Transformation of Land Tenure in Semi-Arid Areas and Implications for Climate Resilient Economic Development Elizabeth Carabine, Catherine Simonet, Claire Bedelian, Stephen Moiko, Mohammed Said & Simon Ndiritu World Bank Conference on Land and Poverty Washington DC 21st March 2017

Pathways to Resilience in Semi-Arid Economies To identify climate change impacts and adaptation options in selected sectors with potential for economic transformation and diversification in the semi-arid lands of PRISE countries. What are the pathways for climate-resilient economic development in semi-arid lands through vertical and horizontal transformation in key value chains? What are the adaptation options for business and private sector investment opportunities in responding to climate change in semi-arid lands? LIZ

This project includes a value chain analysis in key chains, replicated on 6 chains in 4 countries, including livestock (beef and cow’s milk) and cotton. Sectors chosen because of contribution to share in national GDP, national added value, employment importance and potential for economic growth in the future. 3 www.odi.org.uk/prise

LIZ The VCA has been adapted to include the key characteristics of semi-arid lands, which is why we’re calling it VC-ARID. In line with CARIAA’s hotspots approach, VC-ARID takes a territorial or geographical approach that is new, placing semi-arid lands at the centre of the analysis. VC-ARID is novel in it’s approach to analysing climate risk. At each step of each value chain, from production to processing to markets, climate risk is assessed using both qualitative and quantitative methods. This will allow us to start understanding response to risk and possible adaptation options across these chains. Even before we consider climate change and increasing variability, semi-arid lands are already highly variable. This has huge implications for supply and therefore the entire chain. This is explicitly considered in VC-ARID. There is a lot of economic activity taking place in semi-arid lands, but much of it is informal as these areas have been relatively marginalised both politically and economically. There are also significant gender dimensions to consider. Both these factors are included in the VC-ARID methodology. 4 www.odi.org.uk/prise

LIZ VC-ARID follows a common 3-step methodology. Step 1 is complete for all 6 value chains and reports will be published shortly. We are currently coming to the end of Step 2 having conducted quantitative surveys at producer and trader level for each value chain (average n=400, all complete) and qualitative semi-structured interviews and focus group discussions with processors and market actors (these are ongoing). Each research tool explores household characteristics, current livelihood activities, perceptions of climate change and extremes trends and responses to these over the past 10-15 years, perceptions of and responses to a named shock event (drought, floods), perceptions of and responses to future climate trends and perceptions of and responses to other shocks (including conflict, price shocks, idiosyncratic shocks). 5 www.odi.org.uk/prise

Kenya

Livestock routes in Magadi and Namanga, Kajiado County Kajiado in southern Kenya on border of TZ. Weekly livestock markets in towns and centre. Daily markets in terminal markets and accompanying slaughterhouses Cattle trek or truck to local and terminal markets. Livestock move along chain from pastoral sites and enter Nairobi Kajiado livestock are important suppliers of livestock to Nairobi 2 study sites. Contrasting conditions. For contrast of land tenure. Also, Magadi has wildlife and tourism and conservancies. Namanga site is closer to TZ-Kenya highway, Magadi (Shompole and Olkiramatian group ranches) - Communal land tenure - <400mm rainfall - Tourism and wildlife 2) Namanga (Meto group ranch) - Private land tenure - 600mm rainfall - Closer to TZ-Kenya highway

Methodology Producer / trader household survey Focus groups Interviews 2 Group Ranches, Magadi, Kajiado– 170 households 1 Group Ranch, Namanga, Kajiado – 181 households 8 Group Ranches, Laikipia – 410 households Focus groups Kajiado – producers, traders Laikipia – producers, traders Terminal markets – livestock and meat traders/brokers Interviews Women Producers Livestock/meat traders Butcheries (high, mid, low end) Meat markets (low, mid end) Consumers Tourism operators How land tenure affects value chain

Preliminary Results – Magadi, Kajiado Land ownership Ownership (parcels) No. producers % 15 8.3 1 158 87.3 2 4 2.2 3 0.6 1.6 TOTAL 181 100 Parcel size (n = 181)   Mean Min Max SD Parcel size (acres) 115 2 1020 178

