LEGUME FALLOWS FOR FUELWOOD PRODUCTION AND SOIL FERTILITY IMPROVEMENT IN SAURI MILLENNIUM VILLAGE, SIAYA DISTRICT, KENYA.

Transcription

1 LEGUME FALLOWS FOR FUELWOOD PRODUCTION AND SOIL FERTILITY IMPROVEMENT IN SAURI MILLENNIUM VILLAGE, SIAYA DISTRICT, KENYA. MUTINDA GABRIEL KIMILU (B.Sc. Forestry) (Reg. No. N50/10226/06) THESIS SUBMITTED IN PARTIAL FULFILMENT FOR THE DEGREE OF MASTER OF ENVIRONMENTAL STUDIES (AGROFORESTRY AND RURAL DEVELOPMENT) SCHOOL OF ENVIRONMENTAL STUDIES KENYATTA UNIVERSITY, NAIROBI, KENYA. FEBRUARY 2010

2 i DECLARATION I declare that this thesis is my original work and has not been presented for a degree in any other University or any other award. Mutinda Gabriel Kimilu (N50/10226/06) Department of Environmental sciences, Kenyatta University Date... This thesis has been submitted with our approval as University supervisors. Prof. Shyam Manohar Date Department of Environmental Sciences, Kenyatta University P.O BOX , NAIROBI. Dr. Patrick K. Mutuo Date.. Millennium Villages Project, P.O. BOX KISUMU (ICRAF).

3 ii DEDICATION I dedicate this work to my son Collins, daughter Clara and wife Stella for their companion. To my parents, brothers, sisters and friends for their moral support and encouragement.

4 iii ACKNOWLEDGEMENT I convey my heartfelt appreciation to my supervisors Prof. Shyam Manohar of Kenyatta University and Dr. Patrick K. Mutuo of Millennium Villages Project, for their indispensable support and guidance in the design of this study, Laboratory analysis and constructive input during statistical analysis and compiling of this report. I would also like to acknowledge Prof. Cheryl Palm on behalf of Millennium Villages Project-Kenya for sponsoring this study. I also wish to express my sincere gratitude to Eliud Lelerai (MVP) and Andrew Sila (ICRAF) for their assistance in data analysis. The data used in this study were collected with assistance from MVP/ICRAF staff and especially Elvis Weullow and Ateku Dickens Alubaka for their assistance to do soil spectral analysis. I appreciate the MVP programme officer Mr Willis Ombai for facilitating my operations both in the field and also at Kisumu office. I salute all my good friends and express my sincere gratitude for their moral support and encouragement, may GOD remember you all, now and forever.

5 iv TABLE OF CONTENTS Page No. DECLARATION... i DEDICATION... ii ACKNOWLEDGEMENT... iii TABLE OF CONTENTS... iv LIST OF TABLES... vii LIST OF FIGURES... vii LIST OF APPENDICES... viii ABBREVIATION AND ACRONYMS... ixx ABSTRACT... x CHAPTER ONE... 1 INTRODUCTION Background Statement of the problem Justification Research questions Research hypotheses Research objectives... 8 CHAPTER TWO... 9 LITERATURE REVIEW Introduction Improved fallows for soil fertility improvement Improved fallows for Biomass production CHAPTER THREE MATERIALS AND METHODS Study site Climate Soils Agro ecological Zone/Farming System Socio-economic activities Research Methodology Methods of data collections... 28

6 v Soil spectral analysis for N, C, P, Ca, Mg, K, Sand, Silt, Clay, & ph in water Procedures used for economic analysis for legume fallows Data analysis CHAPTER FOUR RESULTS AND DISCUSSION Household characteristics Farming practices The adoption level of legume fallows by farmers in the study area Use of leguminous tree species, Fertilizer, and their sources of farm inputs in the study area Benefits associated with the adoption of legume fallows by farmers in the Study area Leguminous tree species preferred by farmers in the study area Obstacles faced by farmers in legume tree planting in the study area Planting systems of the legume trees on the farms in the study area Legume fallows as an intervention to problems of fuelwood shortages and food security in the study area Perception of farmers on the use of legume fallows for fuelwood production Preference of legume tree species for fuelwood by farmers Fuelwood estimates and economic impacts from use of leguminous tree species Perception of farmers on the use of legume fallows for soil fertility improvement Soil fertility tests under different agricultural inputs Predictions for the 2008 soil batch based on 2006 soil batch calibration models Maize yield estimate from the treatments CHAPTER FIVE CONCLUSION AND RECOMMENDATION Conclusion Recommendations REFERENCES APPENDICES... 82

7 vi LIST OF TABLES Page No. Table 3.1 Calibration model summaries, 2006 soil batch...30 Table 3.2 PC scores and Spectra calibration models, 2006 soil batch 31 Table 3.3 Method/Formula used to calculate maize yield estimates..33 Table 4.1 Household gender, Age and Education..35 Table 4.2 Cultivation types practiced in the study area. 35 Table 4.3 Perennial food and cash crop(s) grown within the study area Table 4.4 Food and horticultural crop(s) grown annually within the study area Table 4.5 Problems faced by farmers during the time of cultivation in the study area.38 Table 4.6 Sources of farm inputs and type 39 Table 4.7 Response of farmers about the Knowledge of agroforestry practices, and training Table 4.8 Benefits associated with legume fallows...42 Table 4.9 List of leguminous tree species preferred by farmers in the study area 43 Table 4.10 Farmers facing problems and obstacles due to legume tree planting Table 4.11 Plot level descriptive statistics on household farms in the study area..46 Table 4.12 Leguminous tree species preferred for fuelwood by farmers Table 4.13 Reasons for preference of T. candida for fuelwood by farmers in the study area Table 4.14 Fuelwood estimates of selected leguminous tree species in the study area.. 50 Table 4.15 Use of t-test to compare means of two sets of data for average costs of fuelwood and average savings of fuelwood in a month at household level...53 Table 4.16 Estimated household food sufficiency and, action to overcome deficit...55 Table 4.17 Shows means of treatments for soil parameters and ANOVA summary..59 Table 4.18 Means of maize yield (t ha -1 ) under different treatments...65 Table 4.19 ANOVA summary Shows statistical differences between maize yield (t ha -1 ) under different treatments.66 Table 4.20 ANOVA summaries - Effects of interaction of other factors to maize yield (t ha -1 )...67 Table 4.21 ANOVA summary- Grouped means of maize yield (t ha -1 ). 69

8 vii LIST OF FIGURES Page No. Fig. 3.1 Map of Siaya illustrating the location of Bar Sauri (Sauri MV).24 Fig. 3.2 Sub villages, homesteads and land use in the Sauri Millennium Village..24 Fig. 3.3 Annual rainfall (mm) in Sauri from Yala weather station, Fig. 4.1 Pie chart presents planting patterns of leguminous species on the farms...45 Fig. 4.2 Bar chart presents the current fuelwood status in the study area Fig. 4.3 A bundle of Tephrosia candida fuelwood collected at household level in the study area..51 Fig. 4.4 PC2 against PC1 scores for the two soil batches (2006 and 2008) spectra...56 Fig. 4.5 Score plot for the wet chemistry data, 2006 soil batch...57 Fig. 4.6 Loadings plot for the soil properties data, 2006 soil batch.58 Fig. 4.7 Shows control plot, and adjacent plot preceded by Crotalaria paulina.64 Fig. 4.8 Graphical presentation of grouped means of maize yield (t ha -1 )...68

9 viii LIST OF APPENDICES Page No. Appendix 1. Structured questionnaire 82 Appendix 2. Climatic data for rainfall and temperature for the study area 91 Appendix 3. Soil map for uniform productivity area (UPA) for Western Kenya..93 Appendix 4. Classification of farming systems by broad category (Dixon, 2001) 94 Appendix 5. Data for the cost of fuelwood from market and savings accrued from using fuelwood produced from legume fallows at household level..96 Appendix 6. Predictions for the soil spectra 2008 soil batch...98

10 ix ABBREVIATION AND ACRONYMS ANAFE African Network for Agriculture, Agroforestry & Natural Resources Education ANOVA Analysis of variance Calc.MC Calculated moisture content CGIAR Consultative Group for International and Agricultural Research HIV-AIDS Human Immuno deficient Virus that causes Acquired Human Immune Deficiency Syndrome. IF Improved Fallows In Log MDGs Millennium Development Goals MPTS Multipurpose trees and shrubs MV Millennium Villages MVP Millennium Villages Projects NGOs Non governmental organizations NIRS Near infrared spectroscopy PCA Principle component analysis RSMEC Root square mean error of calibration RSMECV Root square mean error of cross validation R. sq Root square SPSS Statistical package for social scientists Sqrt Square root t ha -1 Tonnes per hectare

11 x ABSTRACT This research work was conducted between March 2008 (before start of long rains) and August 2008 (the season for harvesting maize), in Sauri Millennium Village, sub location of Yala division, Siaya district, Kenya. The general objective of this study was the adoption of legume fallows in Sauri millennium village with specific objectives;- (i) To study the current status of legume fallows in Sauri millennium village (ii) To investigate the leguminous tree species for high fuelwood production, (iii) To find out the role of leguminous tree species for the improvement of soil fertility and food production in the study area, and (iv) To assess rudimentary economic implications on households from the use of legume fallows. The methodology used was a field survey based on stratified random sampling on households with, and without legume fallows. The size of the Sample frame was based on the Millennium villages project households (three hundred (300) households), out of which ninety (90) households were selected for sampling. Structured questionnaire combined with observation and existing documentation were used to gather data for objectives i, ii and iii, while soil tests, fuelwood quantification and maize yield estimates were done to gather data for objective iv. Social variables were analyzed by use of SPSS package, and t-test used to compare average costs and average savings from fuelwood. Soil spectral analysis was done and calibration models developed from existing Sauri soil spectra and used to make predictions for the new soil samples, and principle component analysis (PCA) model developed to compare the distribution of the two sets of soil spectra within the same spectral space. Analysis of variance (ANOVA) tests were used to compare statistical differences between treatments i.e. means of treatments for soil attributes and means of maize yield. The results showed that, soil fertility and fuelwood production were the motivating reasons for adopting legume fallows. Tephrosia candida is the most recommended for fuelwood and together with Mucuna pruriens and Tephrosia vogelli showed better soil attributes. Mixed intercropping with Tephrosia candida produced 2.2 tonnes per hectare of fuelwood compared to Crotalaria paulina 0.8 tonnes per hectare. All fallowed treatments produced high maize yield up to 5.5 tonnes per hectare compared to non fallowed at 4.6 tonnes per hectare and the controls at 3.6 tonnes per hectare. In conclusion the study has shown that, combining legume fallows with crops has enabled farmers to spend less to buy fuelwood from market, while producing high crop yields on their farms. This has generally improved the livelihood of the rural community. This study recommends, a thorough economic analysis of the intervention, introduction of other leguminous tree species, provision of credit facilities to farmers and the promotion of agricultural productivity which is among the key strategies in Sauri, in order to ensure sufficient fuelwood and food security in the area.

12 1 CHAPTER ONE INTRODUCTION 1.1 Background The Millennium Villages Project (MVP) is aimed at empowering and working with impoverished communities in rural Africa to achieve the Millennium Development Goals (MDGs). The project is designed to demonstrate how the eight-millennium development goals can be met within five years through community led development, with specific targets for reducing poverty by 2015, the global timeline agreed upon by all countries of the world in At the Millennium Summit in September 2000, world leaders set forth quantified and time bound goals, the MDGs, to cut extreme poverty, hunger, diseases, gender inequality, environmental degradation, lack of access to safe drinking water, and sanitation. These MDGs include:- Eradication of poverty and hunger; Achievement of universal primary education; Promotion of gender equality and empowerment of women; Reduction of child mortality; Improvement of maternal health; Combating of HIV/Aids, malaria and other diseases; Ensuring of environmental sustainability; and Developing of a global partnership for development (UN, 2000). In January 2005, the United Nations Millennium Project released a series of reports identifying practical ways to achieve the MDGs (UN Millennium Project, 2005) and the three areas of the world with the greatest number of desperately poor populations living below one US dollar a day, are South Asia (522 million people) Sub Saharan Africa (291 million people), and China (213 million people) (CGIAR 2000). Massive increases (for example, 6% per annum) in agricultural productivity in developing countries are required if the world is to achieve the targets it has set itself towards meeting the MDGs to eradicate poverty and hunger (Goal 1) and

13 2 improve human health (Goals 4, 5 and 6) (UN Millennium Project, 2005). At the same time, the large projected increases in population levels, coupled with the increased economic growth associated with development, will result in massively increased loads on ecosystems and the environment in developing countries over the next several decades, threatening environmental sustainability (Goal 7) (Millennium Ecosystem Assessment, 2005). Twelve millennium villages located in ten (10) African countries (Ethiopia, Ghana, Kenya, Malawi, Mali, Nigeria, Rwanda, Senegal, Tanzania, and Uganda) have been established and the initiative works directly with most of the relevant stakeholders such as the respective communities, community based organizations, non-governmental organizations and the government relevant institutions. Millennium villages are located in hunger hot spots where chronic hunger is wide spread, often accompanied by a high prevalence of diseases, lack of access to medicinal care, and a severe lack of infrastructure. Each village is located in a distinct agro-ecological zone (arid or humid, highland or lowland, grain producing or pastoral) to reflect the range of farming, water and disease challenges facing the continent and to show how tailored strategies can overcome each one of them. In the last three years, two millennium villages namely Sauri and Dertu were set up in Kenya. Sauri founded in the year 2004 in Western Kenya, Nyanza province is the world s first millennium village. In Sauri the land owned by the households is small (0.5 ha), and most of it is utilized for crop production and thus due to continuous cropping and lack of inorganic fertilizers have contributed to depletion of soil nutrients, reduction in yields and creating food insecurity. Shortage of fuelwood has remained a major challenge to the households, since most of their land is utilized for crop production; little is left for woody cover and it has been found that, approximately 46% of households obtain all of their

14 3 fuelwood without paying for it, 3% regularly purchase all of their fuelwood while 51% supplement free collection by purchasing some fuelwood (MVP Baseline report 2007). The Millennium villages project strategy focuses on four interconnected challenges: Agricultural productivity, public health, education, and infrastructure. The interventions are undertaken as a single integrated project and the synergies and tradeoffs assessed and highlighted before decisions are made. For example, higher food production has positive impacts on health and education but might also result in some children, missing school by working on farms. The strategies of the Millennium villages project in Sauri at the village scale basically consist of:- Doubling or tripling staple food crop production to eliminate hunger; Diversifying the farm towards high value products, to facilitate the transformation from sub-subsistence farming into small scale enterpreneurs and improve nutrition in the household; Decreasing malnutrition ( measured by % of underweight children less than 5 years of age) by half in 5 years and to negligible levels in 10 years; eliminating micronutrient deficiencies in the village and providing school meals with locally produced foods; Eliminating obstacles to school attendance, particularly for girls, encouraging education beyond primary school through scholarship and supporting adults through gender specific skills training and services; Increasing household access to clean water supply as well as schools, clinics and improving latrine condition; Providing energy alternatives to generate power for schools, clinics, public spaces and equip homes with improved cooking structures to increase efficiency and family health, create effective transport and communication systems to facilitate economic growth; and Rehabilitating the environment by soil conservation, watershed protection and tree planting. Tremendous achievements and definite potential in poverty alleviation and improved livelihood in Sauri Millennium Village households have been recorded. Noticeable

15 4 achievements in the sector of agriculture and environment include: - The use of fertilizers and improved seeds; use of legume fallows (Improved fallows); Increased maize yields by three fold, from 1.9 t ha -1 in 2004, 4.9 t ha -1 in 2005 to 6.2 t ha -1 in 2006; Farmers planted high value and nutritious crops for income generation such as groundnuts, tissue culture bananas, onions, kales, chilies, and soy beans; Locally produced foods to support school meals programme; and to date 40,240 trees have been planted as woodlots, spring buffers and in other sites (MVP Annual report 2006). The main question addressed in this research is; can the use of legume fallows enhance food security, fuelwood production and other benefits that improve the livelihood of the rural households. 1.2 Statement of the problem Improved fallows is a rotational system that uses preferred tree species as the fallow species (as opposed to colonization by natural vegetation) in rotation with cultivated crops as in traditional shifting cultivation. The term improved implies usage of improved multipurpose trees and shrubs (MPTS) together with improved plant management techniques and improved plant arrangement. Their ability to produce economic benefits (production role) and service roles have been found to overcome key problems both locally and globally (Garrity D.P, 2004), hence seen as a solution/option to a better rural livelihood and Sauri is no exception. Thus, in Sauri are these key problems, the driving force to the adoption of Improved Fallows, just like a case in Zambia where farmers abandoned adoption of Improved Fallows after seed buying companies stopped the purchase of seeds produced by farmers from the fallows since they were driven by economic returns (income) derived from seed production (Alwin Keil, 2001).

