Land and Natural Resources Degradation in the Arid and Semi-Arid Lands in Kenya October 2018 Technical Report Land and natural resources degradation in the Arid and Semi-Arid Lands, Kenya Technical Report Client World Bank Authors Ephraim Nkonya (IFPRI, USA) Aaron Minnick (WRI, USA) Eric Ng’ang’a (WRI, Kenya) Johannes Woelcke (UNIQUE) Date: 26.10.2018 TABLE OF CONTENTS List of tables .................................................................................................................................. iv List of figures ..................................................................................................................................v List of MAPS .................................................................................................................................. vi List of abbreviations ..................................................................................................................... vii 1 Introduction ............................................................................................................................. 1 2 Garissa, Turkana and Wajir ...................................................................................................... 2 3 Drivers, extent and cost of degradation ................................................................................ 10 3.1 Drivers of land degradation............................................................................................ 10 3.2 Extent of land degradation ............................................................................................. 16 3.3 Cost of land degradation ................................................................................................ 23 4 Restoration options................................................................................................................ 24 4.1 Rangeland restoration .................................................................................................... 25 4.2 Cropland restoration ...................................................................................................... 28 4.3 Reforestation and afforestation ..................................................................................... 29 5 Spatial analysis ....................................................................................................................... 30 5.1 Methodology .................................................................................................................. 30 5.2 Reforestation and afforestation ..................................................................................... 31 5.3 Rangeland restoration .................................................................................................... 34 5.4 Cropland restoration ...................................................................................................... 35 6 Lessons learned and past experience .................................................................................... 37 7 Policy recommendations........................................................................................................ 40 8 Reference list ......................................................................................................................... 45 9 Annex ..................................................................................................................................... 54 Annex 1: Analytical methods for analyzing drivers of adoption of land management practices for restoration of degraded lands .......................................................................... 54 Annex 2: Cost benefit analysis methodological approach ..................................................... 54 Annex 3: Opportunities and challenges of provision of extension services in Kenya............ 56 Annex 4: Indigenous knowledge ............................................................................................ 58 Annex 5: Comparison of Wajir county and national level budget allocation ........................ 60 UNIQUE | Kenya Land Restoration iii LIST OF TABLES Table 1: Potential livelihood impacts of irrigation in the AOIs ..................................................... 5 Table 2: Drivers of adoption of ISFM, Kenya ............................................................................... 12 Table 3: Extent of forest and rangeland degradation ................................................................. 17 Table 4: Adoption of ISFM, agroforestry, manure and inorganic practices (by county, percentage of households) ..................................................................................... 21 Table 5: Annual cost of land degradation due to land use/cover change, 2000-09 ................... 24 Table 6: Restoration options, justification and main challenges for degraded biomes ............. 24 Table 7: Financial Net Present Value of rotational grazing for a 20 year planning horizon ....... 26 Table 8: Economic and Financial NPV for restoration of degraded cropland ............................. 29 Table 9: Criteria for identification of restoration area by biome ................................................ 30 Table 10: Restoration potential of forest and riverbanks ........................................................... 32 Table 11: Rangeland restoration potential at sub-county in the AOI ......................................... 34 Table 12: Cropland restoration potential in the AOI................................................................... 36 Table 13: Gaps in current government interventions and policy recommendations ................. 41 UNIQUE | Kenya Land Restoration iv LIST OF FIGURES Figure 1: Area of Interest: Garissa, Turkana and Wajir ................................................................. 2 Figure 2: Severity of poverty in the AOI compared to national poverty level .............................. 3 Figure 3: Irrigation development in Kenya - compared to SSA regions ........................................ 4 Figure 4: Kenya Government environmental regulations for the protection of water bodies ..... 6 Figure 5: Distance to the nearest rural service in the AOI compared to other areas ................... 8 Figure 6: Access to formal agricultural extension services ........................................................... 9 Figure 7: Content of advisory services in the AOI and ASAL (by source) ...................................... 9 Figure 8: Access to agricultural advisory services in the AOI compared to other areas (by topic) ................................................................................................................................ 10 Figure 9: Trend of livestock population (TLU) in Kenya, 1991-2016 ........................................... 13 Figure 10 Livestock production constraints in the ASAL ............................................................. 14 Figure 11: Comparison of indigenous cattle carcass weight across regions ............................... 14 Figure 12: Charcoal price trend in Kenya, 2000-2018 ................................................................. 15 Figure 13: Trend of use of fuelwood and other cooking energy source among Kenyan rural households.............................................................................................................. 16 Figure 14: Formal and informal sources of seeds and planting material for forages in the ASALs of Kenya .................................................................................................................. 26 Figure 15: Financial Net Present Value of rational grazing ......................................................... 27 Figure 16: Economic NPV of rotational grazing........................................................................... 27 Figure 17: Major crops grown in each of three AOI counties ..................................................... 28 Figure 18: Financial and economic analysis of reforestation and riverbank restoration ........... 30 Figure 19: Comparison of adoption rate of soil fertility management practices in Kenya ......... 38 Figure 20: Trend of agroforestry and fertilizer adoption rate in Kenya, 1997-2013 .................. 38 UNIQUE | Kenya Land Restoration v LIST OF MAPS Map 1: Forest degradation in the AOI......................................................................................... 18 Map 2: Level of rangeland degradation in the AOI ..................................................................... 19 Map 3: Riverbank degradation in the AOI................................................................................... 20 Map 4: Adoption rate of agroforestry in Kenya by county ......................................................... 22 Map 5: Cropland degradation as reflected by adoption of ISFM in AOI and other areas .......... 23 Map 6: Forest and riverbank restoration potential in the AOI ................................................... 33 Map 7: Rangeland restoration potential ..................................................................................... 35 Map 8: Cropland restoration potential in Turkana County ......................................................... 36 UNIQUE | Kenya Land Restoration vi LIST OF ABBREVIATIONS AOI Area of Interest ASAL Arid and Semi-Arid Lands AWM Agriculture Water Management CBA Cost-Benefit Analysis CBO Community-based organization CIAT The International Center for Tropical Agriculture CIMMYT International Maize and Wheat Improvement Center CPAs Charcoal Producer Associations ENPV Economic Net Present Value FMNR Farmer-Managed Natural Regeneration FNPV Financial Net Present Value GDP Gross Domestic Product GoK Government of Kenya ha Hectare IBLI Index-Based Livestock Insurance ICRAF The World Agroforestry Center ICRISAT The International Crops Research Institute for the Semi-Arid Tropics ICT Information and Communication Technologies IFPRI International Food Policy Research Institute IGAD Intergovernmental Authority on Development ILRI International Livestock Research Institute IRR Internal Rate of Return ISFM Integrated Soil Fertility Management IWDM Integrated Watershed Development and Management KCC Kenya Cooperative Creameries Ltd KEFRI Kenya Forestry Research Institute KLDP Kenya Livestock Development Program km2 Square Kilometer KNAIS Kenya National Artificial Insemination LUCC Land Use-Cover Change m Meter MEA Millennium Ecosystem assessment MENR Ministry of Environment and Natural Resources MRR Marginal Rate of Return NDVI Normalized Difference Vegetation Index NEDI North-Northeastern Development Initiatives NGO Non-Governmental Organizations NPV Net Present Value NTFP Non-Timber Forest Products PES Payment for Ecosystem Services r Discount Factor RPLRP Regional Pastoral Livelihoods Resilience Project UNIQUE | Kenya Land Restoration vii RWHM Rainwater Harvesting and Management SLM Sustainable Land Management SSA Sub-Saharan Africa TLU Tropical Livestock Units USA United States of America WRI World Resources Institute UNIQUE | Kenya Land Restoration viii 1 INTRODUCTION Land degradation is severe in Kenya due to deforestation and land use cover change (LUCC) which replaces high value biomes with low-value biomes. Due to deforestation and charcoal- making, Kenya lost 12,400 ha of forest from 1990-2015. Deforestation is especially severe in the Rift Valley (Baker and Miller 2013). The closed canopy forest – which covered approximately 12% of the land area – has been reduced to only 1.7% of its original size (GOK 2010). Excluding charcoal and other subsistence uses, Kenya’s forests account for 3.6% to Kenya’s GDP and sup- port agriculture, livestock, energy, trade, and other industries – which cumulatively contribute about 39% of the GDP. Forests comprise the country’s water towers and catchments where over three quarters of the renewable surface water originates (GoK 2014). Conversion of grasslands and shrublands to cropland has also occurred in many provinces – leading to 16% of cropland expansion from 1990-2015. On static biomes – i.e., biomes which did not experience LUCC, use of land degrading management practices has led to reduced productivity of cropland and grazing lands. Over 80% of Kenya’s total land area is classified as arid and semi -arid land (ASAL) and is con- sidered being at risk of desertification. The ASAL region is home to about 30% of Kenya’s human and 50% of its livestock population. 