44. Uasin Gishu

Total Page:16

File Type:pdf, Size:1020Kb

44. Uasin Gishu Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized PROJECTS INCOUNTIES WORLD BANK-FUNDED KENYA WORLD BANK-FUNDED PROJECTS IN COUNTIES KENYA March, 2016 DATA SOURCE: 1. Kenya County Fact Sheets: Populaton & Populaton density - Kenya Natonal Bureau of Statstcs 2009 Census. Poverty gap Index Source: Kenya Natonal Bureau of statstcs (2012) County Poverty Trends based on WMS II (1994), WMS III. (1997bs (2005/06) and KIHBS. 2. Exchange rate US$-KSH 103 Central Bank of Kenya average July-September 2015. Disclaimer: The informaton contained in this booklet, is likely to be altered, based on changes that occur during project preparaton and implementaton. The booklet contains informaton on all actve projects in the country as of June 2015. It also captures actve regional projects that impact on various countes in Kenya. The booklet takes into account the difculty of allocatng defned amounts to countes in projects that have a natonal approach and impact. It has applied pro rata amounts as defned in each secton. However, it has not captured informaton under the following projects: EAPP-P112688, KEMP-P120014 & P145104, KEEPP103037, ESRP P083131 & P129910, EEHP -P126579, EATTFT-P079734 & NCTIPP082615, WKCDD & FMP P074106, AAIOSK-P132161, EARTTD-P148853, and KGPED-P14679. Design: Robert Waiharo Photo Credits: Isabela Gómez & Gitonga M’mbijiwe TABLE OF CONTENTS Preface ........................................................................................................................................................................................................... i Map of 47 Countes ........................................................................................................................................................................................ ii Funding per County - Jan 2016 ....................................................................................................................................................................... iii COUNTIES 1. Baringo .................................................................................................................................................................................................... 2 2. Bomet ...................................................................................................................................................................................................... 4 3. Bungoma .................................................................................................................................................................................................. 6 4. Busia ........................................................................................................................................................................................................ 8 5. Elgeyo Marakwet ..................................................................................................................................................................................... 11 6. Embu ........................................................................................................................................................................................................ 14 7. Garissa ..................................................................................................................................................................................................... 16 8. Homa Bay ................................................................................................................................................................................................. 19 9. Isiolo ........................................................................................................................................................................................................ 21 10. Kajiado ..................................................................................................................................................................................................... 23 11. Kakamega ................................................................................................................................................................................................ 26 12. Kericho ..................................................................................................................................................................................................... 29 13. Kiambu ..................................................................................................................................................................................................... 30 14. Kilif .......................................................................................................................................................................................................... 34 15. Kirinyaga .................................................................................................................................................................................................. 37 16. Kisii .......................................................................................................................................................................................................... 39 17. Kisumu ..................................................................................................................................................................................................... 41 18. Kitui ......................................................................................................................................................................................................... 44 19. Kwale ....................................................................................................................................................................................................... 47 20. Laikipia .................................................................................................................................................................................................... 51 21. Lamu ........................................................................................................................................................................................................ 54 22. Machakos ................................................................................................................................................................................................ 56 23. Makueni .................................................................................................................................................................................................. 59 24. Mandera .................................................................................................................................................................................................. 62 25. Marsabit .................................................................................................................................................................................................. 64 26. Meru ....................................................................................................................................................................................................... 66 27. Migori ...................................................................................................................................................................................................... 68 28. Mombasa ................................................................................................................................................................................................. 70 29. Muranga .................................................................................................................................................................................................. 73 30. Nairobi ..................................................................................................................................................................................................... 76 31. Nakuru ..................................................................................................................................................................................................... 81 32. Nandi ....................................................................................................................................................................................................... 84 33. Narok ....................................................................................................................................................................................................... 86 34. Nyamira ................................................................................................................................................................................................... 89 35. Nyandarua ............................................................................................................................................................................................... 91 36. Nyeri .......................................................................................................................................................................................................