16 5 Food insecurity compounded by shortages of fuelwood have become key problems in Sauri Millennium Village. Population growth has reduced per-capita land availability to such an extent that traditional bush fallows can no longer be practiced and low soil fertility is becoming a major constraint to crop production. This decline of soil fertility in smallholder farming systems is a major factor inhibiting equitable development in much of sub-saharan Africa (Sanchez and Palm, 1996). In Sauri, due to population pressure fields that are small (0.5 ha) are simply cropped more frequently, and together with lack of inorganic fertilizers have resulted to soil infertility leading to food insecurity due to low crop production. Improved fallows (IF) based on leguminous trees have become a low cash-input agroforestry practice that can restore soil fertility, resulting high crop production, hence enhancing food security. Also, although the government of Kenya have initiated the use of electricity at the village level, through the rural electrification programme, the installation cost has remained high for the rural poor communities. Hence, the use of fuelwood as the alternative and cheap source of energy is inevitable. Due to the acute shortages and high demand of fuelwood as the main source of energy, it has become costly for the households in that, they have to buy the product and women have to spend more time on collecting firewood at nearby and distant roadsides, community land or forest/woodlots, yet this wasted time could be utilized on other economical roles. 1.3 Justification To alleviate basic rural food insecurity, which occurs partially as a result of soil nutrient depletion, through repeated crop harvest and soil erosion, has become among the major constraints for sustainable food production in sub-saharan Africa (Mafongoya et al., 2006). This problem is further aggravated by the wide spread practice of continuous cropping that uses little if any fertilizer and manure because of high farm acquisition costs (Kwesiga et

17 6 al., 2003), hence, the need for soil fertility replenishment practices, involving organic inputs, is inevitable. The adoption of agroforestry practices has been advocated as an alternative to continuous cropping because of high capacity to replenish soil fertility, improve crop production, and enhance food security and household income in regions where commercial fertilizers are unaffordable to most smallholder farmers (Kwesiga et al., 2003; Mafongoya et al., 2006). At the same time, because of the high cost of electricity, fuelwood has remained the main source of energy to the rural poor communities in Kenya for many years. The acute shortages and high demand of fuelwood has negatively impacted on the environment, as the main sources sometimes the state forests/woodlots become highly degraded due to encroachment. In the households, women and children are burdened with the responsibility of collecting firewood and the collection distances continue to increase due to depletion from the village environs. Also, the land owned by the households is small (0.5 ha), and most of it is utilized for crop production, resulting to minimal areas under woody cover. Therefore, the need for scientific interventions such as agroforestry can address the problem of fuelwood availability in Sauri millennium village. There might be other reasons a part from food insecurity and fuelwood shortages, that may cause farmers adopt improved fallows. A case in Zambia found that among the benefits, farmers were interested in planting improved fallows primarily to sell the seeds to ICRAF and other seed buying companies (Alwin Keil 2001), and once these seed buying companies withdraw from the programme the farmers became demoralized towards the adoption of improved fallows. Thus, there is need to find out whether the same applies to Sauri and the real reasons why farmers adopt improved fallows.

18 7 1.4 Research questions 1) What are the motivations to farmers to practice and expand legume fallows? 2) Which are the leguminous tree species suitable for fuelwood production in Sauri millennium village? 3) What is the role of leguminous tree species for the improvement of soil fertility and food production in the study area?. 4) How are the economic implications on households from the use of legume fallows? 1.5 Research hypotheses 1) Legume fallows can supply fuelwood as the main source of energy to the households on a sustainable basis. 2) Legume fallows can enrich soil fertility and enhance crop production in Sauri millennium village. 3) The use of Legume fallows can improve the livelihood of the households in Sauri Millennium village (economic savings). 4) There exists a variety of legume plants that farmers can choose and plant in their farms.

19 8 1.6 Research objectives 1) To study the current status of legume fallows in Sauri millennium village. 2) To investigate the leguminous tree species for high fuelwood production in Sauri millennium village. 3) To find out the role of leguminous tree species for the improvement of soil fertility and food production in the study area. 4) To assess rudimentary economic implications on households from the use of legume fallows.

20 9 CHAPTER TWO LITERATURE REVIEW 2.1 Introduction The earliest form of agroforestry, shifting cultivation, is a rotational system in which, after a period of cropping, soil fertility is restored by a fallow of natural vegetation (forest or savannah). It is fully sustainable with adequate lengths of fallow under low population densities, but these circumstances are rarely found today (Young, 1997). Many other indigenous agroforestry systems achieved maintenance of soil fertility, for example, rotations of cereals with Acacia Senegal (gum Arabic) in the Sahel zone of Africa, or the multistrata forest cropping systems of Sumatra, Indonesia (Young, 1997). The origin of agroforestry as a modern scientific study was the publication in 1977 of a review of research needs on, Trees, Food and People (Bene et al, 1977). This was where the term agroforestry was coined, but more importantly it was the breakthrough in the recognition of the key concept, that trees and shrubs grown on farmland had distinctive and valuable roles to play. This led to the establishment of the International Centre for Research in Agroforestry (ICRAF). Various authors have defined agroforestry in various ways. According to (Bene et al, 1977), Agroforestry is a sustainable management system for land that increases overall production, combines agricultural crops, tree crops and forest plants and/or animals simultaneously or sequentially and applies management practices that are compatible with the cultural patterns of local population. According to (King and Chandler, 1978), Agroforestry is a sustainable land management system, which increases the overall yield

21 10 of the land, combines the production of crops (including tree crops) and forest plants or animals simultaneously or sequentially on the same unit of land and applies management practices that are compatible with the cultural patterns of local population. According to (Nair, 1984), Agroforestry is a land-use that involves deliberate retention, introduction, or mixture of trees or other woody perennials in crop/animal production field to benefit from the resultant ecological and economical interactions. The definition that has stood the test of time, was formulated by (Lundgren, 1982) and according to him, Agroforestry is a collective name for land-use systems and technologies in which woody perennials including trees, shrubs, bamboos etc. are grown in association with herbaceous plants (crops, pastures) or livestock, in a spatial arrangement, a rotation, or both; there are usually both ecological and economic interactions between the trees and other components of the system. Agroforestry is a dynamic, ecologically based, natural resources management system that, through integration of trees on farms and agricultural landscapes, diversifies and sustains production for increased social, economic, and environmental benefits for land users at all levels (World Agroforestry Centre, 2003). There have been worldwide efforts to recognize the social, economic and environmental benefits of agroforestry, especially in terms of increasing food security, reducing poverty, improving the livelihoods of small-scale farmers in developing countries, and halting natural resources degradation. World-wide adoption of agroforestry have helped farmers by:- Increasing land productivity due to improved soil fertility and conservation measures through the use of (for instance) improved fallows and hedge rows intercropping strategies; Supplying fodder supplements (e.g. from Gliricidia sepium leaves ) that increase milk production for dairy cattle; Diversifying farm production systems that provide tree products across all seasons (wet

22 11 and dry), helping farmers to bridge the off season dry periods by having access to tree products such as fruits, nuts and leafy vegetables from trees and shrubs; Increasing wood energy availability to families from lopped branches in hedge rows, woodlots, boundary planting or improved fallows; Contributing to incomes among small-scale farmers from sale of products such as fruits, fodder, tree seedlings and poles (ANAFE 2006). 2.2 Improved fallows for soil fertility improvement. An improved fallow which is an agroforestry system is defined as the planting of one or few tree species as a substitute to natural fallow to achieve benefits of the latter in a shorter time (Prinz, 1986; Young, 1997). Rao et al. (1998) distinguished two categories of improved fallows:- The short duration fallows with fast growing leguminous trees or shrubs seeking to replenish soil fertility and; the medium to long duration fallows with diverse species and aimed at rehabilitating degraded and abandoned lands as well as exploiting tree products. In Central America, many agroforestry systems are being established on abandoned agricultural land because farmers are recognizing the potential for financial returns from the agroforestry systems, especially where native species are used for soil fertility improvement (Piotto et al., 2003b). Through the use of agroforestry systems it has been found to offer ecological benefits such as improved nutrient cycling, soil conservation, and recovery of biodiversity (Piotto et al., 2003b). An on farm study of alley cropping in an orchard to place in a tropical fruit orchard in Holualoa Island of Hawaii and showed that in two years time with no fertilizer inputs expect for mulch from the hedgerows, showed significant increase in total nitrogen and potassium in the soil, as well as improvement in soil ph (more neutral) (Elevitch and Wilkinson, 1998). In Costa Rica, improved fallows on

23 12 degraded land with Acacia mangium has helped control erosion and improved nutrient reserves, while supplying timber products (FACT Net, 1999). Agroforestry systems identified by Garrett and Buck (1997) of short rotation woody crops like the tree- agronomic crop systems (alley cropping and intercropping) has many benefits. In USA and Canada, Short rotation woody crops in the riparian component of agroforestry systems provided numerous benefits. For instance the Poplar trees effectively lower subsurface nitrate (N) concentrations and stabilizes degraded agricultural stream banks while growing rapidly (O Neill and Gordon, 1994). Short rotation woody crops as part of a 20 meter wide multispecies riparian buffer strip in Iowa effectively removed nutrients, pesticides, and sediments in addition to stabilizing stream banks (Schultz et al. 1995). Seiter et al. (1999) experimented with alley cropping in Oregon and determined the amount of biomass input from inorganically fertilized hedgerows of alder ( Alnus rubra) and black locust (Robinia pseudoacacia) to corn planted in the alleys. Mean prunnings biomass ranged from 0.9 to 4.7 Mg t ha -1 of dry matter, but this was not enough to maintain corn yield over four years. Thevathasan and Gordon (1997) examined the effects of poplar leaves on corn and barley (Hordeum vulgare) in Southern Ontario, Canada and found that, the addition of poplar leaves through leaf fall may have increased nitrification rates and total soil organic carbon. Silvoarable agroforestry, the deliberate combined use of trees and arable crops on the same area of land, has been proposed in order to improve the environmental performance of agricultural systems in Europe. In France, Spain, and Netherlands the adoption of agroforestry systems was found to be high and showed to reduce soil erosion by up to 70%,

24 13 to reduce N leaching by 20-30%, to increase C sequestration over 60 years by up to 140 t C ha -1, and to increase landscape diversity up to four times (Palma, 2006). In Claveria in Northern Mindanao, Philippines, where soils are acidic, low in phosphorous and generally unproductive led to the introduction of contour hedgerow systems in 1985 using nitrogen fixing trees to minimize on erosion, restore soil fertility and improve crop productivity. Although the adoption of this system was slow, because of the high labour requirement to maintain the hedgerows, poor adaption of leguminous trees to acid soils and competition on between trees and maize crops, an alternative approach was needed to restore the degraded soils (Mercado et al, 2001). Agroforestry practices in India, such as improved fallows proved important in maintenance and enhancement of soil fertility leading to food security and environmental sustainability and currently India is self-sufficient in terms of food production. Maintaining and enhancing soil fertility of farmlands through agroforestry practices to grow food grains as well as tree biomass has helped meet the demand of the rising population in India (Pandey, 2007). Perennial crop combinations, in agroforestry system like home gardens which are widely practiced in the humid tropics of South Asia, South America and Africa, play various functions including control of soil erosion, nutrient inputs and shading crops to reduce evapotranspiration (Young, 1997). In these systems, it s estimated that between 10 and 20 t ha -1 of biomass are returned to the soil every year as litter and prunnings, with soil organic content increase of between 1.6 and 4 Mg Carbon per hectare per year (Young, 1997). The regular addition of prunnings and root turnover over the years in hedgerow intercropping systems contributes to build up of soil organic matter and nutrient stocks in the soil (Kang

25 14 et al., 1999; Kumar et al., 2001). The association of trees with crops or pastures has become a sustainable alternative to slash and burn agriculture (Sanchez et al.,1999; Schroeder, 1994; Sanchez, 1995) and has huge potential for carbon sequestration in croplands which is an indicator of soil health. Estimates have shown that the combination of woody perennials and crops has the potential to store between 29 and 53 Mg per hectare aboveground C in the humid highlands of Africa, between 39 and 195 Mg per hectare C in South America and between 12 and 228 Mg per hectare C in South east Asia (Dixon et al., 1993; Krankina and Dixon, 1994). Nitrogen deficiency is one of the major factors limiting maize (Zea mays) production in sandy soils of Zambia, Malawi, Tanzania, Zimbabwe and elsewhere in southern Africa. Over the years, inorganic fertilizers (major N suppliers) have become unaffordable to most farmers following the removal of agricultural subsidies (Howard and Mungoma, 1996). Application of micro doses of inorganic fertilizers (especially N) in tree-crop systems has generally increased the synergy in nutrient availability there by producing high maize yields than unfertilized maize. Short-duration planted fallows (or improved fallows) using a wide range of leguminous tree species such as Sesbania sesban, Gliricidia sepium, Tephrosia vogelii and Cajanus cajan have been found to replenish soil fertility and to increase subsequent maize yields (Kwesiga et al., 1999). Consequently, small-scale farmers in eastern Zambia are adopting improved fallows. Tephrosia vogelii, a direct seeded species, is widely preferred over other species because it does not have to be raised in a nursery (Mafongoya et al., 2004). In contrast to species like Sesbania sesban and Gliricidia sepium, it does not need inoculation with specific Rhizobium strains as it nodulates with native rhizobial populations in a wide range of soils. Tephrosia vogelii is also less affected by pests than the other tree legumes, perhaps due to its pesticidal properties. For example,