90% of the total meat consumed in the country comes from the ASAL (GoK 2010). The livestock sector in the ASAL employs 10 million people – which is 90% of the adult labor force and accounts for 95% of household income (GoK 2010). Overgrazing in the ASAL region (Mwaura et al 2017) is due mainly to the rapidly increasing livestock population. While grassland areas declined, the number of heads of cattle almost doubled from 14 million in 1990 to 21 million in 2016 (FAOSTAT 2016). This study analyzes the severity and cost of land degradation in the ASALs focusing on three Areas of Interest (AOIs) – Garissa, Turkana, and Wajir Counties. It identifies suitable restoration options and makes recommendations on how to facilitate their large-scale uptake. Spatial maps are used to present the results – an approach which will help the government and development partners to design and implement investment projects. Chapter 2 provides relevant background information about the institutional, environmental and economic environment of the AOIs. Chapter 3 discusses the cost and drivers of land degradation. Findings of the spatial analysis on the extent of land degradation in the AOIs are presented in Chapter 5. Chapter 6 describes some lessons learnt and past experiences with resource conservation and sustainable land manage- ment before Chapter 7 concludes and proposes some policy recommendations. UNIQUE | Kenya Land Restoration 2 GARISSA, TURKANA AND WAJIR Garissa, Turkana and Wajir are the three largest and among the poorest counties in Kenya. In terms of surface area they account for 28% of Kenya’s total surface area of 610,000 km2. How- ever, they account for only 4% of the nation’s population of 37,724,850 people (NBS 2016a). The three counties – located in the eastern and north-western regions (Figure 1) - are among the poorest counties in Kenya (Figure 2). The overarching developmental challenges in the ASAL are infrastructure, water deficit and abject poverty. With respect to poverty, headcount and severity of poverty all three counties are significantly well above the national average. In Turkana for example, the poverty head-count amounts to almost 80% and the county is the poorest in Kenya. All three counties have sparse population and poor market infrastructure, which hampers development. The main livelihoods in the three counties is livestock production (KNBS 2015b). Figure 1: Area of Interest: Garissa, Turkana and Wajir UNIQUE | Kenya Land Restoration 2 Figure 2: Severity of poverty in the AOI compared to national poverty level Notes: Poverty headcount = number of people below poverty line as % of total population Severity of poverty = proportionate poverty gap in the population Source: KNBS 2015 Water development in the ASAL The population of the AOI faces a severe water shortage, especially for livestock. Droughts which hit Kenya in 2008 to 2011, cost the Kenyan livestock sector US$3.3 billion (ILRI 2015). Loss of livestock due to hydrological shocks could tip households into destitution and desper- ation. Studies have shown that the significant livestock mortality in the ASAL pastoral commu- nities tips household into a poverty trap (McPeak and Barrett 2001, Lybbert et al. 2004, Barrett et al. 2006). Discussions with county officials in Turkana and Wajir demonstrated that currently counties do not elaborate strategies for addressing the severe water shortage for livestock. However, they consider it as a priority area for investments. Particularly, rainwater harvesting and man- agement (RWHM) is lacking in Kenya’s ASAL. Of interest is the comparison of allocation to wa- ter resource development at national and Wajir county level. At national level, the sectors of Environment Protection and Water and Natural Resources account for only 2% of total budget expenditures compared to 16% for Wajir’s Ministries of Water Resource Development and En- ergy, Environment, and Natural Resources (Annex 9.5). The severe water shortage in the ASAL is the major reason behind the big difference between the two budgets. So far water development has not been considered systematically in programs for restora- tion of degraded lands in Kenya, even though such combined efforts have shown high payoff. Agriculture Water Management (AWM) - which is management of water used for both irri- gated and rainfed crops, livestock production and inland fisheries - is poorly developed in Kenya – even on sub-Saharan Africa’s (SSA) scale (Ngigi 2002). Only 2% of cultivated area is equipped for irrigation – compared to 3.5% for SSA (Figure 3). Similarly, only 2% of cultivated area is under AWM – compared to SSA’s 4.5%. Irrigation development in the ASAL region is UNIQUE | Kenya Land Restoration 3 even lower. The Sudano-Sahelian region – with comparable water deficit – has the highest AWM development in SSA. Figure 3: Irrigation development in Kenya - compared to SSA regions Key: Sudano-Sahelian: Burkina Faso, Cape Verde, Chad, Djibouti, Eritrea, The Gambia, Mali, Mauritania, Niger, Senegal, Somalia, Sudan Eastern: Burundi, Ethiopia, Kenya, Tanzania, Uganda, Rwanda Gulf of Guinea: Benin, Côte d’Ivoire, Ghana, Guinea, Guinea-Bissau, Liberia, Nigeria, Sierra Leone, Togo Central: Angola, Cameroon, CAR, DRC, Rep. of Congo, Equatorial Guinea, Gabon, Sao Tome & Principe Southern: Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia, Zimbabwe Source: Calculated from Svendsen et al 2009. Recently, President Uhuru Kenyatta has declared that the government plans to develop two million ha of irrigated land. However, no feasibility study has been conducted so far to verify the area or specify the investments required. The Vision 2030 – which aims “to transform Kenya into a newly industrializing, middle-income country providing a high quality of life to all its citizens by 2030 in a clean and secure environ- ment” – has set a target of developing 1.2m ha irrigated area in the ASALs – a level which suggests developing 32,000 ha of irrigated area per year. If this goal is achieved, it will benefit a large population of people in Turkana – an area with the largest irrigation potential in the AOI (34,180 ha) (Table 1). Wajir has the smallest irrigation potential and consequently fewer potential beneficiaries. However, the crops planned in each AOI counties are cereals, legumes and fruits (banana & mango). Vegetables are not planned for – though their demand is increas- ing fast with increasing middle income and urban population (Rischke et al. 2015). Plans to invest in irrigated fodder is important but its implementation needs to be considered in terms of strategic commercialization of livestock fed with irrigated fodder. UNIQUE | Kenya Land Restoration 4 Table 1: Potential livelihood impacts of irrigation in the AOIs County Irrigation Potential (ha) Crops Expected Production(Ton) No of beneficiaries (000)a Garissa 4560 24.8 760 Maize 1.9 14.1 95 Paddy 0.4 2.6 380 Sorghum 0.8 5.6 380 G/ grams 0.4 19.0 380 Cow peas 1.0 43.2 570 Fodder 2.4 1,235 Banana 9.5 760 Mango 8.6 Turkana 34,180 449 8300 Maize 207.5 1537.0 3320 Sorghum 6.6 49.2 3,320 Green grams 8.3 377.3 830 Bananas 20.8 830 Mangoes 41.5 4,980 Fodder 74.7 4,200 Maize 10.5 77.8 525 Paddy 2.0 14.6 2,100 Sorghum 4.2 31.1 2,100 G/ grams 2.3 105.0 2,100 Cow peas 5.3 238.6 525 Bananas 13.1 1,050 Mangoes 52.5 Wajir 260 2.1 100 Maize 0.3 1.9 40 Sorghum 0.1 0.6 40 Cow peas 0.1 4.5 10 Bananas 0.3 10 Mangoes 0.5 60 Fodder 0.9 a Total population per county is not reported since beneficiaries of the listed crop could be double-counted. Source: FAO 2013 Institutional environment The Government of Kenya and its development partners have increased their efforts to spur ASAL development. The recent oil discovery in Turkana (Johannes et al. 2015) and groundwater discovery in Turkana and Wajir and neighboring counties (Luedeling et al. 2015) has raised in- terest in developing the three counties. The increased attention is a radical departure from the 50- year neglect of the ASAL. Decentralization has led to a significant allocation of national resources to the counties and has given the counties a greater mandate to plan their own development reflecting local needs. The 47 counties in Kenya are allocated 15% of the total revenue collected at national UNIQUE | Kenya Land Restoration 5 level (Kimenyi 2018). County governments are given the mandate to collect additional revenue from within their area of jurisdiction (Khaunya et al. 2015). As part of the government’s efforts to speed up development in northern Kenya, the ASAL counties receive a higher allocation of the national level revenues. Accordingly, development partners have joined hands in addressing the ASAL development challenges. For example, the World Bank finances US$253 per capita in North-Northeastern Development Initiatives (NEDI) compared to only US$111 per capita in the rest of the country (World Bank 2016). Although almost all forest area and rangelands in the AOI are community-owned there is no clear mandate for villages to enact and enforce by-laws. Discussion with county officials in Tur- kana and Wajir showed that the counties have not yet enacted significant legislation for natural resources management because they are in the early stage of establishing their institutions. For example, the Turkana Land Act is still under discussion and has not been finalized. Given the key role played by rivers in the three counties for supplying water for both people and livestock, regulations have been placed to safeguard riverbanks. The national environ- mental protection law requires the establishment of a buffer zone around water bodies (GoK 2013). No cultivation or any activities are allowed within 15-30 m from water bodies (Figure 4). County level legislation on the protection of riverbanks exists and is in conformity with the national level statutes. To successfully implement this regulation, the central and county gov- ernments promote tree planting along water bodies. Figure 4: Kenya Government environmental regulations for the protection of water bodies Source: Authors – based on data processed by KFS (2013) Management of pastoral conflicts and supporting nomadism is another important institu- tional challenge which the ASAL counties are facing. All three AOI counties share borders with countries which have decades-long armed conflicts. This has created a supply of small arms, UNIQUE | Kenya Land Restoration 6 which have changed the nature of the traditional weapons used in conflicts. The pastoral com- munities in all three counties acquire guns to defend themselves from invaders from across international borders and other domestic cattle rustlers. Garissa and Wajir are neighboring So- malia – a country with no formal government for the past 27 years and with constant tribal fighting. Turkana is neighboring South Sudan, a country which has experienced civil war for more than 40 years and Uganda where Karamoja pastoralists live – both of which use small arms in cattle rustling operations. Cattle rustling is showing an upward trend as it becomes commercialized. The rustlers steal livestock and sell them in urban markets – as opposed to the tradition of keeping the stolen livestock as a symbol of wealth and prestige (Khisa 2016). A study done in Samburu and Marsa- bit showed cattle rustling increased from 5 to 20 incidents per year in the selected communi- ties (Ibid). In addition to commercialization of cattle raids and the fatal weaponry used, climate change has increased frequency of drought and higher livestock mortality, which in turn forces pastoralists to replenish lost livestock by cattle rustling (Meier et al. 2007). Government efforts to disarm pastoralists have been used as a strategy for addressing cattle rustling. However, such practices disadvantage the pastoralists against cattle rustlers from neighboring countries. Worse still, studies have shown a strong correlation between firearms recovered and frequency of cattle raids (Khisa 2016). The constitution gives greater recognition to customary institutions used in the communal pastoral areas in the ASAL (Odote 2015) and encourages the application of traditional dispute resolution mechanisms in land conflicts (GoK 2010). Cross-cultural traditional conflict resolution approaches worked in the decades-long con- flicts between the Sukuma and Maasai of Tanzania. It ended when clan leaders from both groups met and resolved the cattle rustling conflict. The Government of Tanzania facilitated the meet- ings and conflict resolutions process. However, several studies report that the militarization of cattle rustling has brought an end to traditional conflict resolution avenues (Brock-Utne 2004; Kariuki 2015). Access to roads, markets and information Farmers in the AOI counties travel a distance five times longer than the rest of the country to reach an input or output market. Figure 5 also shows that farmers in AOI counties travel twice the distance that farmers in the rest of the country travel to reach the nearest all-weather road. Studies have shown that access to roads, markets and extension services are key drivers of adop- tion of sustainable land management practices and productivity (e.g. see Barrett 2008; Barrett et al. 2010). UNIQUE | Kenya Land Restoration 7 Figure 5: Distance to the nearest rural service in the AOI compared to other areas Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 Access to advisory services in the AOI is the lowest countrywide (Figure 6). The department of extension froze hiring extension agents for many years. Additionally, many extension agents are retiring – leaving behind a big gap. Currently one Kenyan public extension agent serves around 6000 rural farmers, a level which is higher than the average at regional and sub-regional level, but reflects the limited number of providers. Based on 228 working days1 per year, it will take one Kenyan extension agent 26 years to visit each of the 6000 farmers under her/his jurisdiction. The number of extension providers are even more limited in the ASAL region. Advisory services offered by formal extension services – which includes extension services offered by government, NGOs, and research institutions (including universities and colleges) – reach only about 20% of households in Kenya and only 9% of farmers in the AOI. This underscores the limited access to advisory services in the AOI. 1There are 13 public holidays, 102 weekend days and 20 days of annual vacation. Thus, the total non-working days are 137. UNIQUE | Kenya Land Restoration 8 Figure 6: Access to formal agricultural extension services Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 Extension service providers affiliated with the government are the major providers of any form extension services (Table A 2). The content offered by those formal providers is mainly related to production. For advisory services related to climate/drought early warning, agricultural mar- keting and veterinary services, non-formal advisory service providers are the major providers (Figure 7 and Table A 2). For example, of farmers receiving services related to agricultural mar- keting only 28% of farmers received services from formal/public services, while 78% from infor- mal/private sources (Figure 7 and Table A 2). In general, the low numbers of the public advisory service provision illustrate the potential role other type of service providers, such as from the private sector, could play. Figure 7: Content of advisory services in the AOI and ASAL (by source) Source: Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 UNIQUE | Kenya Land Restoration 9 Despite their high acceptability among pastoralists, use and promotion of indigenous knowledge by formal extension agents is rare. Pastoral communities have a rich indigenous knowledge of rangeland management. Studies have shown that indigenous pastoral knowledge is effective and sustainable (Reed et al. 2007; Niamir 1998). The pastoralists have a deep knowledge of their ecological environment and their livelihoods have sustainably man- aged rangelands and water resources for decades. For example, Table A 4 (Annex) shows the calendar for Turkana people. Each month has a word which has a meaning, which translates into rainfall seasons, condition of rangelands, other biomes and other prevailing conditions that pastoralists must cope with. Indigenous knowledge related