,864 67 59 Siraro 93,728 53,381 33,822 87,203 1.025 1995 Total Supply Balance Total Stock Annual Total Stock Yield Stock per ha Yield Yield (tons) (tons/ha) % (tons) (tons) (tons) 1,321,909 8.51 4% 59,141 1,200,857 (99,549) 1,682,290 10.95 3% 56,481 1,487,307 (201,597) 1,398,652 7.83 5% 67,159 1,185,782 (206,387) 163,786 3.91 4% 6,636 101,165 (75,419) 1,154,670 7.10 5% 54,056 1,004,430 (141,976) 603,168 6.79 4% 26,682 521,310 (78,158) 1,866,235 26.81 3% 65,293 1,799,484 (23,060) 3,654,209 32.54 3% 122,506 3,504,954 (39,367) 2,011,280 19.64 3% 69,204 1,866,081 (121,069) 490,258 7.65 4% 17,582 349,915 (123,830) 714,806 6.95 4% 26,873 477,993 (252,321) 316,978 5.85 4% 12,269 276,732 (53,334) 226,179 5.05 4% 8,757 210,103 (21,700) 203,232 6.75 4% 7,912 171,146 (36,059) 233,703 7.64 4% 8,921 215,256 (24,048) 370,003 5.61 4% 13,914 287,785 (71,728) 510,629 4.98 3% 17,728 323,471 (201,966) 849,425 15.06 4% 31,334 670,338 (148,852) 1,218,312 12.00 4% 43,679 932,349 (242,692) 1,982,827 19.89 4% 77,150 1,730,585 (175,611) 1,352,940 15.70 3% 37,558 1,000,670 (315,103) 3,359,676 25.24 4% 119,438 2,957,785 (283,445) 2,062,092 25.43 3% 69,827 1,693,972 (303,907) 2,366,491 55.95 3% 76,586 2,195,532 (99,796) 1,943,498 49.58 3% 63,480 1,767,637 (115,931) 1,827,689 15.62 4% 73,277 1,513,776 (241,208) 1,262,956 22.88 4% 47,782 1,091,443 (124,162) 746,196 34.23 3% 24,483 579,489 (143,908) 2,605,436 63.70 3% 85,440 2,425,333 (102,424) 1,044,080 11.14 3% 27,843 990,699 (59,360) PPENDIX 4: TABLE A4.6 FUELWOOD BALANCES: 1995 HEWA Annual Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consumtion Total Supply Balance ode # Area fuelw ood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) ).67.60 Shashamene 84,236 125,620 58,231 183,851 842,852 10.01 3% 22,474 717,232 (161,376) 1.67.61 Arsi Negele 30,284 45,619 21,875 67,494 688,366 22.73 3% 17,779 642,747 (49,715) 1.67.62 Alaba 105,800 57,415 33,703 91,117 904,615 8.55 3% 25,425 847,200 (65,692) 1.67.63 Dalocha 75,900 104,499 17,133 121,632 3,111,155 40.99 3% 101,775 3,006,655 _ ( I 0.857) 1.67.64 Silti 43,740 148,614 3,285 151,900 853,094 19.50 3% 28,784 704,480 (123,115) 1.67.65 Lanfero 94,216 33,928 23,838 57,767 1,072,749 11.39 3% 35,093 1,038,820 (22,673) 1.67.66 Ziway Akakbabi 98,608 34,668 20,452 55,120 786,611 7.98 3% 21,271 751,943 (33,849) t.67.67 Meska & Mareko 85,100 260,620 11,445 272,065 2,074,260 24.37 3% 68,126 1,813,640 (203,940) '.67.68 Dugda 78,552 31,341 24,213 55,554 751,170 9.56 3% 24,929 719,829 (30,625) '.67.69 Sodo 83,400 113,482 8,600 122,082 797,231 9.56 3% 27,133 683,749 (94,949) -.67.70 Kondaltiti 81,300 63,859 12,880 76,739 523,284 6.44 4% 19,294 459,425 (57,445) •67.71 Bora 63,748 17,235 12,122 29,357 569,507 8.93 3% 15,775 552,272 (13,582) .68.72 Liben Zikwala 63,284 14,654 18,172 32,826 1,520,271 24.02 3% 43,321 1,505,617 10,496 .68.73 Adaa 81,776 91,505 34,715 126,220 880,397 10.77 3% 25,190 788,892 (101,029) .68.74 