26 15 it is less susceptible to the root-knot nematodes Meloidogyne javanica and Meloidogyne incognita than Sesbania species (Desaeger and Rao, 2000). In Malawi the application of Leucena leucocephala leaf prunnings in alley cropping system raised maize yield grain and increased soil ph, organic Carbon, Total N, S and exchangeable Ca, Mg and K (Jones et al., 1996; Wendt et al., 1996). Maize yield also increased from 0.49 t ha -1 in the controls to 2.73 t ha -1 in alley cropping with several species in Malawi. The potential of planted fallows to ameliorate soil fertility and increase nutrient stocks have also depended on several factors including the fallow species, the length of the fallow and the soil and climatic conditions. Significant increases of soil organic matter (SOM) have been obtained with fallows of Cajanus cajan (pigeon pea) on degraded soils in Western Kenya (Onim et al., 1990), Tephrosia vogelii in Cameroon (Prinz, 1986), Tephrosia candida in Nigeria (Gichuru, 1991) and in single and mixed legume species in Western Kenya (Ndufa, 2001). After five fallowing phases of 6 months each with Crotalaria grahamiana, alternated with maize cropping phases in between them, soil C contents in top 5 cm depth increased by 6% in till system due to the incorporated fallow biomass and about 20% in no-till practices, compared to continuous maize cropping (Mutuo et al., 2005). A strategy of integrated nutrient management-based use of all available nutrient sources, namely mineral and organic fertilizers, have been adopted and agroforestry options found to offer a lot of opportunities to small-scale farmers to replenish soil fertility cheaply and in a more sustainable manner. Over the years, World Agroforestry Centre Southern Africa programme has been involved in identifying and domesticating tree species (now popularly known as fertilizer trees ) for various soil fertility replenishment practices (ICRAFSA, 2007). The most common species include Cajanus cajan, Calliandra calothyrsus, Flemingia macrophylla, Gliricidia sepium and Leucaena leucocephala. Others are Senna

27 16 siamea, Senna spectabilis, Sesbania macrantha, Sesbania sesban and Tephrosia vogelii. These species have been found to have the potential to restore soil fertility of fallow land and at the same time produce fuelwood or fodder on farms as by-products. Of these Sesbania sesban, Tephrosia vogelii, Leucaena leucocephala and Gliricidia sepium have been the most promising and commonly adopted by farmers in Southern Africa. The research resulted in domestication and use of the above tree species in ways such as improved fallows, mixed cropping, rely cropping and biomass transfer. Earlier agroforestry research carried out in Gairo, Tanzania found that shrub species such as Senna singuena which is indigenous to the area and which has been noted to improve soil fertility elsewhere (Nduwayezu, 2001) has the potential for soil fertility improvement and other by products such as fodder and fuelwood, especially due to its adaptability to local conditions and acceptance by farmers. Short duration planted fallows or improved fallows, usually with Nitrogen fixing trees and shrubs, like Sesbania sesban, Tephrosia vogelii and Crotalaria grahamiana are among the most widely used or promoted leguminous species in western Kenya (Niang et al., 2002). Several studies have demonstrated the complementary value of improved fallows to inorganic fertilizers in increasing crop yields (Niang et al., 2002; Jama et al., 1998; Gathumbi et al., 2004). They are more efficient than natural fallows and can, in certain soils, have the same effects as inorganic fertilizers on crop yields (Kwesiga and Coe 1994; Place et al., 2003). Improved fallows, particularly Sesbania sesban, also control weeds, including striga (Striga hermontheca) that parasitizes on maize and other cereal crops (Gacheru and Rao, 2001). In addition, the proportion of poor households in western Kenya, which use improved fallows, exceeds the use rates of most other soil-fertility improvement options (Place et al., 2002).

28 Improved fallows for Biomass production. The main concern in biomass production includes fuelwood, fodder, timber and seed production. Agroforestry technologies can generate fuelwood in addition to providing other tree products. In Central America, agroforestry systems have been found to offer forest products such as wood, firewood and mulch. Planting of selected tree species has become an attractive alternative for farmers, for instance firewood from thinning has become an additional source of income. Recently, interest in agroforestry systems including native tree species has grown among small farmers in Central America (Montagnini et al., 1995; Montagnini and Mendelsohn, 1997; Piotto et al., 2003a; 2003b). Farmers have interest in planting indigenous species which have timber accepted in high demand, in the local markets, since most of the indigenous species have become scarce in natural forests due to logging or in some cases their extraction has been banned. They consider reforesting their farms with valuable species (MPTS) as a viable alternative to other land uses, such as extensive cattle ranching, which became unprofitable and degraded their lands. Studies on agroforestry systems such as silvopastoral in North America have shown that, managing for livestock, firewood and commercial hunting nearly doubled the expected Net Present Value (NPV) over managing for livestock alone (Standiford and Howitt, 1993). For states like Missouri, where oak-hickory forests are predominant, a silvopastoral practice could provide a profitable means of inspiring land owners to manage under utilized forest land. Other agroforestry systems like the riparian systems, where use of short rotation woody crops as part of the 20 meter wide multispecies riparian buffer strip in Central Iowa provided commercial timber and other products in addition to improving the aesthetics of the agro ecosystem (Schultz et al., 1995). Although substantial fuelwood is derived from

29 18 converting forests into farm lands in many areas of USA and Canada, considerable amount of fuelwood are obtained from agroforestry practices on marginal and farm lands (FAO, 1996). Environmental protection and land reclamation are benefits provided by several actinorhizal species e.g. Hippophae rhamnoides is widely planted in Northern Europe to prevent soil erosion and produce biomass. Planting Alnus, or alders, for lumber, pulp or fuelwood production is the second most common use of actinorhizal trees. Wood harvested from native stands is sold as fuelwood or pulped and combined with softwood pulp for paper production. Mean annual wood yields for 8 to 10-year-old red alder, Alnus rubra, were nine oven-dry t ha -1 yr -1 in British Columbia, and maximum production was 28 ovendry t ha -1 yr -1 (FACT Net, 1986). In India agroforestry contribute to livelihood improvement where people have a long history and accumulated local knowledge, particularly ethno forestry practices and indigenous knowledge systems on tree-growing (Pandey, 2007). The farms often have an average of 20 Acacia nilotica trees per ha, of 1 to 12 years of age and Small farms have more tree density. At a ten-year rotation, these trees provide a variety of products, including fuelwood (30 kg/tree), brushwood for fencing (4 kg/tree), small timber for farm implements and furniture (0.2 m3), and non-timber forest products such as gum and seeds. Thus, trees account for nearly 10% of the annual farm income distributed uniformly throughout the year than in rice monoculture (Pandey, 2007). Fuelwood is a very important source of energy for many smallholder farms in Africa. Women and children are the ones who traditionally collect fuelwood from the secondary

30 19 forests. This task can compete for labour with other productive functions in the household (Mafongoya et al., 2004). Fuelwood from improved fallows on farm may provide a means to conserve the natural vegetation, which is under threat due to deforestation. In the study conducted in Zambia, two-year improved fallows using Sesbania sesban produced about 15 t ha -1 of fuelwood from on-farm trials (Kwesiga et al., 1999), and farmers rated Sesbania sesban and Senna siamea most highly. Other studies have shown that, depending on the species, improved fallows have the potential to produce fuelwood and fodder and a wide range of fuelwood yields have been reported under researcher-managed conditions. Examples include, 5 24 t ha -1 within a duration of 1 3 years in western Kenya (Swinkels et al., 1997; Jama et al., 1998; Gathumbi et al., 2004), t ha -1 after 2 years in south western Uganda highlands (Siriri and Rausen, 2003), 10 t ha -1 after 2 years in eastern Zambia (Sanchez, 1995), and t ha -1 after 2.7 years in coastal Kenya (Jama and Getahun, 1991). These systems can also have high returns on investments, whether fertilizers, an expensive commodity in rural Africa, are used (Jama et al., 1998) or not (Siriri and Rausen, 2003). There is, however, limited information on the fuelwood production potential of improved fallows under farmer managed conditions and the extent to which it can meet household energy needs. Knowledge of the fuelwood production potential of improved fallows would help in management in association with crops. Besides species differences, age of the fallows and stand density are two management factors that would probably influence the amount of fuelwood that is produced by farmers as researcher-managed studies indicate (Jama et al., 1998; Gathumbi et al., 2004). In Gairo, Tanzania which is a semi-arid area, small farmers divert productive time from crop production to collection of fuelwood and in addition, there is shortage of dry season fodder (Mugasha et al., 2003). Since 1989 various agroforestry technologies tested in Gairo such as improved fallows and relay cropping were found to be suitable technologies for

31 20 improving soil fertility and fodder supply (Mgangamundo, 2000). Combining boundary tree planting and soil fertility improving trees/shrubs in a single land management unit was found to hold great potential for improving soil fertility, fuelwood and fodder supplies at the same time (Mgangamundo, 2000). In Ethiopia ninety-four percent of its population relies on wood-based and biomass fuel for household energy (Badege et al., 2003), Scarcity of firewood has become acute in many parts of the country causing a continuous rise in prices, and thus increasing the economic burden on the household budget. Animal dung and crop residues are increasingly being used for household fuel rather than being added to the soil to improve soil fertility, thus further exacerbating the problems of environmental degradation (Badege et al., 2003). In the dry lands, Kenya included (Rocheleau et al., 1988) found that woodlots established in croplands and enriched by introducing multipurpose trees and shrubs, herbaceous crops or animals produced fuelwood, fodder and sustain the soil and water resources of the site. E.g. farmers in coffee and tea plantations benefits from dispersed shade trees that provide fuelwood, timber as well as improving soil fertility. In Embu, Kenya, fodder banks of highly value leguminous trees and shrubs planted on farms are used as a substitute for dry meal and source of fuelwood. Calliandra calothyrsus has been used as a feed supplement for dairy cows and other livestock, it has high protein content and animals that fed on it, produce more milk with significantly higher butter content. (Denning, 1998). According to studies done in Western Kenya, low adoption of improved fallow technology where leguminous shrubs such as Sesbania sesban, Tephrosia vogelii and other plants such as Tithonia diversifolia that were grown for a period of 12 to 24 months as a means of

32 21 improving crop yields was observed (Kwesiga, Coe, 1994; Niang et al., 1996; Rutunga et al., 1999). The period when these shrubs/plants are grown does reduce land available for crop production and so, farmers are reluctant to let their land lie fallow for one to two years, although the two-year period also results in large amount of woody materials, which accumulate some nutrients that are normally taken away from the field as fuelwood or rails materials (Rutunga et al., 1999). One strategy to overcome these problems may be to shorten the fallow period to no more than one season and to produce sufficient high quality biomass. Some species like Leucaena leucocephala, Calliandra calothyrsus, and Sesbania sesban give high quality fodder for dairy livestock (Rutunga et al., 1999) and may be better used as fodder than green manure (Jama et al., 1997). Other studies on Western Kenya have also showed that, farmers, especially women, planted some of the shrubs especially Tephrosia candida and Tephrosia vogelli for firewood and generating income from the sale of their seeds. Market for the seeds was one of the factors that motivated farmers to plant improved tree fallows (Evelyne et al., 2006) because the projects concerned bought seeds from the farmers so that it could distribute to other farmers. Improved fallows can be more profitable than continuous cropping and natural fallow practices. Results of an on-farm trial in Western Kenya showed that crotalaria fallow 7 9 months old is more profitable than continuous maize cropping. This is the case for both the returns to land (an important indicator where land is scarce) and returns to labour (an important indicator where labour is scarce) (Amadalo et al., 2003). According to a study by Place et al., (2003) in Western Kenya, farmers actually claimed that improved fallows reduce the amount of labour time required in the following season due to weed suppression, but this has not been quantified. Farmers cut the trees low to the ground and do not de-stump. While many claim that the soils are easier to work with, the presence of

33 22 stumps and roots on average means that farmers spend an extra 10 days per hectare on land preparation the season after cutting (66 days/ha as opposed to 56 days/ha). For comparison, the total amount of labour for a maize/bean crop is 136 during the long rains and slightly less during the short rains (about 120). The fallow system enables the saving of the 120 days, while adding 23 days (when direct seeded into a maize field), giving a net savings of about 97days per hectare. Other studies in Western Kenya have shown that, extra costs of improved fallows compared to continuous cropping, consisted of tree seeds, labour for establishing and removing the trees, and the maize yield forgone during the fallow. Extra benefits included crop labour and other crop inputs saved during the fallow, fuelwood and increased maize yields after the fallow (Swinkels et al., 1997). Improved fallows require less labour than continuous cropping, over three seasons and the reduction was 83 work day s ha -1 or 21% under low yield scenario, thus the higher the opportunity cost of labour the more profitable is the improved fallows. The extra costs of improved fallows compared to unimproved fallows consisted of planting and cutting down the trees, minus cost of clearing the natural fallow, and this was estimated to require 5.8 work days ha -1 (Swinkels et al., 1997).

34 23 CHAPTER THREE MATERIALS AND METHODS 3.1 Study site Sauri Millennium Village (MV) covers the entire Sauri sub location, which is in Yala, Siaya district, Western Kenya (Figure 3.1). Sauri sub-location is located in the Western Kenya highlands, meters above sea level, west of the Rift Valley and 30 km north of Lake Victoria. The equator lies just to the south of Sauri (0 o 06N). The general topography is undulating with ephemeral streams, rivers and wetlands, which meander through rounded hills (MVP Baseline Report 2007). Siaya District covers an area of 1520 km 2, with a population of about 493,326 people (226,682 men & 266,644 women). Yala division which is in Siaya District covers an area of 214 km 2 and a population of about 86,117 people (40,475 men & 45,642 women), while Sauri sub location (Sauri millennium village) in Yala division, is a conglomerate of 11 villages encompassing about 5,000 people and covers an area of 8 km 2, with 614 homesteads, an average of 1.6 households in each home stead. The total area under cultivation (agricultural fields) is about 69% of the total area (MVP Baseline Report 2007). The villages include;- Nyamboga, Silula, Nyamninia A, Nyamninia B, Sauri A, Sauri B, Luero, Madiri, Yala A, Yala B, Kosoro, and Yala Town (Figure 3.2).