to sustainable rangeland man- agement includes aspects such as enclosures, nomadic livelihoods, and selective tree harvest- ing. Annex 9.5 provides details of some of sustainable indigenous knowledge practices. Interestingly, on the topic of output marketing, farmer-to-farmer advisory services is the third most important source (Table A 2. This underscores the role that farmers could play and fill in the gaps of public providers (Krishnan and Patnam 2013). With respect to climate early warning, media are the most important source with 60% indicating the increasing role modern ICT could play. Veterinary services are largely provided by government extension agents in AOI and by agro-vet dealers and private companies in the rest of the country. Figure 8: Access to agricultural advisory services in the AOI compared to other areas (by topic) Source: Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 3 DRIVERS, EXTENT AND COST OF DEGRADATION 3.1 Drivers of land degradation This section presents original research results on the drivers of degradation of cropland. We use an econometric approach to determine drivers of land degradation. The analytical approach is given in Annex 1. The focus is on drivers of adoption of ISFM. Understanding the drivers of ISFM indirectly implies the drivers of land degradation. For example, we show below that rural services increase adoption of ISFM. This suggests that poor access to rural services is a driver of land degradation. UNIQUE | Kenya Land Restoration 10 The discussion on drivers of rangeland management is based on literature review . Unfortu- nately, the 2013 Agricultural Sector Household Baseline Survey did not collect good data on live- stock management. For example, there was no question on grazing land management. Drivers of cropland degradation Access to rural services is a major driver of adoption of ISFM. As expected, access to rural ser- vices is correlated with adoption of ISFM in Kenya (Table 2). Belonging to farmer groups is also associated to higher propensity of adoption of ISFM, suggesting the need for investing in access to rural services as part of land restoration efforts. Proximity to all-weather roads in Kenya is positively associated with propensity to ISFM adoption. Access to market does not seem to play a significant role, likely due to strong relationship between market access and roads or district headquarters. Access to general agricultural extension and agroforestry advisory services is pos- itively correlated with ISFM adoption in Kenya. The limited access to extension services is due to small number of staff. As discussed above, the department of extension froze hiring extension agents for many years and many extension agents are retiring – leaving behind a big gap. Human capital increases adoption of ISFM – a knowledge-intensive agricultural practice. Edu- cation increases the propensity to adopt ISFM in Kenya (Table 2). This is consistent with empiri- cal evidence from Africa – which has shown that education is associated with higher adoption of agricultural technologies (Alene and Manyong 2007; Appleton and Balihuta 1996) – especially those related to knowledge intensive technologies such as ISFM (Bationo et al. 2007). The AOI counties have among the lowest level of education in Kenya (CRA 2011). It is thus not surprising that ISFM adoption is low in the AOI. The number of adults – a proxy of family labor supply– is negatively correlated with adoption of ISFM. It is expected that family labor would increase ISFM adoption since the technology is labor intensive – especially if it involves biomass transfer (Nkonya et al. 2015). However, the unexpected result could be linked to poverty factors associated with large families – which could limit ISFM adoption. Capital endowment has weak impact on adoption of ISFM. Contrary to a priori expectations, land tenure does have a significant impact on adoption of ISFM. This could be due to the limited variability of land tenure type. Land size reflects wealth and financial ability to adopt ISFM. How- ever, cropland size does not have significant association with adoption of ISFM. Number of livestock is negatively correlated. Other studies have shown that livestock rearing increases biomass production (through manure) and provides animal draught power to biomass transfer (Nkonya et al. 2015) and both enhance adoption of ISFM. The negative correlation with number of livestock could be due to the lower dependency on crop production among predom- inantly livestock keepers’ households – especially in the AOI. UNIQUE | Kenya Land Restoration 11 Table 2: Drivers of adoption of ISFM, Kenya Probit maximum likelihood coefficients Structural Reduced Human capital Male-headed household 0.098*** 0.108*** Education of household head (cf no education) • Primary 0.399*** 0.420*** • Post-primary 0.470*** 0.498*** Number of adults -0.005*** -0.004*** Physical capital Farm size 0.000 -0.0001 Land tenure (Freehold) • Customary -0.167*** -0.171*** • Leasehold/rented -0.228** -0.260** TLU -0.018*** -0.017*** Access to rural services Distance (km) to market 3.73e-06 4.76e-06* Distance (km) to all-weather road -0.005*** -0.006*** Belong to farmer group 0.202*** Received general agricultural extension 0.075** Received agroforestry extension services 0.225*** Have access to credit services 0.230*** Constant -0.983*** -0.933*** TLU=Tropical Livestock Units: conversion factors to TLU: Cattle = 0.7, Sheep = 0.1, Goats = 0.1, Pigs = 0.2, Chicken = 0.01 & Donkey=0.5 Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 Drivers of adoption of land management practices for restoration of grazing lands The main driver of rangeland degradation in the AOI is overgrazing . Livestock population has been increasing fast in Kenya, seeing an increase of more than 80% over the last 26 years (Fig- ure 9). During the same period, the total area of grazing lands has decreased (FAOSTAT 2016). Wildfire frequency in rangelands in Kenya has increased (Phillips 2012) – largely due to climate change, charcoal burning and pastoral practices (Sankaran et al. 2008). Higher frequency and intensity of wildfire increases rangeland degradation. UNIQUE | Kenya Land Restoration 12 Figure 9: Trend of livestock population (TLU) in Kenya, 1991-2016 Notes: TLU = Tropical livestock unit. Conversion factor to TLU: Camel=1.0; Cattle=0.7, goat or sheep = 0.1. Source: Computed from FAOSTAT raw data. Consistent with ISFM results reported above, access to rural services is among the most im- portant constraints reported by pastoralists (Figure 10). ASAL pastoralists reported access to markets as one of the leading constraints of livestock production (Figure 10). Likewise, access to extension services is the most important constraint reported by pastoralists. Water scarcity and diseases are also reported to be major constraints. This illustrates the need to invest in improv- ing agricultural markets and all-weather roads to incentivize farmers to invest in rangelands and cropland improvement and to increase agricultural water development investment. Such invest- ment could increase rangeland productivity by increasing carcass weight of animals. For exam- ple, carcass weight of two heads of indigenous cattle from SSA is equivalent to the weight of only one indigenous cattle from East Asia, North America and Europe (Figure 11). Rangeland improvement will help increase carcass weight – which in turn will help farmers obtain higher prices. UNIQUE | Kenya Land Restoration 13 Figure 10 Livestock production constraints in the ASAL Source: Onono et al. 2013 Figure 11: Comparison of indigenous cattle carcass weight across regions Notes: NAM=North America, NENA=Near East and North Africa; SE = South East; LAC=Latin America and Caribbean countries; SSA= sub-Saharan Africa. Source: FAOSTAT raw data online. Pilot studies done by ILRI and other partners have shown that implementation of Index-Based Livestock Insurance (IBLI) is effective in de-risking livestock production in the ASAL. IBLI sim- plified by using satellite imagery to objectively assess vegetation data in near-real time. This information can be used to determine the risks and impacts of drought on livestock. The sat- ellite data are then combined with household-level livestock data to determine payments. Thereby, the basis risk is reduced (ILRI 2015). It is the satellite imagery and household data which determines payment – rather than livestock mortality, which could be hard to deter- mine. Initial assessment shows high acceptability of IBLI (Ibid). Even in the northeastern area, UNIQUE | Kenya Land Restoration 14 IBLI has been made compliant with the Islamic sharia law by using the “takaful” system in which pastoral community members contribute money into a pool system to guarantee all members of compensation if a shock happens (ILRI 2015). Drivers of forest degradation Charcoal making is the major driver of deforestation in the ASAL region. Kenya is one of the largest charcoal consumers in SSA and its consumption is expected to double by year 2030 (Njenga et al 2013). To address the deforestation challenge, Kenya set the Charcoal Regulations of 2009 (also known as the “Charcoal Rules”) – charcoal producers need to have a license to produce charcoal and have to be members of the Charcoal Producer Associations (CPAs) (Wajiru and Omedo 2016). The CPAs responsibilities include identifying sources of wood, ensuring sus- tainable harvesting and carbonization technologies and selling from centralized points (Ibid). Despite this effort, it is estimated that 60% of Kenya’s charcoal is produced and sold by non-CPA members. The inefficient earth kilns – with a 10-15% rate of carbonization – remains the pre- dominant production process (Ibid). A study done in Ewaso North forest conservancy – which covers ASAL counties of Isiolo, Samburu and Marsabit – showed that the major driver of increasing charcoal making is the increasing prices of charcoal and urbanization (KFS 2013). For example, price of charcoal in Nairobi in- creased by six fold from US$0.12/kg in 2000 to 2017 US$0.75/kg in 2018 – a 34% annual increase (Error! Reference source not found.). However, the price spiked in the past five years, rising from about US$0.2 to US$0.75. The increased enforcement of the charcoal rules and kerosene, electricity and other cooking energy sources are among the drivers of the charcoal price spike (Daalberg 2018). Figure 12: Charcoal price trend in Kenya, 2000-2018 Source: Extracted from Daalberg 2018 Demand for fuelwood in rural areas is also a major driver of deforestation. About 85% rural households use fuelwood and its intensity of use has remained unchanged in the past 15 years (Error! Reference source not found.). Thus, increasing human population has increased fuel- wood harvesting – contributing to deforestation. UNIQUE | Kenya Land Restoration 15 Figure 13: Trend of use of fuelwood and other cooking energy source among Kenyan rural households Source: Extracted from Daalberg 2018 3.2 Extent of land degradation We use the Millennium Ecosystem assessment (MEA) definition of land degradation. MEA de- fines land degradation as long-term loss of on-site and off-site terrestrial ecosystem goods and services, which humans derive from them (MEA 2005). Two types of land degradation are analyzed in this study: • Land degradation due to land use/cover change (LUCC). Land degradation due to LUCC occurs if a low-value biome replaces a high value biome. A biome is a community of plants and/or animals occupying a distinct area. This includes forests, cropland, shru- blands, etc. • Using land degrading management practices in a biome which did not experience LUCC. For example, overgrazing on rangeland, which remained rangeland, is consid- ered to be degradation. Different approaches are used to measure degradation of land, forests, and rangelands. We measured rangeland productivity using normalized difference vegetation index (NDVI) data. NDVI is a standardized indicator of vegetation health – healthier plants have high NDVI. For forests, productivity is measured using its density. The denser a forest, the more productive it is. For land we regard the non-adoption of agroforestry and integrated soil fertility man- agement (ISFM) as indicators of degradation on cropland. ISFM is a set of soil fertility man- agement practices that include the use of improved germplasm, judicious amount of mineral fertilizers, and organic inputs adapted to local conditions (Vanlauwe et al 2015). Riverbank degradation is analyzed based on the degree of tree clearing along riverbanks. Degradation of forests is very severe in the three counties. About 76% of the forest area in both Garissa and Turkana are degraded (Table 3 and Map 1). In Wajir the situation is even more severe, since 97% of its forest area is degraded. In the three counties there is no forest UNIQUE | Kenya Land Restoration 16 under national ownership (gazette forest). All forest areas are under community ownership. Table 3: Extent of forest and rangeland degradation Extent of biome as Area degraded as per- Biome area percent of total sub- cent of total biome county area area Subcounty Range- Range- Forest Rangelands Forest Forest lands lands Extent (1000 ha) Percent Garissa County 305.7 3991.4 5.4 93.3 76.2 94.9 - Balambala 0.8 419.8 0.2 99.1 100 96.3 - Daadab 0.8 667.5 0.1 98.2 40.8 86.7 - Fafi 15.8 1518.3 1 97.8 66.4 71.4 - Garissa-urban 0.7 65.6 1 98.5 100 98 - Ijara 276.4 689.2 28.2 70.2 50 100 - Ladgera 11.2 631 1.7 96.3 100 100 Turkana County 278.5 6180.3 3.6 89.8 75.8 73.1 - Loima 39.3 815.8 4.4 91.3 85.1 58.9 - Turkana Central 10.8 487.7 1.9 85.8 55.9 94.2 - Turkana East 28.1 970.4 2.5 86.4 71.4 84.4 - Turkana North 73.1 1831.2 3.7 93.2 99.9 69.6 - Turkana South 14.7 661.4 2 90.2 42.6 51.1 - Turkana West 112.5 1413.8 7.3 92.1 100 80.4 Wajir County 104.6 5487.1 1.5 96.8 82.1 82.3 - Eldas 1 392.6 0.2 95.8 27.6 90.2 - Tarbaj 15.6 927.4 1.6 97.9 99.7 88.3 - Wajir East 6.5 390.9 1.6 97.4 99.7 64.8 - Wajir North 12.8 836.5 1.5 97.5 99.8 82.5 - Wajir South 56.6 2070.5 2.6 95.7 87.9 66.8 - Wajir West 12.1 869.2 1.3 96.4 77.9 100 Source: Authors – based on data processed by KFS (2013) UNIQUE | Kenya Land Restoration 17 Map 1: Forest degradation in the AOI Source: Authors – based on data processed by KFS (2013) Rangeland degradation is also severe in all three counties (see Table 3). Degraded rangeland area as a share of total