Environment and Natural Resources Global Practice Policy Note 96150 Tanzania’s Tourism Futures Harnessing Natural Assets SEPTEMBER 2015 WORLD BANK GROUP REPORT NUMBER 96150-TZ EnviroNment and Natural Resources Global Practice Policy Note Tanzania’s Tourism Futures Harnessing Natural Assets © 2015 World Bank Group 1818 H Street NW Washington, DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org E-mail: feedback@worldbank.org All rights reserved This volume is a product of the staff of the World Bank Group. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of World Bank Group or the governments they represent. The World Bank Group does not guarantee the accuracy of the data included in this work. 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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, World Bank Group, 1818 H Street NW, Washington, DC 20433, USA, fax: 202-522-2422, e-mail: pubrights@worldbank.org. Cover Photo: Magda Lovei / World Bank. CONTENTS Acknowledgments v Abbreviations and Acronyms vii Executive Summary ix Chapter One: Introduction 1 Chapter Two: Anatomy of the Tourism Sector 3 Chapter Three: Challenges and Opportunities 7 A. Linkages between Tourism and the Rural Economies Need to Be Strengthened 7 B. Economic Consequences of Concentrated Tourism 9 C. Infrastructure Development 11 Chapter Four: Tourism Futures 13 A. Tourism in the Serengeti Ecosystem 14 B. Diversifying the Tourism Product—The Case of Ruaha National Park 18 Chapter Five: Way Forward 27 A. Maintain and Strengthen the HVLD Segment 28 B. Diversify the Product 30 References33 Appendix A: Trend of Visitors Arrivals at NPs for FY2006/07–2011/12 37 Appendix B: Serengeti Bioeconomic Model 39 Appendix C: Ruaha Model 47 BOXES Box 4.1: The Hidden Ecology of the Serengeti 14 Box 4.2: A Description of the Analytical Modeling Framework Used 15 Box 4.3: Water Scarcity in the Ruaha Landscape 22 Box 5.1: The Wildlife Management Areas and Other Benefit Sharing in Tanzania 28 Box 5.2: Namibia Communal Conservancies and Tourism 29 FIGURES Figure 1.1: Map of Tanzania 2 Figure 1.2: Export Revenues (in $million) from Tourism and Travel versus Minerals and Energy 2 Figure 2.1: Foreign Visitors to Tanzania (2000–12) 4 Figure 2.2: Tourist Numbers (thousands) and Receipts (US$, millions) 5 Figure 2.3: Total Contribution of Travel and Tourism to GDP  5 Figure 3.1: Population and Protected Areas 8 Tanzania’s Tourism Futures iii Figure 3.2: Poverty and Protected Areas 8 Figure 3.3:  Soil Cation Exchange Capacity 12 Figure 4.1: Map Showing Formal Irrigation Schemes in Usangu Wetland 21 TABLES Table 2.1: Key Travel and Tourism Performance Indicators, 2013 4 Table 3.1: Average Tourist Expenditure Categories 9 Table 3.2: Consequence of US$1 Spent in the Tourism Sector 9 Table 4.1: Effects of Policy Changes 16 Table 4.2: Boosting Tourist Numbers 17 Table 4.3: CGE Simulations (in US$, millions) 18 Table 4.4: A 10 Percent Increase in Tourism Values  19 Table 4.5: Comparing Ruaha to the Serengeti 20 Table 4.6: Payoffs from Irrigation versus Hydropower 23 Table 4.7: Approximate Accommodation and Travel Cost and Transportation Time 23 Table 4.8: Approximate Distances by Road  24 Table 4.9: Average Aviation Prices (one way, US$) 24 iv Tanzania’s Tourism Futures ACKNOWLEDGMENTS This brief report was led by Richard Damania with a core team comprising Ann Jeannette Glauber, Pasquale Scandizzo, Tobias von Platen, Alvaro Federico Barra, and Dinesh Aryal from the World Bank Environment and Natural Resources Global Practice and Mahjabeen Haji from the Macroeconomics and Fiscal Management Global Practice. The report was produced under the strategic guidance of Philippe Dongier, Country Director for Tanzania, Uganda, and Burundi and Magda Lovei, Practice Manager for the Environment and Natural Resources Global Practice. This work was conducted in close consultation with the Ministry of Natural Resources and Tourism (MNRT); Tanzania National Parks Authority (TANAPA); Vice Presi- dent’s Office—Division of Environment (VPO—DOE); the President’s Office Plan- ning Commission; the Tanzania Confederation of Tourism; Hotel Association of Tanzania (HAT); and the Development Partners Group on Environment (DPG—E). The report was strengthened by the excellent comments and suggestions of the peer reviewers Hannah Messerli, Giovanni Ruta, Urvashi Narayan, and Kirk Hamilton. Comments of Michael Toman on the analytical model are also gratefully acknowl- edged. Excellent inputs and suggestions were provided by Dennis Rentsch of the Frank- Development furt Zoological Society, Robert Layng of U.S. Agency for International ­ (USAID), Charles Dobie of Selous Safari Company and Jeroen Harderwijk of Asilia Africa, and Nicola Colangelo of Coastal Tours. Tanzania’s Tourism Futures v ABBREVIATIONS AND ACRONYMS CBNRM Community-based natural resource MNRT Ministry of Natural Resources and Tourism management NP National park CBV Community Business Ventures PES Payment for Environmental Services CEC Cation Exchange Capacity RNP Ruaha National Park CGE Computable General Equilibrium SAM Social Accounting Matrix GDP Gross domestic product SNP Serengeti National Park GTAP Global Trade Analysis Program TANAPA Tanzanian National Parks Authority GoT Government of Tanzania USAID U.S. Agency for International Development HAT Hotel Association of Tanzania WMA Wildlife management areas HVLD High-value low-density WTO World Trade Organization MET Ministry of Environment and Tourism WTTC World Travel and Tourism Council Tanzania’s Tourism Futures vii EXECUTIVE SUMMARY Tanzania is endowed with a rich storehouse of nature-based tourist attractions. Tourism is focused primarily around its renowned attractions in the “Northern Circuit”1—the great plains of the Serengeti, the wildlife spectacle of the Ngorongoro Crater, Mount Kilimanjaro the highest mountain in Africa, as well as the island of Zanzibar with its lush tropical beaches. The tourism industry has emerged as a robust source of growth and an economic stabilizer in times of crisis. In just over a decade, annual tourist numbers have soared from about 500,000 in 2000 to over 1 million visitors in 2012. The sector generates the bulk of export revenues for the country, typically surpassing minerals and gold, is a reliable source of revenue to the government, and provides well-remunerated direct employment to over 400,000 people. Official statistics from Tanzania’s recently updated gross domestic product (GDP) series2 suggest that in 2013 tourism accounted for about 9.9 percent of GDP (equivalent to an amount of US$4 billion in direct and indirect contributions).3 Economic simulations reported in this study indicate that the sector has significant ­ cross-sectoral spillover effects and linkages that dominate those of other traditional sectors of the economy. A decline in tourism revenue would have an impact on the exchange rate and consequences that reverberate throughout the economy. Apart from these obvious economic benefits, tourism can stimulate broader benefits to the economy—upgrades to infrastructure, conservation of natural habitats, and gender equity. 1 Including the Serengeti ecosystem (comprising Serengeti National Park [SNP] and Ngorongoro Conservation Area) as well as Tarangire, Arusha, Lake Manyara, and Mount Kilimanjaro National Parks. 2 The new series for the period between 2005 and 2013, using 2007 as a base year, was produced by the National Bureau of Statistics, with technical assistance from Statistics Denmark and with the support of other development partners. 