35 24 Fig. 3.1 Map of Siaya illustrating the location of Bar Sauri (Sauri MV) Fig. 3.2 Sub villages, homesteads and land use in the Sauri Millennium Village.

36 Climate The area is classified as the sub-humid tropics with an average temperature of 24 o C, ranging from 18 to 27 o C with an annual rainfall of about 1800 mm. Rainfall is bimodal, divided into the long rainy season from March to June (1120 mm) and the short rainy season from September to December (710 mm). The short rains are extremely variable but highly predictable due to strong influence of the El Nino Southern Oscillation (MVP Baseline Report, 2007). Climatic data (appendix 2) for rainfall for the last twenty (20) years was collected daily at the Yala township weather station, located adjacent to the Sauri Millennium village, while temperature data for the last ten years was collected at the Kisumu Meteorological station, situated at the Kisumu Airport. Figure 3.3, is a graphical presentation of annual rainfall for 20 years. In appendix 2, it also shows mean monthly values of rainfall, which reflects the bimodal cycle with the highest rainfall generally occurring in April and the lowest rainfall generally occurring in February Rainfall (mm)) Years Fig. 3.3 Annual rainfall (mm) in Sauri from Yala weather station,

37 Soils The soils of the study area are classified as Oxisols/Nitosols (Kandiudalfic Eutrodox) (soil map for Western Kenya in appendix 3) and they are clayey, reddish, deep, and well drained. Since, they are derived from volcanic materials the soils were once quite fertile but are now depleted in nitrogen (N) and phosphorus (P), two of the essential nutrients for plant growth. The ph borders around 5.5 though soil acidity is not a major problem for plant growth. Soil carbon levels (1.3% C) are half those of the native soils. There are some patches of wetland soils along the rivers and streams (MVP Annual Report 2006) Agro ecological Zone/Farming System This study area is a maize-based farming system according to Dixon s classification (2001) (Details of the classification in appendix 4). Other crops include beans, sweet potatoes, bananas/plantains, cassava, kale, tomatoes, and onions. The bimodal rainfall and high temperature allow two crops per year. Sometimes during the short rainy season there is a possibility of 45% of the crop failing relative to long rains. The vegetation in the area is composed of wood land with scattered trees, and occasional patches of higher tree density. Though densely forested areas are rare in the Sauri landscape, hedges, including homestead hedges, agricultural hedges, and roadside hedges, occupy 2-3 % of the landscape, while swamplands represent less than 5% of the landscape (MVP Annual Report 2006).

38 Socio-economic activities The population density of Sauri is extremely high, close to 700 people per sq. kilometer. Households are scattered throughout the agricultural landscape (Figure 3.2). Agriculture is the primary source of livelihood in the area. The land area for farming is usually less than 0.5 ha per household. Other activities include livestock rearing especially for dairy farming and making of Upesi stoves (improved stoves) by Kawiti women group that are sold to the community. At the onset of the Millennium village project insufficient food was produced for a family of 5 at current production levels. There are 60% to 70% of the people in Siaya District who live below the Kenyan poverty line of $1/day. Over 20% of the children aged less than 5 years are underweight (MVP Annual Report 2006). 3.2 Research Methodology A field survey was conducted between March and August The components of the survey included;-household characteristics i.e. farmers characteristics (age, gender, education); Farming practices i.e. cultivation types; Use of legume tree species by farmers and their perception on legume tree species towards addressing key problems in the study area; Soil sampling; Fuelwood estimates and crop yield estimates. The Sampling design applied was that of Stratified random sampling. Stratification was based on Households planting legume fallows and those not, spread over the entire eleven (11) villages which comprises the Sauri research village. The size of the Sample frame was also based on the MVP conduct Households (three hundred (300) households) from which a sample size of ninety (90) households was selected i.e. 60 households had fallowed plots, 20 households had fertilizer applied plots, while 10 households had control plots.

39 Methods of data collections For the field survey, the use of structured questionnaire (appendix 1) combined with observations and existing documents were applied to gather data for objectives 1-3. Soil tests, fuelwood quantification and maize yield estimates were done to gather data for objective 4. Fuelwood quantification was carried out on households with leguminous tree species, while soil tests were conducted based on plots with different types of leguminous tree species. In the plots soils were sampled at three (3) sites i.e. diagonally near the plot edges and at the centre, to a depth of 15 cm, then the sampled soils were mixed and a sub sample collected. In total, there were ten (10) treatments (different types of land uses) from which reflectance measurements (soil spectral analysis) were done. From the same plots, quadrants of sizes ranging between 3 (three) metres by 3 (three) metres to 5 (five) metres by 5 (five) metres were laid down. Depending on the size of the plots and crop performance, between 1 (one) to 3 (three) quadrants were laid down per plot, number of plants and maize (cobs) were recorded for each quadrant, and total fresh weight of maize (cobs) sampled for each quadrant recorded, then a sub sample of maize (cobs) from the quadrants was collected and the rest left to the farmer. The collected sample was taken to the laboratory where the following measurements were recorded; - Total sample fresh weight (cob), core fresh weight, grain fresh weight, 3 (three) moisture meter readings, 3 (three) core dry weight readings and 3 (three) grain dry weight readings. Before recording both grain and core dry weights, they were initially sun dried for 3 (three) to 4 (four) days in order to loss moisture content, then they were oven dried at a temperature of 60 0 centigrade. Three (3) dry weight readings were recorded after every 12 (twelve) hours to achieve a constant dry weight (grain storage moisture content). These measurements were used to calculate maize yields and, hence compare treatment effects to crop production.

40 Soil spectral analysis for N, C, P, Ca, Mg, K, Sand, Silt, Clay, & ph in water. The Near infrared (NIR) analysis procedure. The soil samples collected before the start of long rains, 2008 were air dried and passed through a 2mm sieve, and stored in paper bags at room temperature. The air-dried soil samples were parked half-full in 12mm deep, and 55mm diameter polystyrene Petri dishes and given laboratory identity numbers. These soil samples were scanned and diffuse reflectance measurements (spectra) recorded for each sample, using Multi Purpose Analyzer (MPA) which is a Fourier Transform Infra Red (FTIR) spectrometer (Bruker MPA Spectrometer) at wavelength from 0.35 m to 2.5 m. The method in use is the Sphere Macrosample which has the sample compartment unit that operates on the transmission mode and the integrating sphere windows that operates on the diffuse reflectance mode. The integrating sphere has got different accessories i.e. the rotating arm that rotates the cup or wide Petri dish on the sphere windows and fixed vial mount that mounts the vial on the sphere window. The samples were scanned through the bottom of the Petri dish using a high intensity source probe. The probe illuminates the sample and collects the reflected light through computer software known as OPUS then stored in the computer and the whole operation can be shown by the computer monitor. To sample within dish variation, reflectance spectra were recorded at two positions, successfully rotating the sample dish through 90 between readings. Variation in readings within dishes can occur because of different individual spectrometers in the instrument having different fields of view (CAMO Inc., 1998). The average of 32 spectra (the manufacturer s default value) was recorded at each position to minimize instrument noise. Before scanning of the soil samples, background measurements were done that lasted for 8 hours, and kaolinite and Mua soil standards spectra readings recorded. These acted as reference readings to the reflectance readings for each wavelength band. To determine soil properties/attributes,

41 30 normally a sub sample is selected for wet chemistry analysis, or using the spectra for the soil samples, prediction for the soil properties/attributes were done, based on the existing Sauri soil spectra analyzed in These soil spectra are available in the continuously updated reflectance spectral libraries in world agroforestry centre (Shepherd and Walsh, 2002). Partial Least Square (PLS) calibration models (table 3.1) were developed using the software OPUS (Bruker Optik GmbH ) which offers a variety of spectral preprocessing procedures, optimization capabilities and model cross validations, from the existing Sauri soil spectra (soils batch analyzed in 2006). Table 3.1 Calibration model summaries, 2006 soil batch. Calibration Validation Parameter R. sq RSMEC R. sq RSMECV lnc lnn Clay sqrtexca sqrtexmg lnexk lnexp lnph sqrtsand Silt Extractable Phosphorous gave a poor calibration model and therefore could not be reliably used to make prediction for the 2008 spectra. As a remedy for the model that failed to give good calibration, the soil data was centered and their suitable transformation (same as for Partial Least Square calibration because these are parametric methods and would assume

42 31 normality of the data variables), to create Principle Component Analysis models (table 3.2). Principle Component Analysis is a multivariate statistical technique that summarizes the variability of large data sets using a smaller set of variables called latent variables or principal components (PCs). The reduction in the number of variables used to describe the data facilitates interpretation of the relationship between observations. Table 3.2 PC scores and Spectra calibration models, 2006 soil batch. Calibration Validation Parameter R. sq RSMEC R. sq RSMECV PC PC PC The method of integrating physical and chemical indicators with a principal components analysis (PCA) could represent a more systems-like description of overall soil quality. PCA was conducted with the Unscrambler version 7.5 (CAMO Inc., 1998). Spectra were also plotted and continuum-removed, using ENVI (Research Systems Inc.,SanDiego,CA). Use of multivariate scores (principal components) as system descriptors, allowed an effective evaluation and determination of soil quality of the different sites Procedures used for economic analysis for legume fallows The economic impact on the use of legume fallows for fuelwood was determined by using the sets of data for costs of purchasing fuelwood from the market monthly and savings (monies) accrued as a result of using fuelwood produced within the household level on a monthly basis. The two sets of data were compared to find out, whether there were any statistical differences and used to deduce the economic importance of legume fallows on fuelwood production in terms of labour involved in fuelwood collection, income obtained and its effects on the environment.

43 32 The economic importance of legume fallows on crop production was determined by maize yields from different treatments (fallow, fertilizer applied, and the controls). Although there were costs that were incurred like; costs of inputs, labour, cost of land preparation, cost of planting, etc it was not possible to determine their actual costs, but based on maize yields from the treatments it was possible to deduce the economic importance of legume fallows on crop production. 3.3 Data analysis Social variables such as farmers characteristics, farming practices, perception on the use of legume fallows etc were analyzed by use of SPSS package and reported as percentages of the sample population conducted/interviewed and the results presented in form of tables and graphs. Use of t-test (table 4.15) to compare means of two sets of data for average costs of fuelwood and average savings of fuelwood in a month was applied, purposely to deduce on the economic implications from the use of legume fallows for fuelwood production at the household level. From the predicted values of the new soil samples, means of the treatments were calculated and analysis of variance (ANOVA- Table 4.17) tests conducted using the GenStat version 7.2 Discovery Edition 3 statistical package (GenStat, 2007).

44 33 Table 3.3 Method/Formula used to calculate maize yield estimates Yield corr. to 14% (t ha -1 ) calc. MC = Dry yield (t ha -1 ) calc. MC + (1+0.14) Corr. - Corrected Calc. MC - Calculated moisture content Dry yield (t ha -1 ) calc. MC = Total dry wt grain (kg) calc. MC x (10/ qd. size) wt -weight qd - quadrant Total dry wt grain (kg) calc. MC = Total wet grain yield x (grain dry wt/grain fresh wt) Total wet grain yield = (grain ratio/cobs fresh wt) Grain ratio = (grain fresh weight/cob fresh wt) After obtaining yield corrected to 14% (t ha -1 ) calculated moisture content, means/averages of maize yield of the treatments were calculated and analysis of variance (ANOVA- Table 4.19 & Table 4.21) tests conducted using the GenStat version 7.2 Discovery Edition 3 statistical package (GenStat, 2007) to compare whether there were statistical differences between the means. ANOVA (Table 4.20) was also used to compare the effects of other factors to maize yield and assess if there was any interaction between them. These factors are; - Animals, Crop pest and Striga. Its true that, treatments were applied in a farmer managed plots, hence it was very hard for the researcher to control other conditions/factors which had influence on maize yield other than the treatments applied, hence there was the need to assess the effects of interaction of these factors to maize and only a few were considered as mentioned above.

45 34 CHAPTER FOUR RESULTS AND DISCUSSION 4.1 Household characteristics The research sample composed of 90 households, with respondent average age of The youngest respondent interviewed was 18 years old, while the oldest respondent was aged 88 years. Almost half of the respondents were between 36 years and 60 years, a clear indication that, most of the household heads were within the prime age of being economically productive, compared to about 26.7% and 27.8% of the respondents who were between 18 to 35 years and 61 to 88 years, which represents the youthful household heads and the aged household heads respectively. Majority of the household heads were men 60% against women at 40%. The women become household heads after the death of their husbands. More than 56.7% of the farmers in the main sample have attained at least primary level of education, 31.1% and 25.6% being men and women respectively. About 17.8% men and 3.3% women household heads have completed secondary education, while 4.4% men household heads have attained tertiary education, and none of the female household heads have attained tertiary education. Farmers who are illiterate stand at 17.8% (6.7% men and 11.1% women). Despite the illiteracy among women being higher than that of men, their percentages are small, a clear reflection of high proportion of the literate compared to those illiterate within the population of the study area (Sauri millennium village). This fact is confirmed (MVP Baseline Report, 2007) with 95.3% literacy rate among the youth of between years old and over 80% nationally, and adult literacy rate of over 80 % in Sauri and 70% nationally. According to the study (Table 4.1) illiteracy is more common in population above thirty (30) years old.

46 35 Table 4.1 Household gender, Age and Education. Variable No. of farmers Percentages Minimum (age) Maximum(age) Mean Sample size (N) Respondent age % Respondent age group (years) % (years) % (years) Household gender % Female % Male % Household education Male Female Male Female Male Female Male Female Illiterate % 11.1 % Primary % 25.6 % Secondary % 3.3 % Tertiary % 0 % Total % 40 % Farming practices Majority of the farmers (91.1%) in the study area depend on rain-fed agriculture. The rest (8.9%) depend on both rainfall and irrigation (Table 4.2). This is a clear indication that irrigation has not been taken up by most farmers. Table 4.2 Cultivation types practiced in the study area. Cultivation types No. of respondent Percentage (%) Irrigation & rain dependant Rain dependant Total

47 36 The area supports a variety of both perennial and annual crops. Perennial food crops and cash crops grown include; - bananas, fruit trees (mangoes, avocados, and citrus), tubers (cassava, sweet potatoes and arrow roots), sugarcane and coffee (Table 4.3). The annual food crops grown include; - maize, beans, groundnuts, soya beans, sweet potatoes, vegetables (kales, cabbages, cow peas, and other traditional vegetables), sorghum, onions, tomatoes, spices (pepper) and millet (Table 4.4). Bananas are the most popular perennial crops among farmers (table 4.3), and when combined with other perennial crops (fruit trees, tubers, sugarcane and coffee) can improve on the food security of the area as well as being a source of income to the farmers. At least every farmer/household grows maize and beans (Table 4.4)), a clear indication that they are the main food crops in the area. The area also supports different types of food crops and horticultural crops, a clear indication that, the land productivity capacity is good and if well managed can improve on the food security of the area. The most encouraging thing is that, the Millennium Villages Project (MVP) has introduced hybrid seeds for the food crops especially maize and grafted fruit trees like the Mangoes, Citrus species and Avocados. These combined with provision of irrigation water, and legume fallows intercropping with crops can improve on the food security of the area, as well as being a source of income to the community.