Lume 86,176 45,223 22,912 68,135 401,668 4.66 3% 10,698 356,445 (57,438) .68.75 Adama 85,172 188,007 37,635 225,642 350,802 4.12 3% 9,974 162,795 (215,668) .68.79 Minjar 82,400 19,946 17,551 37,497 236,658 2.87 2% 5,471 216,712 (32,026) .68.80 Shenkora 26,000 10,307 10,870 21,177 326,158 12.54 3% 8,168 315,851 (13,009) .68.81 Gimbichu 67,200 16,170 15,653 31,823 189,196 2.82 3% 5,395 173,026 (26,428) .69.82 Akaki 94,500 83,338 24,876 108,215 195,468 2.07 4% 6,929 112,130 (101,286) .69.83 Alem Gena 131,552 60,505 38,580 99,085 275,556 2.09 4% 10,283 215,051 (88,803) .69.84 Kersa & Malimo 43,100 13,127 10,277 23,404 180,472 4.19 4% 6,708 167,345 ■ (16,696) .69.85 Welmera 36,300 36,985 23,727 60,712 207,113 5.71 3% 6,304 170,128 (54,408) 69.86 Addis Alem 63,400 36,464 19,048 55,512 427,050 6.74 3% 14,312 390,586 (41,200) 69.90 Sululta 109,500 28,412 30,189 58,600 292,022 2.67 3% 8,902 263,610 (49,698) 69.91 Mulo 36,000 8,847 9,218 18,065 218,689 6.07 3% 6,555 209,843 (11,510) 69.92 Adaberga 118,300 69,842 27,007 96,849 921,417 7.79 3% 31,270 851,575 (65.57S, 69.93 Meta Robi 84,600 86,642 28,211 ' 114,853 685,798 8.11 4% 24,472 599,157 (90,380) Total 4,662,785 6,857,102 1,153,151 8,010,253 59,827,235 12.83 3% 2,050,805 52,970,133 (5,959,449) PPENDIX 4: TABLE A4.7 FUELWOOD BALANCES: 1995 'DAMO Annual Rate of Increase in Consumption = 1.025 1995 EGION/Wereda Total Consumtion Total Supply Balance >de # Area fuelwood twigs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) % (tons) (tons) (tons) .71.01 Boloso Sore 42,000 398,663 874 399,538 1,425,226 33.93 3% 49,208 1,026,563 (350,330) .71.02 Koyisha 110,000 199,816 419 200,235 1,221,241 11.10 5% 57,647 1,021,425 (142,588) .71.03 Ofa 45,000 160,345 1,269 161,614 558,425 12.41 5% 25,432 398,080 (136,182) .71.04 Sodo Zuriya 64,100 274,919 430 275,349 2,692,607 42.01 3% 86,514 2,417,688 (188,835) .71.05 Humbo 96,736 117,116 13,996 131,112 1,973,900 20.41 4% 81,129 1,856,783 (49,983) .71.06 Damot Gale 123,200 304,858 60 304,918 1,543,387 12.53 3% 51,377 1,238,529 (253,541) .71.07 Da mot Weyide 83,500 180,369 17,281 197,650 4,429,414 53.05 3% 138,323 4,249,045 (59,327-) .72.08 Shebedino 110,228 272,085 116,371 388,455 1,923,170 17.45 3% 60,418 1,651,085 (328,038) .72.09 Awasa Zuriya 102,032 264,928 21,092 286,021 1,729,229 16.95 3% 56,284 1,464,301 (229,737) .72.10 Dale 146,900 215,044 101,654 316,698 2,179,001 14.83 3% 74,593 1,963,957 (242,105) .72.11 Aleta Wendo 78,300 220,487 111,248 331,735 1,110,389 14.18 5% 50,387 889,902 (281,348) .72.12 Arbi Gona 68,400 173,834 345 174,179 3,020,204 44.16 3% 92,556 2,846,371 (81,623) .72.13 Hagere Salem 53,000 263,348 1,148 264,496 710,979 13.41 4% 29,797 447,630 (234,699) .72.14 Bensa 83,800 189,639 12,615 202,254 564,438 6.74 5% 28,776 374,799 (173,477')' 72.15 Aroresa 158,500 28,495 4,498 32,992 1,806,961 11.40 6% 105,509 1,778,466 72,517 .73.16 Buie 112,100 134,441 10,650 145,091 2,852,632 