3 Other linkages include wider effects from investment, the supply chain, and induced income impacts. (Source: World Travel & Tourism Council, Economic Impact 2014). Tanzania’s Tourism Futures ix Tanzania operates within a globally competitive »» Finally, HVLD tourism attracts people who care tourism industry, including with competitors for more about experience (for example, wilderness) and less wildlife tourism. Yet, Tanzania has reached an envi- about price (that is, more inelastic demand). This able position as a high-value low-density (HVLD) tourist group might include the so-called high-net-worth destination by restricting supply and targeting the high- individuals and also includes interest groups (hob- end segment of the market that is largely unaffected by byists, birdwatchers, and climbers). economic fluctuations. The industry attracts some of the world’s most illustrious tour operators, many of whom Hence, not every destination in Tanzania will fit into the market only Tanzania. The HVLD approach has served HVLD category and there is a need for a differentiated strat- the country remarkably well: egy that plays to the economic strengths of each attraction »» It provides a buoyant flow of revenues. In contrast, and asset. Kenya attracts twice the number of visitors as Tan- zania but raises half as much revenue. Attracting a CHALLENGES AND OPTIONS large number of tourists implies that Kenya draws Tanzania has neither fully leveraged its immense visitors from the more price-competitive (elastic) endowment of potential tourist attractions nor segment of the market. the opportunities for poverty reduction that the »» High-value visitors are typically unaffected by tourism sector offers. Despite an abundance of assets, turbulence in the global economy. During the tourism remains heavily concentrated along the Northern 2008–09 recession, tourist numbers plummeted Circuit, and there is a need to diversify the tourism prod- across the globe, yet tourist numbers in Tanzania uct without diminishing its revenue potential. There are were largely unaffected (Lunogelo et al. 2010). concerns that the major tourist spots in the Northern Cir- »» Low visitor numbers can minimize congestion at cuit are reaching the limits of their carrying capacity. Car- popular sites and preserve the economic value rying capacity limits will be reached once the product and of the product by providing visitors with an experience on offer has been diminished and degraded, authentic wilderness experience. This can also either as a consequence of overcrowding, which dimin- avoid overcrowding, which has adverse ecologi- ishes the experience, or ecological damage, both of which cal consequences that diminish the value of the reduce the earning potential of the asset. This together product. with a suite of pressures from intrusive activities and developments are adding to existing pressures on the It is important to note that the HVLD approach region. Additionally, population densities and poverty will not succeed at every destination in Tanza- incidence are disproportionately higher around the pro- nia. Though HVLD tourism is much sought after, it is an tected areas, suggesting that the benefits from tourism sel- exceptional occurrence. For HVLD tourism to succeed, a dom trickle down to the local population. Finally, there host of conditions must prevail: are immense infrastructure needs in the economy across »» The product on offer must be rare or even unique. all sectors, including to improve access to and within the The Serengeti clearly falls into this category. The many underused tourist assets. Building infrastructure wildebeest migration is obviously unique and the “right” is critical because infrastructure choices have authentic wilderness experience on offer is excep- long-lived and difficult-to-reverse impacts on land, tour- tional and atypical. By contrast, the experience ism prospects, water use, and future patterns of develop- (congestion and location) and product (wildlife ment. Development of strategic infrastructure to promote observable) on offer at National Parks (NPs) (such development and connectivity can be fully consistent with as Arusha NP) is unexceptional, so it is not able to efforts to conserve the natural assets that are the basis of attract the HVLD market segment. Tanzania’s tourism and growth. Developments around »» As a corollary, since such HVLD tourism assets are key tourism assets must be carefully planned and executed rare, by implication there is less competition, allowing to ensure that they do not erode economic value and the for higher prices to be charged for the experience. sustainability of the underlying ecosystem. x Tanzania’s Tourism Futures These developments will require close coordina- driven by demands for grazing land, poaching, aggres- tion between the private and public sector. Today, sive expansion of tourism, and plans for potentially intru- the business climate in Tanzania is neither conducive sive infrastructure development. To assess the economic toward tourism operations nor investment. In particular, implications of these trends, this study has developed the levies and taxes within the tourism sector are unpre- linked models to simulate the consequences of alterna- dictable, uncertain, and often duplicative. This reduces tive futures. The analysis captures connections between Tanzania’s ability to compete with the tourism industry in renewable resource (wildlife) stocks and flows, the effects neighboring countries, many of which have already estab- on tourism, and livelihoods in the Serengeti and the lished a better environment for their tourism industry, resulting micro and macroeconomic impacts (through a including more robust regulatory systems for protection Computable General Equilibrium [CGE] model).5 The of their natural resources. Because public resources are conclusions are instructive for policy purposes. and will remain limited, the government must consider how to best attract private investment, and take measures The distributional and macroeconomic conse- toward establishing an environment of trust and predict- quences are striking. The effects from a plausible ability for the private sector so that current players can scenario where pressures combine to reduce the carry- operate effectively and partnerships can be fostered for ing capacity of the ecosystem by 20 percent and hence a the strategic development of the tourism industry.4 decline in the tourism experience are diffused through the economy and especially large among poor rural house- Tanzania is now at a crossroads and must make holds. When tourism revenues fall, the exchange rate is far-reaching strategic decisions. This report affected so that the impact is transmitted to all other sec- explores the implications of two contrasting develop- tors of the economy. The loss of bushmeat as a result of ment strategies, based on guidance from the government a reduction of carrying capacity is another large loss that of Tanzania (GoT). The first strategy assesses increas- affects the rural sector disproportionately. In the scenario ing development in the Northern Circuit with a focus considered, overall GDP declines by 7 percent. The quali- on the iconic Serengeti ecosystem. The second scenario tative results are robust and hold across a variety of other promotes tourism development in “new” areas of Tan- scenarios. zania with a focus on the Southern Circuit and Ruaha National Park (RNP). The report identifies opportunities, Could the fortunes of the economy and the Seren- challenges, and constraints of building a more diversified geti be reversed by boosting the number of tour- tourism product. ists who visit? This is a counterproductive strategy. With a diminished tourism product on offer it is only possible to TOURISM AND increase tourism numbers by reducing prices significantly so that total revenue from tourism declines further.6 Other DEVELOPMENT IN THE important results are worth noting. NORTHERN CIRCUIT There can be little doubt that the allure of the Impacts on carrying capacity are found to have Serengeti has been pivotal in building Tanzania’s synergistic effects. In other words, small unconnected tourism industry. It is the last intact, fully functioning pressures, when combined, deliver disproportionately savanna wilderness ecosystem in Africa. It is among Afri- larger and unwelcome impacts. For instance, a small drop ca’s premier tourist destinations and most people have it in carrying capacity of the ecosystem or a small reduc- on their “bucket list”—a place to see at least once in their tion in the size of the ecosystem has a minor impact on lifetime. The principle threats to the Serengeti are those resource stocks (that is, wildlife numbers). However, when 5 The model was created before the release of the recently updated GDP num- 4 World Bank, Tanzania Sixth Economic Update. “The Elephant in the bers by the Tanzania National Bureau of Statistics and, as such, reflects GDP Room—Unlocking the Potential of the Tourism Industry for Tanzanians.” numbers that were available before the rebasing exercise. January 2015. 