A Review Farm Forestry Evolution for the Last 100 Years in Kenya: A Look at Some Key Phases and Driving Factors

The study reviews the evolution of tree growing in Kenya from pre-colonial through colonial to the present day in order to understand some factors that have influenced such developments. The study is based on desktop literatures reviews of various studies done in the country over the years and the authors’ experiences. The study indicates that forest resources management during pre-colonial period were based on individual communities’traditional structures that ensured that its members had abundant supplies of land and resources to support their socioeconomic activities. Forestlands were viewed as reserves for future agricultural expansion depending on community population growth and settlement patterns. In 1895 the country was declared British Protectorate that heralded the entry of colonial settlers that drastically changed land ownership through displacement and concentration of indigenous populations. Improved health services led to drastic population growths that further shrunk available productive land and forest resources to levels that could not adequately accommodate traditional land uses. The resultant was seriousland degradation in Africa reserves that prompted the Colonial Government to initiate agricultural and land use transformations that included afforestation in highly populated for environmental conservation, boundary marking and supply of tree products. Another parallel development was forest reservation and expansion of public plantation by Forest Department that involved planting of fast growing exotic species such as Eucalyptus, Pines and Cypress among others that diffused to neighbouring farms, missionary centres, schools and emerging elite Africans for amenity and social status. The emergence of Acacia mearnsii as a cash crop for African farmers in Central and western Kenya in 1930s was another development that enhanced adoption of tree growing on farms in the country. After independence in 1963 more policies and strategies to promote tree growing on former settler farms and African reserves for environmental conservation and subsistence needs implemented.  The last chapter of the farm forestry evolution was the commercialization of farm forestry operations due increased demand for various forest products beyond the capacity of public forests. The key markets niches mostly for firewood in tea processing, transmission poles manufacturing, charcoal and sawnwood for rural and urban markets were lucrative enough to motivate millions of smallholder farmers to expand their farm forestry investments. The markets based incentives to meet the growing demand for various products has transformed farm forestry in Kenya into multibillion sector enterprises that competes with public and private plantations products in local markets. The lessons learnt in Kenya case is the multiple factors that have shaped farm forestry development over the last 100 years and the critical role played by market related factors that enabled smallholder tree growers to enter into lucrative short rotation wood product markets. Keywords: Farm forestry evolution, phases, driving factor

Farm Forestry Development in Kenya: A Comparative Analysis of Household Economic Land Use Decisions in UasinGishu and Vihiga Counties

Tree growing on farms in Kenya is an important land use that has evolved over the last 100 years into multi-billion subsistence and commercial oriented enterprises.  The smallholder farms in medium and high potential areas are facing serious shortage of quality farming land that has created severe competition among various competing land uses mostly agriculture and farm forestry. Therefore the economic competitiveness of farm forestry as a land use is assumed to be proportional to the size of household land allocated to its use. Understanding household decisions making in allocation of land to competing land uses has increasingly become an important subject to resource economists and policy makers. Therefore a study was undertaken in 2011/2012 to evaluate the socioeconomic decisions making in relations to farm forestry in two counties in high potential agricultural areas of western Kenya. The two counties were selected for the study differed settlement in history, agricultural land use, farm forestry development and demographic characteristics. Uasin Gishu represents the recently settled former European settler farms and Vihiga to represents the former African Reserves. The study was based on range of models such as spatial land use concepts, integrated land use decision making and land use efficiency criterion to underpin the household production function.  260 households were surveyed using systematic sampling methods with questionnaires being administered randomly to households in locations within selected divisions.  The main data extracted from the standard questionnaire were household structure, ratio of land used for cropping, grazing and farm forestry, product output, prices, market information, marketing procedures and distribution of trees by species.  Data was analysed by use of OLS regression models to generate key farm forestry decision making parameters.  The results show that household land size had strong influence on farm forestry decisions irrespective of household’s production strategy.  Farm forestry incomes proved to be an importance driving force in decisions to plant trees thus supporting the importance of economic objectives on household land use decisions. A farm forestry income was stronger in areas where markets and marketing infrastructure were better developed.  The density of planted trees increased with decreasing land size attested the strength of subsistence and commercial dimension of trees within an agricultural landscape. The study points out some policy lessons for development of farm forestry in developing countries like Kenya that include putting in place policies and regulations that attract, expand and sustain farm forestry product demand and infrastructure that improve marketing efficiency and thus better income to farmers from sale of trees. Keywords: Farm forestry, Land use, Household decision makin

The Influence of Land Quality on Allocation of Land for Farm Forest in Kenya: The Case of Vihiga County