25.45 3% 89,457 2,718,191 (55,634) 73.17 Wenago 103,936 159,657 86,302 245,959 755,495 7.27 7% 50,916 595,838 (195,043) 73.18 Yirge Chefe 85,500 115,147 59,285 174,431 809,928 9.47 6% 50,414 694,782 (124,017) 73.19 Fiseha Genet 87,300 82,147 43,860 126,006 658,452 7.54 8% 52,977 576,305 (73,029) 73.20 Amaro 173,860 44,475 22,782 67,257 1,723,947 9.92 7% 126,413 1,679,472 59,156 74.21 Uraga 134,700 103,480 29,393 132,874 3,494,940 25.95 3% 119,993 3,391,460 (12,881) 74.22 Bore 122,600 83,649 11,459 95,107 7,717,347 62.95 3% 250,599 7,633,698 155,491 74.23 Odo Shakiso 435,800 32,080 13,927 46,006 18,097,323 41.53 4% 640,458 18,065,244 594,452 74.24 Adola 120,200 35,866 13,044 , 48,910 6,438,770 53.57 4% 226,991 6,402,904 178,081 74.25 Wadera 108,300 11,746 361 12,107 1,552,615 14.34 5% 77,612 1,540,868 65,505 75.26 Hagere Mariam 525,700 142,558 51,864 194,422 6,944,168 13.21 5% 344,580 6,801,610 150,158 75.27 Burji 173,500 21,318 8,319 29,637 2,537,605 14.63 6% 152,566 2,516,286 122,929 75.28 Yabelo 650,900 27,651 5,604 33,255 6,359,352 9.77 5% 325,480 6,331,701 292,225 75.29 Teltele 989,772 19,106 4,187 23,292 10,007,850 10.11 5% 543,359 9,988,744 520,066 75.30 Arero 442,300 15,498 3,511 19,009 5,685,102 12.85 4% 200,606 5,669,604 181,597 75.31 Dire 1,394,080 44,092 9,625 53,718 12,859,675 9.22 5% 638,921 12,815,583 585,204 75.32 Moyale 1,611,308 17,097 3,531 20,628 19,331,207 12.00 4% 680,868 19,314,110 660,240 76.33 Liben 1,739,492 55,789 11,529 67,318 19,051,641 10.95 4% 674,530 18,995,852 607,212 Total 10,377,044 4,409,741 792,532 5,202,274 153,766,619 14.82 4% 6,234,688 149,356,878 1,032,415 APPENDIX 4: TABLE A4.8 FUELWOOD BALANCES: 1995 WELLEGA Annual Rate of Increase in Consumpti
REGION/Wereda Total Consumption Code # Area fuelw ood tw igs Total (ha) wood (tons) (tons) (tons) 13.85.01 Limu 351,792 100,132 459 100,591 13.85.03 Gida Kiremu 145,820 120,401 978 121,379 13.85.04 Abe Dengoro 106,100 34,586 10,864 45,450 13.85.05 Horo 97,976 67,740 18,473 86,213 13.85.06 Jardega Jarte 53,072 31,791 9,829 41,619 13.85.08 Abay Chomen 71,008 29,066 7,768 36,834 13.85.09 Guduru 220,052 93,053 29,332 122,384 13.85.10 Jima Genet 75,384 81,934 25,160 107,094 13.86.11 Gudeya Bila 81,500 36,589 5.S77 42,166 13.86.12 Sibu Sire 141,000 68,956 17,717 86,673 13.86.13 Gobu Seya 44,900 34,785 390 35,175 13.86.14 Boneya Boshe 36,800 33,670 10,439 44,110 13.86 15 Wama Hagelo 45,200 32,855 10,415 43,270 13.86.16 Wayu Tuka 28,200 48,948 14,907 63,856 13.86.17 Guto Gida 70,400 67,251 15,746 82,996 13.86.18 Sasiga 192,600 59,740 5,634 65,373 13.86.19 Diga 77,300 43,926 10,869 54,796 13.87.20 Meko 94,300 39,855 4,569 44,423 13.87.21 Dabo Hana 133,900 68,813 7,310 76,122 13.87.22 Leka Dulecha 70,400 124,020 14,667 138,687 13.87 23 Jima Arjo 76,100 161,594 20,810 182,404 13.87.24 Nunu Kumba 69,200 97,416 12,208 109,624 13.87.25 Sachi 16,000 20,275 2,772 23,047 13.87 26 Noli Kaba 181,400 181,117 3,401 184,518 