6 Since demand is inelastic. Tanzania’s Tourism Futures xi they are combined, one factor tends to exacerbate the and serves as a vital watershed in its landscape. Spectacu- effects of the other so that the joint effects exceed the lar landscapes around the Ruaha River combined with an sum of the individual impacts. This has significant policy abundance of charismatic species make the park an obvi- conclusions that calls for considering the impacts of dis- ous tourist attraction. Among its many accolades, the Ruaha parate pressures simultaneously. Debates on the volume landscape can boast of the following: 10 percent of all lions and impact of tourism and tourist infrastructure seldom left in the world, the third largest population of wild dogs, consider effects emanating from the agriculture and land and the second largest elephant population after Botswana, use or connectivity and vice versa. as well as prominent endemics such as the newly discovered Kipunji monkey. Despite these attractions, in a typical year Finally, if carrying capacity declines, the econom- Ruaha receives about 20,000 visitors while the Serengeti ically prudent (optimal) strategy is to expand the sees over 250,000 tourists. wilderness areas to restore the payoffs from tourism, trophy hunting, and livelihood resources. This is often To be competitive, it needs to offer a visitor expe- the reverse of what is observed when complementary rience that is no worse and preferably better than pressures lead to a reduction in habitats together with a rivals in a similar category. The tourist experience decline in ecosystem productivity. is not measured in terms of the product on offer alone but the whole continuum of interactions that include travel time and costs. A comparison suggests that travel DIVERSIFY TOURISM TO THE costs and quality of experience may not match the prices SOUTHERN CIRCUIT that the tourists have to pay in competing markets, even Tanzania has the opportunity to avoid these the high-end attractions such as Chobe NP in Botswana. adverse outcomes by diversifying its tourism Additionally, to attract investment in Ruaha or elsewhere, product. Recognizing that crowding diminishes the eco- the country needs a more enabling business environment. nomic value of tourism in the Serengeti there would need This is a wider problem but is likely to especially deter to be investments in building tourism at new destinations. global investors. Coupled with its immense natural endowment, there is the potential for Tanzania to solidify and consolidate its Ruaha receives little official publicity and more emerging position as Africa’s premier wildlife tourism des- generally it is widely overlooked in travel media. tination, similar to the status achieved by Costa Rica in The Tanzania Tourist Board publicizes the Southern Latin America. Circuit but does not highlight Ruaha. An Internet search with key words such as “Tanzania, wildlife tourism, and Diversification has two relevant elements: spa- lions” fails most often to bring up any links to Ruaha, and tial and market segments. There is scope to expand the branding of Tanzania as “The land of Kilimanjaro, the available tourist destinations, but there is also scope to Zanzibar, and the Serengeti” simply reinforces the bias diversify the tourism product by attracting different mar- in favor of the Northern Circuit. It is no surprise that ket niches and experiences. Examples include the ability an attraction that remains hidden from potential visitors to package wildlife and cultural travel as well as different attracts few tourists. income ranges and special interest groups who could be attracted to the many available destinations. The most far-reaching and challenging problem for Ruaha lies with the management of water A Southern Circuit exists and its development is a flows from the Great Ruaha River. The river origi- government priority, but the route is poorly known nates in the Usangu highlands and flows through Ruaha and infrequently traveled. The Ruaha National Park and then into the Mtera and Kidatu hydropower plants. has long been recognized as an ecological jewel with the On average, the river provides 56 percent of runoff to the potential to become a major tourist destination in the Mtera and Kidatu hydropower stations which in turn gen- Southern Circuit. It is the biggest national park in Tanzania, hydropower-derived erate more than half of the country’s ­ xii Tanzania’s Tourism Futures electricity. The river is also an important livelihood strategy that maximizes tourism revenue and not resource for many thousands of residents who rely on it tourist numbers. The latter, as demonstrated in this for domestic, livestock, and irrigation purposes. report, could prove to be counterproductive. The Great Ruaha River was once a peren- Going forward, the approach would build and differenti- nial river but has now become seasonal with ate tourism by location (for example, Serengeti versus the extended dry periods due largely to upstream South); product (wildlife, beach, culture, and adventure); irrigation. The major irrigated areas have expanded and market segment (domestic, international, and confer- dramatically from 3,000 ha to over 115,000 ha7 and ence). Specifically: this has coincided with an increase in the frequency and »» Preserve and Strengthen the Status of the duration of zero-flow periods. Increased competition Jewel in the Crown of Tourism. The allure for water has resulted in loss of livelihood income for and iconic status of the Serengeti has been pivotal downstream users and has adversely impacted tourism in allowing the country to maintain its status as an potential of the RNP.8 exclusive HVLD tourist destination. »» Address the Litany of Pressures on the A study of the value of water in alternative uses suggests Northern Circuit. There are risks that current that it would be economically prudent to reallocate water trends could undermine the earning potential in the dry season that would enable flows through the NP.9 of the Serengeti with adverse consequences that However, this will be especially challenging and will call would be transmitted widely through the economy. for greater investment in administrative and institutional Congestion of tourists is not conducive to a high- capacity to build measurement and monitoring systems value tourism experience. Intrusive infrastructure with adequate enforcement capabilities. developments and over-building, a feature com- mon in other tourist areas, is also certain to under- THE WAY FORWARD mine the value of the product as would policies Tanzania’s natural assets have catalyzed a buoyant and within and outside the ecosystem that damage the robust tourism industry and also play a pivotal role in sus- carrying capacity and hence the wilderness value taining the livelihoods of the rural poor. To build upon of the ecosystem. this success Tanzania needs to play to the comparative advantage of each region and attraction. This calls for a The focus of tourism on the Northern Circuit has meant that Tanzania’s vast endowment of other tourist assets remain underused. Building tourism in the Southern Cir- 7 Tanzania Hydropower Sustainability Assessment: Case Study of Great Ruaha cuit has not been easy in a market that grows more com- River (Vol 2). November 2014. World Bank. 8 Few tourists would be attracted by the sight of a distressed ecosystem resulting petitive and better informed each day as a consequence in increased inter- and intra-species competition, higher mortality rates, and of improved connectivity and globalization. To grow reduced diversity. tourism in the Southern Circuit will call for the following 9 However, there are three prominent dissenting views. It is argued that the measures: absence of dry season flows is a consequence of climate change and altera- tions in vegetation and thus, unconnected to irrigation. Another view holds »» Branding and publicity. The Southern Circuit that under idealized management systems, Mtera Dam’s water can be sup- needs to define and develop a brand to distinguish plied entirely by wet season flows, so there is no need for dry season supplies. itself from rivals. Finally, it is arguable that cheap supplies of oil or gas resulting from recent »» Addressing the challenges of accessibility. exploration efforts may diminish, or even eliminate, the need for hydropower. World