rangeland is 95% in Garissa, 82% in Wajir and 73% in Turkana. Map 2 shows that almost the entire land area in each county is degraded rangelands. A number of sub- counties report 100% degradation of rangelands. UNIQUE | Kenya Land Restoration 18 Map 2: Level of rangeland degradation in the AOI Source: Authors – based on data processed by KFS (2013) Although limited in number, rivers play an important role for ASAL livelihoods. The extent (land area) of riverbanks is small given that the AOIs are in the drylands. Map 3 shows the severity of land degradation along all rivers. Riverbank degradation is most severe in the southern part of Garissa County. UNIQUE | Kenya Land Restoration 19 Map 3: Riverbank degradation in the AOI Source: Authors – based on data processed by KFS (2013) Land degradation on cropland is severe. Table 4 shows no adoption of ISFM in Turkana and Wajir and only 4% adoption in Garissa. Adoption of agroforestry is also zero in Wajir and only 1% and 5% in Turkana and Garissa respectively. Comparison of adoption of ISFM and agrofor- estry in the AOI and the rest of Kenya shows that adoption of both integrated soil fertility man- agement practices is the lowest in the AOI compared to other regions of the country (Table 4, Map 4 and Figure 8). At national level, Kenya has one of the highest adoption rates in sub- Saharan Africa (SSA) but the high adoption rate is concentrated in the sub-humid and humid zones (Table 4). Even adoption of the use of manure – whose production is highest in the AOIs is low. UNIQUE | Kenya Land Restoration 20 Table 4: Adoption of ISFM, agroforestry, manure and inorganic practices (by county, percent- age of households) County ISFM Agroforestry Manure Inorganic fertilizer Samburu 0.0 0.0 5.7 0.0 Wajir 0.0 0.0 0.0 0.0 Mandera 1.0 1.0 6.6 1.0 Turkana 0.0 1.4 0.7 0.7 Marsabit 0.9 1.9 1.9 0.0 Kwale 1.5 2.5 37.7 2.0 Isiolo 1.7 3.4 4.2 4.2 Garissa 4.3 5.4 9.2 4.3 Kajiado 2.2 5.8 21.9 1.8 Tana river 2.9 12.4 2.9 1.9 Kilifi 2.5 12.6 15.5 1.6 Kisumu 5.8 16.3 18.4 5.2 Lamu 4.9 16.7 6.9 6.9 Mombasa 10.6 21.2 23.5 6.8 Narok 6.0 24.0 13.5 12.4 Siaya 23.6 27.1 39.5 41.1 Elgeyo-marakwet 8.3 29.8 10.7 52.9 Kitui 18.4 29.9 48.6 4.4 Nairobi 37.0 35.4 58.3 31.7 Nandi 8.7 37.3 10.4 77.2 Kisii 16.1 37.9 18.2 56.1 Laikipia 22.4 39.8 29.2 16.1 Machakos 45.8 40.2 71.9 37.0 Homabay 11.1 40.3 17.2 17.5 Taitataveta 11.6 42.0 19.6 16.1 Transnzoia 1.5 43.1 1.9 8.2 Migori 18.5 44.4 23.4 68.5 Kiambu 61.9 46.5 67.4 69.6 Bungoma 20.1 48.8 21.8 60.8 Kericho 15.4 50.2 17.9 48.8 Nyandarua 41.0 52.0 42.7 67.8 Nakuru 15.7 52.7 17.6 54.1 Nyamira 14.8 53.2 15.3 85.2 Tharaka 31.4 53.6 50.7 29.3 Uasingishu 7.9 58.2 9.7 32.7 Kakamega 34.0 58.3 38.3 54.1 Bomet 10.9 58.7 12.7 67.4 Nyeri 66.8 59.9 70.6 74.7 Kirinyaga 54.1 62.0 57.4 66.1 Embu 57.7 62.0 63.5 66.3 UNIQUE | Kenya Land Restoration 21 County ISFM Agroforestry Manure Inorganic fertilizer Meru 47.4 62.7 54.2 58.9 Makueni 49.1 63.5 62.5 21.5 Muranga 66.8 63.6 71.8 67.3 Vihiga 63.6 64.1 64.1 83.1 Busia 25.5 70.3 31.4 38.1 Baringo 0.0 72.5 0.0 1.3 Westpokot 0.0 93.9 0.0 0.0 National (Kenya) 25.3 41.8 33.1 39.1 SSAa 6.2 24 24.6 19.1 Sources: SSA adoption – Nkonya et al. (2016), Adoption rates in Kenya - Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 Map 4: Adoption rate of agroforestry in Kenya by county Source: calculated from Kenya Agricultural Sector Household Baseline Survey, 2013 UNIQUE | Kenya Land Restoration 22 Map 5: Cropland degradation as reflected by adoption of ISFM in AOI and other areas Source Kenya Agricultural Sector Household Baseline Survey, 2013 3.3 Cost of land degradation Using the MEA (2005) of land degradation as long-term loss of ecosystems, Mulinge et al. (2016) estimated the cost of land degradation in Kenya due to LUCC to be about US$1.3 billion per year (Table 5). The per capita cost of land degradation due to LUCC was highest in Coast and Northeastern provinces. The northeastern province includes Garissa and Wajir while Rift Valley Province – with the third highest per capita cost of land degradation – in- cludes Turkana. The cost of land degradation due to using land degrading management prac- tices on static cropland and grazing lands was found to be US$116.7 million and US$77.914 million in 2007 respectively. The total cost of land degradation – including LUCC and land de- grading management practices – was US$1.525 billion or 5.6% of Kenyan GDP in 2007. UNIQUE | Kenya Land Restoration 23 Table 5: Annual cost of land degradation due to land use/cover change, 2000-09 Percent of Annual cost of land Annual per capita cost of Kenya land degradation, 2007 land degradation, 2007 Province area US$ million US$ million Central 2.0 80.9 144 Coast 14.2 290.2 680 Eastern 25.0 214.2 296 Nairobi 0.1 2.3 8 North-Eastern (In- cludes Garissa & 22.7 187.8 640 Wajir) Nyanza 2.2 72.1 104 Rift Valley (includes 32.5 452.1 352 Turkana) Western 1.3 31.0 56 Total 100 1330.6 272 Cost of land degra- dation as percent 4.9 32.4 of GDP Source: Mulinge et al. 2016 4 RESTORATION OPTIONS A national-level study commissioned by the Ministry of Environment and Natural Resources (MENR) established the national restoration options for degraded lands. The National Assess- ment of Forest and Landscape Restoration Opportunities in Kenya (MENR 2016) discusses sev- eral restoration options based on biophysical and socio-economic criteria. Table 6 summarizes the restoration options applicable to the AOI and associated justification and main challenges of implementing them. They are then discussed in more detail in the sections below. Table 6: Restoration options, justification and main challenges for degraded biomes Restoration Biome Justification Main Challenges options Rotational grazing & farmer Indigenous Formal land tenure and fencing block managed natural knowledge and livestock movements along stock routes regeneration effective Rangelands (FMNR) Degradation, climate change, & increasing Low-cost practice livestock population overwhelm existing pasture resources UNIQUE | Kenya Land Restoration 24 Seeding leguminous Collection of seeds is labor intensive Vegetation plants significantly Limited distribution of formal and informal reseeding increases nutritive suppliers of seed and planting material (fig- value of rangelands ure 14). Timber and non-tim- Weak tenure security of community forests Reforestation and ber forest products Rampant deforestation due to high demand afforestation of highly beneficial to Forests for charcoal and fuelwood community communities forests Low survival rates due to moisture defi- Growing value of ciency timber and NTFP Planting trees along buffer zone. Weak tenure security of community Trees to be Water is a priority forests. There is no riparian planning planted to cover resource in drylands Riverbanks which will ensure ownership and payment 30m from main for both people and for ecosystem services for rewarding those river and 15m livestock who invest in planting and managing trees. from secondary river. ISFM is labor intensive; production of ISFM, FMNR and Low-cost and high manure or other biomass is a challenge. Cropland agroforestry returns However, this challenge could be ad- dressed by using FMNR and agroforestry. Source: The second column is extracted from MENR (2016); the rest of the columns are from the authors 4.1 Rangeland restoration Rotational grazing is the most commonly used restoration option by pastoralists in SSA. It is a low-cost practice and has been shown to significantly improve forage productivity (Conant et al. 2002). Rotational grazing leads to increased milk production and weight gain of livestock. An- other restoration option for rangelands in ASAL counties is vegetation reseeding using legumi- nous plants. (Mwendia et al. 2016). While rotational grazing is well-established and based on indigenous knowledge, vegetation reseeding is new and requires collection of seeds – an aspect which is labour-intensive. Rangeland degradation is occurring because rate of adoption of rota- tional grazing is limited (Kahiga 2015). Seed availability from formal and informal markets (Figure 14) is also limited – and this poses a challenge to widespread adoption of the practice. Seeds and planting materials for forages in the ASAL go through a complex process before they reach livestock keepers as illustrated in Figure 10. Market failure is also a major problem given that the demand for forage seed/planting material is low due to the low adoption rate of pasture improvement in the ASAL. Forage harvesting – such as cut-and-carry is not a common livestock feeding system among the pastoral communities. However, animal fattening practices are done using other methods - by grazing selected animals on fodder banks – which is common among pastoralists. Fodder banks are enclosures – which are not grazed during the rainy season to allow grass to grow for fatten- ing selected livestock like pregnant or lactating cows, or animals for sale. The fodder banks are also used in the dry season for all animals when there is shortage of forage in the surrounding rangelands (Angassa and Oba 2008). UNIQUE | Kenya Land Restoration 25 Figure 14: Formal and informal sources of seeds and planting material for forages in the ASALs of Kenya Source: Mwendia et al. 2016 Rotational grazing is a profitable practice. Table 7 shows the results of a financial analysis of rotational grazing. Pastoralists will reach the breakeven point after 4 years (Table 7 and Figure 15), since they have to invest in building barriers using local materials and use more labor to control animal movement. For every US$ they invest, they get an average of US$2.5 in return. The results imply there is strong financial incentive for adoption of rotational grazing compared to the continuous grazing, which is practiced by majority of the pastoralists (Kahiga 2015). Table 7: Financial Net Present Value of rotational grazing for a 20 year planning horizon r=10% r=20% FNPV (US$000) 12.68 3.19 IRR 19% 9% Breakeven point (year) 4 4 Average MRR 2.5 2.5 Notes: r = discount factor, MRR = marginal rate of return Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 UNIQUE | Kenya Land Restoration 26 Figure 15: Financial Net Present Value of rational grazing Notes: Off-take rate = 16% for farmers using rotational grazing & 10% for the BAU; Livestock feeding on rotation grazing gain weight and attract a 30% higher price than those grazing on continuous Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 Economic NPV for rotational grazing also shows break-even on the fourth year but with higher returns because ecological benefits of carbon sequestration are considered. This further illus- trates that there are strong economic and financial incentives for practicing rotational grazing compared to continuous grazing. Figure 16: Economic NPV of rotational grazing Notes: ENPV includes the carbon sequestration due to rotational grazing. One hectare stores of range- lands under rotational grazing stores 1.5tons C/ha/year (Tennigkeit, T. and Wilkes, A. 2008). UNIQUE | Kenya Land Restoration 27 4.2 Cropland restoration The major crops grown in the AOI are sorghum and millet – both of which traditionally receive very low rate of inorganic fertilizer. The cropland management practice which is likely to be adopted widely in the ASAL is agroforestry since it is based on indigenous knowledge and its non-timber forest products (NTFP) serve other useful purposes. As seen in the discussion above, agroforestry adoption rate in the AOI is low. As it will be seen in the discussion below, extension services play a key role in promoting adoption of SLM practices. ISFM is another key restoration option. Judicious application of inorganic fertilizer – micro-dosing - has been shown to signifi- cantly increase grain yield. The major problem is the low adoption of improved millet and sor- ghum varieties in the ASAL. Implementing ISFM using agroforestry as a source of organic input is the most amenable practice. The economic and financial analysis is based on three crops, which are major crops grown in each of the three counties. Figure 17 shows that banana is grown mainly in Garissa and accounts for 30% of cropland area. Other crops account together for about 70% of the cropland area of the county (Table A 1). Millet is the major crop in Turkana while sorghum is the leading crop in Wajir. Figure 17: Major crops grown in each of three AOI counties Sources: Garissa, Turkana and Wajir County statistical abstracts, 2014 ISFM has been shown to have many economic and environmental benefits. Nkonya and Koo (2017) show that compared to other technologies, ISFM is the most profitable practice since it has the lowest yield variability and is more sustainable. One of the challenges of ISFM is its high labor intensity if organic inputs are supplied from external sources – such as hauling ma- nure from kraals (bomas) to crop plots. Hence, both production of external inputs and high labor intensity are daunting challenges. The practical option for addressing such challenge is agroforestry, which, once trees are planted, labor to maintain the trees is minimal and no bio- mass transfer labor is required. Our economic and financial analysis combines ISFM and agro- forestry, where the latter constitutes the organic soil fertility management element. Using agroforestry and judicious amount of inorganic fertilizer, farmers begin receiving profits UNIQUE | Kenya Land Restoration 28 in the second year (Table 8) when the fast-growing Faidherbia albida leguminous plant is used (Garrity et al. 2010). Banana, grown only in Garissa, is the most profitable crop while the profits for millet and sorghum are low due to their low prices. They are staple food crops in all three counties and their production ensure food security. The results suggest high returns as the average marginal rate of return is 2. The results also suggest that there are financial and eco- nomic incentives to adopt ISFM – in which agroforestry is combined with inorganic fertilizer. The BAU option is no application of organic and inorganic fertilizer, against which NPV for the SLM practice is computed. Table 8: Economic and Financial NPV for restoration of degraded cropland Millet Sorghum Banana NPV, (US$000), 20-year total ENPV, r=10% 11.8 11.9 24.2 ENPV, r=20% 5.6 5.7 11.7 FNPV, r=10% 7.1 7.3 21.6 FNPV, r=20% 2.8 2.9 10.2 Break-even year 2 2 4 IRR 12.1 12.1 18.5 MRR 2.3 2.3 4.0 Notes: r = discount