13.88 27 Yubdo 60,900 87,506 650 88,156 13.88.28 Gimbi 160,900 151,290 8,074 159,364 13.88.29 Lalo Asabi 46,096 80,228 1,611 81,839 13.88.30 Boji Dirmeji 162,392 54,672 1,353 56,025 13.88 31 Boji Chekorsa 24,420 73,494 716 74,211 13.88 32 Ayera Guliso 80,100 75,565 879 76,444 13.88.33 Nejo 273,496 175,571 10,110 185,681 Dn = ' 1.025 1995 Total Supply Balance Total Stock Annual Total Stock Yield Stock per ha Yield Yield (tons) (tons/ha) % (tons) (tons) (tons) 3,195,235 9.08 6% 200,805 3,095,103 100,21 1,143,974 7.85 6% 65,944 1,023,573 (55,43 920,228 8.67 5% 47,792 885,642 2,34 954,689 9.74 4% 40,520 886,949 (45,69 501,407 9.45 4% 21,954 469,616 (19,66* 465,016 6.55 5% 21,853 435,950 (14,98 843,122 3.83 5% 46,003 750,069 (76,38: 603,349 8.00 4% 24,596 521,415 (82.49J 747,372 9.17 6% 42,465 710,783 295 1,314,225 9.32 7% 86,016 1,245,269 (65/ 441,810 9.84 7% 28,980 407,025 (6,195 252,896 6.87 6% 14,600 219,225 (29,509 394,304 8.72 7% 25,812 361,450 (17,459 263,574 9.35 6% 16,007 214,626 (47,r.4S 718,480 10.21 7% 47,874 651,230 (35,122 1,980,918 10.29 7% 133,602 1,921,179 68,229 686,792 8.88 6% 44,533 642,866 (10,263 1,719,449 18.23 5% 86,661 1,679,594 42,238 2,535,446 18.94 5% 131,546 2,466,633 55,423 669,868 9.52 6% 42,468 545,847 ,, (96,219 711,058 9.34 6% 42,841 549,464 ' (139,563 585,819 8.47 6% 36,535 488,402 (73,089 284,932 17.81 6% 17,216 264,657 (5,831 2,631,115 14.50 6% 163,903 2,449,998 (20,615 679,695 11.16 6% 41,971 592,189 (46,185 2,080,894 12.93 5% 106,684 1,929,604 (52,680 568,728 12.34 5% 30,700 488,500 (51,139 1,027,083 6.32 6% 65,926 972,412 9,902 990,947 40.58 6% 54,878 917,453 (19,332) 791,150 9.88 6% 46,276 715,585 ' (30,168) 3,099,458 11.33 5% 163,284 2,923,887 (22,396) APPENDIX 4: TABLE A4.8 FUELWOOD BALANCES: 1995 WELLEGA Annual Rate of Increase in Consumption = 1.025 1995 RLGIOW/Wereda Total Consumption Total Supply 2c de # Balance Area fuelw ood tw igs Total Total Stock Annual Total Stock Yield (ha) wood Stock per ha Yield Yield (tons) (tons) (tons) (tons) (tons/ha) '3.88.34 % (tons) (tons) (tons) Jarso 129,320 92,594 430 93,024 1,147,344 8.87 5% 57,972 3.88.35 Menesibu 284,744 190,175 3,325 1,054,750 (35,052) 193,500 2,588,234 9.09 5% 3.88.36 Haru 32,300 134,120 2,398,060 (59,380) 70,973 902 71,874 391,459 12.12 3.89.39 Asosa 5% 18,471 320,486 (53,403) 315,620 143,406 1,684 145,089 2,679,839 8.49 5% 124,297 2,536,433 3.89.40 Begi 320,972 180,172 884 (20,792) 181,056 2,495,672 7.78 5% 3.89.41 Gidami 218,156 123,805 2,315,500 (57,252) 71,175 1,058 72,233 1,843,919 8.45 2.90.42 5% 95,902 1,772,744 Jima Haro 37,700 37,582 425 38,007 23,669 329,110 8.73 5% 16,610 3.90.43 Gawokebe 132,300 49,569 293 291,528 (21,396) 49,862 1,147,664 8.67 5% 3.90.44 % Dale Wabera 79,600 61,023 1,098,095 11,161 101,353 748 102,102 835,821 10.50 3.90.45 Dale Sedi 6% 48,087 734,467 (54,015) 54,900 75,449 467 75,916 579,371 3 ">0.46 10.55 6% 32,906 503,921 Lalo Kile 98,800 59,791 