Magadi, Kajiado – Responses to climate change

Laikipia – Responses to changes in rainfall patterns (%) Respondent type/Group ranch Increased mobility (distance & frequency) Storage or purchase of fodder Change in water mngt Partial shift to other livelihoods Banking livestock assets Change in herd mngt Reduce herd size Others All (N=664) 27.0 9.5 9.9 17.5 11.0 8.9 15.5 0.8 Ilngwesi (N=76) 0.0 36.8 9.2 22.4 15.8 Ilpolei (N=82) 12.2 19.5 24.4 2.4 Koija (N=108) 42.6 5.6 16.7 22.2 6.5 0.9 Kuri Kuri (N=77) 3.9 22.1 27.3 13.0 14.3 Makurian (N=110) 41.8 2.7 29.1 9.1 8.2 3.6 Murupusi (N=108) 23.1 12.0 1.9 38.9 Munichoi (N=99) 50.5 16.2 6.1 Tiamamut (N=4) 50.0 25.0 82% households reported pastoralism as their main activity. While main reason for keeping livestock was household consumption, the majority of the household heads reported more income (Kshs 22700 (USD 227)) from livestock sales in the last three months compared to other activities at Kshs 21000 (USD 210). Change in herd management includes Long-term response options in grazing management include Grassland monitoring, revision of range management standards, changes in grazing and land use strategies, and increases in management flexibility, finding alternative grazing. most important factor is controlling stocking rates; follow recommended stocking rates for the region, site, and range condition; adjusting to more conservative stocking rates, especially in drier cli mates, will increase resilience; avoid over-grazing which increases vulnerability to climate change

Statistical Summary N= 410 Variable name Variable definition Mean Std. Dev. Avg_rainfall Average annual rainfall (in mm) 649.584 80.240 Avg_temp Average annual Temperature (in °C) 28.009 0.633 Raindelayno Number of times Delay in rainy season affected livestock since 2000 4.388 5.163 Droughtno Number of times drought affected livestock since 2000 2.214 0.995 Earlywarning Access to early warning information after devolution (yes=1) 0.334 Grazingpranch Access to grazing provided by private ranches (yes=1) 0.689 Wealthscore Wealth index 0.000 1.627 Lvstksize Livestock size in a standardized unit (TLU) 19.463 21.048 Age Age of the household head (years) 44.186 12.974 Male Male dummy Male=1 female=0 0.923 Higheduc Highest level of education in the household (years of schooling) 9.566 3.822 Hhsize Household size 6.423 2.575 dist2manmkt Distance to the main market (km) 7.956 5.213 Credit Access to credit after devolution (yes=1) 0.189 Pastoralist Pastoralism the main activity of this household (yes=1) 0.816 Following the climate change adaptation literature, the variables hypothesized to influence adoption of adaptation strategies include: temperature, rainfall, human capital (proxied by education and age), gender, credit facilities, income, household size, ownership of properties such as land and household assets, infrastructure and livestock size (e.g. Berhanu and Beyene 2015; Di Falco et al 2011; Getachew et al., 2014; Hassan and Nhemachena, 2008; Mengistu and Haji 2015; Ndamani  and Watanabe 2016). As you can see we produced for each HH an information of Average rainfall and coefficient of variation Average maximum and minimum temperature and coefficient of variation. Using climate interpolation measure. N= 410