factor, MRR = marginal rate of return 4.3 Reforestation and afforestation Tree-planting is a long-term investment which requires secure tree tenure for land users. Data on forest tenure indicates that almost all forests in the AOIs are owned by communities. This underscores the key role which participatory forest management will need to play in implement- ing forest restoration interventions. Planting acacia trees to restore degraded forests is financially profitable. Farmers break even only in the fifth year – which poses adoption challenge for poor farmers who heavily discount future consumption. The results of the financial analysis show that there is strong incentive for planting trees provided the farmers can internalize the benefits. This is likely the largest challenge which could be addressed by ensuring that the farmers reap the long-term benefits of investing in planting trees. A successful example which could be emulated is the Nigerien Rural Code, which gave tree tenure to those who plant or protect trees. UNIQUE | Kenya Land Restoration 29 Figure 18: Financial and economic analysis of reforestation and riverbank restoration 5 SPATIAL ANALYSIS 5.1 Methodology MENR used option-specific criteria to identify opportunity areas for restoration. Additional cri- teria were added during the consultation meeting as part of this study. Table 9 summarizes the criteria and justification of restoration of forests, rangelands, croplands and riverbanks. Table 9: Criteria for identification of restoration area by biome Criteria Justification Source i. Environmental – precipitation, soils, topography, hydrology and Livestock sector in the ASAL floristic dynamics. home to about 30% of Kenya’s - Consultation ii. Fauna – wildlife and livestock human population; supports 50% with stake- Rangelands numbers, distribution, popula- of Kenya’s livestock population holders tion dynamics and habitat utili- zation. and supplies 90% of the total - MENR (2016) iii. Economical/political - land- meat consumed in the country. use/cover type, projected land demands and na- tional devel- i. Potential opment goals for natural (FAO 1975). regenera- - Bioenergy (woodfuel) ac- - Consultation tion of native trees – e.g. Acacia. counts over 95% of cooking with stake- ii. Protection of land with slope ex- energy Forests holders ceeding - Trees used for livestock - MENR ≥35%; riverbank, lake and dam browsing; building mate- buffer zones. (2016) rial, beekeeping, etc UNIQUE | Kenya Land Restoration 30 i. As above - Water sources a most limit- - Consultation ii. Environmental law requires tree ing natural resource in ASAL with stake- Riverbanks buffer zone of 30m for main - Potable water and livestock wa- holders river and 15m for secondary tering - MENR river - Coarse grain cereal (millet and (2016) i. Current cropland only sorghum – are staple food - Consultation ii. Exclude cropland areas with crops – which ensure food se- with stake- Croplands slope curity and livelihood di- versi- holders iii. more than 35% fication - MENR iv. Exclude protected areas - Potential for banana produc- (2016) tion and other horticultural crops exist in semi- arid areas in Garissa In this report, biome restoration potential means that there is the opportunity to significantly increase the productivity of the biome. Restoration potential does not necessarily mean a biome was degraded previously – but rather that productivity could be increased. Restoration could also mean expansion of a certain biome. This means restoration potential could exceed a degraded area of the same biome reported above. 5.2 Reforestation and afforestation The total area with high potential for restoration is 136% of the current forest cover. Table 10 reports the restoration potential for forest and riverbanks in the sub-counties of the AOI. Map 6 shows where the reforest and afforestation areas are located. Among the three AOI counties, Garissa has the largest forest area (of currently 429,000 ha), which is 5.4% of its total surface areas. Ijara subcounty accounts for 92% of total county forest area. Turkana – the largest county by area in Kenya – has about 307,000 ha forest cover, which is 4% of Kenya’s surface area. Wajir has the smallest area under forest cover, but the area with high potential for forest restoration at 150%. In all three counties, the area with high potential for restoration is greater than the current forest area. This suggests that there are other non-forest areas with high po- tential for afforestation and reforestation. Riverbank restoration is largely concentrated in Garissa (Table 10 and Map 6). UNIQUE | Kenya Land Restoration 31 Table 10: Restoration potential of forest and riverbanks Subcounty Forest Riverbank Forest Percent of current total Extent (000ha) biome area Garissa County 429.2 7.7 136 - Balambala 0.8 0.3 100 - Daadab 2.1 0.5 246 - Fafi 19.9 4.4 126 - Garissa Township 0.7 0.1 99 - Ijara 394.6 1.7 143 - Ladgera 11.2 0.7 100 Turkana County 306.9 3.8 132.7 - Loima 49.3 1 125 - Turkana Central 19.2 0.7 179 - Turkana East 38.9 0.6 139 - Turkana North 71.6 0.1 98 - Turkana South 23.9 0.7 163 - Turkana West 104 0.7 92 Wajir county 117.8 1.9 150 - Eldas 3.7 0.2 361 - Tarbaj 15.6 0 100 - Wajir East 6.5 0.4 100 - Wajir North 12.2 0.4 95 - Wajir South 64.3 0.6 114 - Wajir West 15.6 0.4 128 Source: Authors – based on data processed by KFS (2013) UNIQUE | Kenya Land Restoration 32 Map 6: Forest and riverbank restoration potential in the AOI Source: Authors – based on data processed by KFS (2013) UNIQUE | Kenya Land Restoration 33 5.3 Rangeland restoration An area equivalent to 99% and 65% of the rangelands in Wajir and Garissa, respectively, has high potential for restoration (Table 11). In Garissa, the central and north-western parts show particular potential (Map 7). The area with potential for rangeland restoration in Turkana is only 45% of current rangeland area. Map 7 shows this area concentrated in the northern and central part of the county. In Garissa and Turkana, areas which were under grazing lands are either not degraded or do not have potential for restoration using the rotational grazing or reseeding prac- tices. Table 11: Rangeland restoration potential at sub-county in the AOI Subcounty Extent (000ha) Percent of total biome area Garissa county 2617.6 65 - Balambala 247.7 5 - Daadab 440.3 9 6 - Fafi 991.9 6 - Garissa Township 39.2 5 6 - Ijara 296.7 0 4 - Ladgera 601.8 3 9 5 Turkana county 3645.3 45 - Loima 370.2 4 - Turkana Central 78.9 5 1 - Turkana East 123.7 6 1 - Turkana North 1786.2 3 9 - Turkana South 89.4 8 1 - Turkana West 1196.9 4 8 5 Wajir county 5406.5 99 - Eldas 389.5 9 - Tarbaj 917.4 9 - Wajir East 390.8 9 1 - Wajir North 803.9 0 9 - Wajir South 2035.7 0 6 9 - Wajir West 869.2 8 1 0 0 UNIQUE | Kenya Land Restoration 34 Map 7: Rangeland restoration potential 5.4 Cropland restoration Crop production in the AOI is limited. Table 12 shows that Garissa has the largest cropland area, which is 5% of the county’s surface area. However, banana occupies 65% of total cropland area and is detected as forest in the satellite imagery used. The extent of millet and sorghum area was too small to illustrate the area on a map. The area in Turkana under crop is only about 3% of total surface area (Map 8). Wajir has even a smaller cropland area – covering less than one percent of its surface area (which cannot be made visible on a map). As Table 4 shows, adoption rate of ISFM and agroforestry is in the AOI low – suggesting almost the entire cropland area is degraded and requires restoration. UNIQUE | Kenya Land Restoration 35 Table 12: Cropland restoration potential in the AOI Garissa Turkana Wajir Surface area (000 ha) 4359.4 6818.5 5681.9 Cropland area (000 ha) 219.7 186.8 12.3 Cropland area as percent of surface area 5.0 2.7 0.2 Adoption rate of agroforestry 0.0 0.0 4.3 Restoration potential (000 ha) 219.7 186.8 11.7 Map 8: Cropland restoration potential in Turkana County UNIQUE | Kenya Land Restoration 36 6 LESSONS LEARNED AND PAST EXPERIENCE This chapter examines policies and strategies related to land restoration implemented in the past. The cases offer useful lessons for future interventions. Kenya dairy sector Kenya has the highest per capita dairy production in SSA and its level is more than twice the SSA regional average (Ngigi et al. 2010; FAOSTAT 2008; Otte and Chilonda 2002). Early efforts of dairy development started from 1954 to 1962 – which was part of the import-substituting in- dustrialization launched by the colonial government – with largescale dairy producers being the major beneficiaries. After independence in 1963, the government of Kenya implemented agri- cultural marketing policies and facilitated access to secure land rights to smallholder farmers in the fertile highlands. However, the government imposed significant government control – aimed at helping small dairy farmers. This posture was relaxed to create conducive environment for private dairy sector development (Ngigi et al. 2010). Additionally, the government invested in provision of artificial insemination, dips and other veterinary services. For example, the govern- ment established Kenya National Artificial Insemination (KNAIS) to support dairy farmers – a strategy which significantly increased adoption rate of improved dairy cows. The government also invested in research and advisory services to provide affordable production technologies. Dairy extension services provided advisory services on intensive dairy feeding systems including production of grass-legume forage animal feed supplement and crop-livestock synergistic inter- action (Murethi et al. 1995). On marketing, Kenya Cooperative Creameries Ltd (KCC) – which was formed in 1931 – serves as the powerful cooperative for dairy farmers marketing services. KCC has built an elaborate milk value chain. To reduce spoilage of the highly perishable milk, KCC built chilling centers and pro- cessing centers in major milk-producing districts. The processing plants produce and package milk in different forms – fresh, condensed, ultra-heat-treat long shelf life, butter, ghee, cheese and fermented fresh milk. One of the iconic government regulation strategies to help integrate smallholder dairy farmers in the value chain, was to accept milk from all producers who meet minimum quality standards (Ngigi et al. 2010). However, marketing reforms in 1992 abolished KCC’s monopoly and paved the way for private companies and cooperatives to participate in the milk value chain (Ibid). The competition further improved the milk value chain performance as 45 private dairies and 150 cooperative milk processing plants were formed. It is estimated that there are 1.8 million smallholder dairy farmers – who produce 56% of the 5.2 million liters an- nually since 2012 (FtF 2018). The private sector milk businesses and cooperatives have expanded to support the small to large dairy farmers. There are more than 200 milk cooling and bulking plants – which serve the key role of reducing spoilage (FtF 2018). There are 92 dairy processors – who are vertically linked with dairy producers – buying milk with legally binding terms and conditions (Ibid). The two largest processors are Brookside and New KCC – which account for approximately of 75% of the raw milk market (Ibid). UNIQUE | Kenya Land Restoration 37 Important lessons can be drawn from the Kenya dairy success story. The land tenure security, which was initiated soon after independence in 1963 and the elaborate milk value chain devel- opment – centered on the competitive sector – have been the major drivers of a successful dairy sector in Kenya. Soil fertility management practices in western Kenya Excluding South Africa, Kenya has one of the highest adoption rate of soil fertility management practices in SSA (Figure 19). The adoption rate of agroforestry has increased dramatically in the past 20 years and by 2013, it has surpassed the adoption rate of inorganic fertilizer (Figure 20). Figure 19: Comparison of adoption rate of soil fertility management practices in Kenya Source: Extracted from Table 2 Figure 20: Trend of agroforestry and fertilizer adoption rate in Kenya, 1997-2013 Source: Computed from Place et al. 2013. UNIQUE | Kenya Land Restoration 38 The high adoption rate of soil fertility management practices has largely been driven by im- proved market access, pluralistic agricultural extension services – involving more than 12, 000 active NGO advisory services (Anderson 2017); and national and international research organ- izations (Haggblade et al. 2010). Active research and extension efforts by ICRAF on agroforestry, CIMMYT, CIAT and ICRISAT – in collaboration with national agricultural institutions – significantly contributed to development and dissemination of soil fertility management practices in Kenya. Additionally, the soil fertility management practices developed, significantly increased yield and were acceptable among the smallholder communities (Haggblade et al. 2010). As shown before, improved soil fertility management practices lead to much higher yield and profit than tradi- tional land degrading management practices. And as illustrated by the famous study “more peo- ple, less erosion” in Machakos (Tiffen et al. 1994), access to markets has significantly contributed to higher uptake of improved soil fertility management practices in Kenya (Boyd and Slaymaker 2000). Farmer-managed natural regeneration (FMNR) FMNR approaches have been shown to be cost-effective and their adoption rate is high – if ap- propriate advisory services are provided to encourage communities to practice them. Studies in Kenya have shown that FMNR has been very successful in the ASAL region. FMNR is appropriate for the resource-poor pastoralists since it is cheap, rapid, farmer led and implemented, and uses local skills and resources (World Vision 2018). Studies done in Niger under comparable pastoral farming systems showed that FMNR increased pastoral household income by US$6/ha (Garrity et al. 2010). Another appealing feature of FMNR is that it is an indigenous knowledge and farmer to farmer advisory service that has been one of the leading channels of FMNR diffusion (Taylor 2011; MURIUKI 2017). As demonstrated in Niger (Moussa et al. 2016), tree tenure is also crucial for widespread adop- tion of tree planting and protection. It is important to use indigenous trees to minimize the low survival rates of exotic trees. It is