560 60,351 (43,010) 1,112,167 11.26 6% 64,026 3 >( .47 Yemalogi Welel 88,100 41,061 370 1,052,376 3,675 41,431 1,185,015 13.45 6% 3. -•( .48 Anfilo 157,000 72,294 1,143,954 30,862 73,598 1,852 75,450 1,675,444 10.67 3 k .49 Seya 7% 119,440 1,601,846 43,991 111,400 123,707 1,596 125,303 1,289,031 3 50 11.57 5% 70,712 Hawa Gelan 62,300 60,572 552 1,165,324 (54,591) 61,124 803,338 12.89 6% Total 5,411,920 3,748,013 52,048 742,766 (9,075) 298,831 4,046,844 53,906,461 9.96 6% 3,031,958 50,158,448 (1,014,886) WOODY BIOMASS INVENTORY AND STRATEGIC PLANNING PROJECT
APPENDIX 5
WOODY BIOMASS DEVELOPMENT ZONE ANALYSIS
VOLUME III. STRATEGIC PLAN Page 137 APPENDIX 5: Table A5.1 Woody Biomass Development Zone Analysis
Wereda Population Families Total Deficit/ Single Deficit family hedge (tons) (kgs) (meters) Enset Land Use Systems: few indigenous treesin landscape Kokir Gedeb 70,237 10,034 71,728 7,149 433 Cheha 133,381 19,054 14,885 781 47 Eza Weleni 212,536 30,362 242,692 7,993 484 Enemer ener 191,692 27,385 175,611 6,413 389 Gumer 268,114 38,302 315,103 8,227 499 Konteb 319,656 45,665 283,445 6,207 376 Limu 287.982 41,140 303,907 7,387 448 Kedida Gamela 148,064 21,152 99,796 4,718 286 Angaacha 145,039 20,720 115,931 5,595 339 Timbaro 247,233 35,319 241,208 6,829 414 Omo Sheleko 136,407 19,487 124,162 6,372 386 Kachabira 123,010 17,573 143,908 8,189 496 Sike 161,289 23,041 102,424 4,445 269 Siraro 162,712 23,245 59,360 2,554 155 Silte 119,007 17,001 123,115 7,242 439 Meskan Mareka 218,509 31,216 203,904 6,532 396 Soddo 109,887 15,698 94,949 6,048 367 Kondaltiti 81,657 11,665 57,445 4,924 298 Koisha 152,843 21,835 142,588 6,530 396 Ofa 128,002 18,286 136,182 7,447 451 Sodo Zuria 207,214 29,602 188,835 6,379 387 Damot Wende 184,853 26,408 59,327 2,247 136 Basketto 88,561 12,652 2,975 235 14 Chencha 105,884 15,126 66,753 4.413 267 Dita 85,718 12,245 12,678 1,035 63 Arba Minch 110,185 15,741 5,061 322 19 Bonke 125,308 17,901 31,397 1.754 106 Kemba 112,047 16,007 17,831 1,114 68 Janjero 39,980 5,711 34,727 6,080 369 Tocha 67,667 9,667 57,149 5,912 358 Wushaya 42,231 6,033 10,254 1,700 103 Mareko 71.010 10,144 105,749 10,424 632 Lume 72,752 10,393 86,304 8,304 503 Gena Boska 54,319 7,760 79,833 10,288 624 Manjio 105,295 15,042 36,812 2,447 148 Tikur Enchet 42,267 6,038 75,419 12,490 757 Nono 96,718 13.817 39,367 2,849 173 Ameya 89,760 12,823 121.069 9,442 572 Wenchi 88,690 12,670 123,830 9,773 592 Woliso 151,200 21,600 252,321 11,682 708 Total 5,358,916 765,559 4,460,034 5,826 305 Total T rees/ha Family size 7.00 Trees in on farm Hedge Kgs/meter= 16.5 fields fields Pollard tree kgs/tree 90 Farm Size= 0.7 217 79 113 24 9 12 242 89 127 194 71 102 249 91 131 188 69 99 224 82 117 143 52 75 170 62 89 207 76 108 193 71 101 248 91 130 135 49 71 77 28 41 219 80 115 198 73 104 183 67 96 149 55 78 198 73 104 226 83 118 193 71 101 68 25 36 7 3 4 134 49 70 31 12 16 10 4 5 53 19 28 34 12 18 184 68 97 179 66 94 52 19 27 316 116 165 252 92 132 312 114 163 74 27 39 378 139 198 86 32 45 286 105 150 296 109 155 354 130 185 153 56 80 APPENDIX 5: Table A5.1 Woody Biomass Development Zone Analysis Zone 1b. Enset Land Use Systems: many indigenous trees in landscape