mobility storefodder watermgt Shiftlvhds banklvstk herdmgt 0.528*** (1) (2) (3) (4) (5) (6) VARIABLES mobility storefodder watermgt Shiftlvhds banklvstk herdmgt Avg_rainfall -0.006*** 0.006*** 0.005*** 0.003** -0.001 0.004*** (0.001) Avg_temp 0.089 -0.530*** -0.064 -0.358*** -0.403*** 0.026 (0.126) (0.160) (0.129) (0.133) (0.139) (0.132) Raindelayno 0.029* -0.060** -0.030 -0.028 -0.062*** 0.034** (0.017) (0.024) (0.020) (0.019) (0.016) Droughtno 0.585*** -0.290*** 0.064 -0.047 -0.484*** -0.081 (0.097) (0.102) (0.085) (0.077) (0.121) (0.074) Earlywarning 0.604*** 0.305 -0.193 0.204 0.735*** 0.226 (0.187) (0.206) (0.208) (0.166) (0.183) (0.168) Grazingpranch 0.528*** 0.272 0.801*** -0.036 -0.136 0.579*** (0.177) (0.220) (0.205) (0.175) (0.202) (0.172) Wealthscore -0.057 -0.027 0.069 0.086 0.061 (0.055) (0.068) (0.054) (0.053) (0.061) (0.052) Lvstksize 0.002 -0.002 0.001 0.004 -0.006 (0.004) (0.005) Age 0.007 0.008 (0.007) (0.008) Male -0.195 -0.204 0.415 -0.211 -0.374 (0.232) (0.280) (0.318) (0.239) (0.317) (0.258) Higheduc 0.043** -0.020 0.056*** 0.029 0.016 (0.023) (0.021) (0.022) Hhsize 0.030 -0.052 0.018 -0.048 0.039 -0.042 (0.038) (0.045) (0.041) (0.040) (0.036) dist2manmkt 0.057*** -0.041** -0.082*** -0.018 0.025 -0.066*** (0.015) Credit 0.364* -0.510* 0.441** 0.038 0.184 0.257 (0.198) (0.260) (0.203) (0.210) (0.243) (0.199) Pastoralist 0.474** 0.179 -0.055 -0.296 -0.122 0.277 (0.216) (0.252) (0.213) (0.195) (0.192) Constant -2.049 11.003** -3.340 8.996** 11.036*** -3.442 (3.722) (4.702) (3.897) (3.905) (4.119) (3.881) Observations 431 Model chi-square 592.1 mobility storefodder watermgt Shiftlvhds banklvstk herdmgt Grazingpranch 0.528*** 0.272 0.801*** -0.036 -0.136 0.579*** (0.177) (0.220) (0.205) (0.175) (0.202) (0.172)

Diversification into Tourism Sector Opportunities for tourism – pastoral areas with high wildlife populations Conservancies - dry season grazing areas Conflict or coexistence between livestock and tourism? Drought refuges OR Competition for grazing Opportunities for profitable private sector enterprises operating along beef value chain. eg: Mara Beef Ol Pejeta There are linkages between tourism/conservancies and the beef value chain Tourism susceptible and suffering from political, economic and health shocks in Kenya Opportunities to increase local pro-poor impact – eg locally sourced beef or vegetables in lodges? Opps for tourism to set up private sector enterprises operating as profitable commercial livestock value chains – linking pastoralists to markets, removing inefficiences, (vertical integration?)

Results for Laikipia 7 out of 8 Group Ranches have a conservancy area. The main benefits of the conservancies are reported as: dry season grazing (60%), community development projects (39%), improved security (28%) and school bursaries (27%). Not direct transfer of income from the tourism activities to the households. Although the conservancies have very useful benefits to the communities they come with several challenges. Table 28 reports the problems associated with conservancies. The main problem of conservancies is the increase predation by wildlife (55.2%). Other challenges includes; increased wildlife competition for grazing (32%), grazing fines (32%), reduced access to grazing land (29.5%) and increased wildlife disease transmission (17.8%). The problems associated with the group ranches vary considerably across all the group ranches. For example, grazing fines (96.3%) are very high in Munichoi group ranch while reduced access to grazing land and increased predation by wildlife (both at 90.2%) in Ilgwesi group ranch are very high. The increased predation by wildlife in Ilgwesi is mainly damage for their crop farming.

Inputs – breeds, water points, grass banks Production – sustainably managed conservancy grazing areas Trading – improved infrastructure, direct guaranteed markets for pastoralists Local processing – rangeland slaughterhouse, premium conservation local beef, value addition Domestic – lodges sell beef directly purchased from pastoralists, value added products, high value quality products transfer greater value back along the value chain, greater opportunity for margin capture to be relayed back to pastoralists

PRISE Overseas Development Institute 203 Blackfriars Road London SE1 8NJ United Kingdom Tel. +44 (0)20 7922 0438 info@odi.org.uk www.odi.org.uk This work was carried out under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA), with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Ottawa, Canada. The views expressed in this work are those of the creators and do not necessarily represent those of the UK Government’s Department for International Development, the International Development Research Centre, Canada, or its Board of Governors.