Bank (November 2014) found that (1) irrigation expansion is responsible Transport costs are high and the area is hard to for the absence of dry season flows in the Great Ruaha River, (2) dam opera- reach by road. Without adequate access there is tional procedures could significantly improve current hydropower generation limited scope for commercializing the potential of at Mtera and Kidatu, and (3) climate change has not had any effect to date on the RNP. the power generation at Mtera or Kidatu. Rather, climate change is likely to result in increased hydropower potential at these sites as well as other current »» Developing a marketable product. The pro­ and planned sites. duct on offer must be competitive both in price and Tanzania’s Tourism Futures xiii experience. If Ruaha is to play a part in the South- challenge for policy is to create a set of commercial incen- ern Circuit it would be essential to address the water tives for tourism operators to strengthen local linkages constraint and restore flows to the NP. while remaining commercially profitable. Two schemes »» Developing a strategy that recognizes the merit consideration: Southern Circuit’s strengths and weak- »» Community conservancies. These are an nesses. Though Ruaha, for example, presents extension of the more familiar Community Busi- spectacular options for wildlife tourism, it is not ness Ventures (CBV) between communities and likely, for many reasons, to gain the type of popu- private tour operators, where pieces of commu- larity witnessed in the Northern Circuit. The strat- nity-reserved land are subleased to private tourism egy for the Southern Circuit can look to diversify investors. toward different types of tourism, especially niche »» Building local capacity. Another promising markets, such as cultural or adventure tourism as model entails building supply chains into local well as beach tourism. communities to strengthen economic linkages. Agriculture is an obvious entry point because of Poverty is high around tourist attractions, suggesting that the availability of land. To address these issues few of the benefits trickle down to the rural poor. There would require intensive programs of capacity is a need to strengthen linkages with the local economy building to develop partnerships and a mutual and develop policies and incentives to share benefits with understanding of priorities between the industry the poorest who often live close to tourist attractions. The and local communities. xiv Tanzania’s Tourism Futures CHAPTER ONE INTRODUCTION It is no exaggeration that tourism has shaped the development fortunes of Tanzania. The country is endowed with an enviable range of natural attractions that bring tourists from around the globe. The most renowned attractions include the great plains of the Serengeti, which support the world’s last remaining large animal migration; the wildlife spectacle of the Ngorongoro Conservation Area which also hosts the earliest hominid remains; Mount Kilimanjaro, the highest mountain in the African continent; and Zanzibar with its tropical beaches and home to Stone Town, a cultural World Heritage Site (see figure 1.1). Tourism provides a robust stream of revenues for the country, with ben- efits that reverberate widely through the economy. The sector generates the bulk of exports for the country. World Trade Organization data (WTO 2013)10 indicate that since 2008, the combined export revenues from travel and tourism have exceeded those from the mining and energy sector (see figure 1.2). Unlike the low-value-added exports of minerals or agricultural commodities where revenues are vulnerable to global price volatility, demand in the tourism sector has been grow- ing at a stable rate. As a relatively labor-intensive sector, tourism serves as a robust source of good quality jobs in the country, with the potential to alleviate poverty. Resilience in demand and an ability to generate employment make the sector an ideal vehicle for propelling development and growth, especially in lagging regions of the country. The macroeconomic simulations reported in this study suggest that the economic impact of the sector is often underestimated. The economic benefits are stronger than might appear, with cross-sectoral spillover effects and linkages domi- nating those of other traditional sectors of the economy. Apart from these obvious economic benefits, tourism can stimulate broader benefits to the economy: upgrades to infrastructure, conservation of natural habitats, gender equity by providing decent jobs for women, and greater integration into global economies. However, Tanzania 10 WTO (World Trade Organization). 2013. WTO Trade Statistics: http://stat.wto.org/StatisticalProgram/WSDB StatProgramHome.aspx. Tanzania’s Tourism Futures 1 FIGURE 1.1.  MAP OF TANZANIA FIGURE 1.2.  EXPORT REVENUES (IN has not fully leveraged the opportunities for job creation $MILLION) FROM TOURISM and poverty reduction that the tourism sector offers. AND TRAVEL VERSUS This report explores the contribution, the poten- MINERALS AND ENERGY tial, and the challenges that confront the sector. Tourism and travel Minerals and energy $1,800 It briefly describes the structure of the sector in Tanzania $1,600 and compares it to some of its closest competitors in Sub- $1,400 Saharan Africa. It identifies the limits and opportunities $1,200 of current policy priorities through a series of integrated $1,000 economic-biological models and suggests alternative strat- $800 egies for growth and development of the industry. It begins $600 with a brief overview of the sector and then explores $400 alternative development paths for the sector—one which $200 focuses on the established Northern Circuit and the other $0 which explores the opportunities and constraints of diver- 2008 2009 2010 2011 2012 sifying tourism into the Southern Circuit, especially in the Source: World Trade Organization Statistics 2013. Ruaha landscape. 2 Tanzania’s Tourism Futures CHAPTER TWO ANATOMY OF THE TOURISM SECTOR Largely unaffected by turbulence in the global economy, tourism growth has been rapid and robust. Within a decade the number of foreign visitors has doubled from about 500,000 tourists per year in 2000 to just above 1,000,000 per year by 2012 (see figure 2.1).11 The world share of international tourist arrivals to Tanzania has also increased from 0.05 percent in 1995 to 2 percent by 2012 with approximately 5 percent of international tourist receipts accruing to the country (WTTC 2013). The majority of international tourists (close to 80 percent) arrive from either Europe or America, with Asian tourists exhibiting a rapid increase over recent years as a result of focused promotional efforts (GoT 2012). About 64 percent of visitors in 2010 arrived on packaged tours organized through travel agencies that dominate the market. The average length of stay has remained stable over a decade at about 11 days, the highest in East Africa. Around 55 percent of visitors were aged between 25 and 44 years and 27 percent were aged between 45 and 64 years. Tanzania’s tourism is predominantly nature-based and largely focused on three assets: the Serengeti, Mount Kilimanjaro, and Zanzibar. Tour- ism is focused on the exceptional natural assets—abundant wildlife, spectacular iconic landscapes, and tropical coral-fringed beaches—which these areas provide. Wildlife tourism, especially along the Northern Circuit, remains the country’s primary attrac- tion, followed by beach tourism in Zanzibar. Most tourists combine a wildlife experi- ence with a beach excursion. The annual park revenues from Serengeti and Mount Kilimanjaro represent 85 percent of the total park system revenue and provides an income stream sufficient to manage the entire Tanzanian National Parks Authority potential (TANAPA) system.12 Yet these represent just a small fraction of the country’s ­ 11 The total number of visitors to Tanzania is not available because the Mainland and Zanzibar entry statistics are not coordinated, and hence some double counting occurs. The figures reported here are for both Mainland Tanzania and Zanzibar. 12 TANAPA manages the country’s 16 national parks, providing conservation, anti-poaching, education, and community services. Of these 16 parks, only four produce a revenue surplus, with two—Kilimanjaro and Serengeti—responsible for 85 percent of TANAPA income; the remaining 12 are subsidized by these revenues. Tanzania’s Tourism Futures 3 FIGURE 2.1.  