Code # Wereda Population Families Total Deficit/ Single Deficit family hedge (tons) (kgs) (meters)
Telo 59,547 8,507 66,465 7,813 474 Boloso Sore 314,766 44,967 350,330 7,791 472 Humbo 117,672 16,810 49,983 2,973 180 Shebedino 429,922 61,417 328,038 5,341 324 Awassa Zuria 252,528 36,075 229,737 6,368 386 Dale 329,297 47,042 242,105 5,147 312 Aleta Wendo 346,887 49,555 281,348 5,677 344 Arbi Gona 137,491 19,642 81,623 4,156 252 Haggere Salem 210,126 30,018 234,699 7,819 474 Bensa 177,697 25,385 173,477 6,834 414 Buie 122,060 17,437 55,634 3,191 193 Wenago 279,717 39,960 195,043 4,881 296 Yirge Chefe 208,210 29,744 124,017 4,169 253 Fishe genet 144,585 20,655 73,029 3,536 214 Urage 128,868 18,410 12,881 700 42 Sachi 9,640 1,377 5,831 4,234 257 Borecha 40,236 5,748 29,111 5,065 307 Didessa 64,734 9,248 46,243 5,000 303 Gechi 51,687 7,384 78,810 10,673 647 Gumay 49,584 7,083 65,509 9,248 560 Bedele 58,697 8,385 76,240 9,092 551 Chora 72,691 10,384 53,253 5,128 311 Dega 32,043 4,578 10,884 2,378 144 Darimu 75,238 10,748 107,331 9,986 605 Bilo 24,961 3,566 7,667 2,150 130 Metu 56,572 8,082 47,896 5,926 359 Hurumu 37,355 5,336 45,046 8,441 512 Becho 20,170 2,881 37,548 13,031 790 Limukosa 186,735 26,676 177,990 ' 6,672 404 Goma 207,003 29,572 423,782 14,331 869 Seku Chekosi 254,768 36,395 282,341 7,758 470 Mana 145,146 20,735 294,769 14,216 862 Kersa 141,736 20,248 85,968 4,246 257 Tiro Afeta 89,805 12,829 71,999 5,612 340 Sekoru 139,723 19,960 161,781 8,105 491 Omo Nada 179,408 25,630 153,381 -5,984 363 Dedo 224,543 32,078 246,943 7,698 467 Tiku Gesha 76,165 10,881 70,608 6,489 393 Chema 103,522 14,789 86,816 5,870 356 TemenaYaz 136,345 19,478 39,784 2,043 124 Total 5,737,880 819,697 5,205,940 6,394 388 Total Trees/ha Family size 7.00 ge Trees in on farm Hedge Kgs/meter= 16.5 ;rs) fields fields Pollard tree kgs/tree 90 Farm Size= 1.39 237 87 62 236 87 62 90 33 24 162 59 43 193 71 51 156 57 41 172 63 45 126 46 33 237 87 62 207 76 55 97 35 26 148 54 39 126 46 33 107 39 28 21 8 6 128 47 34 153 56 40 152 56 40 323 119 85 280 103 74 276 101 73 155 57 41 72 26 19 303 111 80 65 24 17 180 66 47 256 94 67 395 145 104 202 74 53 434 159 115 235 86 62 431 158 114 129 47 34 170 62 45 246 90 65 181 66 48 233 86 62 197 72 52 178 65 47 62 23 16 194 71 51 APPENDIX 5: Table A5.1 Woody Biomass Development Zone Analysis '.one 2a:Cereal land use systems on vertisols : few to no indigenous trees in landscape