Recommended publications
  • Nakuru County
    Kenya County Climate Risk Profile Nakuru County Map Book Contents Agro-Ecological Zones Baseline Map ………………….…………………………………………………………... 1 Baseline Map ………………………………………………………………………………………………….……………... 2 Elevation Map ...…………………….……………………………………………………………………………………..... 3 Farming Systems Map ……………….…….…………………………………………………………………………...... 4 Land Cover Map …………...……………………………………………………………………………………………...... 5 Livestock Production Systems Map ..…………………………………………………………………………......... 6 Mean Precipitation Map ……………….……………………………………………………………………………....... 7 Mean Temperature Map ……………………………………………………………………………………………....... 8 Population Density Map .………………………………………………………………………….…………………...... 9 Satellite Map .……………………………………………………………..………………………………………………... 10 Soil Classes Map ..……………………………………………………………………………………………..………...... 11 Travel Time Map ……………….…………………………………………………………………………………..…...... 12 AGRO-ECOLOGICAL ZONES a i o p ! ! i ! g ! ! ! k ! n i ! i ! ! ! ! r ! ! ! a ! ! a L ! ! !! ! ! ! ! B ! ! Solai ! ! ! ! Subukia ! ! ! ! ! ! Athinai ! ! ! ! Moto ! ! Bahati ! ! Rongai Kabarak N ! ! ! Menengai ! ! ! ! y Molo ! ! Dondori ! Turi ! a ! Nakuru ! ! ! Keusa Lanet Kio ! Elburgon ! ! ! Sasamua ! ! Chesingele Njoro n ! ! ! d N a k u r u ! ! ! ! Keringet ! a Kiriri ! Kariandusi ! Mukuki ! ! Elmentaita r Kabsege ! Gilgil ! ! Likia ! u East Mau ! ! ! a Olenguruone Mau ! ! F Cheptwech ! Narok ! ! ! Ambusket ! ! ! Morendat ! ! ! ! Naivasha ! ! Marangishu ! ! ! ! Ngunyumu Kangoni ! ! ! ! ! ! ! Longonot ! ! ! u ! ! ! b Akira Mai ! ! ! Legend ! Mahiu N a r o k ! m ! Town ! Agro-ecological
    [Show full text]
  • Internal Ex-Post Evaluation for Grant Aid Project the Project for The
    Internal Ex-Post Evaluation for Grant Aid Project conducted by Kenya Office: March 2018 Country Name The Project for the Reinforcement of Vaccine Storage in Kenya The Republic of Kenya I. Project Outline In Kenya, provision of medical service focusing more on prevention was a key issue to improve the situation under which many people have suffered from preventable diseases and more expenses for their treatments were required. In particular, according to the WHO mortality country fact sheet 2006, the main causes of death for children under 5 years were pneumonia (20%), diarrhea (16%) and measles (3%) which were diseases Background preventable by immunization. Therefore, the government of Kenya had been implementing vaccination under “the Kenya Expanded Programme on Immunization” (KEPI) since 1980. However, there was insufficient storage capacity for vaccines and transportation of vaccines from the National Vaccine Depot to the Regional Vaccine Depots was not smoothly carried out, which hampered efficient immunization services. To enable more efficient stock management and delivery of vaccines by construction of the Central and Objectives of the Regional Vaccine Depots and procurement of equipment for adequate storage of vaccines, thereby contributing to Project improvement for the full immunization coverage in Kenya 1. Project Site: Nairobi (later moved to Kitengela), Kakamega (Western Province), Meru (Eastern Province), Garissa (North Eastern Province), Nyeri (Central Province), Nakuru, Eldoret (Rift Valley Province), Kisumu (Nyanza Province), Mombasa (Coast Province)1. 2. Japanese side Consultant services: Design of facilities, equipment, and supervision of construction Construction: Nairobi Central Vaccine Depot, Kakamega Regional Vaccine Depot, Meru Regional Contents of the Project Vaccine Depot, and Garissa Regional Vaccine Depot Equipment: Cold rooms, freezer rooms, freezer, pallet lifts, tool boxes etc.