48 37 Table 4.3 Perennial food and cash crop(s) grown within the study area Perennial food/cash crops No. of respondent Percentage (%) bananas bananas, fruit trees δ bananas, fruit trees δ, tubers γ bananas, sugarcane bananas, sugarcane, fruit trees δ bananas, sugarcane, tubers γ bananas, tubers γ bananas, coffee N/A ( No perennial crops) Total δ Farmers have one or a combination of the fruit tree species (Mangoes, Avocados, Citrus). γ Farmers have one or a combination of the tubers (Cassava, Sweet potatoes, Arrow roots). Table 4.4 Food and horticultural crop(s) grown annually within the study area Annual food crops/horticultural crops No. of respondent Percentage (%) maize, beans maize, beans, groundnuts maize,beans, groundnuts, soya beans maize, beans, groundnuts, sweet potatoes maize, beans, groundnuts, sweet potatoes, soya beans maize, beans, groundnuts, sweet potatoes, vegetables * maize, beans, groundnuts, vegetables *, onions, tomatoes maize, beans, groundnuts, vegetables *, soya beans maize, beans, sorghum maize, beans, sorghum, groundnuts maize, beans, sorghum, groundnuts, millet maize, beans, sorghum, groundnuts, vegetables * maize, beans, sorghum, millet, groundnuts, sweet potatoes maize, beans, sorghum, sweet potatoes maize, beans, sorghum, vegetables * maize, beans, sorghum, vegetables *, sweet potatoes maize, beans, soya beans maize, beans, soya beans, groundnuts, sorghum, sweet potatoes maize, beans, sweet potatoes maize, beans, sweet potatoes, groundnuts, sorghum maize, beans, vegetables * maize, beans, vegetables *, groundnuts maize, beans, vegetables *, groundnuts, soya beans maize, beans, vegetables *, groundnuts, tomatoes, sweet potatoes maize, beans, vegetables *, soya beans maize, beans, vegetables *, tomatoes maize, beans, vegetables *, tomatoes, sweet potatoes maize, beans, vegetables *, sweet potatoes maize, beans, vegetables *, sweet potatoes, groundnuts maize, beans. vegetables *, onions, pepper maize, beans, vegetables *, onions, sweet potatoes, tomatoes, Total * Farmers have one or a combination of the various types of vegetables (Kales, Cabbages, Cow peas, Traditional vegetables).

49 38 The study showed that, farmers were faced with problems that are related to crop production and most of them highlighted several problems. These problems were;- Crop destruction by animals, infertile soils, termites, yield destruction by pests (weevils), unfavorable weather, crop diseases, labour constraints, lack of inputs, insufficient land, striga (Striga hermonthica) weed, water logging, land disputes, lack of market for the post harvest, poor germination and retarded growth. Most of the farmers (22.1%) lacked farm inputs, hence coming out as the major problem in the area, followed by crop destruction by animals (17.8%) and striga (Striga hermonthica) weed (15.3%) (Table 4.5). Generally, addressing these farmers problems can enhance on food security in the area. Table 4.5 Problems faced by farmers during the time of cultivation in the study area Problems faced by farmers No. of respondent Percentage (%) Lack of inputs Crop destruction by animals Striga weeds Unfavorable weather Labour constraints Termites Infertile soils Diseases Yield destruction by pests Land disputes Insufficient land Water logging Lack of market for post harvest Poor germination Retarded growth None Total

50 The adoption level of legume fallows by farmers in the study area Use of leguminous tree species, Fertilizer, and their sources of farm inputs in the study area. Most of the farmers (94.4%) combine leguminous tree species and fertilizers, while the remaining minority use either leguminous tree species or fertilizer on their farms for crop production, a clear indication that most farmers are aware of the importance of legume fallows for crop production, reflecting a high adoption rate of the intervention. Majority of the farmers (94.4%) indicated Millennium villages project subsidy as their source of farm inputs (Table 4.6), this is a contradiction since subsidies reduced from 89% to 45% to 25% in 2005, 2006 and 2007 respectively (MVP Baseline Report, 2007) a fact that was confirmed during maize yield harvesting where farmers indicated they either purchased inputs or obtained loans from a microfinance provider. Table 4.6 Sources of farm inputs and type Sources of farm inputs No. of respondent Percentage (%) MVP subsidy Gifts Total Type of farm inputs Legume and Fertilizer. No combination Total The study has shown that, 96.7% of farmers in the area are knowledgeable on the use of agroforestry practices, while only 3.3% of the farmers have no knowledge about agroforestry. Only 16.7% of the farmers have attended agroforestry training while 83.7% have not (Table 4.7). This indicates that, most farmers are knowledgeable on the use of agroforestry practices, although most of them have not gone for any formal training. This is

51 40 possible because from history other Non Governmental Organizations like ICRAF who have had similar programmes/activities in the area before. Between the uptake of improved fallows in Western Kenya has been significant. This has been achieved through close collaboration between the World Agroforestry Centre and its many research and development partners in the region. Monitoring in 17 villages (Sauri sub location included) found about 22% of farmers had been consistently using improved fallows with another 7% beginning to test the technology in 2001, and the adoption rates were higher where farm sizes were larger and farmers had more contact with informed and knowledgeable extension or research services (Amadalo et al, 2003). The high level of knowledge on agroforestry practices by farmers translates to high adoption of legume fallows in the area. Table 4.7 Response of farmers about the Knowledge of agroforestry practices, and training Knowledge on agroforestry No. of respondent Percentage (%) Knowledgeable Not knowledgeable Total Attended agroforestry training Yes No Total

52 Benefits associated with the adoption of legume fallows by farmers in the Study area. There is no doubt that, use of legume tree species by farmers, offers a variety of benefits to them. The research has shown that around 90% of farmers use legume tree species on their farms to derive fuelwood. About 97.8% of farmers integrate crops with legume tree species to enrich soil fertility. Seed production has been another motivation for legume tree planting by farmers on their farms and about 80% of farmer s plant legume tree species for seed production. Other benefits why farmers plant leguminous tree species on their farms include;-fodder production (4.4%), and timber production (1.1%) (Table 4.8). Soil fertility, fuelwood and seeds have come out clearly as the reasons which motivate farmers to adopt legume fallows in the study area. This is also confirmed by a research done by (Kuntashula et al (2005) in Zambia, where farmers agreed that in addition to soil fertility improvement being the single most important consideration, fuelwood was the second most important benefit from improved fallows. Farmers in the study area can confidently praise the presence of the Millennium villages project which has improved their livelihood from the use of legume fallows resulting to high crop yields and availability of fuelwood in their households. Farmers also plant legume tree species for seed production which the Millennium villages project buys from them. This has provided a ready market for the seeds, motivated the farmers and boosted their sources of income.

53 42 Table 4.8 Benefits associated with legume fallows Benefits No. of respondent Percentage (%) Fuelwood Soil fertility Seeds Fodder Timber Total The study showed that the proportion of farmers adopting legume fallows had risen from 42.2% in 2007 to 74.1% in 2008 an increase of 31.9%, and the fallows cover an area of acres which on average is 0.42 acres at household level (corresponding fallowed area for 2007 was not available to compare the areas). It s possible to deduce that from the high rate of adoption of the intervention, farmers really value the benefits derived from legume fallows Leguminous tree species preferred by farmers in the study area This study showed that some farmers would prefer integrating single legume tree species with crops on their farms while others combine different legume tree species in the same farm. About 33.5% of the farmers prefer planting Crotalaria paulina, 30.5% prefer Tephrosia candida while 13.8% prefer Mucuna pruriens; these were the most preferred legume tree species and mostly integrated with crops in the area (Table 4.9). A clear indication that farmers are motivated to adopt them due to their ability to enhance soil fertility resulting to high crop yields, provide fuelwood and seed production which are important in the improvement of the livelihood of the community. Other leguminous tree species preferred by farmers includes; - Crotalaria grahamiana (7.2%), Sesbania sesban (5.4%), Calliandra calothyrsus (4.2%), Leucena leucocephala (1.2%) Tephrosia vogelli

54 43 (0.6%) and Gliricidia sepium (0.6%). Five of the 90 farmers had no preference at all on any leguminous tree species (Table 4.9). Table 4.9 List of leguminous tree species preferred by farmers in the study area. Leguminous tree species No. of respondent Percentage (%) Crotalaria grahamiana Mucuna pruriens Crotalaria paulina Tephrosia candida Tephrosia vogelli Calliandra calothyrsus Sesbania sesban Leucena leucocephala Gliricidia sepium None ( No preference) Total Obstacles faced by farmers in legume tree planting in the study area. The proportion of farmers facing problems in legume fallow planting (39%) was less than those who do not face any problem (61%) (Table 4.10). Mostly encountered problems include; - Labour constraints, lack of appropriate seedlings, lack of sufficient land, and land tenure (Table 4.10). Other problems cited by farmers include, the poor payment from sale of legume tree seeds, poor germination, and that Crotalaria paulina harbors caterpillars. Lack of sufficient land and land tenure (among the main challenges) can be attributed to population pressure in the area and to enhance food security and overcome other household problems like fuelwood and source of income, then intensification and growing of high value crops are important.

55 44 Table 4.10 Farmers facing problems and obstacles due to legume tree planting. Farmers facing problems in legume tree planting. Farmers facing no problem in legume tree planting No. of farmers Percentage (%) Total Obstacles faced in legume tree planting. Labour constraints. Lack of appropriate seedlings. Lack of sufficient land. Land tenure. Land tenure, Labour constraints. Legume trees act as habitat for destructive animals. Other reasons. None (Don t face obstacles) Total Planting systems of the legume trees on the farms in the study area Farmers have different ways of arranging the leguminous tree species and the agricultural crops/components (agrosilvicultural) on their farms. Majority of the farmers, around 93% prefer mixed intercropping with crops while 2% prefer planting leguminous trees a long the boundary (Figure 4.1). On some farms (about 4%) no particular patterns of planting system were observed. The common planting system (mixed intercropping) is done in such a way that crops are grown first during the start of long rains (March-April) then in June-July leguminous trees are planted and allowed to stay even after crop harvesting, hence relay cropping. Mixed intercropping is a better pattern in terms of intercropping crops with legume trees in that it utilizes land properly for maximum production. This is suitable in the area because of the

56 45 small sizes of the farms, which range between 0.1 acres to 4.0 acres and that s why adoption of this planting system of legume fallows is high in the area. Fig. 4.1 Pie chart presents planting patterns of leguminous species on the farms. 4.3 Legume fallows as an intervention to problems of fuelwood shortages and food security in the study area. As indicated earlier in the household characteristics, the research was conducted on 90 households. Each household had a maximum of three plots and a minimum of one plot making a total of 165 plots. The plot sizes ranged from 0.1 acres to 4.0 acres with an average mean size of 0.74 acres per plot. On average kgs of fertilizers were applied on the plots costing about KSh 1, Out of the 165 plots, fuelwood was produced from 103 plots and on average around bundles (a bundle is about 11 kgs to 23 kgs depending on the legume tree species) of fuelwood was produced per plot. Table 4.11 shows a descriptive statistics of the plots.

57 46 Table 4.11 Plot level descriptive statistics on household farms in the study area. No. of plots Range (acres) Mean (acres) Std. Deviation Plot size (Acres) Fertilizer amount (Kg) Fertilizer price (KSh) Amount of wood fuel produced (bundles) Perception of farmers on the use of legume fallows for fuelwood production. In the area most of the household farms are small and utilized for crop production, with minimal areas under woody cover, which has led to shortages of fuelwood. Results from this study showed that a small number (13.33%) of the farmers face acute shortages of fuelwood, and the fuelwood produced from the fallows could not last more than three months (Fig 4.2). About 35.56% of the farmers, whose fuelwood status was classified as barely sufficient, could produce fuelwood from the fallows that could last between three to six months. Close to half (42%) of the farmers were able to produce sufficient fuelwood from the fallows that could last for more than six months in a year. A small number of farmers (around 9%) were not able to provide information about fuelwood produced in their fallows (Fig 4.2), some of whom claimed the fallow species were left on the farms to rot. Previously 5% and 51% regularly purchased and supplemented free collection by purchasing firewood respectively (MVP Baseline Report, 2007), compared to this study there is a clear indication that farmers are spending less costs on firewood and saving much time on free collection of firewood. With over 40% of the farmers getting sufficient supply of fuelwood from legume fallows, there is a clear indication that legume fallows can provide fuelwood to the households on a sustainable basis. Since women and children are burdened with the responsibility of

58 Proportion of farmers 47 collecting fuelwood, producing fuelwood in the household level, means their time and labour can be utilized on other productive roles. Mugo (1999), for instance, estimated that women who collect fuelwood for cooking from far off places spend, on average, 130 hour per year, as compared to only 36 hour spent by those who harvest firewood from their own farms. Again our forests/woodland will be spared from encroachment for fuelwood collection because farmers can source the commodity right from within their household boundaries. In other cases where the source of fuelwood is the market, means sourcing the commodity at household level will increase farmers savings, which is put to other uses. 40% 35% 30% 25% 20% 15% 10% 5% 0% Acute shortage Barely sufficient Sufficient (future doubtful) Sufficient (now & future) Others Fig. 4.2 Bar chart presents the current fuelwood status in the study area. Acute shortages- Fuelwood produced from fallows can not last for 3 months. Barely sufficient- Fuelwood produced from fallows can last for 3 6 months. Sufficient (future doubtful) - Fuelwood can last for 6-9 months. Sufficient (now & future) Fuelwood can last for over 9 months. Others- Means there were fallow species, but either left in the farms to rot, etc

59 Preference of legume tree species for fuelwood by farmers. The leguminous tree species introduced by the Millennium villages project in the area include; - Tephrosia candida, Tephrosia vogellii, Crotalaria paulina, Mucuna pruriens (soil fertility) and Crotalaria grahamiana. Other species like Calliandra calothyrsus and Sesbania sesban were introduced by other NGOs like ICRAF working in the area. The study has shown that most farmers (87.78%) prefer Tephrosia candida for fuelwood production (Table 4.12). All other legume fallow species were less preferred by farmers for fuelwood production. Only 2 farmers had no preference at all on the leguminous tree species for fuelwood production. These farmers who had no preference on the leguminous tree species introduced in the area depended more on fuelwood from woodlots/woodland, market or other tree species on their farms. Table 4.12 Leguminous tree species preferred for fuelwood by farmers Leguminous tree species for fuelwood No. of farmers Percentages (%) Tephrosia candida Calliandra calothyrsus Crotalaria grahamiana Sesbania sesban Crotalaria paulina Others (No preference) Total Several reasons were listed by farmers as to why they had high preference for Tephrosia candida for fuelwood. These included; - Big trunks and grow tall, dries faster, produces quality fire (less smoke), easy to cut, produces large quantities of firewood, income from sale of firewood and easily accessible. Majority of the farmers listed more than one reason on why they preferred Tephrosia candida as the best leguminous tree species for fuelwood. Around 43% of the farmers interviewed indicated that Tephrosia candida produces quality

60 49 fire (less smoke), 22.2% said it has big trunks and grows tall while 21.7% said it dries faster and according to the study these were the main reasons for preferring Tephrosia candida (Table 4.13). About 7.2% of the farmers gave no reason; either they preferred other leguminous tree species or they had not used Tephrosia candida for fuelwood (Table 4.13). Table 4.13 Reasons for preference of T. candida for fuelwood by farmers in the study area. Reasons No. of respondent Percentage (%) Big trunks and grows tall Dries faster Produces quality fire (less smoke) Easy to cut Produces large quantities of firewood Sells the firewood Only accessible Others Total Fuelwood estimates and economic impacts from use of leguminous tree species Fuelwood estimates has been based on plots with pure stands of Tephrosia candida and Crotalaria paulina i.e. plots with only one species at a time; otherwise it was hard to estimate fuelwood on plots with combination of more than one legume tree species because it was not possible to determine area occupied by each legume tree species. Fuelwood estimates were also based on the legume tree species which were introduced in the area by Millennium villages project. Table 4.14, gives a descriptive statistics summary of fuelwood estimates in the study area.

