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Front Section-Pgs I-1.Indd In Chapter 8 LIST OF MAPS AUTHORS AND CONTRIBUTORS Map 8.1 Upper Tana: Landforms and Rivers Norbert Henninger (WRI) CONTENTS Map 8.2 Upper Tana: Population Density, 1999 Dan Tunstall (WRI) Map 8.3 Upper Tana: Poverty Rate, 1999 Karen Holmes (consultant) u Landscapes, People, and Poverty .... 109 Map 8.4 Upper Tana: Poverty Density, 1999 Greg Mock (consultant) Landforms 110 Map 8.5 Upper Tana: Household Reliance on Ecosystems for Drinking Water Janet Nackoney (WRI) Map 8.6 Upper Tana: High Share of Piped Drinking Water and Poverty Rate Florence Landsberg (WRI) Population, Road Network, and Map 8.7 Upper Tana: Irrigation Efforts and Other Water Uses Mohammed Said (ILRI) Administrative Units 111 Map 8.8 Upper Tana: Small-Scale Irrigation Efforts and Poverty Rate Hyacinth Billings (WRI) Spatial Patterns of Poverty 112 Map 8.9 Upper Tana: Small-Scale Irrigation Efforts and High Share of Piped Stephen Adam (WRI) Drinking Water Carolina de Rosas (WRI) u Water-Related Ecosystem Services .. 113 Map 8.10 Upper Tana: Food Crops as Percentage of All Cropland Indicators Examined 113 Map 8.11 Upper Tana: High Share of Food Crops and Poverty Rate Map 8.12 Upper Tana: Milk Production Drinking Water Use and Poverty 114 Map 8.13 Upper Tana: High Milk Production and Poverty Rate Irrigation Efforts, Other Water Uses, Map 8.14 Upper Tana: High Share of Food Crops and High Milk Production and Poverty 116 Map 8.15 Upper Tana: Average Number of Crops Grown in Cropland Map 8.16 Upper Tana: High Average Number of Crops Grown in Cropland and High Share of Piped Drinking Water and Poverty Rate Small-Scale Irrigation Efforts 118 Map 8.17 Upper Tana: Share of Woodlots in Cropland Map 8.18 Upper Tana: High Share of Woodlots in Cropland and Poverty Rate u Food-Related Ecosystem Services .. 119 Map 8.19 Upper Tana: High Average Number of Crops Grown and High Share of Indicators Examined 119 Woodlots in Cropland Food Cropping and Poverty 120 Map 8.20 Upper Tana: Summary of Poverty Rates in Areas Outlined by Selected Ecosystem Indicators Milk Production and Poverty 122 High Food Cropping and High Milk Output 124 Biodiversity- and Wood-Related Ecosystem Services ............................ 125 WHAT THIS CHAPTER SHOWS Indicators Examined 125 This chapter examines maps of various ecosystem services and poverty patterns in a single region—the upper watersheds of the Tana River—to demonstrate how Number of Agricultural Crops and Poverty 126 such maps can help to highlight the relationships among people, ecosystems, and poverty. After providing a brief overview of landforms, population distribution, Woodlots in Cropland and Poverty 128 and poverty patterns in the upper Tana, the spatial relationships between selected ecosystem indicators and poverty in three topic areas: water-related ecosystem High Number of Agricultural Crops and services; food-related ecosystem services; and biodiversity- and wood-related ecosystem services are discussed. The chapter concludes with a detailed summary that High Share of Woodlots in Cropland 130 highlights poverty for six selected ecosystem indicators and suggests possible future analyses based on the patterns observed. p t 108 u NATURE’S BENEFITS IN KENYA: AN ATLAS OF ECOSYSTEMS AND HUMAN WELL-BEING q 8 The Upper Tana: Patterns of Ecosystem Services and Poverty This chapter focuses on a single region of Kenya also offer important insights on poverty-environ- managing ecosystems more wisely and identifying and examines a range of ecosystem services used in ment relationships: It could help to identify areas opportunities for poverty reduction. It will be the this region. Unlike Chapters 3–7, which paint broad where natural resource investments could boost task of Kenya’s technical institutions responsible national pictures of a single ecosystem service such environmental income for communities or reduce for data collection and analytical products to take as water or food, here we integrate data on several vulnerability of the poorest households from further the examples in this chapter to the next level. It will services to give a more holistic picture of supply resource degradation. Or it could help to locate also require decision-makers who are motivated and demand in a particular area. The maps show better-off communities that can afford to pay for to ask questions and to understand the power (and the “key supply areas” of such services as food from land use practices to ensure a continued supply of limitations) of the data and the associated tools. We crops and livestock; drinking and irrigation water ecosystem services such as sufficient water for the hope that these examples will inspire an improved use; and levels of crop diversity and woodlots in dry season or migration corridors for wildlife. multisectoral analysis of ecosystem services and of agroecosystems. The following three sections—water-related poverty-environment relationships in the upper This kind of analysis is important because eco- ecosystem services, food-related ecosystem services, Tana, and