equally important to avoid introduction of invasive species, which could alter the ecological systems of the ASAL. For example, Prosopis juliflora tree (locally known as ‘Etirae’ in Turkana) – native to South America – was introduced in the ASAL in Kenya in the 1970-80s to help with rehabilitation efforts. Prosopis has a very aggressive growth habit - making it very difficult to eradicate after establishment. Currently, Prosopis covers over 1.5 mil- lion ha in 15 counties in Kenya – including all AOI – and continues to expand exponentially (Choge et al. 2010). It has reduced pasture production on grazing lands and rangelands and has cause loss of biodiversity among others. Group ranch development and destocking campaigns As an effort to commercialize pastoral production and consequently high reduced stocking rates among pastoral communities, the government of Kenya initiated group ranching to provide ten- ure security and to incentivize Maasai pastoralists to invest in rangeland improvement (Mwangi 2001; Rutten 1992). The Land Groups Act was passed in 1968 to provide legal framework for ranch operation. Through the Kenya Livestock Development Program (KLDP), dips, stock han- dling facilities, fire breaks and water resources were developed in areas deemed central to the group ranches. Pastoralists were also given loans and extension services (Ibid). The government UNIQUE | Kenya Land Restoration 39 sought to enhance land tenure security by converting the traditional communal grazing land ownership to smaller ranching groups, each of which were given a land title. Stocking rates were also restricted by allocating grazing quotas to ensure carrying capacity of rangelands is not ex- ceeded (Ibid). A study done by White and Meadows (1981) found that Group ranch development had minimal impact on livestock commercialization and destocking. Stocking rate increased – leading to more severe degradation (Mwangi 2001). One of the reasons for failure of group ranching was the limited understanding of the deep-seated tradition of keeping large herd of cattle for a host of non-economic objectives. Among the non-economic objectives of keeping large herds are: as a status symbol of wealth, clout in community, paying dowry, and other traditions. The economic reasons are also diverse. Livestock serve as insurance against shocks – under which livestock is liquidated to pay for emergence needs. Livestock serve as a “live” bank. For example, Kamuanga et al. (2008) estimates that livestock accounts for more than 50% of capital held by rural house- holds in SSA. Maasai pastoralists regard selling livestock as selling wealth to buy poverty (Rutten 1992). The lesson from this failed effort is the importance of seriously considering indigenous knowledge when planning interventions. Fertilizer subsidies to promote adoption of SLM in the ASAL Crop subsidies in Kenya are mainly targeted to maize farmers. Kilimo Plus subsidies started in 2007 and targeted poor maize farmers by providing them with 100kg of fertilizer and 10 kg of improved maize seed (Mason et al. 2015). By 2012, Kilimo Plus had reached 63,737 farmers or about 2% of the 3.52 million rural households in Kenya but given that the target was maize farm- ers, only few farmers in the ASAL were beneficiaries. However, the maize price support, which increased maize price to an artificial level and encouraged farmers in the ASAL to grow maize, could have increased production risks and compromised security (Kamau et al. 2012; World Bank 2015). A study by Makau et al. (2016) also showed that fertilizer subsidy in Kenya crowds out commercial development of fertilizer marketing. Fertilizer subsidies reduced farmers’ propen- sity to buy fertilizer from open market by 30%. One kilogram of subsidized fertilizer displaces 0.2kg of commercial fertilizer. Other methods of incentivizing adoption of land restoration tech- niques are required. 7 POLICY RECOMMENDATIONS This chapter summarizes the discussion in the previous chapters and concludes by proposing policy recommendations. The spatial analysis shows severe land degradation on rangelands, forests, riverbanks and cropland. The economic analysis clearly shows high returns to adoption of land management practices which restore degraded rangelands, forests, river banks and croplands. However, the low adoption of land restoration practices illustrates that the financial incentives are only part of other requirements for adoption of land restoration practices. Farm- ers mostly lack knowledge of the proposed measures and are very reluctant to make new in- vestments in the current high risk environment. The policy recommendations below discuss the incentives required to increase adoption of land restoration practices and gaps in the current UNIQUE | Kenya Land Restoration 40 policies and institutions. The table below structures government interventions and associated gaps that this study identifies as well as lists policy recommendations to address those gaps. Table 13: Gaps in current government interventions and policy recommendations Major Government Policy/Strategy Policy Recommendations Policy/Strategy Gaps • Traditional ranching not receiving signifi- cant public investment – e.g. promotion of Subsidies target- ex- port Create/increase incentives for restoration of de- ing poor farmers • Crops grown in graded lands ASAL do not receive as significant an in- vestment as maize does • Administrative units below county do not have mandate to en- act and enforce natu- Create institutional environment and rural ser- Decentralization ral re- source manage- vices conducive for investments in land improve- ment regulations. ment • Customary institu- tions are not fully utilized. • Investment in live- stock services still lim- • Vision 2030, de- ited velop world-class in- • Road density in frastructure ASAL is lowest • Ministry of Northern • Extension services Enhance rural services Kenya and Develop- weakest in ASAL ment of other Arid • Water development Areas – Enhance for live- stock lim- rural services ited • Weak support of farmer groups UNIQUE | Kenya Land Restoration 41 Major Government Policy/Strategy Policy Recommendations Policy/Strategy Gaps • National Drought • No masterplan for Management Au- Integrated Water- thority (NDMA) shed Development • Kenya National Ag- and Management De-risking livelihoods (major risks include ricultural Insurance (IWDM) for livestock drought & cattle rustling) Policy Taskforce • Disarmament • Reduce cattle rus- strongly correlated to tling by disarma- higher frequency of ment cattle rustling Create incentives for investment in land restoration Incentives for restoration of degraded lands need to increase. Current subsidy programs have not been successful in increasing the adoption of rangeland, forest and cropland restoration practices. It is imperative to re-examine the subsidy approach and to even reorient it towards payment for ecosystem services (PES). The PES could be an effective incentive to adopt tree planting – especially on public land like riverbanks, communal grazing area and on private land. Create an institutional environment that is conducive for investments in river basins Due to the dynamic nature of river water and given that its course passes across more than one county, implementation of riverbank restoration will require a riparian approach. Plant- ing trees and other strategies for protecting riverbanks has direct benefits to all who use river water resources. Additionally, beneficiaries and stakeholders along the river basins have dif- ferent types of water uses. This suggests the need for all stakeholders to be involved in the planning process and if possible pay for the ecosystem services for those who invest in riverbank protection. This calls for appropriate national and county level legislation and sup- port to ensure such plans and subsequent investments are acceptable and strongly supported by legislative instruments to safeguard them against potential conflicts, free-riding and other vices. Integrated water resource management (IWRM) in which catchment or riparian ap- proach is used (GWP 2000; Mtisi and Nicol 2013) is recommended. IWRM is based on coordi- nated approach to water development and management (including land and related re- sources) with the objective of equitably and simultaneously maximizing economic and social welfare without compromising ecosystems (GWP 2000). Enhance rural services Priority should be given to enhance the effectiveness and reach of the extension service. This will require increasing the number, diversity and capacity of extension agents to provide advi- sory services on CSA, ISFM, pasture management and other SLM practices. A specific challenge in the ASAL/AOI is also the relatively low population density and the mobility of the pastoral- ists. Hence, there needs to be sufficient resource allocation for ensuring mobility of extension agents. Further, extension agents need to be adequately incentivized to work in the remote areas of the AOI/ASAL. UNIQUE | Kenya Land Restoration 42 Content and quality of advisory services offered to farmers needs to improve. Surveys illustrate the weak capacity of extension agents to provide advisory services on CSA, ISFM, rotational graz- ing, water harvesting and other practices. For example, only 32% of extension agents promoted organic soil fertility management practices. For pasture management, the results show a lack of emphasis on livestock management practices. Given the water deficit challenge in the ASAL, it is important to promote agricultural water management (AWM) practices. AWM will signifi- cantly reduce crop and livestock production risks in the ASAL and enhance food and nutrition security. For extension agents who are already in services, short-term training is required to in- crease their capacity to provide up-to-date knowledge for restoration of rangelands, CSA, RWHM and other SLM practices. Agricultural college curriculum also needs to include these prac- tices in their training to equip future advisory service providers. Griftu Pastoralist Training College – which has recently been converted into a full-fledged livestock training institute and research centre – is an excellent example of the recent effort to support pastoral production systems in the ASAL. The World Bank provided US$2 million for training extension agents for pastoralists. Indigenous knowledge should be exploited. There is need for conducting studies to document the indigenous knowledge of rangeland management and use them to provide advisory services. Given climate change and other emerging external factors which challenge use of some indige- nous knowledge practices, there is need to discuss how some of the indigenous practices can be adapted and used complementary to innovative technologies and practices. One example is in- surance which is discussed in the next section. In addition to increasing the number of public extension agents, efforts need to be undertaken to increase the diversity of service providers. Other SSA countries have shown promising results in increasing service provision by private agents and NGOs. This could be done by increasing the capacity building of agricultural input traders to provide technical advisory services. Survey re- sults show that private agricultural input traders reach more farmers than the formal providers. While this diversification of service providers is encouraging, it has to be ensured that private agents also receive adequate training. In addition, strong regulatory mechanisms are required to ensure that private companies do not give biased advisory services with the aim of promoting their products which could be inferior or not required by farmers. A close follow-up done by extension agents and other technical government officials will help to regulate private agricul- tural input traders. Another approach to deal with the sparse population and mobility of pastoralists is the in- creased use of modern ICT to spread relevant information. An example is a SNV program for improving pastoralist production and marketing through farmer groups. The program included a mobile application which disseminates price information and other useful information to pastoralists in Isiolo County in northeastern Kenya. As a result, income of participants increased by about 35% (SNV 2012). De-risk livelihoods There is need to reexamine the current approach of disarming pastoralists as it does not seem to work. The same approach used to resolve Maasai-Sukuma conflicts in Tanzania could be used to end the cattle rustling in the ASAL. However, the transboundary nature of cattle rus- tling and conflicts creates a much more complex environment. The Intergovernmental Author- UNIQUE | Kenya Land Restoration 43 ity on Development (IGAD) countries program needs to increase efforts to address this chal- lenge. The World Bank has invested about US$70 million in its Regional Pastoral Livelihoods Resilience Project (RPLRP) – which covers all AOI counties in Kenya. One of the components of the RPLRP is resolving cattle rustling and other conflicts. This implies the need to use more protracted efforts to end these conflicts. Market-driven livestock insurance should be promoted. There is a need for facilitating devel- opment of the Index-Based Insurance (IBLI) to ensure its high acceptability and fully commer- cialize it. In partnership with the World Bank, ILRI is working with the Kenya National Agricultural Insurance Policy Taskforce to fully commercialize IBLI on a largescale. The well-established pas- toral communities and their customary institutions could be exploited to increase acceptability of IBLI. On the supply side, there is need to use aggregators and guarantors could further en- hance the IBLI market. Such an approach has been used successful by the Grameen Bank (Yunus 1999). UNIQUE | Kenya Land Restoration 44 8 REFERENCE LIST Agrawal, A., & Ostrom, E. (1999). Collective action, property rights, and devolution of forest and protected area management. In Collective Action, Property Rights, and Devolution of Nat- ural Resource Management. Exchange of Knowledge and Implications for Policy:21-25. Anderson M. 2017. NGOs: Blessing or curse? African Report. Online at http://www.theafricare- port.com/East-Horn-Africa/ngos-blessing-or-curse.html. Angassa, A. and Oba, G., 2008. Herder perceptions on impacts of range enclosures, crop farm- ing, fire ban and bush encroachment on the rangelands of Borana, Southern Ethiopia. Human ecology, 36(2):201-215. Baker, T.J. and Miller, S.N., 2013. Using the Soil and Water Assessment Tool (SWAT) to assess land use impact on water resources in an East African watershed. Journal of hydrology, 486:100-111. Barrett, C. B. (2008). Smallholder market participation: Concepts and evidence from eastern and southern Africa. Food policy, 33(4): 299-317. Barrett, C. B. (2008). Smallholder market participation: Concepts and evidence from eastern and southern Africa. Food Policy, 33:299–317. Barrett, C. B., Carter, M. R., & Timmer, C. P. (2010). A century-long perspective on agricultural development. American Journal of Agricultural Economics, 92(2):447–468. Barrett, C.B., P.P. Marenya, J.G. McPeak, B. Minten, F.M. Murithi, W. Oluoch-Kosura, F. Place, J.C. Randrianarisoa, J. Rasambainarivo and J. Wangila, 2006, Welfare Dynamics in Rural Kenya and Madagascar, Journal of Development Studies, 42(2): 248-77 Bond, M. E. (1983). Agricultural responses to prices in Sub-Saharan African countries. Staff Pa- pers, 30(4), 703-726. Boyd, C. and Slaymaker, T., 2000. Re-examining the'More People Less Erosion'Hypothesis: Spe- cial Case of Wider Trend? ODI Natural Resource Perspectives, 63:1-5. Brock-Utne, B. (2004). Peace Research with a Diversity Perspective: A Look to Africa. Interna- tional Journal of Peace Studies:109-123.Vanlauwe, B., Descheemaeker, K., Giller, K. E., Huising, J., Merckx, R., Nziguheba, G., & Zingore, S. (2015). Integrated soil fertility management in sub- Saharan Africa: unravelling local adaptation. Soil, 1(1):491-508. UNIQUE | Kenya Land Restoration 45 Chantarat, S., Mude, A. G., Barrett, C. B., & Carter, M. R. (2013). Designing index-based live- stock insurance for managing asset risk in northern Kenya. Journal of Risk and Insurance, 80(1):205- 237. Choge, S. K. 2010. Management of Prosopis by community groups in Baringo District. Technical Project Report for KAPP. KEFRI, Kenya. 