61 50 Table 4.14 Fuelwood estimates of selected leguminous tree species in the study area Legume tree species T. candida C. paulina Total No. of plots occupied per species Total plot area (acres) Mean/average plot area (acres) ± ± Amount of fuelwood in total area (bundles) Mean/average fuelwood per plot (bundles) ± ± Fuelwood production per plot (bundles/plot) Fuelwood production per acre (bundles/acres) Fuelwood production per hectare (bundles/ha) Weight of one bundle at household level (kg) 23 ± ± Fuelwood production per hectare (kg/ha) The results showed that approximately 30.8 bundles of Tephrosia candida fuelwood were produced from an average plot area of 0.79 acres, grown on a spacing of 0.75 meters by 0.75 meters (0.75 M x 0.75 M). Also approximately bundles of Crotalaria paulina were produced from an average plot area of 0.84 acres, grown on the same spacing as that of Tephrosia candida (Table 4.14). Therefore 39 bundles of Tephrosia candida and 28.9 bundles of Crotalaria paulina were produced in an area of one acre. Measurements taken at the household level indicated that a bundle of fuelwood was approximately 23 kg and 11 kg for Tephrosia candida and Crotalaria paulina, respectively (figure 4.3). Approximately kg (2.2 tons) and kg (0.8 tons) of Tephrosia candida and Crotalaria paulina fuelwood was produced from an area of one hectare (Table 4.14). Description of a bundle of fuelwood at the household level is that bundle which an adult Woman can carry on her head. This is illustrated in figure 4.3 below.

62 51 Fig. 4.3 A bundle of Tephrosia candida fuelwood collected at household level in the study area. The study showed that among the leguminous tree species adopted in the study area, Tephrosia candida was the most preferred species for fuelwood and when integrated with crops could produce about 2.2 t h -1 of fuelwood compared to 0.8 t ha -1 of fuelwood from Crotalaria paulina within a period not exceeding one year. This observation of high fuelwood by Tephrosia candida fallows relative to the other species is consistent with the results of other studies. Jama et al (2008) found that among the six month old fallows, Tephrosia candida produced the highest fuelwood (8.9 t ha -1 ), compared to Crotalaria paulina, Crotalaria grahamiana and Tephrosia vogelli, which produced between 5.6 and 6.2 t ha -1 of fuelwood, and the trend was the same for twelve and eighteen old months Tephrosia candida. The difference of this study to that of Jama et al (2008) is that, in this study the legume tree species were integrated with crops, while that of Jama et al (2008) the legume tree species were in rotation with crops and the stand densities were high compared to integrating the fallow species with crops, thus the high fuelwood yields. The similarity of these two studies is that, the studies were done under farmer managed conditions. Other studies included that of Mafongoya et al (2003) who observed a yield of

63 t ha -1 from eighteen months old Tephrosia candida fallows compared to 6.2 t ha -1 from Tephrosia vogelli fallows under farmer managed conditions in eastern Zambia. In western Kenya, Albrecht and Kandji (2003) observed higher total aboveground biomass yield of 31 t ha -1 from 18 months old Tephrosia candida compared to 24.7 t ha -1 for Crotalaria grahamiana and 19.8 t ha -1 for Crotalaria paulina fallows. To ascertain the importance of legume fallows in the households, comparison were done between savings from the use of fuelwood produced in the study area from legume fallows and costs of purchasing fuelwood from the market. Savings were made during the period/months when enough fuelwood was produced from legume fallows and included monies accrued from sales of the firewood from legume fallows. Costs of fuelwood from market incurred during the months when fuelwood from legume fallows was not available. This was also supplemented by free firewood collection from woodlots/woodland, road reverses, own trees on farm etc. The results showed that, when enough fuelwood was produced from legume fallows, households on average saved Ksh 163/= per month (Table 4.15) for an average period of about 6 months and spent an average of Ksh 107/= to purchase fuelwood from the market for an average period of 3 months when fuelwood was not available from legume fallows (Table 4.15). Households without legume fallows sourced their fuelwood from own trees on farm, woodlots/woodland while very few bought it at the market, where a bundle of fuelwood consisting of approximately 7 12 pieces of wood cost Kshs 20/=, and their weight varied depending on the tree species. Comparisons were done by use of t-test (Table 4.15) between means of two sets of data for costs of fuelwood and savings from fuelwood in a month. Costs in a month are expenses of purchasing fuelwood at the market, while savings in a month are monies saved by using

64 53 fuelwood and sales of firewood produced from legume fallows in the households. Data for the costs of fuelwood and savings from fuelwood is shown in appendix 5. Table 4.15 Use of t-test to compare means of two sets of data for costs of fuelwood and savings from fuelwood in a month at household level. Costs in a month (Ksh) Savings in a month (Ksh) Number of observations Minimum 0 0 Maximum Sum Mean S.E Standard deviation Paired T statistics P-value at 95%CI 0.06 The statistics above indicates that, there are differences between the means. The positive implication of the differences between the means is that, savings are more than costs. An indication that use of legume fallows had boosted fuelwood production at the household level and the money saved could be used for other purposes. Figure 4.2 which shows the current status of fuelwood reflects that, where fuelwood status was sufficient then farmers were able to save more i.e. Ksh 163/= per month for at least six (6) months, compared to costs of purchasing fuelwood at the market at KSh /= per month, which was also supplemented by free firewood collection from woodlots/woodland, road reserves, own trees on farms and gifts. In other cases like where there was acute shortage of fuelwood, farmers were able to save for at least three months but spend the rest of the months (9 months) purchasing the commodity at the market, also supplemented by free firewood collection from woodlots/woodland, road reserves, own trees on farm and gifts, hence they rarely saved. Generally the economic implication with the adoption of legume fallows is the assurance of income from sales of legume products like seeds, fire wood etc and the

65 54 savings accrued as a result of reduced expenses from the purchases of fuelwood at the market. This has led to increased income levels in the households resulting to improvement in the livelihood among the community. The adoption of legume fallows also has direct impact on the environment in that, the community no longer puts pressure on woodlots/woodland in fuelwood collection since farmers are able to derive fuelwood at the household level. Other studies on Western Kenya showed that, farmers especially women, planted some of the shrubs especially Tephrosia candida and Tephrosia vogelli for firewood and generating income from the sale of their seeds. The market for the seeds is one of the factors that motivated them to plant improved tree fallows (Evelyne et al., 2006). Cecelski, (1985); Kumar and Hotchkiss, (1988) found that increased labour allocation to wood collection affected the time women spend on food production, food processing, food preparation and income generating activities Perception of farmers on the use of legume fallows for soil fertility improvement. This study showed that, one of the motivating reasons why farmers adopted legume fallows was soil fertility, which is directly linked to crop production. Results show that 44.4% of the farmers got sufficient/adequate yields by combining crops with legume fallows, and these yields were used by their families until the next harvest, while 55.6% of the farmers claimed the yields obtained were insufficient/inadequate and could not last until the next harvest (Table 4.16). A majority of the farmers (96%) who had yield deficits overcame it through buying, while a minority received gifts (Table 4.16). Although legume fallows enhance soil fertility which in turn influences crop production (Kwesiga et al, 1999), there might be other reasons why farmers failed to get sufficient yield. These could be due to the

66 55 composition of the families (extended families) depending on a small piece of land and other problems faced by farmers in farming and legume tree planting. Table 4.16 Estimated household food sufficiency and, action to overcome deficit. Food Yield status No. of farmers Percentage (%) Sufficient food yield Insufficient food yield Total To over come food deficit Buying Gifts Total Note. Sufficient food yield;- Food yields lasted until the next food harvest. Insufficient food yield;- Food yields could not last until the next food harvest Soil fertility tests under different agricultural inputs To prove the above perception, results for soil tests (table 4.17) shows the attributes of soil properties from different treatments (fallowed, fertilizer applied and control plots). Through spectral analysis, attributes of soil properties determined were;- Soil organic carbon, Total Nitrogen, Exchangeable Calcium, Exchangeable Magnesium, Exchangeable Potassium, Extractable Phosphorous, ph, and Texture (Clay, Sand and Silt) (Table 4.17). These soil attributes/properties, they are important indicators of soil fertility which enhance crop production. Figure 4.4 shows results for the Principle Component Analysis (PCA) model developed to compare the distribution of the two sets (Sauri soil batch analyzed in 2006 and the new soil samples, 2008) within the same spectral space, using calibration models developed from soil batch analyzed in 2006.

67 56 Fig. 4.4 Principal component 2 (PC2) against Principal component 1 (PC1) scores for the two soil batches (2006 and 2008) spectra. The scores plot shows that the 2008 spectra are well within the 2006 spectra space which also was selected for wet chemistry analysis. Therefore a calibration model developed for the 2006 was used to make predictions for the second (2008) batch. Principle Component Analysis (PCA) model results (figure 4.5 and 4.6) obtained by using the soil properties data available for the 50 samples chemically analyzed for nutrients of the 2006 soil batch.

68 57 Fig. 4.5 Score plot for the wet chemistry data, 2006 soil batch (source, Reflectance spectral library, ICRAF (2006), Nairobi). This plot shows that there is some degree of variability within the 50 samples with wet chemistry data, although the majority (towards the right and along PC1) appears similar due to the closeness. The first two principal components (PC1=31% and PC2=29%) accounts for a total of 60% variation in the ten soil parameters.

69 58 Fig. 4.6 Loadings plot for the soil properties data, 2006 soil batch (source, Reflectance spectral library, ICRAF (2006), Nairobi). From the loadings plot, Carbon and Nitrogen appear to be highly correlated together with Silt, whereas ph, Calcium and Magnesium show strong correlation and are all associated with PC1. PC2 is strongly associated with both Extractable P and Extractable K which are correlated. Since both PC1 and PC2 contain aggregated soil data which are used as general soil fertility indicators, they are also used to calibrate against spectra Predictions for the 2008 soil batch based on 2006 soil batch calibration models. Predictions were made for the soil samples using the calibration models developed except for Extractable P. For PC1 predictions, the more positive values are associated with high levels of Carbon, Nitrogen and Silt, while the less positive values are associated with ph, Calcium and Magnesium. The more positive PC2 values are associated with high Extractable K and Extractable P whereas Clay content is associated with negative PC2 values. Therefore in this case, the prediction values for Extractable P are the PC2 values. Based on the different types of treatments, the prediction values are shown in appendix 6.

70 59 There were ten different sets of the treatments for the soil tests. These included;- Treatment A: - Plots applied with basal fertilizer DAP (> 49.4 kgs ha -1 ) Treatment B: - Plots applied with insufficient fertilizer DAP(< 49.4 kgs ha -1 ) Treatment C: - Plots with Tephrosia candida + Basal fertilizer DAP (> 49.4 kgs ha -1 ) Treatment D: - Plots with Tephrosia vogellii + Basal fertilizer DAP (> 49.4 kgs ha -1 ) Treatment E: - Plots with Crotalaria paulina + Basal fertilizer DAP (> 49.4 kgs ha -1 ) Treatment F: - Plots with Crotalaria paulina + insufficient fertilizer DAP (< 49.4 kgs ha -1 ) Treatment G: - Plots with Mucuna pruriens + Basal fertilizer DAP (> 49.4 kgs ha -1 ) Treatment H: - Plots with Mucuna pruriens + insufficient fertilizer DAP (< 49.4 kgs ha -1 ) Treatment I: - Plots with Tephrosia candida + insufficient fertilizer DAP (< 49.4 kgs ha -1 ) Treatment J: - Control plots (no fertilizer and legume fallows) The means of the treatments were calculated and Analysis of Variance (ANOVA) done to determine the effects of the treatments on soil properties/attributes as shown in table Treatment Table 4.17 Shows means of treatments for soil parameters and ANOVA summary. ExCa (me/100g Soil) Means ExK (me/100g Soil) ExMg (me/100g Soil) ExP(PC2) ph in C% N% (mg P/kg) Clay% Sand% Silt% water A B C D E F G H I J Anova s.s m.s d.f v.r F.pr < <0.001 < s.e.d of means l.s.d 5% level

71 60 Inferences were made using the F probability values when the significance level is 0.05 (set up alpha value) (Table 4.17). If the F probability values (reports significance level) are less than 0.05 then the null hypothesis is rejected. This indicates that the means of the treatments were not the same or equal, hence this would imply there were treatment effects. Alternatively if the F probability values are greater than 0.05 then the null hypothesis is accepted. This would imply that the means of the treatments were the same or equal, hence there were no statistical differences on the effects of treatments. According to the results (Table 4.17), there were no statistical difference on the effects of treatment to C%, N%, and silt since their F probability values were 0.639, and 0.09 respectively. These could be attributed to several factors which include; - Application of organic matter (manure) by farmers in their farms; land uses/treatments keeps changing every season, meaning their effects could be felt on the successive seasons and also the control plots were not properly managed by farmers i.e. crop residue and herbaceous plants were left on the field to decay and decompose, hence adding organic matter to the soil. Under farmer managed conditions it has been found that the residual effect from a shortduration improved fallow may last one to two seasons, depending on the level of degradation of the soil, and the amount of nitrogen accumulated by 8 months fallow species of Crotalaria species and Tephrosia species being 199 kg ha -1 and 173 kg ha -1 respectively (Amadalo et al, 2003). Albrecht and Kandji (2003) found that Soil organic carbon (SOC) increased over the duration of the fallow phase in a few tropical soils with different tree species in the sub-humid tropics. In Kenya fallow phase of 1.5 years in ferralsol (clayey), Crotalaria grahamiana, Crotalaria paulina and Tephrosia vogelii produced Mg ha -1 yr -1.