    [Show full text]
  • Cholera Outbreak Has Affected 7 Counties: Nairobi, Migori, Homa Bay, Bomet, Mombasa, Nakuru and Muranga Counties
    MINISTRY OF HEALTH CHOLERA SITUATION REPORT IN KENYA AS AT 5TH MAY 2015 Weekly Situation Summary Since 26th December 2014, Cholera outbreak has affected 7 counties: Nairobi, Migori, Homa Bay, Bomet, Mombasa, Nakuru and Muranga Counties. Migori, Homabay and Bomet Cholera outbreaks are now considered successfully controlled The outbreak first started in Nairobi County on 26th December 2014. Later the outbreak was reported in Migori County on 30th January 2015, Homa Bay County on 2nd February 2015, Bomet County on 12th March 2015, Mombasa County on 6th April 2015, Nakuru 8th April and Muranga county on 18th April 2015. As of 5th May 2015, a total of 2156 cases and 42 deaths (CFR=1.9%) had been reported nationally distributed as follows: Nairobi 145 cases, 5 deaths (CFR 3.4%); Migori 915 cases, 12 deaths (CFR 1.3%); Homa Bay 377 cases, 5 deaths (CFR 1.4%) , Bomet 272 cases, 2 deaths (CFR 1.5%) ,Mombasa 69 cases, 5 deaths (CFR 7.2%), Muranga 278 cases, 1 death (0.4%), and Nakuru 100 cases, 12 deaths (CFR 12%) Cumulatively, 274 new cases were reported in the last one week (164 in Muranga, 73 in Nakuru, 17 in Mombasa and 20 in Nairobi). This is an increase from the previous week where 35 new cases were reported. 6 new deaths were reported in the last one week (5 in Nakuru and 1 in Nairobi). There are 34 current admissions in Mombasa, Nakuru and Nairobi Counties. 1 | Page New cases reported in Nairobi were detected in new epicentres- Kibera, Mukuru Kayiaba and Mukuru Kwa Njenga slums.
    [Show full text]
  • Livestock Herd Structures and Dynamics in Garissa County, Kenya Patrick Mwambi Mwanyumba1*, Raphael Wahome Wahome2, Laban Macopiyo3 and Paul Kanyari4
    Mwanyumba et al. Pastoralism: Research, Policy and Practice (2015) 5:26 DOI 10.1186/s13570-015-0045-6 SHORT REPORT Open Access Livestock herd structures and dynamics in Garissa County, Kenya Patrick Mwambi Mwanyumba1*, Raphael Wahome Wahome2, Laban MacOpiyo3 and Paul Kanyari4 Abstract In Kenya’s Northeastern Province, pastoralism is the main livestock production system and means of livelihood. However, pastoralists are facing increasing risks such as drought, insecurity, animal diseases, increasing human populations and land fragmentation. This study sought to evaluate household livestock herd structures and dynamics in view of such risks and subsistence and market demands. The study was conducted in Garissa County of Kenya, using a cross-sectional household survey. The data was analysed for descriptive statistics of household livestock status, dynamics and demographic parameters. The results showed that females of reproductive age formed over 50 % of all livestock species. Cattle had the highest turnover and all species’ mortalities accounted for the greater proportion of exits. Cattle had the highest multiplication and growth rates, but also the highest mortality, offtake, commercial offtake and intake rates. Goats had the lowest mortalities, offtake, commercial offtake and intake rates. Overall, the herds were structured to provide for both immediate and future needs in terms of milk, sales and herd replacement as well as for rapid recovery after disasters. The livestock herd dynamics indicate efforts at culling, restocking, retention of valuable categories of animals, and natural events. Livestock populations would be annihilated over time if the trends in end balances and negative growth rates were to continue and not be interrupted by the upward phases of the livestock cycles.
    [Show full text]
  • Kenya Country Office
    Kenya Country Office Flood Situation Report Report # 1: 24 November 2019 Highlights Situation in Numbers The National Disaster Operations Center (NDOC) estimates that at least 330,000 330,000 people are affected - 18,000 people have been displaced and 120 people affected people have died due to floods and landslides. (NDOC-24/11/2019) A total of 6,821 children have been reached through integrated outreach 31 services and 856 people have received cholera treatment through UNICEF-supported treatment centres. counties affected by flooding (NDOC-24/11/2019) A total of 270 households in Turkana County (out of 400 targeted) and 110 households in Wajir county have received UNICEF family emergency kits 120 (including 20-litre and 10-litre bucket), soap and water treatment tablets people killed from flooding through partnership with the Kenya Red Cross. (NDOC-24/11/2019) UNICEF has reached 55,000 people with WASH supplies consisting of 20- litre jerrycans, 10-litre buckets and multipurpose bar soap. 18,000 UNICEF has completed solarization of two boreholes reaching people displaced approximately 20,500 people with access to safe water in Garissa County. (NDOC-24/11/2019) Situation Overview & Humanitarian Needs Kenya has continued to experience enhanced rainfall resulting in flooding since mid-October, negatively impacting the lives and livelihoods of vulnerable populations. According to the National Disaster Operations Center (NDOC) 24 November 2019 updates, major roads have been cut off in 11 counties, affecting accessibility to affected populations for rapid assessments and delivery of humanitarian assistance, especially in parts of West Pokot, Marsabit, Mandera, Turkana, Garissa, Lamu, Mombasa, Tana River, Taita Taveta, Kwale and Wajir Counties.