15pp (Mimeo, KEFRI) Colchester, M., & MacKay, F. (2006). Forest peoples, customary use and state forests: the case for reform. In Paper to 11th Biennial Congress of the International Association for the Study of Common Property. Bali, Indonesia (pp. 19-22). Conant, R. T., and Paustian, K. 2002. “Potential Soil Carbon Sequestration in Overgrazed Grass- land Ecosystems.” Global Biogeochemical Cycles 16(4): 90-1-90-9. Cotula, L., ed. (2007). Changes in “Customary” Land Tenure Systems in Africa (Ed). London: In- ternational Institute for Environment and Development (IIED). CRA (Commission on Revenue Authority). 2011. Kenya County Fact Sheet. Online at http://siteresources.worldbank.org/INTAFRICA/Resources/257994- 1335471959878/Kenya_County_Fact_Sheets_Dec2011.pdf Daalberg. 2018. Scaling up clean cooking in urban Kenya with LPG & Bio-ethanol. A market and policy analysis. Online at https://www.dalberg.com/system/files/2018-06/Dalberg_Long- form%20report_FINAL_PDF_0.pdf Di Falco S. 2014. Adaptation to climate change in Sub-Saharan agriculture: assessing the evi- dence and rethinking the drivers. European Review of Agricultural Economics 41 (3): 405–430. Ellis, J., D.L. Coppock, J.T. McCabe, K. Galvin and J. Wienpahl. 1984. Aspects of energy con- sump- tion in a pastoral ecosystem: Wood use by the south Turkana. In: Barnes, C, J. Ensminger and P. O'Keefe (eds.) Wood, energy and households: Perspectives on rural Kenya. Energy and Develop- ment in Africa series no. 6. The Beijer Institute and the Scandinavian Insti- tute of African Studies. Pp l64-187. FAO. 2013. Study on Opportunities and Threats of Irrigation Development in Kenya’s Drylands Interim Findings and Recommendations. FAO. 1975. Evaluation and mapping of tropical African rangelands. Online at http://www.fao.org/wairdocs/ilri/x5543b/x5543b00.htm#Contents UNIQUE | Kenya Land Restoration 46 FtF (Feed the Future). 2018. Enhancing Investment Attractiveness in Kenya’s Dairy Sector. FtF Policy Brief. Global Water Partnership (2000) Integrated Water Resources Management - Technical Advi- sory Committee Background Papers Series No. 4. Global Water Partnership; Stockholm, Swe- den GoK (Government of Kenya). (2010). Strategic Plan: 2008-2012. Ministry of Livestock Develop- ment. GoK (Government of Kenya). (2013). National Environment Policy, 2013. Haggblade S., G. Tembo, D. Kabore, C. Reij, O.C. Ajayi, S. Franzel, P. Mafongoya, and F. Place. 2010. Sustainable Soil Fertility Management Systems In: Haggblade S. and P. Hazell (eds). Suc- cesses in African Agriculture. Lessons for the Future Johns Hopkins:262-320. Hazell, P. (2007). All-Africa review of experiences with commercial agriculture. Case study on livestock. Background paper for the Competitive Commercial Agriculture in Sub–Saharan Africa (CCAA) Study. http://siteresources.worldbank.org/INTAFRICA/Resources/257994- 1215457178567/Ch11_Livestock.pdf. Accessed July 02, 2018. Henderson, B., Gerber, P., Hilinksi, T., Falcucci, A., Ojima, D. S., & Salvatore, M. (2015). Green- house gas mitigation potential of the world’s grazing lands: modeling soil carbon and nitrogen fluxes of mitigation practices. Agriculture, Ecosystems & Environment, 207:91–100. ILRI. 2015. Corporate Report 2014–2015. Online at https://cgspace.cgiar.org/bitstream/han- dle/10568/68631/ILRI_2014-15_CorporateReport.pdf?sequence=1&isAllowed=y Johannes, E. M., Zulu, L. C., & Kalipeni, E. (2015). Oil discovery in Turkana County, Kenya: a source of conflict or development? African Geographical Review, 34(2):142-164. Kahiga P. 2015. Rotational grazing (Kenya). World Overview of Conservation Approaches and Technologies(WOCAT) report. Online at https://qcat.wocat.net/en/wocat/technolo- gies/view/technologies_1741/. Kamau, M., Mathenge, M., and Kirimi, L., (2012). How can Kenya better manage maize prices? Effects of import tariffs, regional trade and producer price support. Tegemeo Institute of Agri- cultural Policy and Development, Policy Brief, No.7. Kamuanga, M., Somda, J., Sanon, Y., & Kagoné, H. (2008). The future of livestock in the Sahel UNIQUE | Kenya Land Restoration 47 and West Africa: Potentials and challenges for strengthening the regional market. OECD. http://www.oecd.org/swac/publications/38402714.pdf. Accessed August 8, 2018. Kariuki, F. (2015). Conflict resolution by elders in Africa: Successes, challenges and opportuni- ties. Alternative Dispute Resolution, 3(2):30-53. KFS (Kenya Forest Services). 2013. Land use/land cover 2010. KFS (Kenya Forest Services). 2013. Analysis of drivers and underlying causes of forest cover change in the various forest types of Kenya. Online at http://www.kenyaforestservice.org/doc- uments/redd/Analysis%20%20of%20Drivers%20of%20Deforestation%20&forest%20Degrada- tion%20in%20Kenya.pdf. Khisa, C. S. (2016). Trends in Livestock Rustling and The Dynamics of Socio-Economic Develop- ment in Samburu And Marsabit Counties. In: Kenya. Strategic Journal of Business & Change Man- agement, 3(4):1437-1451. Krishnan, P. and Patnam, M., 2013. Neighbors and extension agents in Ethiopia: Who matters more for technology adoption? American Journal of Agricultural Economics, 96(1):308-327. Kwapong, N. A., & Korugyendo, P. L. (2010). Revival of agricultural cooperatives in Uganda. IFPRI USSP Policy Note, 11. Luedeling, E., Oord, A. L., Kiteme, B., Ogalleh, S., Malesu, M., Shepherd, K. D., & De Leeuw, J. (2015). Fresh groundwater for Wajir—ex-ante assessment of uncertain benefits for multiple stakeholders in a water supply project in Northern Kenya. Frontiers in Environmental Science, 3, 16. Lybbert, T.J, C.B. Barrett, S. Desta and D. Layne Coppock, 2004, Stochastic Wealth Dynamics and Risk Management among a Poor Population. Economic Journal, 114(498): 750-77. Makau, J.M., Irungu, P., Nyikal, R.A. and Kirimi, L.W., 2016. An assessment of the effect of a na- tional fertiliser subsidy programme on farmer participation in private fertiliser markets in the North Rift region of Kenya. African Journal of Agricultural and Resource Economics 11(4):292- 304. Mason N. A. Wineman, L. Kirimi, and D. Mather. 2017. The Effects of Kenya’s ‘Smarter’ Input Subsidy Program on Crop Production, Incomes and Poverty. Feed the Future Innovation Lab for Food Security Policy. Policy Research Brief 26. UNIQUE | Kenya Land Restoration 48 Mason, N. M., Wineman, A., Kirimi, L., & Mather, D. L. (2015). The Effects of Kenya's' smarter' Input Subsidy Program on Crop Production, Incomes, and Poverty. Tegemeo Institute of Agri- cul- tural Policy and Development. McPeak, J.G. and C.B. Barrett, 2001, Differential Risk Exposure and Stochastic Poverty Traps among East African Pastoralists. American Journal of Agricultural Economics, 83: 674-79 MEA (Millennium Ecosystem Assessment). (2005). Dryland systems. In R. Hassan, R. Scholes, & N. Ash (Eds.), Ecosystem and well-being: Current state and trends (pp. 623–662). Washington, DC: Island Press. Meier, P., Bond, D., & Bond, J. (2007). Environmental influences on pastoral conflict in the Horn of Africa. Political Geography, 26(6), 716-735. MENR (Ministry of Environment and Natural Resources). 2016. Technical Report on The Na- tional Assessment of Forest and Landscape Restoration Opportunities in Kenya 2016 MNREM (Ministry of Natural Resources, Energy and Mining – Malawi) (2017). Forest Land- scape Restoration Opportunities Assessment for Malawi. NFLRA (Malawi), IUCN, WRI. xv + 126pp. MOA (Ministry of Agriculture). 2013. The National Accelerated Agricultural Inputs Access Pro- gram (NAAIAP) Progress Report. Moussa B., E. Nkonya, S. Meyer, E. Kato, T. Johnson and J. Hawkins. 2016. Economics of land degradation and improvement in Niger. In: E. Nkonya, A. Mirzabaev and J. von Braun (eds). Eco- nomics of Land Degradation and Improvement – A Global Assessment for Sustainable De- velop- ment. Springer: 499-540. Mtitsi S. and A. Nicol. 2013. Good Practices in Water Development for Drylands Mulinge W., P. Gicheru, F. Murithi, P. Maingi, E. Kihiu, O.K. Kirui and A. Mirzabaev. 20016. Eco- nomics of Land Degradation and Improvement in Kenya. In: E. Nkonya, A. Mirzabaev and J. von Braun (eds). 2016. Economics of Land Degradation and Improvement – A Global Assessment for Sustainable Development. Springer: 471-98. Murethi, J. G., R. S. Tayler, and W. Thorpe. 1995. Productivity of alley farming with leucaena (Leucaena leucocephala Lam. de Wit) and Napier grass (Pennisetum purpureum K. Schum) in coastal lowland Kenya. Agroforestry Systems 3: 59-78. UNIQUE | Kenya Land Restoration 49 Muriuki J. 2017. Farmer Managed Natural Regeneration. Online at http://landscapepor- tal.org/projects/5. Mwangi, E., 2001. Fragmenting the Commons: The Transformation of Property Rights in Ken- ya's Masai Land. Unpublished manuscript, Department of Political Science, Indiana University, Bloomington. Mwaura, F., Wamalwa, J. and Mwake, T., 2017. The Effect of Small Scale Topographic Gradient on the Distribution and Community Utilization of Indigenous Woody Species in a Lowland Dry- land Environment, Lokapel Area, Turkana, Kenya. Natural Resources, 8(09):592. Mwendia S., Notenbaert A. and Paul B. 2016. Forage seed systems in Kenya. Working Paper. Centro Internacional de Agricultura Tropical (CIAT). Nairobi, Kenya.12 Ngigi M., M. A. Ahmed, S. Ehui and Y. Assefa. 2010. Smallholder Dairying in Eastern Africa. In: Haggblade S. and P. Hazell (eds). Successes in African Agriculture. Lessons for the Future Johns Hopkins: 209-269. Ngigi, S., 2002. Review of irrigation development in Kenya. In: Blank, H.G., C.M. Mutero and H. Murray-Rust, eds. 2002. The changing face of irrigation in Kenya: Opportunities for anticipating change in eastern and southern Africa. Colombo, Sri Lanka: International Water Management Institute. Njenga, M., Karanja, N., Munste, C., Iiyama, M., Neufeldt, H., Kithinji, J., Jamnadass, R., 2013. Charcoal production and strategies to enhance its sustainability in Kenya. Development in Practice, 23:3, 359-371. DOI:10.1080/09614524.2013.780529 Nkonya E. and J. Koo. 2017. The Unholy Cross: Profitability and Adoption of Climate-Smart Agri- culture Practices in Africa South of the Sahara. In De Pinto, A., and J. M. Ulimwengu (Eds). 2017. A Thriving Agricultural Sector in a Changing Climate: Meeting Malabo Declaration Goals through Climate-Smart Agriculture. ReSAKSS Annual Trends and Outlook Report 2016. Wash- ington, DC: International Food Policy Research Institute: 103-113. Nkonya E., T. Johnson, H.Y. Kwon, and E. Kato. 2016. Economics of land degradation in sub- Sa- haran Africa In: E. Nkonya, A. Mirzabaev and J. von Braun (eds). Economics of Land Deg- rada- tion and Improvement – A Global Assessment for Sustainable Development. Springer: 215-260. Nkonya, E., J. Pender, E. Kato. 2008. “Who knows who cares? Determinants of enactment, awareness and compliance with community natural resource management regulations in Uganda.” Environment and Development Economics 13(1):79-109. UNIQUE | Kenya Land Restoration 50 Ochieng, J., Knerr, B., Owuor, G. and Ouma, E., 2018. Strengthening collective action to im- prove marketing performance: evidence from farmer groups in Central Africa. The Journal of Agricultural Education and Extension:1-21. Odhiambo, M.O. The Unrelenting Persistence of Certain Narratives: An Analysis of Changing Pol- icy Narratives about the ASALs in Kenya; A Position Paper Prepared for the New Perspec- tives on Climate Resilient Drylands Development Project; IIED: London, UK, 2013. Onono, J. O., Wieland, B., & Rushton, J. (2013). Constraints to cattle production in a semiarid pastoral system in Kenya. Tropical animal health and production, 45(6): 1415-1422. Opiyo, F., Wasonga, O., Nyangito, M., Schilling, J., & Munang, R. (2015). Drought adaptation and coping strategies among the Turkana pastoralists of northern Kenya. International Journal of Disaster Risk Science, 6(3), 295-309. Ostrom, E. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. New York: Cambridge University Press. Ostrom, E. (2005). Self-governance and forest resources. Terracotta reader: A market ap- proach to the environment, 12. Ostrom, E. (2008). The challenge of common-pool resources. Environment: Science and Policy for Sustainable Development, 50(4), 8-21. Otte J. and P. Chilonda. 