72 61 The analysis showed that there were statistical differences on the effects of treatments to ExCa, ExK, ExMg, ExP, Clay, Sand and ph. There was high significant difference between treatments, for ExCa at F probability value of less than (P < 0.001). This clearly indicated that there were treatment effects on the availability of ExCa and from the means of treatments Mucuna pruriens + basal fertilizer provided high amount of available ExCa (6.27), followed by treatment of Tephrosia vogellii + basal fertilizer with available ExCa (5.9) while treatment of Crotalaria paulina + insufficient fertilizer provided the least amount of ExCa (3.14) even worse than the controls (4.5). The study showed that, there was significant difference between treatments, for ExK at F probability value equal to (P=0.031), this implied that, there were treatment effects on the availability of ExK. From the treatments, Mucuna pruriens + basal fertilizer provided the highest amount of ExK (2.03), followed by Tephrosia vogellii + basal fertilizer with ExK (0.85) while Crotalaria paulina + basal fertilizer and Crotalaria paulina + insufficient fertilizer with ExK (0.11) each, providing the least amount of ExK. The results also indicated that, there was significant difference between treatments for ExMg (P= 0.043), a clear indication that there were treatment effects on the availability of ExMg. Mucuna pruriens + basal fertilizer provided high amount of ExMg (1.551), followed by Tephrosia vogellii + basal fertilizer with ExMg (1.541) while Crotalaria paulina + insufficient fertilizer provided the least amount of ExMg (1.404) and the controls provided (1.485), but with small standard error of deviation of the means (0.055). There was also a significant difference between treatments for ExP at F probability value equal to (P= 0.046). A clear indication that there were treatment effects on the availability of ExP. Tephrosia vogellii + basal fertilizer provided the highest amount of

73 62 ExP (6.05), followed by Tephrosia candida + insufficient fertilizer and Mucuna pruriens + basal fertilizer with ExP (4.26) and ExP (4.18) respectively. Mucuna pruriens + insufficient fertilizer provided the least amount of ExP (0.77) which was far below the amount provided by the controls (2.56). These results, showed a trend where treatments with Mucuna pruriens have provided high amount of nutrients except for ExP. The roots of Mucuna pruriens are not deep rooted a factor that fails to enhance the availability of fixed P in the soil. Studies have showed that in small-scale farming systems in Africa, crop harvesting removes almost all of the P accumulated by cereal crops (Sanchez et al., 1997). In agroforestry systems, root systems may account for as much as 80% of the primary production. Application of plant biomass as green mulch can contribute to P availability, either directly by releasing tissue P during decomposition and mineralization (biological processes) or indirectly by acting on chemical processes that regulate P adsorption-desorption reactions. Soil organic matter contributes indirectly to raising P in soil solution by complexing certain ions such as Al and Fe that would otherwise constrain P availability. Decomposing organic matter also releases anions that can compete with P for fixation sites, thus reducing P adsorption. The more extensive root systems that trees and shrubs have compared to crops increase the exploration of larger soil volumes which results in enhanced P uptake. Recycled tree biomass is an important source of available P (Jama et al., 1997). Other studies have showed, Mucuna pruriens produce fairly large amounts of biomass, and high rates of N 2 fixation. The highest net input of N into the soil from the green manure of Mucuna pruriens a herbaceous legume adapted to a wide range of soils in the tropics, was reported as 3.95 biomass t ha -1 compared to Crotalaria paulina 0.16 biomass t ha -1 (Giller, 2001). Approximately two third of the Nitrogen captured by fallows comes from biological

74 63 fixation and the rest from the sub soil (Gathumbi, 2000). Sileshi et al., (2002) reported that some fallows are attacked by pests that cause defoliation such as alphids on Crotalaria species in Western Kenya. The same was reported by farmers (this report) that Crotalaria paulina harbors insects (caterpillars) leading to a possibility that, this could have affected leaf biomass of Crotalaria paulina causing low levels of nutrients as observed in most of the plots which had Crotalaria paulina. Observations in the field (Figure 4.7) showing two contrasting plots clearly indicated that visual symptoms are a sign of nutrient deficiency. Yellowish leaves and stunted growth of crops, seen particularly in maize, indicate an inadequate supply of nitrogen and planted and managed fallows can increase the amount of available nitrogen in the topsoil (Amadalo et al., 2003). Still plants suffering from an inadequate supply of potassium are identified by leaves that are yellowed and scorched and burned seen from their tips and along the leaf edges, while the inside remains green. Some tree and shrub species such as Tithonia diversifolia and sesbania sesban accumulate potassium in their leaf biomass. When this biomass decomposes, the potassium becomes available to crops. Using these species in improved fallow systems can reduce the potassium deficiency for the next crop (Amadalo et al., 2003).

75 64 Control plot. Plot preceded by C. Paulina. Fig. 4.7 Shows control plot, and adjacent plot preceded by Crotalaria paulina. In figure 4.7, the left side shows a section of the control plot, while on the right shows the section of the plot that was preceded by the fallow species. It is evident that, the maize plants on the control plot look yellowish and this could be associated with lack of nutrients which are important for plant growth. This was observed in Pedro Oduma s household Silula village, in the study area. Soil texture affected changes in other nutrients as a result of the treatments. In treatment G (Mucuna pruriens + Basal fertilizer) Clay % and Silt % were observed to be low and high respectively, and nutrients level were high compared to other treatments. In treatment F (Crotalaria paulina + Insufficient fertilizer), clay % was high and nutrient levels low compared to other treatments except for Nitrogen and Phosphorous. Low silt % was observed in treatment I (Tephrosia candida + Insufficient fertilizer) which had high percentage of Carbon and Phosphorous. Low sand % was observed in treatment F

76 65 (Crotalaria paulina + Insufficient fertilizer) where nutrient levels were low except for Nitrogen and Phosphorous. High sand % was observed in treatment D (Tephrosia vogellii + Basal fertilizer) where there was a trend of high nutrients level. According to these results, Nitrogen and Phosphorous were not influenced by soil texture, especially sand and clay Maize yield estimate from the treatments. With actual results as below table 4.18, shows maize yield (t ha -1 ) derived under different treatments. Table 4.18 Means of maize yield (t ha -1 ) under different treatments Treatment n (sample size) Maize grain yield (t ha -1 ) Std error of mean A- Plots with basal fertilizer applied b B- Plots applied with insufficient fertilizer ab C- Plots with T. candida + Basal fertilizer 12 5 bc D- Plots with T. vogellii + Basal fertilizer bc E- Plots with C. paulina + Basal fertilizer c F- Plots with C. paulina + Insufficient fertilizer bc G- Plots with Mucuna + Basal fertilizer bc H- Plots with Mucuna + Insufficient fertilizer abc I- Plots with T. candida + Insufficient fertilizer abc J- Control plots a a There is intersection between treatments B, H, I, J b There is intersection between treatments A, B, C, D, F, G, H, I c There is intersection between treatments C, D, E, F, G, H, I ab There is intersection between treatments A, B, C, D, F, G, H, I bc There is intersection between treatments A, B, C, D, F, G, H, I abc There is intersection in all the treatments. The results of this study showed that, all the fallowed treatments produced high maize yields compared to the fertilizer applied and the control plots. Plots with Mucuna + Basal fertilizer produced the highest at 5.5 t ha -1 of maize, followed by plots with Paulina + Basal fertilizer producing 5.4 t ha -1 of maize. The lowest yields of maize produced from the

77 66 fallowed treatments were from plots with T. candida + Insufficient fertilizer at 4.6 t ha -1 followed by plots with Mucuna + Insufficient fertilizer at 4.9 t ha -1. Other fallowed treatments such as T. vogellii + Basal fertilizer, Paulina + Insufficient fertilizer and T. candida + Basal fertilizer produced 5.2 t ha -1, 5.1 t ha -1 and 5.0 t ha -1 of maize yields respectively. Fertilizer applied treatments produced low yields compared to fallowed treatments. Plots with Basal fertilizer applied produced 4.6 t ha -1 of maize yields while plots applied with Insufficient fertilizer produced 4.2 t ha -1 of maize yields and the controls produced the least maize yields at 3.6 t ha -1 (Table 4.18). Analysis of variance (ANOVA) on maize yield (t ha -1 ) was done to determine whether there were any statistical differences between the treatments as shown in the ANOVA summary in table 4.19 (df = 9, f = 1.44, p = 0.177). Inference was made using the F probability value, when the significance level is 0.05 (set up alpha value). From the ANOVA results the F probability value (0.177) is more than This implies that the means of maize yield from the treatments were the same or equal, a clear indication that there were no differences on the effects of treatments to maize yield. This is also evidenced by the intersection between treatments (Table 4.18). Table 4.19 ANOVA summary Shows statistical differences between maize yield (t ha -1 ) under different treatments. Yield corrected to 14% t ha -1 calc. MC Source of variation DF SS MS F F pr. Treatment Error Total

78 67 Since the study was done on farmer managed plots, there was need to assess the effects of interaction of other factors i.e. striga, crop pest, and animals to maize yield and the ANOVA summaries are shown in Table Table 4.20 ANOVA summaries - Effects of interaction of other factors to maize yield (t ha -1 ) Effects of striga on maize yield (t ha -1 ) at different treatments ANOVA -for Striga, Yield versus Striga, Treatment Source DF SS MS F P Striga treat Error Total Effect of crop pest on maize yield (t ha -1 ) at different treatments ANOVA - for Crop pest, Yield versus Crop pest, Treatment Source DF SS MS F P Crop pest treat Error Total Effect of animals on maize yield (t ha -1 ) at different treatments ANOVA - for Animals, Yield versus Animals, Treatment Source DF SS MS F P Animal treat Error Total N = Number of plots affected by striga, Crop pest and Animals. Treatments N Mean Std deviation A B C D E F G I Treatments N Mean Std deviation A B C D E F G I J Treatments N Mean Std deviation A C E F G H I J There was a significant difference (F= 3.33, df = 7, P = 0.009) in the effects of striga on the yields in the treatments and more effect was noted in treatment A. There was also a significant difference (F = 2.42, df. = 8, P = 0.026) in the effects of crop pest on the yields in the treatments and more effect was noted in control (J) and treatment B. There was also

79 Grouped means of maize yield(t ha -1 ) 68 a significant difference in the effects of animals on the yields (F = 2.83, df = 7, P = 0.028) and more effect was noted in control (J) and treatment A (Table 4.20). These results (Table 4.20) have demonstrated clearly that maize yields were affected by the effects of striga, crop pest and animals, hence explaining why there were no statistical differences between the means of maize yield under the different treatments. Further analysis was done where the treatments were re-grouped to 3 (three) treatments i.e. fallowed treatment, fertilizer applied and the controls to determine whether there were any statistical difference between the treatments (Figure 4.8) Fertilizer applied Fallowed Control Fig. 4.8 Graphical presentation of grouped means of maize yield (t ha -1 ) The results (figure 4.8), showed that fallowed treatment produced the highest amount of maize yield at 5.16 t ha -1, while fertilizer applied treatment produced 4.4 t ha -1 and the controls produced 3.56 t ha -1. The ANOVA summary (Table 4.21) showed that there was significant differences between the treatments (df = 2, F = 5.376, P = 0.006). This was a clear indication that there were treatment effects on maize yield production.

80 69 Table 4.21 ANOVA summary- Grouped means of maize yield (t ha -1 ). Yield corr. to 14% t ha -1 calc.mc Source of variation d.f ss m.s F f pr. Between groups Within groups Total In related studies, the effect of intercropping Clotararia species and Mucuna pruriens with maize for soil fertility in Meru South showed that maize intercropped with Mucuna and Clotararia alone or with combination with half rate of fertilizer had significantly higher yields than maize planted in the unfertilized control. All the maize intercropped with the legumes had 80% higher yield than the control (KARI Annual Report, 1999). Improved fallows with Sesbania species or Tephrosia species have been shown to give subsequent maize grain yields of 3 4 t ha -1 without any inorganic fertilizer addition, also organic inputs of various tree legumes applied at 4 t ha -1 can supply enough nitrogen for maize grain yields of 4 t ha -1 (Palm, 1995). Studies in Zambia involving inter-cropping legume fallows (Tephrosia vogelii, Cajanus cajan and Gliricidia sepium) with maize or growing the trees in pure stands for a 2-year fallow showed that, maize yields following improved fallows averaged 3.6 t ha 1, almost as high as for continuously cropped maize with fertilizer (4.4 t ha 1 ) and much higher than maize planted without fertilizer (1.0 t ha -1 ) (Garrity et al., 2006). Other studies in a farmer-managed trial in Western Kenya have showed that, maize yield during the season following improved fallows of several species (Crotalaria grahamiana, Sesbania sesban, Tephrosia vogelli) averaged 4.1 t ha -1 but only 1.7 t ha -1 under the normal farmer practices of no inorganic fertilizer inputs or use of farmyard manure (Amadalo et al., 2003).

81 70 The results of this study have proved that, integrating legume fallows with crops has resulted in improved soil attributes which have led to improved crop production. Most of the plots that had fallow treatments showed good soil attributes e.g. exchangeable Phosphorous and Nitrogen which are some of the most limiting nutrients in soil (MVP Baseline Report, 2007) and plant growth were observed to be high in most of the fallowed treatments, especially Mucuna pruriens, Tephrosia candida and Tephrosia vogelli. These soil attributes reflected in crop performance and it has been found that, all the fallowed treatments produced high maize yields compared to non fallowed treatments, and especially plots that had Mucuna pruriens and Crotalaria paulina produced the highest amount of maize yields respectively. Again plots that were preceded by fallow species showed good plant vigour/health compared to plots where fallows were not planted. This evidence is illustrated in figure 4.7, which shows a control plot adjacent to another plot that was preceded by Crotalaria paulina.