    [Show full text]
  • Registered Voters Per Constituency for 2017 General Elections
    REGISTERED VOTERS PER CONSTITUENCY FOR 2017 GENERAL ELECTIONS COUNTY_ CONST_ NO. OF POLLING COUNTY_NAME CONSTITUENCY_NAME VOTERS CODE CODE STATIONS 001 MOMBASA 001 CHANGAMWE 86,331 136 001 MOMBASA 002 JOMVU 69,307 109 001 MOMBASA 003 KISAUNI 126,151 198 001 MOMBASA 004 NYALI 104,017 165 001 MOMBASA 005 LIKONI 87,326 140 001 MOMBASA 006 MVITA 107,091 186 002 KWALE 007 MSAMBWENI 68,621 129 002 KWALE 008 LUNGALUNGA 56,948 118 002 KWALE 009 MATUGA 70,366 153 002 KWALE 010 KINANGO 85,106 212 003 KILIFI 011 KILIFI NORTH 101,978 182 003 KILIFI 012 KILIFI SOUTH 84,865 147 003 KILIFI 013 KALOLENI 60,470 123 003 KILIFI 014 RABAI 50,332 93 003 KILIFI 015 GANZE 54,760 132 003 KILIFI 016 MALINDI 87,210 154 003 KILIFI 017 MAGARINI 68,453 157 004 TANA RIVER 018 GARSEN 46,819 113 004 TANA RIVER 019 GALOLE 33,356 93 004 TANA RIVER 020 BURA 38,152 101 005 LAMU 021 LAMU EAST 18,234 45 005 LAMU 022 LAMU WEST 51,542 122 006 TAITA TAVETA 023 TAVETA 34,302 79 006 TAITA TAVETA 024 WUNDANYI 29,911 69 006 TAITA TAVETA 025 MWATATE 39,031 96 006 TAITA TAVETA 026 VOI 52,472 110 007 GARISSA 027 GARISSA TOWNSHIP 54,291 97 007 GARISSA 028 BALAMBALA 20,145 53 007 GARISSA 029 LAGDERA 20,547 46 007 GARISSA 030 DADAAB 25,762 56 007 GARISSA 031 FAFI 19,883 61 007 GARISSA 032 IJARA 22,722 68 008 WAJIR 033 WAJIR NORTH 24,550 76 008 WAJIR 034 WAJIR EAST 26,964 65 008 WAJIR 035 TARBAJ 19,699 50 008 WAJIR 036 WAJIR WEST 27,544 75 008 WAJIR 037 ELDAS 18,676 49 008 WAJIR 038 WAJIR SOUTH 45,469 119 009 MANDERA 039 MANDERA WEST 26,816 58 009 MANDERA 040 BANISSA 18,476 53 009 MANDERA
    [Show full text]
  • County Urban Governance Tools
    County Urban Governance Tools This map shows various governance and management approaches counties are using in urban areas Mandera P Turkana Marsabit P West Pokot Wajir ish Elgeyo Samburu Marakwet Busia Trans Nzoia P P Isiolo P tax Bungoma LUFs P Busia Kakamega Baringo Kakamega Uasin P Gishu LUFs Nandi Laikipia Siaya tax P P P Vihiga Meru P Kisumu ga P Nakuru P LUFs LUFs Nyandarua Tharaka Garissa Kericho LUFs Nithi LUFs Nyeri Kirinyaga LUFs Homa Bay Nyamira P Kisii P Muranga Bomet Embu Migori LUFs P Kiambu Nairobi P Narok LUFs P LUFs Kitui Machakos Kisii Tana River Nyamira Makueni Lamu Nairobi P LUFs tax P Kajiado KEY County Budget and Economic Forums (CBEFs) They are meant to serve as the primary institution for ensuring public participation in public finances in order to im- Mom- prove accountability and public participation at the county level. basa Baringo County, Bomet County, Bungoma County, Busia County,Embu County, Elgeyo/ Marakwet County, Homabay County, Kajiado County, Kakamega County, Kericho Count, Kiambu County, Kilifi County, Kirin- yaga County, Kisii County, Kisumu County, Kitui County, Kwale County, Laikipia County, Machakos Coun- LUFs ty, Makueni County, Meru County, Mombasa County, Murang’a County, Nairobi County, Nakuru County, Kilifi Nandi County, Nyandarua County, Nyeri County, Samburu County, Siaya County, TaitaTaveta County, Taita Taveta TharakaNithi County, Trans Nzoia County, Uasin Gishu County Youth Empowerment Programs in urban areas In collaboration with the national government, county governments unveiled
    [Show full text]
  • Facilitator's Training Manual