Wereda Population Families Total Deficit/ Single Deficit fam ily hedge (tons) (kgs) (meters) Shekora 34,731 2,105 13,009 6,180 69 Gimbuchu 49,428 2,996 26,428 8,822 98 Akaki 74,030 4,487 101,286 22,575 251 Alem Gena 116,568 7,065 88,803 12,570 140 Kursa Malima 34,573 2,095 16,696 7,968 89 Welmera 79,579 4,823 54,408 11,281 125 Addis Alem 65,605 3,976 41,200 10,362 115 Sululta 95,071 5,762 49,698 8,625 96 Mulo 28,487 1,726 11,510 6,667 74 Merti 60483 3,666 14449 3,942 44 Jeju 100747 6,106 16255 2,662 30 Serie 98040 5,942 21487 3,616 40 Dodota 54137 3,281 49850 15,193 169 Limo & Bilbo 113872 6,901 65829 9,539 106 Gedeb 101123 6,129 35784 5,839 65 Kofele 148541 9,002 11954 1,328 15 Shirku 149885 9,084 508 56 1 Tena 96100 5,824 24227 4,160 46 Robi 99465 6,028 19887 3,299 37 Suda 123938 7,511 16098 2,143 24 Toyo 78246 4,742 70975 14,967 166 Digelu & Toyo 97708 5,922 89302 15,080 168 Sinana 25496 1,545 1428 924 10 Dawa 70240 4,257 53334' 12,529 139 llu 44813 2,716 21700 7,990 89 Becho 47230 2,862 36059 12,597 140 Tole 49947 3,027 24048 7,944 88 Ad a a 104130 6,311 101029 16,009 178 Lume 68102 4,127 57438- 13,916 155 Minjar 54636 3,311 32020 9,670 107 Total 578,072 35,035 403,038 10,561 117 Double Total Trees/ha Family size 7.00 hedge Treesin on farm Hedge Kgs/meter= 16.5 (meters) fields fields Pollard tree kgs/tree 90 34 69 34 Farm Size= 2.00 49 98 49 125 251 125 70 140 70 44 89 44 63 125 63 58 115 58 48 96 48 37 74 37 22 44 22 15 30 15 20 40 20 84 169 84 53 106 53 32 65 32 7 15 7 0 1 0 23 46 23 18 37 18 12 24 12 83 166 83 84 168 84 5 10 5 70 139 70 44 89 44 70 140 70 44 88 44 89 178 89 77 155 77 54 107 54 59 117 59 APPENDIX 5: Table A5.1 Woody Biomass Development Zone Analysis Zone 2b:Cereal land use systems jn Central Rift Valley: moderately stocked with indigenous trees
Wereda Population Families Total Deficit/ Single Double Total Trees/ha Fa m i ly size= 7.00 Deficit family hedge hedge Trees in on farm Hedge Kgs/meter= 16.5 (tons) (kgs) (meters) (meters) fields fields Pollard tree kgs/tree 90 Shashamene 188,088 26,870 101,376 3,773 229 114 42 19 Farm Size= 2.20 Arsi Negele 105,315 15,045 49,715 3,304 200 100 37 17 Lanfero 96,982 13,855 22,673 1,636 99 50 18 8 Ziway 63,955 9,136 33,849 3,705 225 112 41 19 Dugda 80,854 11,551 30,625 2,651 161 80 29 13 Bora 35,984 5,141 13,582 2,642 160 80 29 13 Total 571,178 81,597 251,820 2,952 179 89 33 15
:Cereal land use systems in Centra! Rift Valley: lightly to very lightly moderately stocked with indigenous trees
Wereda Population Families Total Deficit/ Single Double Total T rees/ha Family size= 7.00 Deficit family hedge hedge Trees in on farm Hedge Kgs/meter= 16.5 (tons) (kgs) (meters) (meters) fields fields Pollard tree kgs/tree 90 Hitosa 114,846 16,407 123038 7,499 455 227 83 45 Farm Size= 1.86 Afaba Kulito 161,915 23,131 65,692 2,840 172 86 32 17 Dalocha 134,490 19,213 19,857 1,034 63 31 11 6 Adama 92,245 13,178 ' 215,668 16,366 992 496 182 98 Damot Gale 240,966 34,424 253 7 0 0 0 0 Limu Seka 151,207 21,601 36486 1,689 102 51 19 10 Jeldu 141,612 20,230 99549 4,921 298 149 55 29 Dendl 171,386 24,484 201597 8,234 499 250 91 49 Ambo 168,826 24,118 206387 8,557 519 259 95 51 Chellya 166,672 23,810 