Kenya has long history of promoting tree growing on farms for various purposes ranging from  laying claim to property and boundary marking in 1940s to response to socioeconomic drivers such commercial interests through vibrant market for tree products. The Rural Afforestation and Extension Services Division (RAES) started in 1971 was aimed at accelerating tree growing on farms through training of farmers, establishment of tree nurseries countrywide and deployment of extension staff to offer technical services to rural farmers. Farms within agricultural landscapes are not uniform but differ in various forms such as slope, drainage, soil texture, fertility, water holding capacity, stone/rock outcrops and other attributes that impose land quality variation hence influencing their potential uses. The study was therefore undertaken to evaluate the influence of land quality on farm forest land use allocation through use of land quality concept developed by von Thunnen in 1826.  The study was done in one of the highly populated counties in western Kenya, the Vihiga County where farm forests occupies 30% of household land. Samples of 112 households were surveyed in 4 sub-counties. The study mapped quality aspects within households land profile into four categories  gentle,  steep, steep and rocky and flood plain and swampy and intensity of trees in respective category. OLS regression analysis was used to determine the influence of land quality on farm forest land allocations. The results indicate that farm forest allocations was not significantly influenced by poor land quality aspects across the study household lands. This is because the land sizes were very small and farm forests were adopted across the household land profile irrespective of quality aspects. However, households indicated that poor quality lands were preferable for farm forest largely for they were not favourable for crop production. The study observes that farm forests were highly influenced  by high population density and small land sizes that has masked the importance land quality in land use allocation decisions. Keywords: farm forest, land quality, land use allocatio

Socioeconomic Factors Influencing Farm Forestry Investment Decisions in Kenya: The Case of Uasin Gishu and Vihiga Counties

In Kenya, traditional farm landscapes are an overlay agricultural crops livestock and various farm forest formations. Tree growing in agricultural landscapes in the country has a long history. However the intensity has developed over the last 100 years across the country at varying pace and configurations depending on various factors largely driven by demand and supply conditions. Therefore the study was premised on the fact that household land is allocated to tree growing based on the household subsistence needs and extra to satisfy market demands. The study to evaluate the socioeconomic factors that influenced adoption farm forestry by households in two counties in high potential agricultural areas of western Kenya was undertaken in 2015. The two counties were selected for the study differed in various attributes such as settlement history, agricultural land use, farm forestry development and demographic characteristics. Uasin Gishu represents the recently settled former European settler farms and Vihiga represents the former African Reserves settled hundreds of years ago. The study used integrated land use decision making concept to underpin the household production function.  The survey involved 260 households that were systematically sampled with questionnaires being administered randomly to households in locations within selected sub counties. The main data extracted from the questionnaire were household land sizes, age of household head, educational levels of household head, cultural factors, farm forest incomes, distance to forest product markets, farm employees, settlement years, household sizes and crop incomes.  Data was analysed by use of OLS regression models to generate key farm forestry decision making variables.  The results show that the most stable and significant explanatory variables were land size, farm forestry incomes and off-farm incomes. This shows that they were the most important variables in farm forestry land use decisions in western Kenya.  The study also revealed that the two counties were significantly different in their farm forestry activities with Vihiga being more intensive as compared to Uasin Gishu.  Farm forestry incomes proved to be an importance driving force in scaling up tree growing on individual farms hence indicating the importance of economic objectives on household land use decision making. Farm forest income was stronger in areas where markets and marketing infrastructure were better developed. The study provides some factors that policy makers need to consider in order to positively influence farm forest development in Kenya and other developing countries. Keywords: Farm forestry, Land use, farm incomes, household decision makin

Value of Pollination Services in Farmlands Adjacent to Mau, Cherangany and Mt. Elgon Forests

Pollination plays a vital role in crop yield and quality and by extension food security. Approximately 75% of global food crops depend on pollination services. Forests are the primary habitats of natural pollinators and communities farming near them benefit from this valuable supporting service. This study estimated the economic value of crop pollination dependency on natural forests within Mau, Cherangany and Mount Elgon Water Towers using the Pollination Value Array Tool developed by Food and Agricultural Organization (FAO). To determine the value of crop pollination on farmlands adjacent to the forests, a buffer zone of 5 km between the forest and the farms was developed using GIS. Using the developed maps, a list of pollination dependent crops grown within these zones was identified from the FAO tool. Crop production data were obtained from Ministry of Agriculture in all the Counties neighboring the three ecosystems. The crop data gathered include the quantity of crop harvested per season and the producer price in Ksh per metric ton. This data was entered into the Pollination value array tool which computes; the Total Economic Value of crop (TVC) and the Economic Value of Insect Pollinators (EVIP) using the Pollination Dependency Ratios (PDR) of the crops. The contributions of natural /insect pollinators to crop production in the Mau, Cherangany and Mt. Elgon were estimated at Ksh 314 million (12.7%), 67 million (9.7%) and 549 million (17.4%) respectively. The total economic value attributed to insect pollination in the three ecosystems amounted to Ksh 931million in 2015. Keywords: Pollination Services, Crop Production, Pollination Dependence Ratio, Economic Value, Food security DOI: 10.7176/JNSR/9-10-08 Publication date:May 31st 201