FOREIGN VISITORS TO TANZANIA (2000–12) 1,200,000 1,000,000 800,000 600,000 400,000 200,000 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Source: Tanzania Tourism Statistical Bulletin 2012, Tourism Division, MNRT. tourism assets. Despite plans to develop the Southern TABLE 2.1.  KEY TRAVEL AND TOURISM Circuit (anchored around the Selous Game Reserve and PERFORMANCE INDICATORS, RNP, two high-density animal habitats together totaling 2013 70,300 km2, about the size of Georgia or Sierra Leone), Key Indicator 2013 Value fewer tourists visit these areas. Between 2006 and 2012, the RNP had on average just above 20,000 annual visi- Average length of stay (days) 11 tors while the key national parks within the Northern Tourism contribution to GDP (%) 9.9 Circuit had significantly higher average annual visitations Tourism contribution to GDP growth (%) 2.8 rates: Serengeti NP—322, 000; Kilimanjaro NP—48,000; Number of people directly employed 402,500 Arusha NP—60,000; Lake Manyara NP—157,000; and Direct and indirect (induced) employment 1,196,000 Tarangire NP—116,000 (see appendix A). With the Capital investment (TZS, billions) 1,634.2.1 majority of tourism concentrated in a few areas in the Source: WTTC (2014), Tanzania National Bureau of Statistics. north, there are significant opportunities for diversifica- tion of tourism products, which could allow for continued tourism industry builds skills and human capital and pro- sector growth. vides higher-paying employment prospects that can pull families out of poverty. The bulk of workers (96 percent) Table 2.1 provides a snapshot of some of the are Tanzanians and the managerial cadre is split equally economic impacts of the industry, based on data between nationals and foreigners, with 22 percent Tan- from the World Travel and Tourism Council (WTTC). zanian females. The industry invested TZS 1,634.2 billion or US$882.9 million in 2013—an increase of 1.3 percent from the Tanzania attracts some of the world’s most previous year. The travel and tourism sectors combined illustrious tour operators. Tanzania’s natural accounted for nearly 9.9 percent of GDP in 2013 and assets are exceptional, as evidenced by the number and contributed to almost 3 percent of the country’s growth. caliber of active tour operators. Many operators mar- About 30 percent of the industry’s revenue is paid to ket only Tanzania, and some headquartered in Kenya the government in taxes and fees. Tourism has stimu- bring their more exclusive customers to Tanzania and lated about 1.2 million jobs (11 percent of total employ- Kenya’s private reserves. Official statistics suggest that ment) of which 402,500 jobs were created directly in the Tanzania has about 32,000 hotel rooms of all types, industry. It is widely presumed that employment in the with 58,000 beds and room occupancies of around 4 Tanzania’s Tourism Futures FIGURE 2.2. TOURIST NUMBERS FIGURE 2.3.  TOTAL CONTRIBUTION OF (THOUSANDS) AND RECEIPTS TRAVEL AND TOURISM TO GDP 20 (US$, MILLIONS) 15 Revenue Tourist # 10 1,600 5 1,400 0 1,200 ya a ia ia a r nd an ca ib an n Ke am ga as 1,000 w nz ts U ag N Ta Bo ad 800 M 600 Source: WTTC (2014). 400 200 0 rapidly than in Tanzania,13 and as a result, Kenya receives Kenya Tanzania 50 percent more tourists but generates about Source: WTTC (2014). 50 percent less revenue from tourism in total than Tanzania. Higher visitation rates in Kenya’s national parks 60 percent, which far exceeds the global average of have also led to important negative impacts on the wildlife about 30–50 percent. In the period of 2001 to 2011, that is the very draw for tourists (World Bank 2010). hotels and restaurants alone contributed between 2.3 percent and 2.8 percent to the GDP of Mainland The HVLD approach brings clear advantages to Tanzania (Bank of Tanzania 2013). Until recently the Tanzania—particularly for high wildlife areas— country’s reputation as an elite destination was built and the policy needs to be strengthened, formal- primarily by small- to medium-sized privately owned ized, and complemented where this approach is hotels, except in Dar es Salaam, where familiar interna- suitable. There is also scope to develop a diverse tional groups operate. There is some evidence that the set of products catering to different market travel industry has been gradually diversifying its prod- niches. The HVLD is a sound strategy which ensures ucts and services through creative packaging, including that Tanzania competes in a market with more inelastic visits to local communities. demand, where visitors are willing to pay more for an exclusive experience. This is the more stable segment of Tanzania reached an enviable position as a high- the market with fewer competitors—differentiating Tanza- expenditure low-density destination, by restrict- nia’s tourism products from other regional competitors— ing supply and targeting the high-end segment and hence generates more predictable and resilient flows of the market. The impressive performance reflects the of tourism revenue. Although niche markets attract fewer government’s commendable HVLD approach. F ­ igure 2.2 numbers, they have high rates of growth, with custom- shows that while Tanzania received fewer visitors in 2011 ers who are prepared to pay a significant premium for a compared to Kenya, the country generated the most crowd-free wilderness experience. The HVLD segment absolute revenue as each visitor to Tanzania spends sig- is also the more resilient part of the market. During the nificantly more per trip. Thus, despite lower tourist num- 2008–09 economic crisis, tourist numbers were largely bers than most of the important regional competitors, unaffected in Tanzania even when tour operators, on Tanzania’s total tourism revenue is the highest, something average, raised prices (UN WTO and ILO 2011), while made possible by the limited supply. Figure 2.3 shows the other tourism destinations saw visitor numbers from tra- relative economic importance of the sector for the same ditional markets plummet. The HVLD segment is less regional neighbors. The HVLD strategy is also a good one vulnerable to economic shocks and involves demanding for maximizing revenues without exceeding the carrying capacity of natural attractions on which Tanzania’s tour- ism depends. Kenya which has developed mass-market 13 The growth in Kenya’s tourism industry has also been far more volatile in beach products linked to wildlife tourism provides a use- recent years as a result of internal and external political shocks (that is, election ful contrast; lower-end tourist arrivals have grown more violence and spillover from chronic instability in Somalia). Tanzania’s Tourism Futures 5 customers who are difficult to attract but easy to lose. TANAPA; the newly created Tanzanian Wildlife Authority Forgoing this much-sought-after market niche is likely a (TAWA), responsible for management of most protected counterproductive strategy if the intention is to maximize areas outside the National Parks System; the Ngorongoro revenues from tourism. Conservation Area Authority (NCAA), which manages the high-value Ngorongoro Crater; and the Tanzania Tour- An additional long-term benefit is that lower vol- ist Board (TTB), which is responsible for marketing the umes allow for the sustainability of the distinc- industry. The Tanzania Investment Center (TIC) handles tive natural environments upon which tourism investment promotion. As tourism is a non-union issue, depends. This contrasts significantly with mass tourism Zanzibar has a distinct set of agencies: the Ministry of that has eroded the value of the wildlife tourism market Information, Culture, Tourism and Sports; the Tourism elsewhere. High tourist numbers in wildlife areas are not Commission; the Zanzibar Investment Promotion Agency only a possible threat to sustainability but repel the higher- (ZIPA); and the Commission for Land and Environment. value tourists, precipitating a downward spiral along the The Tourism Confederation of Tanzania, the umbrella value chain. This suggests the need for a diversified set of private sector institution, has 14 industry and trade mem- tourism products that preserve the high-value niches while ber associations. A Tourism Master Plan was created in competing with lower-margin segments at other locations. 