141976 5,963 361 181 66 36 Bako Tibe 83,849 11,978 78158 6,525 395 198 72 39 Dano 60,571 8,653 23060 2,665 162 81 30 16 Goro 123,264 17,609 201966 11,469 695 348 127 69 Adaberga 94,908 13,558 65579 4,837 293 147 54 29 Meta Robi 105,886 15,127 90380 5,975 362 181 66 36 Giba Keremu 107,003 15,286 55435 3,626 220 110 40 22 Horo 62,222 8,889 45693 5,140 312 156 57 31 Jardegna Jarte 36,824 5,261 19666 3,738 227 113 42 22 Abay Chomen 25,656 3,665 14981 4,087 248 124 45 24 Gudurn 111,483 15,926 76382 4,796 291 145 53 29 Jima Garet 93,776 13,397 82498 6,158, 373 187 68 37 Sibu Sere 73,054 10,436 657 63 4 2 1 0 Goba Seya 30,788 4,398 8195 1,863 113 56 21 11 Boneya Boshe 39,193 5,599 29509 5,270 319 160 59 31 Wama Hagelo 39,949 5,707 17459 3,059 185 93 34 18 Waya Tuka 58,594 8,371 47849 5,716 346 173 64 34 Guto Gida 53,510 7,644 35122 4,595 278 139 51 27 Diga 50,557 7,222 10263 1,421. 86 43 16 8 Leku Dulecha 63,295 9,042 96219 10,641 645 322 118 64 Jima Arjo 74,315 10,616 139563 13,146 797 398 146 79 Numu Kumba 47,557 6,794 73089 10,758 652 326 120 64 Ude Koba 157,537 22,505 20615 916 56 28 10 5 Total 3,137,956 448,279 2,342,841 6,424 329 164 60 32 APPENDIX 5: Table A5.1 Woody Biomass Development Zone Analysis Zone 2d:Cereal land use systems on non-vertisols in Central and Western Highlands: moderately to lightly stocked with indigenous trees
Wereda Population Families Total Deficit/ Single Double Total Trees/ha Family size 7.00 Deficit fam ily hedge hedge Trees in on farm Hedge Kgs/meter= 16.5 (tons) (kgs) (meters) (meters) fields fields Pollard tree kgs/tree 90 2.00 Yubdu 80,727 11,532 46,185 4,005 243 121 44 22 Farm Size= Gimbi 109,476 15,639 52680 3,368 204 102 37 19 Lalo Asabi 70,728 10,104 51139 5,061 307 153 56 28 Bojo Chekorse 67,248 9,607 19332 2,012 122 61 22 11 Ayere Guliso 68,684 9,812 30168 3,075 186 93 34 17 Nejo 130,923 18,703 22396 1,197 73 36 13 7 Jarso 86,254 12,322 35052 2,845 172 86 32 16 Menesibo 169,254 24,179 59380 2,456 149 74 27 14 Haru 64,263 9,180 53403 5,817 353 176 65 32 Asosa 130,295 18,614 20792 1,117 68 34 12 6 Begi 167,681 23,954 57252 2,390 145 72 27 13 Jima Haro 34,198 4,885 21390 4,378 265 133 49 24 Dale Wabere 93,516 13,359 54015 4,043 245 123 45 22 Dale Sedi 69,906 9,987 43010 4,307 261 131 48 24 Seya 106,531 15,219 54591 3,587 217 109 40 20 Hawa Gala 55,549 7,936 9075 1,144 69 35 13 6 Total 1,505,233 215,033 629,860 3,175 192 96 35 18
:Cereal land use systems in Eastern and Southern Lowlands: moderately stocked with indigenous trees
Trees/ha 7.00 Code # Wereda Population Families Total Deficit/ Single Double Total Family size D eficit fam ily hedge hedge Trees in on farm Hedge Kgs/meter= 16.5 (tons)' (kgs) (meters) (meters) fields fields Pollard tree kgs/tree 90 2.10 Zala 63,859 9,123 6,891 755 46 23 8 4 Farm Size= Kucha 109,110 15,587 18,405 1,181 72 36 13 6 Dera Malo 59,145 8,449 20,256 2,397 145 73 27 13 8 Total 232,114 33,159 45,552 1,445 88 44 16