    Department of Children's Services Facilitator’s Training Manual Implementing the Guidelines for the Alternative Family Care of Children in Kenya (2014) July 2019 This report was supported in part by Changing the Way We CareSM, a consortium of Catholic Relief Services, the Lumos Foundation, and Maestral International. Changing the Way We Care works in collaboration with donors, including the MacArthur Foundation, USAID, GHR Foundation and individuals. For more information, contact [email protected]. © 2020 This material may not be modified without the express prior written permission of the copyright holder. For permission, contact the Department of Children’s Services: P. O Box 40326- 00100 or 16936-00100, Nairobi Phone +254 (0)2729800-4, Fax +254 (0)2726222. FOREWORD The Government of Kenya’s commitment to provide for children out of family care is demonstrated by the various policies and legislative frameworks that have been developed in the recent years. All children are equal rights-holders and deserve to be within families and community as enshrined in the Constitution of Kenya 2010 and the Children Act 2001. The development of this training manual recognizes the role of the family and the community in the care of our children while the accompanying user friendly handbook aims to boost the skills and knowledge of case workers and practioners in the child protection sector. All efforts need to be made to support families to continue to care for their children and, if this is not possible, to place a child in a family-based alternative care arrangement, such as; kinship care, foster care, guardianship, Kafaalah, Supported Independent Living (SIL), or adoption.
    [Show full text]
  • Territoires Supprimés De La Liste Des Territoires Infectés Entre Les 31 Mars
    — 168 NÉPAL — NEPAL (excl. Hyderabad, Division TYPHUS À POUXt Conor, Province Biratnagar (A) & Kat­ Hyderabad, District. B 28.1 LOUSE-BORNE TYPHUS FEVER f Canar, Canton................ B 24.X11 mandu ( A » ................ B 21.1 Hyderabad, D. : Hyder­ Biratnagar ( A ) ................ B 21.1 Carchi, Province abad ........................... B 11.11 5JO-6.IV Katmandu ( A ) ................ ■ 22.V.63 Tharparkar, District . B 4.11 Tulcan, Canton .... B 21.1 Khairpur, Division Afrique — Africa Chimborazo, Province PAKISTAN Jacobabad, District . B 25.11 Alausi, C anton.................. B 7.1 Khairpur, District . A 11.III AFRIQUE DU SUD1 Chaîna (P )....................... B 4.IU Nawabshah, District. B 21.1 SOUTH AFRICA1 Dacca (excl. A) .... A 25.111 XSukkur, District .... B 7.1 PÉROU — PERU Karachi (PA) (excl. A) . A 25.111 Cape, Province Lahore (excl. A) . A 25.111 Lahore, Division Ârequipa, Dep, LyaJIpur ( A ) ................... B 10.XII Gujranwala, District. B 21.1 Glen Grey, District . B 30.TV.65 Arequipa, Province . B 28.1 Multan ( A ) ................... B 31.XII Gujranwala, D.: 1 Aucune information reçue depuis le/ Peshawar ( A ) .....................A 25JH G ujranw ala......... B 21.1 No information received since: 7.VI.65. Quetta (A )............................ A 11.III Lahore, District.......... A 11.01 Asie — Asia Sargodha ( A ) ................ B 4.HI Sheikhupura, District . B 21.1 Sialkot, District .... B 24.XU BURUNDI YEMEN East Pakistan Sialkot, D. : Sialkot . B 31.XII Muramvya, Province Sana, Province (excl. Chittagong, Division Multan, Division Muramvya, Air. .... B 25.0 Sana (A ))...................... B 9.X.63 Commilla (Tippera), D. B 21.1 MuzafFargarh, District B 10.XIÏ Mwaro, Ait. ................... B 4.10 Noakhali, District .