82 71 CHAPTER FIVE CONCLUSION AND RECOMMENDATION 5.1 Conclusion This study demonstrates that soil fertility and fuelwood production were the main benefits that motivated farmers to adopt legume fallows and their benefits were achieved simultaneously. Through legume mixed intercropping farms that are small in sizes (0.74 acres) have been found to produce fuelwood that can last over six months in a year as well as enrich soil fertility through improved soil attributes that are reflected in the production of high maize yields compared to non fallowed farms. Tephrosia candida is the most highly recommended legume tree species for fuelwood production by farmers, and together with Mucuna pruriens and Tephrosia vogelli have been found to offer better soil attributes which is also reflected in high maize yields. Increasing fuelwood at the household level has enabled farmers to have less expenses on buying fuelwood at the market and the accrued savings channeled to other activities. This also implies that women and children could save considerable time, which is currently spent in search of firewood. The saved person-days could be transferred to other development activities. Availability of adequate fuelwood could also release livestock and crop residues that are currently utilized as fuel energy for use as organic fertilizers. This is essential for improving soil fertility and crop yields, as well as mitigating land degradation. The adoption of legume fallows also has direct positive impact on the environment because the communities have no pressure on forests/woodland for fuelwood collection since the commodity is derived within the households.

83 72 The economic implication of adopting the intervention is the assurance of income from sales of legume products like seeds, firewood etc, savings accrued as a result of reduced expenses from the purchases of fuelwood at market and the indirect benefits of soil fertility which is reflected in high crop production. This has led to increased income levels in the households resulting in improvement in the livelihood among the community. Therefore, it is concluded that, legume fallows are a promising technology/intervention that is viable in this densely populated region and what is needed next is greater research and development efforts to scale up the technology. 5.2 Recommendations A thorough economic analysis of the intervention is needed to provide the actual costs in crop production in terms of investment costs involved like labour, land preparation, seeds, etc and the economic returns achieved from the use of the intervention, comparing it with other land uses i.e. non fallowed and fertilizer applied agricultural fields. Introduction of other leguminous tree species apart from the already existing ones will give farmers a wider choice of options. For example Cajanus cajan a leguminous shrub that does very well in similar conditions like that of the study area, can be used as a food crop as well as improve soil fertility and this implies that food security, soil fertility are ensured and also will fulfill fuelwood. There is need for provision of credit facilities to farmers. The Millennium Farms an initiative of Millennium villages project need to be recommended for their efforts of providing farm inputs (fertilizer, crop seeds and fallow seeds) and micro finances as loans to farmers.

84 73 Promotion of agricultural productivity is among the key strategies that should be put into focus, in order to improve the rural livelihood of the local community. Raising the productivity of crops, vegetables, trees and livestock will increase or improve poor people s access to both food and income. This is translated into improved nutrition in the households, decreasing malnutrition among children and eliminating micronutrient deficiencies in the village and providing school meals with locally produced foods. Also, obstacles to school attendance will be eliminated because parents will no longer have problems in paying school fees of their children s. This study had limitations, for instance the criteria for stratification of research sample was based on available information on Millennium villages project data base. In some cases the information in the data base was not reflective of that in the field and this ended up with some treatments having fewer replicates to others. The honesty of some of the farmers were questionable in that some of the control plots were tempered with i.e. they had applied fertilizer or organic manure yet these farmers were compensated by the project. In other cases most of the farmers could not differentiate between the two Tephrosia species i.e Tephrosia candida and Tephrosia vogelli and this could also have effects on the final findings.

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93 82 APPENDICES Appendix 1: Structured questionnaire. Topic: -Legume fallows for fuel wood production and soil fertility improvement in Sauri Millennium Village. Date... Administered by... Questionnaire NO SECTION 1 General information a) Household Name of the Household head Sex..Age Household ID No... Respondent s Name..Sex.Age Sub location Village. b) Education level. Household Head. (1) Illiterate, (2) Primary, (3) Secondary, (4) Tertiary Respondent. (1) Illiterate, (2) Primary, (3) Secondary, (4) Tertiary Profession(s) - Household head... Other training. c) Farm size (acres) Plot 1 (Acres) Plot 2.(Acres) Plot 3 (Acres)

94 83 SECTION II Farming practices 1. Type of cultivation practiced- (1) Irrigation (2) Rain dependant 2. Main crops cultivated- Perennials- (1) Bananas (2) Tubers (cassava, sweet potatoes, arrow roots) (3) Sugarcane (4) Fruit trees (5) Others. Annual crops- (1) Maize (2) Beans (3) Vegetables (4) Groundnuts (5) Sorghum (6) Tomatoes (7) Onions (8) Others 3(a) Do you fertilize your farm? Plot 1- Yes/No Plot 2- Yes/No Plot 3- Yes/No.. 3(b) If yes, what do you use? Plot 1- (1) Fertilizer, (2) Manure, (3) fertilizer trees, (4) Others-specify. Plot 2- (1) Fertilizer, (2) Manure, (3) fertilizer trees, (4) Others-specify. Plot 3- (1) Fertilizer, (2) Manure, (3) fertilizer trees, (4) Others-specify. 3(c) How much fertilizer did you apply at planting/willing to apply in the long rains (08)? Plot. Fertilizer type. Amount of fertilizer used. Rates/Price. 1. (1) Diammonium Phosphate, (2) Urea..Kg...Ksh 2. (1) Diammonium phosphate, (2) Urea. Kg.Ksh 3. (1) Diammonium phosphate, (2) Urea. Kg.Ksh 3(d) Do you combine fertilizer with legume fallows? YES/ NO If yes, which legume tree species (1) Tephrosia candida (2) Tephrosia vogellii (3) Paulina (4) Mucuna (5) others

95 84 3(e) This season (long rains, 08) which legume tree spp have you combined with crops? Plot 1- (a) T. candida Plot 2- (a) T. candida Plot 3- (a) T. candida (b) T. vogellii (b) T. vogellii (b) T. vogellii (c) Paulina (c) Paulina (c) Paulina (d) Mucuna (d) Mucuna (d) Mucuna (e) Others (e) Others. (e) Others 3(f) How do you obtain them (Inputs)? (1) MVP subsidy, (2) Purchase, (3) Loan, (4) Gift, (5) others specify... 3(g) If No (Does not fertilize farm), Why? Plot 1- (a) Lack of inputs Plot 2- (a) Lack of inputs Plot 3- (a) Lack of inputs (b) others (b) others (b) others 4. In farming what problems do you face? (a) Striga weeds (b) Lack of inputs (fertilizer, seeds, water). (c) Unfavorable weather (hailstorm, drought, strong winds etc) (d) Labour constraints (f) Infertile soils (e) Crop destruction by animals (moles, rodents etc) (g) Post harvest (yield) destruction by pests (weevils) (h) Lack of access to market for post harvest (yield) (i) Others 5(a) Do you have an idea about Agro forestry? Yes/No 5(b) If NO, are there trees on your farm? Yes/No... What role do those trees play? (a) Fuel wood (b) Soil fertility (c) Fodder (d) Seeds (e) Timber (f) Others-specify

96 85 5(c) If YES, Why do you practice improved fallows? (a) Fuel wood (b) Soil fertility (c) Fodder (d) Seeds (e) Timber (f) Others-specify 6(a) How did you learn about improved fallows? (1) Worked in forestry related issues (2) Initiated through MVP/ICRAF/NGOs (3) For the love of trees (4) Others-specify. 6(b) Have you ever gone for any training or attended a course on Agro forestry? YES/NO If YES, please gives details in the table below COURSE OFFERED BY DURATION DETAILS OF CONTENT 7(a) which leguminous tree species have you planted on your farm? (1) Tephrosia candida (2) Tephrosia vogellii (3) Paulina (4) Mucuna (5) others 7(b) why did you prefer these leguminous tree species? Rank them according to their importance (1) Soil fertility (2) Fuel wood (3) Fodder (4) Seed production (5) Fast growing (6) Only accessible (7) Timber (8) Others-specify 8(a) Do you face any obstacles in legume tree planting? (1) Yes (2) No

97 86 8(b) If YES, what are they? (1) Lack of sufficient land (2) Lack of appropriate seedlings (3) Unfavorable weather (4) Land tenure (5) Lack of knowledge (6) Others-specify.. 9. Planting pattern/system (Observe);- (1) Along boundary (2) A long terraces (3) Randomly within the farm (4) Woodlot (5) Hedgerows (6) others-specify... SECTION III From the reasons/roles given for planting legume trees; (i) Do you see them as a solution to the problems you face? - Yes/No (ii) For fuel wood;- (1) Sufficient (now &future) (2) Sufficient (future doubtful) (3) Barely sufficient (4) Acute shortage (5) Others-specify (iii) Which legume tree species do you prefer for fuel wood? (1)Tephrosia candida (2) Tephrosia vogelii (3) Paulina (4) Mucuna (5) Others (iv) Why do you prefer them (leguminous tree species mentioned above)? (1) Produces large quantities of firewood (2) Dries faster (3) Produces quality fire (less smoke) (4) Easy to cut (5) Only accessible (6) Big trunks and grows tall (7) Others

98 87 (v) How much fuelwood do you produce from your farm using legume tree spp(approx.)? Plot 1.. (Bundles) (a) Species i.. (b) Species ii (c) Species iii.. (d) Species iv Plot 2 (Bundles) (a) Species i (b) Species ii (c) Species iii (d) Species iv. Plot 3 (Bundles) (a) Species i (b) Species ii. (c) Species iii (d) Species iv (vi) Other sources of fuel wood;- (1) Market, (2) Forests, (3) Own trees on farm, (4) Others-specify (vii) If source is market, how much fuel wood do you buy to meet the deficit. (Bundles) and at what price (KSh) and for how long. (Month) (viii) How much do you save by sourcing fuel wood on your Farm?...and for how long (ix) For soil fertility /food security - Is yield enough for your family? Yes/No.. (x) If NO, how do you meet the deficit? (1) Buying, (2) Borrowing, (3) Relief, (4) Others-specify.

99 88 SECTION IV: 2008 Harvest estimates field data sheet. Identification Field Staff Name Date Field Number/ Plot Number Field Size - area planted (acres). Quadrant Number Quadrant 1 Quadrant 2 Quadrant 3 Quadrant Size Crop production information- Maize. Q1. Maize Variety.. Q2. Planting Density information. Space between rows/lines. Quadrant 1. Quadrant Quadrant Space between planting holes.... Q3. Date Planted Q4. Did you use Basal fertilizer? 1. Yes..2. No Q5. If yes, how did you obtain the fertilizer? (use the codes below).. 1. MVP Subsidy 2. Purchase 3. Loan 4. Gift 5.Other (specify).. Q6. What was the total amount of Basal fertilizer used in kgs?... Q7. Date of Basal fertilizer application Q8. If no, why did you not apply basal fertilizer?... Q9. Did you use organic manure on the crop area? 1. Yes 2. No

100 89 Q10. If yes, what type(s) and Quantities were used? Type(s) Quantity. Q11. Date of manure application Q12. If no, why did you not apply organic manure?... Q13. Did you apply Top dressing fertilizer? 1. Yes 2. No Q14. If yes, how did you obtain the fertilizer? (use the codes below).. 1. MVP Subsidy 2. Purchase 3. Loan 4. Gift 5.Other (specify) Q15. What was the total amount of Top dressing fertilizer used in kgs?... Q16. Date of Topdressing fertilizer application.. Q17. If no, why did you not apply Topdressing fertilizer?... Q18. Was the crop area preceded by Improved fallow? 1. Yes 2. No.. Q19. If yes in Q18. above, Which species were used?... (list all using codes below). Specify if Other 1. Mucuna, 2. Paulina, 3. Tephrosia candida, 4. Ochlereuca, 5.Grahamiana 6. Sesbania, 7. Other(specify) Q20. What area of land was covered by the fallow(s) Q21. Number of Plants. Number of cobs. Quadrant Quadrant Quadrant Q22. Total fresh weight of cobs sampled in the quadrant (kgs). Quadrant 1. Quadrant 2 Quadrant 3.

101 90 Q23. Cobs dry weight 1. Cobs dry weight 2. Cobs dry weight 3. Quadrant Quadrant Quadrant Q24. Which problems did you experience with your crop? Pests. 1. Yes 2. No Striga Weeds. 1. Yes 2. No Other weeds. 1. Yes 2. No.. Animals. 1. Yes 2. No.. Other (Specify) Q25. Crop Stand/Yield quality 1. Poor 2. Average. 3. Excellent Q26. Date of harvest Q27. Compare Harvest to Worse. 2. Average 3. Better Q28. Farmer Yield Estimate

102 91 Appendix 2: Climatic data for rainfall and temperature for the study area. i) Monthly means rain fall (mm) in Sauri from Yala weather station, Month/ Year Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Dec. Total Mean Mean Note: 1989 and 2005 Rainfall data, not available.

103 92 ii) Monthly temperatures (0 0 c) in Sauri Millennium village, Year/Month Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec 1998 Max Min Mean Max Min N/A N/A Mean Max Min Mean Max Min Mean Max Min Mean Max 29.9 N/A N/A N/A N/A Min Mean Max N/A N/A N/A N/A N/A Min Mean Max Min Mean Max Min Mean Max Min Mean Source: Kisumu Meteorological station, Kisumu Airport Latitude: 00 06S, Longitude: 34 45E, Height 3769ft or 1149M A.M.S.L. Note: N/A, Means no records were recorded, the apparatus was not in good condition.

104 93 Appendix 3: Soil Map for Uniform Productivity Area (UPA) for Western Kenya (May, 1987). Note: legends related to soils shown below. The highlighted region includes Siaya district. More information, (Source soil information data base). Legends: Soil types th Humic Andosols. ne Eutric Nitisols bn Nito-chronic cambisols. be Eutric cambisols bh Humic cambisols. tm Mollic Andosols i - Lithosols re Eutric Regosols rd Drystic Regosols u - Rankers nv Verto-eutric Nitisols vp Pellic Vertisols vc Chromic Vertisols ir Ironstone soils v - Vertisols ws Solodic planosols fr Rhodic ferralsols bt Ando-eutric cambisols nt Ando-humic Nitisols fc Complex of Ferralsols lc Chromic Luvisols qf Ferralic Arenosols kh Haplic Kastanozems ch Haplic Chernozems lo Orthic Luvisols bk Calcic Cambisols xh Haplic Xerosols/yermosol wv-verto-eutric planosols nm Mollic Nitisols li Ferralo-chromic Luvisols bd Drystic Cambisols nd Drystic Nitisols fo Orthic Ferralsols ao Orthic Acrisols ln Nito-chromic Luvisols we Eutric Planosols if Ferric Luvisols lv Vertic Luvisols sl Luvo-orthic solonetz rt Ando-calcaric Regosols tv Vitric Andosols bg Gleyic Cambisols jc-calcaric f l u v i s o l s g m - M o l l i c G l e y s o l s z S o l o n c h a k s hv - Verto-luvic phaeozems ho- Ortho-Luvic Phaeozems hr-chromo-luvic Phaeozems ht Ando-haplic phaeozems