2002. Cattle and small ruminant production systems. A systematic re- view. FAO, Rome. Place, F., Ajayi, O.C., Torquebiau, E., Detlefsen, G., Gauthier, M. and Buttoud, G., 2012. Im- proved policies for facilitating the adoption of agroforestry. In Agroforestry for Biodiversity and Ecosystem Services-Science and Practice. InTech. Phillips, J.F., 2012. Fire: its influence on biotic communities and physical factors in South and East Africa. Fire Ecology, 8(2):2-16. Rischke, R., Kimenju, S.C., Klasen, S. and Qaim, M., 2015. Supermarkets and food consumption patterns: the case of small towns in Kenya. Food Policy, 52:9-21. Rutten, M.E. 1992. Selling wealth to buy poverty: the process of the individualization of land- ownership among the Maasai pastoralists of Kajiado district, Kenya, 1890-1990. UNIQUE | Kenya Land Restoration 51 Sankaran, M., Ratnam, J. and Hanan, N., 2008. Woody cover in African savannas: the role of resources, fire and herbivory. Global Ecology and Biogeography, 17(2):236-245. SNV 2012. Improved Livelihoods for Pastoralists. SNV Practice Brief No. 2. Online at http://www.snv.org/public/cms/sites/default/files/explore/download/improved_liveli- hoods_for_pastoralists.pdf. Svendsen M., M. Ewing and S. Msangi. 2009. Measuring Irrigation Performance in Africa. IFPRI Discussion Paper 00894 Swanson E. and K. Davis. 2014.Status of Agricultural Extension and Rural Advisory Services Worldwide. Summary Report. Global Forum of Rural Advisory Services (GFRAS) report. Taylor, G. F. 2011. From Farmer Managed Irrigation Systems (FMIS) in the Himalayas to Farmer Managed Natural Regeneration (FMNR) in the Sahel: links, lessons & implications for agricul- tural research, climate-smart rural development and development cooperation. Tennigkeit, T., & Wilkes, A. (2008). An assessment of the potential for carbon finance in range- lands. World Agroforestry Centre. Tiffen, M., Mortimore, M. and Gichuki, F., 1994. More people, less erosion: environmental re- covery in Kenya. John Wiley & Sons Ltd. Vanlauwe, B., Bationo, A., Chianu, J., Giller, K.E., Merckx, R., Mokwunye, U., Ohiokpehai, O., Pyp- ers, P., Tabo, R., Shepherd, K.D. and Smaling, E.M.A., 2010. Integrated soil fertility man- agement: operational definition and consequences for implementation and dissemination. Outlook on agriculture, 39(1):17-24. WFP (World Food Programme) and Government of Kenya (GoK). (2013). Asset Creation Pro- gramme Baselines Re-construction and Outcome Monitoring Report. Unpublished. Nairobi, Kenya. Wanjiru, H. and G. Omedo. 2016. How Kenya can transform the charcoal sector and create new opportunities for low-carbon rural development. Stockholm Environment Institute (SEI) and United Nations Development Program (UNDP) Policy Brief: Nairobi, Kenya. World Bank. (2017). Kenya Economic Update, Edition 16 World Bank. (2018). Kenya Economic Update, Edition 17 UNIQUE | Kenya Land Restoration 52 World Bank. 2012. Economic analysis of investment operations: analytical tools and practical applications. World Bank. 2016. Bringing Prosperity to Underserved Counties of Kenya. The North-North- eastern Development Initiatives (NEDI). World Vision. 2018. FMNR for East Africa: Kenya. Online at http://fmnrhub.com.au/pro- jects/fmnr-east-africa-kenya/#.W3rEwXm0XIU. Yunus, M. (1999). The Grameen Bank. Scientific American, 281(5), 114-119. UNIQUE | Kenya Land Restoration 53 9 ANNEX Annex 1: Analytical methods for analyzing drivers of adoption of land management practices for restoration of degraded lands Drivers of adoption of ISFM and other soil fertility management practices We use a probit model to estimate adoption of ISFM: Y*= Φ−1(Y) = Xβ1 + ε, Where Y* is a latent variable representing adoption of ISFM, given by 0 ∗ ≤ 0 = { , 1 ∗ ≥ 1 Φ is a normally distributed cumulative static with Z-distribution, i.e. Φ()(0,1), X is a vector of drivers of adoption of ISFM practices; and βi is a vector of associated coefficients i, i=1, 2. Xβ ~N(0,1); ε is an error term with normal distribution, i.e., ε~N(0,1). Given that some right-hand side variables are potentially endogenous to adoption decision, we check robustness of our results by estimating both structural and reduced model equations. Choice of X vector variables is driven by literature2 and data availability. The empirical model estimated is: ISFMi=0 + 1 + 2 + 3 + 4 + Where: ISFM=1 if household i has adopted ISFM. HC = human capital – includes household endowment of skills, knowledge and experience that drive productivity (e.g. education, age (an indicator of experience), sex of household head or plot owner); PC expresses physical capital including ownership of livestock, productive assets, type of building material, and so forth; SC encompasses social capital, mainly including member- ship to farmer associations or other productive groups; RS stands for rural services including proximity to all-weather road and markets. Annex 2: Cost benefit analysis methodological approach We conducted the cost-benefit analysis (CBA) following the World Bank (2012) approach. The economic CBA analyzes the costs and benefits of an investment after netting out policy dis- tortions. The most common distortions include tariffs, export taxes and subsidies, excise and sales taxes, production subsidies, and quantitative restrictions. Economic analysis also takes into ac- count social benefits and costs of projects. Shadow prices of goods and services are used for goods and services which are not marketed. The economic prices used are the export parity prices – which is the free-on-board (FOB) price of a good or service at a point of export 2 Please see Nkonya et al. (2008) and Di Falco (2014) for a review. UNIQUE | Kenya Land Restoration 54 when the associated taxes, subsidies, and domestic transport costs are netted out (World Bank 2012). However, if the country is a net importer, the appropriate economic price import-par- ity price – which is the CIF price of imports and the associated domestic transport cost (Ibid). The financial analysis is simpler as it uses market prices of goods and services and associated financial flows entity. It does not attach shadow prices to in-kind goods and services such as family labor, manure produced by livestock owned by farmers, etc. Our analysis focuses on restoration practices in rangelands, forests and croplands. The products and associated eco- nomic and financial prices are reported in Table A 1. As part of efforts to determine economic prices, we analyzed the import and exports of livestock, banana, millet and sorghum. We also analyzed the subsidies and taxes. Figure A 1 and Figure A 2 show that Kenya does not export or import a significant volume of livestock or the three crops. It is for this reason that a similar study done by the World Bank (2017) in the ASAL region of Kenya assumed all four commodities are autarkic - i.e., traded locally, and only financial prices are used for the economic analysis. As shown in Table A 1 however, we net out the taxes to get the economic prices. There are no subsidies for all four commodities. As discussed earlier, fertilizer subsidies targeted maize, thus we do not include maize in our analysis since the area under maize is still very limited in all three AOI counties. The distortion considered in this case are the county level taxes re- ported in Table A 1. Table A 1: Financial and Economic prices of goods and services used in the CBA Biome Products Market distortions Unit price Prices (US$) Economic Financial Rangeland Live animal • Cattle US$2/head sold US$/head 202 200 • Shoats (Goat & sheep) US$0.75 US$/head 75.75 75 • Milk 10% of value sold US$/liter 1.1 1 Major crop in each county (with % of total cropland in brackets) - Garissa Banana (30%) 5% of value sold US$/ton 80.75 85 - Turkana Millet (67.5%) 5% of value sold US$/ton 157.7 166 - Wajir Sorghum (57.8%) 5% of value sold US$/ton 157.7 166 Forest Value of forest per ha US$/ha 2352.06 US$/ton of CO2- equiv 7.00 Daily rural wage rate (US$) 3.5 Rural wage rates – county officials and key informants Sources: Commodity prices & taxes– county government data & interviews with county officials. Figure A 1: Live animal export trend UNIQUE | Kenya Land Restoration 55 Source: Calculated from FAOSTAT raw data, http://www.fao.org/faostat/en/#data Figure A 2: Net export crops (1970-2016) grown in AOI counties Annex 3: Opportunities and challenges of provision of extension ser- vices in Kenya Table A 2: Providers of different extension services in AOI and other areas UNIQUE | Kenya Land Restoration 56 Sub-humid AOI Semi-arid & humid Kenya Advisory service provider Percent of service recipients Any agricultural extension service • Agro-vet dealer 0.0 5.2 9.4 8.1 • Research Institute 0.0 6.0 3.6 4.1 • Government extension 91.5 68.5 71.8 71.3 • Commodity cooperative 0.0 5.4 2.2 3.0 • SACCOS 0.0 0.6 0.7 0.7 • Private company 0.0 5.4 6.8 6.3 • NGO 8.5 6.0 3.7 4.4 • Farmer-to-farmer 0.0 1.3 0.6 0.8 • Others 0.0 1.6 1.1 1.3 Climate early warning provider • Agro-vet dealer 0.0 1.2 1.9 1.6 • Research Institute 13.0 3.1 2.6 3.0 • Government extension 13.0 12.5 19.0 16.9 • Commodity cooperative 0.0 2.0 2.9 2.6 • SACCOS 4.3 0.2 0.3 0.0 • Private company 0.0 5.5 3.3 4.0 • NGO 13.0 0.4 2.4 1.9 • Faith-based organization 0.0 1.8 0.8 1.1 • Media 62.5 58.0 58.8 62.5 • Others 0.0 3.3 2.0 0.0 Output markets • Agro-vet dealer 3.1 5.3 4.7 4.8 • Research Institute 1.5 1.6 1.9 1.8 • Government extension 26.9 33.2 35.6 34.7 • Commodity cooperative 0.0 7.8 6.9 7.0 • SACCOS 0.0 1.9 1.8 1.8 • Private company 43.1 26.0 17.6 20.6 • NGO 4.6 0.1 0.9 0.8 • Farmer-to-farmer 20.0 20.7 26.7 24.9 • Others 0.8 3.4 3.8 2.8 Veterinary services • Agro-vet dealer 34.3 24.9 28.1 27.6 • Research Institute 1.4 1.8 2.2 2.1 • Government extension 54.5 29.2 28.6 29.5 • Private company 0.7 41.3 37.6 37.4 • NGO 1.4 0.4 1.4 1.1 • Farmer-to-farmer 7.7 1.1 1.0 1.2 • Others 0.0 1.4 1.1 1.1 Source: Calculated from the Kenya Agricultural Sector Household Baseline Survey, 2013 Table A 3: Number of farmers served by one public extension agent in SSA UNIQUE | Kenya Land Restoration 57 Country Number of farmers (000) served by one public extension agent Zimbabwe 1.50 Ethiopia 1.64 Sierra Leone 5.16 Kenya 5.97 Malawi 6.16 Rwanda 6.83 South Africa 8.71 Ghana 9.77 Zambia 11.46 Liberia 16.09 Mozambique 23.11 Sudan 37.81 Cameroon 53.48 DRC 82.20 Nigeria 205.93 Sub-regional averagea • Central Africa 67.84 • East Africa 10.78 • Southern Africa 10.19 • West Africa 59.24 a Based on countries with available data Source: Computed from Swanson and Davis 2014 Annex 4: Indigenous knowledge One common practice of indigenous pastoral rangeland management is enclosures or forage banks, which are widely used in SSA and in the Kenyan ASAL. Enclosures are not grazed during the rainy season to allow grass to grow for use in the dry season when there is a shortage of forage in the surrounding rangelands (Angassa and Oba, 2010; Verdoodt et al. 2009). Enclosures reduce pressure on grazing lands, restore and preserve degraded forage, conserve biodiversity, improve soil ecology, improve restoration of soil, and prevents soil erosion and environmental degradation in general (Abate et al. 2010; Kamwenda, 2002). Research has shown that the res- toration of degraded rangelands through the use of enclosures has positive effects on biodiver- sity (Verdoodt et al. 2009; Oba et al. 2001; Abebe et al. 2006). Moreover, enclosures have the potential to contribute to carbon sequestration. For example, in the ngitili (enclosures) of north- western Tanzania, approximately 23.2 million tons of carbon has been sequestered between 1986 and 2002 with a value of approximately US$213 million (Barrow and Shah, 2011). The no- madic livelihood practiced by pastoral communities in the ASAL is also meant to allow grasslands to recover and to utilize the different spatial and temporal pasture and water availability (Reid et al. 2016). Mapinduzi et al (2003) reports the Maasai pastoralists in East Africa have rich indig- enous knowledge on biodiversity, forage suitability and carrying capacity. For example, Ellis et al (1984) found that the Turkana pastoral communities sustainably harvested wood biomass by selectively cutting trees that they deem causing minimal harm to sustainability of woodlots. An- other study showed that Turkana pastoralists use some plant species to assess grazing suitability UNIQUE | Kenya Land Restoration 58 and carrying capacity during dry and wet seasons (Oba 2012). Additionally, they assess livestock production performances using milk yield, body hair condition, weight gain and mating fre- quency, all of which have scientific basis (Ibid). Table A 4: Names of month in Turkwana language (in Turkana County) and their meaning Turk- Origin Turk- wana wana word name of from which it Month month is derived Meaning Verb meaning formation of clouds, which is an early January Lomaruk Akimaruk warning sign of an impending rainfall. then comes rain. This is the month of rain. All the February Lochoto Akimaruk, places become muddy The process of pasture germination. During this March Titima Akititimare month there is plenty of grass for livestock April El-el Akielarr To scatter. Botanically it means to blossom To make. This is the month of ritual-festivities, i.e Akidodore Akisichumanakin, Akiuta/Akuuta etc. Farmers on their part May Losuban Akisub Conduct 'Harvest festivals' around the same month. To divide or separate. This is the month that divides the wet June Lotiak Akitiak Season and the dry season Arid, dry land, desert (Adesate). This is the month of livestock Movement in search for pasture and water. People July Lolong'u Along'u and livestock experience hot temperatures To cook. This is the lean month, in which people re- sort to Gathering of wild fruits and cooking wild berries and August Lopo Akipore drawing blood from animals (edung or edapal) This is the month when the trees shed their leaves. It is the month of extreme hardship where people use hooked sticks (Eseger to shake acacia trees to get dry Septem- leaves (ng'atur) and dry seeds (ng'itit) for both people ber Lorara Araraun. and their animals. During this month, the sky is covered by scattered October Lomuk Akimuk. clouds and short rains begin to fall. Novem- ber Lokwang Ekwang, Bright – the month of sunshine and wind. Decem- To fall. The month marks the fall of dry season and ber Lodunge Adudung'iar rise of wet season. UNIQUE | Kenya Land Restoration 59 Annex 5: Comparison of Wajir county and national level budget allo- cation Figure A 3: KES6.76 billion Budget Allocation for Wajir County, 2014/15 Figure A 4: KES 1,498 Billion National Budget for 2016/17 UNIQUE | Kenya Land Restoration 60