    [Show full text]
  • Addressing Sexual Violence and HIV Risk Among Married Adolescent Girls in Rural Nyanza, Kenya Prepared by Chi-Chi Undie
    promoting healthy, safe, and productive transitions to adulthood Brief no. 19 March 2011 Addressing sexual violence and HIV risk among married adolescent girls in rural Nyanza, Kenya Prepared by Chi-Chi Undie arried adolescent girls form a large segment of Kenyan youth, yet they are largely overlooked by researchers and program Mmanagers concerned with the lives of adolescents. As evidence demonstrates, this neglected population of married girls is likely to be vulnerable and in need of support. HIV infection is much higher among adolescent girls in sub-Saharan Africa than among boys. In settings such as Nyanza Province, Kenya, rates of HIV infection are extremely high, and evidence is increasing in some settings that girls who are mar- ried are much more likely to be infected with HIV, compared with their unmarried sexually active counterparts. Sexual violence and HIV/AIDS are a lethal combination. Research indicates that the risk of HIV infection following forced sex is likely to be higher than following consensual sex. Finding ways to tackle sexual violence and HIV infection simultaneously has therefore become a major public health endeavor. Married adolescent girls are particularly vulnerable to sexual vio- lence; however, there is a lack of data to guide intervention efforts specifically for such girls because they have largely remained invisible in programs. This brief describes a program addressing the problem of sex- ual violence and the risk of HIV transmission within marriage in Kenya’s Nyanza Province. The program was based on the Population Council’s analysis of the 2003 Kenya Demographic and Health Survey (KDHS) as well as on formative research within rural Nyanza.
    [Show full text]
  • Adp 2016/2017 Download
    REPUBLIC OF KENYA BARINGO COUNTY GOVERNMENT ANNUAL DEVELOPMENT PLAN 2016/17 County Treasury and Economic Planning AUGUST 2015 Annual Development Plan-2016-2017 i FOREWORD The 2016/2017 Baringo County Annual Development Plan (ADP) is formulated in the model of the current Medium Term Expenditure Framework (MTEF). The Plan is prepared in line with the requirements of Section 126 of the Public Finance Management Act 2012, and in accordance with Article 220(2) of the Constitution. The Annual Plan contains the strategic priority development programmes and projects that will be implemented during the financial year 2016/2017. The Budget preparation process in the Medium Term, adopted the Programme Based Budgeting approach, where the sector working groups in the county formulated their respective sectors’ budget proposals, policies and programmes with clear outputs, outcomes as well as performance indicators which are related to the achievement of the programme objectives. This annual plan is therefore framed against a broad fiscal policy and reform measures underpinning the budget for the 2016/17 Financial Year, which outlines expenditure per priority programmes as well as allocation of resources to all sectors of the County economy. Significant proportion of the County’s budget shall be financed through National Government funding while it is expected that the County Government and development partners shall bridge the gaps. The preparation of the annual plan made reference to key County and National Government Policy documents particularly the Baringo County Integrated Development Plan (2013– 2017), the Second Medium Term Plan (2013 – 2017) and Vision 2030, the approved County Programme Based and Budget (PBB) 2015/2016.
    [Show full text]
  • Value Chain Analysis of Grass Seeds in the Drylands of Baringo County
    Lugusa et al. Pastoralism: Research, Policy and Practice (2016) 6:6 DOI 10.1186/s13570-016-0053-1 RESEARCH Open Access Value chain analysis of grass seeds in the drylands of Baringo County, Kenya: A producers’ perspective Klerkson Okomboli Lugusa1*, Oliver Vivian Wasonga1, Yazan Ahmed Elhadi1 and Todd Andrew Crane2 Abstract Pastoral households are increasingly practising fodder production in response to forage scarcity associated with land degradation, climate variability and change. Understanding the grass seed value chain is a prerequisite for developing sustainable fodder production and guiding appropriate out-scaling in the drylands. This study investigated the producers’ perspectives on grass seed production, marketing and challenges faced along the grass seed value chain in Marigat Sub- County of Baringo County, Kenya. The results show that the dominant actors were the bulking and processing agents who provided inputs and were a source of grass seed market to the producers. The producers preferred contractual agreements that allowed them to sell their grass seed to markets of their choice. As independent grass seed traders allowed for seed price negotiation, they were popular amongst the producers and thus handled the most volume of seeds marketed. Drought occurrence, inability of existing outlets to purchase grass seed at times, together with low prices offered for producers’ grass seed were found to be among the challenges facing the producers. There is need to strengthen the fodder groups with a possibility of registering them as cooperatives for the purpose of collective bargaining for better grass seed prices. Keywords: Land degradation, Fodder production, Pastoral households Introduction and export demand for livestock products, particularly Livestock plays an important role in many developing meat (Tolera et al.
    [Show full text]