2002 for Mainland Tanzania, which emphasized the need for diversifying the tourism product away from the rela- Institutional structures in the sector have stabi- tively crowded Northern Circuit, especially through the lized with responsibility for tourism dispersed creation of the Southern Circuit. Despite these plans and across agencies. Primary responsibility for tourism pol- a wealth of potential attractions, tourism remains depen- icy lies with the Ministry of Natural Resources and Tour- dent on a small range of locations around Arusha (the ism through five entities: MNRT’s Tourism Division; the Northern Circuit) and Zanzibar. 6 Tanzania’s Tourism Futures CHAPTER THREE CHALLENGES AND OPPORTUNITIES Despite the recent growth of the tourism industry, important challenges remain and need to be tackled if the sector is to boost its contribution to growth and poverty reduc- tion goals. Three key issues threaten the value and sustainability of the industry: the need to strengthen linkages with the rural economy, the impacts of visitor numbers on industry value and carrying capacity, and the need for balancing infrastructure growth while maintaining revenue flows from tourism. A. LINKAGES BETWEEN TOURISM AND THE RURAL ECONOMIES NEED TO BE STRENGTHENED A major challenge that has not been adequately addressed is that the proceeds from tourism rarely trickle down to local communities. Greater integration between the tourism industry and local communities is important for inclusive growth and sustain- ability of the sector. Paradoxically, poverty incidence is highest in areas that attract the greatest numbers of tourists, suggesting an urgent need for developing economic linkages and sharing benefits in a more equitable manner. The extent of the problem is illustrated in figures 3.1 and 3.2. Figure 3.1 maps population densities at a 10 km x 10 km spatial resolution using data from Land- scan (2009).14 It shows that population densities in areas around many protected areas (such as west of the SNP) are often as high or greater than in Dar es Salaam. Figure 3.2, which maps the corresponding levels of poverty as defined by the offi- cial poverty line of TZS 23,000 (approximately US$14.25; from Baird et al. 2013), suggests a higher incidence of poverty around protected areas. The problem seems more intense in the mainly agricultural region west of the Serengeti (Baird et al. 2013 and figure 3.2). Caution must be exercised in inferring causality between the presence of a protected area and a high concentration of poverty. Causality may run 14 http://web.ornl.gov/sci/landscan/. Tanzania’s Tourism Futures 7 FIGURE 3.1.  POPULATION AND PROTECTED FIGURE 3.2.  POVERTY AND PROTECTED AREAS AREAS Source: Landscan (2009) and authors’ calculations. Source: Landscan (2009) and authors’ calculations. both ways or may not exist. It is possible that poverty may setting traplines of snares that catch wildebeest, zebra, be induced because of a lack of access to the bountiful giraffes, impala, and eland; these are butchered and dried resources in protected areas—land, water, and the sup- at temporary camps and transported to markets. Annual ply of wildlife that could be harvested for consumption or offtake of wildebeest in the Serengeti alone may be higher sale. In this case, the presence of a protected area might than 100,000 animals per year (Mduma et al. 1996), induce poverty. Conversely, it is also conceivable that the though simulations conducted for this study indicate that abundance of wildlife and other resources attract poor a higher harvest is likely in equilibrium. people to the area, resulting in high levels of both popula- tion density and poverty incidence. All of this suggests that the availability of resources around protected areas attracts individuals with few other employ- There is some evidence to support the latter hypothesis. ment opportunities. Sinclair et al. (2008) report that popu- Harvesting wildlife for meat is widespread around the lation growth rates have exceeded 10 percent around the Serengeti and other national parks (Arcese and Campbell SNP as a consequence of migration from other parts of 1995). There is ample statistical evidence that the rural the country. Hence, there is a need to formalize resource poor around protected areas depend disproportionately use and create better incentives for communities to benefit on bushmeat that often comprises over 60 percent of pro- from activities that are sustainable. tein consumption in their diets (Barett and Arcese 2000; Knapp 2007, 2012; Rentsch and Damon 2013). The large Linkages between tourism and the rest of the herds of resident and migratory game that inhabit most economy, especially with the rural poor, could of Tanzania’s protected areas are a significant source of be strengthened. Table 3.1 illustrates how an average readily accessible protein. In the Serengeti and other pro- hypothetical dollar is spent by a tourist in Tanzania. Not tected areas, there are numerous reports of local teams surprisingly, the bulk of spending (over 60 percent) is on 8 Tanzania’s Tourism Futures TABLE 3.1. AVERAGE TOURIST TABLE 3.2.  CONSEQUENCE OF US$1 SPENT EXPENDITURE CATEGORIES IN THE TOURISM SECTOR Category of Proportion of Receiving Sector Proportion Expenditure US$1 Spent Capital 0.030719 Accommodation 0.28 Agriculture 0.144816 Food and drinks 0.23 Mining and extraction 0.001646 Transport 0.105 Processed food 0.103675 Shopping 0.14 Labor-intensive manufactures 0.035107 Sightseeing 0.105 Capital-intensive manufactures 0.002743 Other 0.14 Utilities and construction 0.017553 Source: Global Trade Analysis Program (GTAP) database. Transportation and communication 0.070762 Financial and other services 0.110258 Tourism 0.161821 accommodation, food, and transport, with little spent Dwelling 0.017553 on other items that might fall in the shopping category. Taxes and government 0.005485 The consequence of this pattern of spending on the local Rest of the world (leakage) 0.281404 economy will depend on how this money is spent by the Source: Authors’ calculations, based on SAM. suppliers in these sectors. Table 3.2 illustrates the consequences of this spending pattern across the economy, with the impacts depend- gests that though tourism is providing important benefits ing on the many interlinkages that exist between sectors. to the Tanzanian economy, there are important opportu- The results are from estimates of the Social Accounting nities to better capture tourism benefits through invest- Matrix (SAM) developed for this work (see appendix B). ments that promote local capacity for providing services The table shows how a dollar spent according to the pat- and goods to the industry and more broadly to strengthen tern in table 3.1 circulates through the different sectors linkages with other sectors of the economy. Such changes of the economy. The consequence of spending on food, would need to be fostered through targeted policies and for example, will depend on whether items purchased economic incentives to build stronger links with the rest have been imported or not. For instance, a crop grown of the economy, especially the more labor-intensive agri- locally will stimulate the agriculture sector, whereas an cultural sector. imported item would register as a “leakage” accruing to the rest of the world. The effects will be determined by the stages of production and processes undertaken B. ECONOMIC within the country. CONSEQUENCES OF CONCENTRATED TOURISM Table 3.2 tracks the consequences of such linkages for the Despite an abundance of assets, tourism remains hypothetical dollar spent in the tourism sector according heavily concentrated along the Northern Cir- to the distribution in table 3.3. Three features are notable. cuit and there is a need to diversify the tourism First, the largest share of spending (28 percent) leaks to product without diminishing its revenue poten- the rest of the world. Second, there are positive impacts tial. There are concerns that the major tourist spots in on agriculture (14 percent) and financial and other ser- Northern Tanzania, commonly referred to as the “North- vices (11 percent), suggesting that tourism is indeed pro- ern Circuit”15 are reaching the limits of their carrying viding important benefits to the Tanzanian