will lead to more detailed cross-cutting system services are typically looked at on a sectoral and biodiversity- and wood-related ecosystem studies in other geographic regions of the country. basis (e.g., water, forests, agriculture), which misses services—provide examples of how to examine the interrelationships among them. Overlapping these relationships between people, ecosystems, and demand for various ecosystem services may pro- poverty. They break new ground by showing for the LANDSCAPES, PEOPLE, AND POVERTY duce conflicts over resource use, requiring tradeoffs first time in one publication where key supply areas of Several distinctive characteristics make the upper among different uses and often between different ecosystem services coincide and where both poorer and Tana River well suited for in-depth analysis: users. Alternatively, there may be opportunities for better-off communities are located in relation to these u Within Kenya, the upper Tana, which covers a synergies among different uses of ecosystem services. supply areas. significant proportion of Central and Eastern Mapping and analyzing spatial patterns of the supply We acknowledge that examining poverty- Province, represents an economically impor- and demand for different ecosystem services in the ecosystem relationships by overlaying two spatial tant region for agricultural production and ex- same geographic area can help communities address indicators can only provide limited insights: It can periences high demand for ecosystem services. management decisions in a more integrated manner. show where in the upper Tana a proposed hypoth- The upper Tana region includes the Aberdare Using spatial analysis to examine a range of esis about the spatial relationship between selected Range and Mount Kenya—two of Kenya’s five ecosystem services in a given area also allows us to indicators is true and where it is not. In most cases, major mountain ranges, and the headwaters compare these with spatial patterns of poverty in the readers will demand additional information requir- for many of Kenya’s largest rivers. These rivers area. It can provide information on how much local ing new indicators or more location-specific data. are an indispensable source of water for crops, communities rely on key ecosystem services, such The simple map overlays portrayed here are not livestock, wildlife, and human use, not only as food, water, forest products, and wildlife. It can sophisticated enough to detect all necessary cor- within the mountain vicinity, but also farther relations or come up with conclusive answers about downstream across a large expanse of arid and causal links. They represent only a first step in semi-arid lands. In fact, the Tana River is the unraveling poverty-ecosystem relationships. only major river running year-round through In effect, we hope to use this chapter to engage Eastern Province. the reader in a dialogue that spurs new questions and further investigations. We see such a dialogue and analytical process as a necessary step toward p THE UPPER TANA: PATTERNS OF ECOSYSTEM SERVICES AND POVERTY t 109 u q u The upper Tana area is home to 3.1 million Map 8.1 Upper Tana: Landforms and Rivers people (about 11.4 percent of Kenya’s total population), whose livelihoods are closely intertwined with multiple ecosystem services. Sources: Administrative boundaries (CBS 2003), permanent rivers (NIMA 1997), 250-meter Digital Elevation Model Most of the area is covered by smallholder (SoK, JICA, and ILRI 1996), subdrainage areas defining upper agriculture. It includes important areas of cash Tana (MoWD and JICA 1992), and landforms (FAO 2000). or export crops such as tea, coffee, vegetables, and rice. The government has set aside a sig- LANDFORMS nificant portion of the land for biodiversity and Mountains watershed protection, including Mount Kenya Footslopes, hills, and mountain footridges National Reserve, Aberdare National Park, Plains Aberdare Forest Reserve, Meru National Park, OTHER FEATURES and Mwea Reserve. Upper Tana boundary u This area also contains a broad cross-section of District boundaries very poor and less poor communities. Within WATER BODIES AND RIVERS the upper Tana are communities with some Permanent rivers of Kenya’s lowest poverty rates; however, the Water bodies area also includes several very poor communi- ties, most of them in the drier plains below the foothills downstream of the Aberdare Range and Mount Kenya. Map 8.2 Upper Tana : Population Density, 1999 The yellow line in Map 8.1 and subsequent maps outlines the upper Tana area. It represents the com- Sources: Administrative boundaries (CBS 2003), permanent mon watershed boundaries of all the major perma- rivers (NIMA 1997), 250-meter Digital Elevation Model nent streams and rivers originating in the Aberdare (SoK, JICA, and ILRI 1996), subdrainage areas defining upper Tana (MoWD and JICA 1992), and 1999 population density Range and Mount Kenya that flow into the Tana (CBS 1999). River. POPULATION DENSITY Landforms (number of people per sq.
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