Larvicidal effect of Mundulea sericea (Leguminosaea) plant extract against Aedes aegypti (L.) (Diptera: Culicidae)

IntroductionThe medical importance of mosquitoes as vectors forthe transmission of serious diseases that causemorbidity, mortality, economic loss, and socialdisruption such as malaria, lymphatic filariasis, andviral diseases is well recorded (Becker et al, 2003).Aedes aegypti, the main carrier for viruses that causedengue and dengue hemorrhagic and yellow fevers, isfound majorly in the tropics and subtropics. There is noeffective vaccine against dengue, and thus the only wayof significantly lowering the incidence of this disease isthrough mosquito control (Malavige et al, 2004).Chemical measures were first tried, but they failed sincetheir overuse led to disruption of natural biologicalcontrol systems and outbreak of new insect species. Inaddition, use of insecticides led to the development ofmosquito resistance, environmental pollution, andundesirable effect on non-target organisms (Brown,1986). In a bid to resolve these problems, interest ininsecticides of natural origin, specifically plant-derivedproducts has recently received close attention.Several studies have emphasized the importance ofresearch and development of herbal substances forcontrolling mosquitoes (Shaala et al, 2005). Theirresults may vary, but natural plant products may be apossible alternative to synthetic substances, as they areeffective and compatible with human and animal lifeand the environment (Chaithong et al, 2006).The genus Mundulea consists of about 15 species,widespread throughout Africa, Madagascar, Mauritius,India, Sri Lanka and Papua New Guinea. Only a singlespecies, Mundulea sericea, is found in Southern Africa.This species occurs in South Africa, Botswana, Namibiaand Angola, north to tropical Africa, and east toMadagascar, India, Sri Lanka and Papua New Guinea(Watt and Breyer-Brandwick, 1962).Mundulea sericea is one of the commonest fish poisonswhere both bark and seeds are used (Neuwinger, 2004).In addition, the Chinese used M. sericea to controltobacco budworm Heliothis virescens (Lepidopteriae:Noctuidae) (Yoshida and Toscano, 1994).The toxic principal of the plant is rotenone, anisoflavonoid (Vedcourt and Trump, 1969). Therotenoids deguelin and tephrosin are the potent activeprinciples which have been isolated from extracts of M.sericea (Luyengi et al, 1994). Deguelin is a natural plantderivedrotenoid, most commonly used as an insecticidein Africa and South America (Udeani et al, 1997).Rotenoids from the bark of M. sericea have beencommercially used as insecticide. These chemicalcompounds in the bark, leaves and seed are the activecompounds responsible for the fish poison. It isreported that the strength varies geographically (Wattand Breyer-Brandwick, 1962).The current study involved extraction and evaluation ofroot bark and seedpod of M. sericea for larvicidalactivities on Aedes aegypt

HIV Prevention in a Time of COVID-19: A Report from the HIVR4P // Virtual Conference 2021.

The HIV Research for Prevention (HIVR4P) conference catalyzes knowledge sharing on biomedical HIV prevention interventions such as HIV vaccines, antibody infusions, pre-exposure prophylaxis, and microbicides in totality-from the molecular details and delivery formulations to the behavioral, social, and structural underpinnings. HIVR4P // Virtual was held over the course of 2 weeks on January 27-28 and February 3-4, 2021 as the coronavirus disease 2019 (COVID-19) pandemic continued to inflict unprecedented harm globally. The HIVR4P community came together with 1,802 researchers, care providers, policymakers, implementers, and advocates from 92 countries whose expertise spanned the breadth of the HIV prevention pipeline from preclinical to implementation. The program included 113 oral and 266 poster presentations. This article presents a brief summary of the conference highlights. Complete abstracts, webcasts, and daily rapporteur summaries may be found on the conference website (https://www.hivr4p.org/)

State of the world’s plants and fungi 2020

Kew’s State of the World’s Plants and Fungi project provides assessments of our current knowledge of the diversity of plants and fungi on Earth, the global threats that they face, and the policies to safeguard them. Produced in conjunction with an international scientific symposium, Kew’s State of the World’s Plants and Fungi sets an important international standard from which we can annually track trends in the global status of plant and fungal diversity

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century