economy. Third, the resources accruing to financial services reflect Including the Serengeti ecosystem (comprising the SNP and Ngorongoro 15 the flow of funds and the dependence on agencies to gar- Conservation Area) as well as Tarangire, Arusha, Lake Manyara, and Mount ner tourists and transfer funds across borders. This sug- Kilimanjaro. Tanzania’s Tourism Futures 9 c ­apacity. This together with a suite of pressures from would need to enter a more competitive seg- further development, infrastructure that neglects adverse ment of the market with likely adverse revenue spillover effects, poaching, and other activities are add- consequences. There is evidence that demand is ing to existing pressures on the carrying capacity of the inelastic in the high-end market, implying that current region. Tourism development must be carefully planned visitors are prepared to pay a high price since they value and executed to ensure it does not erode the value of the the experience (exclusivity) on offer.16 With an inelas- tourist product and the sustainability of the underlying tic demand, boosting visitor numbers by 5 percent, for ecosystem in areas where carrying capacity limits are example, would necessitate a price reduction of more reached. The problem is most severe along the popu- than 5 percent, resulting in a decline in revenues accru- lar wildebeest migration corridor Kenya’s Maasai Mara ing to the country. Put simply if the quality of the tour- Reserve, which adjoins the SNP and provides a salutary ist experience and its reputation is diminished, high-end lesson: Maasai Mara Reserve has nearly twice as many tourists would eschew Tanzania for other more desirable tourist visitors as Serengeti though it is less than a tenth of destinations. Hence caution is warranted before embark- the size, and as a consequence of congestion, Kenya raises ing on a simple strategy of increasing tourist numbers to but a fraction of the revenue. Most of the visitors arrive compete with Kenya or other more price-sensitive mar- in July and August when the wildebeest migrate across the ket niches. Kenyan border. The litany of documented problems is large (Ikiara and Okech 2002): A high-value strategy is not suitable for every »» Lodges built near watering holes compete for market niche. Given the variety of assets and the prime habitat. In these areas, excessive construc- diversity of customers, products can be designed tion of tourist lodges combined with withdrawal of in multiple, interesting, and creative ways. There water from the Mara River for upstream irrigation is scope to diversify the tourism product while maintain- has reduced wildebeest densities, with concomitant ing the earning potential of the Serengeti and the greater impacts on predator abundance and tourist satis- Northern Circuit, particularly through efforts to develop faction. the Southern Circuit. On the other hand competition in »» Congestion of vehicles around traditional wil- the sun-and-sand market has reached a point where beach debeest breeding grounds is thought to have an tourists are largely indifferent about location and highly impact on the timing of the annual wildebeest sensitive to price and travel times, providing an opportu- migration. There is also evidence of impacts on nity for developing beach tourism more intensively along hunting success of large predators because of the Tanzania’s long coastline. Every market segment will call sheer volume of vehicles. for trade-offs, and given the customer base, one destina- »» Tourists often spend more time viewing each other, tion may be better positioned than others to compete for rather than the object of attraction—typically a a given market (customer) segment. The choices would pride of lions surrounded by increasing numbers depend on building an appropriate brand for the alterna- of vehicles. tive products without eroding the value of current tourism »» A vast profusion of lodges and “private” safari assets. camps mean that no camp is isolated and the expe- rience is far removed from a wilderness one. Several alternatives have been proposed to improve the contribution of the tourism industry to the national The consequence is a diminished tourist experience, with economy and generate more efficient patterns of adverse impacts on the economic productivity, biological resource use. One option suggests developing two pri- carrying capacity, and revenue earning potential of the ecosystem. 16 Time series data is sparse but regression of log of tourism numbers using standard procedures in the literature (Lim 2010) suggests an elasticity of about –0.88 for a levels regression and lower elasticity for a regression in first differ- If Tanzania were to pursue a policy of signifi- ences though the price term is not significant, no doubt because of a lack of cantly increasing wildlife tourist numbers it degrees of freedom. 10 Tanzania’s Tourism Futures ority tourism zones: a southern “safari” circuit and a i ­mportant for Tanzania given its high dependence on nat- southern coastal zone. The establishment of these two ural endowments. The issues are complex and there are new zones, or other similar expansions of the industry, often trade-offs between “building right” and “building could attract mid-market tourists who may not be will- more.” Building right typically brings benefits that accrue ing to pay the premiums required to vacation in the tra- over the longer term while consequences of building more ditional Northern Circuit areas but nevertheless want to are immediate and visible gains. experience the ecotourism that is unique to Tanzania. It can also go a long way toward establishing Tanza- Much of Tanzania’s global comparative advan- nia as the ecotourism capital of Africa, much like Costa tage lies in its immense endowment of renew- Rica has branded itself the ecotourism capital of Latin able and non-renewable natural resources. The America. fact that infrastructure needs are so large implies that there are wide opportunities to build right—garnering benefits while minimizing or avoiding possible negative C. INFRASTRUCTURE impacts on the country’s comparative advantage. There DEVELOPMENT are opportunities to improve connectivity while enhanc- ing the revenue potential of tourism. One of Tanzania‘s Tanzania has significant infrastructure needs greatest assets is the wilderness experience that it offers across all of its sectors. Improved roads and irriga- its high-paying clientele. As human population densities tion are needed to improve agricultural yields and pro- increase through Tanzania and the rest of Africa, there mote greater commercialization of agriculture, while will be a growing premium on places that offer such mineral, oil, and gas rents, if judiciously employed, can experiences. Likewise, in a water-constrained economy provide the resources needed to invest in human capital such as Tanzania there is scope to enhance land pro- (a key engine of growth) and fund social infrastructure. ductivity without compromising the revenue potential Infrastructure is important too for the tourism industry. of ecosystems that sustain water flows. In fact, Tanza- Efficient travel hubs, robust road networks, and reliable nia’s protected areas play an important role in regulat- electricity can improve a tourist’s experience and reduce ing downstream water flows and, if well-managed, can the cost, both in terms of time and money. However, for continue to provide these important hydrologic services. Tanzania, where ecotourism is the main attraction, it is Interestingly, Tanzania’s most productive agricultural important that infrastructure investments are done with lands are largely outside of protected areas, as shown consideration of their long-term impacts on local devel- in figure 3.3, which maps total nutrient fixing capac- opment and the tourism assets that should provide an ity of soil as measured by its Cation Exchange Capac- important engine of growth. Therefore, there is a need ity (CEC) (soils with low CEC have little resilience and to weigh the full array of economic benefits and costs of cannot easily build up stores of nutrients). These data different options. suggest that the largest portion of resilient agricultural The fact that much remains to be built in Tan- lands lie outside of protected areas and that there is zania creates an opportunity to build “right.” ample scope for agricultural extensification without Getting infrastructure “right” is critical because infra- necessitating large trade-offs between conversion of structure choices have long-lived and difficult-to-reverse protected areas and agriculture.17 Rather, with proper impacts on land, wildlife, water use, and future patterns planning to target agricultural development in high of development. Infrastructure decisions influence the productivity lands, while conserving adjacent protected type and location of development and, as such, create areas for other environmental services, there are large substantial inertia in economic systems, with irreversible opportunities for win-wins. consequences that need to be weighed against alterna- tives. The right infrastructure also offers substantial co- benefits that could enhance the productivity and earning 17 Another variable that needs to be considered is precipitation levels and capacity of the country’s natural capital. This is especially variability. Tanzania’s Tourism Futures 11 Development of large strategic infrastructure establishing and enforcing transportation and develop- to promote growth and connectivity can be ment corridors that maximize development of targeted consistent with efforts to conserve the natural zones but protect Tanzania’s most valuable natural assets that are the basis of Tanzania’s tour- habitats—is needed to ensure long-term resilience of ism. Strategic planning of infrastructure—through natural habitats. FIGURE 3.3.  SOIL CATION EXCHANGE CAPACITY Source: FAO18. 18 http://data.fao.org/map?entryId=065ec570-b1db-11db-8beb-000d939bc5d8. 12 Tanzania’s Tourism Futures CHAPTER FOUR TOURISM FUTURES Tourism in Tanzania is at a crossroad. The country has done exceptionally well in building a resilient and high-revenue-generating tourism industry that brings significant national economic benefits. However, as noted in the previous section, the path going forward is not without challenges. There are far-reaching strategic decisions to be made. Should the country seek ever greater tourist numbers and thus compete more intensively and directly with its rivals in the “mass” market? Or should it retain its exclusivity? Or might there be options to segment the market with a variety of differentiated products that combine exclusivity in some locations with more intensive development in others? And how should tensions between ever-rising land, water, and infrastructure needs and those of the wildlife tourism industry be resolved? To shed light on these questions, the GoT, through TANAPA, has requested the World Bank to explore the issues through rigorous economic model- ing approaches. Two contrasting scenarios were selected to provide insights into possible future scenarios: »» Spatially concentrated tourism development in the Northern Cir- cuit. The first scenario assesses increasing development in the Northern Cir- cuit with a focus on the iconic Serengeti ecosystem. This scenario describes a spatially concentrated development strategy aimed at enhancing economic activities within and in the immediate neighborhood of the SNP. The policies to be considered include an expansion of agricultural output to stimulate the local economic activity, combined with pressures in the carrying capacity of the ecosystem emerging from a variety of factors, including intensified devel- opment and concentrated tourism. This is analogous to a business-as-usual trajectory that represents the current situation with growing pressures on the ecosystem. »» Geographic diversification and inclusive tourism development by building the Southern Circuit. The second scenario promotes tourism development in “new” areas of Tanzania (with a focus on the RNP) while empha- sizing measures to better promote local economic linkages. This recognizes that economic potential varies with geographic endowments and ­ maximizing Tanzania’s Tourism Futures 13 returns calls for investing in the geographic com- BOX 4.1.  THE HIDDEN ECOLOGY OF THE parative advantage of each region. In this scenario, SERENGETI investments would recognize and build upon the economic potential of each location. The focus Biologists have been studying the ecological structure and dynamics of the Serengeti since the 1950s; it is one of the would be on exploring the constraints and oppor- best studied ecosystems on the planet having produced tunities of the RNP as a complement and possibly over 500 widely cited scientific papers, the key results of an alternative to the Northern Circuit. which are collated in the three edited Serengeti volumes (Sinclair and Arcese 1995; Sinclair and Norton-Griffiths A. TOURISM IN THE 1979; Sinclair et al. 2008); the fourth volume will appear in 2015. The mammal species living in the Serengeti illus- SERENGETI ECOSYSTEM trate almost every known social system: from the unusual There can be little doubt that the allure and monogamy of the jackals and nocturnal cats (Moehlman iconic status of the Serengeti has been pivotal in 1986) to the more sociable groups of lions and hyenas whose fiercest enemies are both each other and members building Tanzania’s tourism industry. The Seren- of their own species (Grinnell et al. 1995; McComb et al. geti is the last intact, fully functioning savanna wilderness 1994). The antelope similarly illustrate a social system that ecosystem in Africa. It is arguably Africa’s premier tour- ranges from the monogamous family groups of dik-diks, ist destination and most people have it on their “bucket through the extended family groups of the giraffe, to matri- list”—a place to see at least once in their lifetime. Few archal societies of elephants and the harems of impala and tourists to Tanzania depart without a visit to the Seren- wildebeest (Jarman and Jarman 1979). All of these social systems lead to selection for the different morphologies that geti. Its central attraction is its wildlife, namely the vast make each species in turn dependent upon the way that herds of wildebeests and zebras that migrate northward resources are distributed and defended. from their calving grounds in the southern part of the ecosystem in February to arrive at Kenya’s Maasai Mara Reserve for the dry season months of July and August. Following the migration of the wildebeest are signifi- of the ecosystem; they are keystone species, and cant numbers of predators: lions, hyenas, cheetahs, and their abundance determines key ecosystem pro- leopards. The open grasslands of the Serengeti provide cesses such as fire frequency and intensity as well as the world-class opportunities to get photographs of these abundance of the major predators, including lions and species interacting in the wild and hunting in the sur- hyenas. Their migration and daily movement patterns rounding reserves is another significant draw. The eco- transfer nutrients from the highly productive soils of the system19 also contains a further 40 easily visible mammal southern part of the ecosystem and concentrate them in species, over 500 bird species, and numerous plants and northern “grazing lawns” that can be used by smaller her- animals (Morell 1997). The Olduvai gorge runs through bivores that focus on shorter grasses during the dry season the southern part of the ecosystem. Over 70 years of (McNaughton 1984). Suppression of fires by wildebeest archaeological study here have produced a vast trove of grazing has allowed the woodlands to recover in the cen- sub-fossils that clearly outline the world where humans tral and northern parts of the ecosystem, creating a large first appeared as a species (Leakey and Hay 1979). In carbon sink. fact, the Serengeti provides the only remaining oppor- The principle threats to the Serengeti are those tunity to consider, and understand the world as humans driven by demands for grazing land, poaching, first saw it (see box 4.1). an aggressive expansion of tourism, and plans The vast herds of wildebeest that attract both the for potentially intrusive development. Climate tourists and the predators are the central ­ drivers change may eventually be a threat, but it is more likely that this will initially manifest itself as increased frequency of extreme droughts (both longer and drier) followed by 19 Throughout this paper, the Serengeti ecosystem is consistently defined to imply the ecological biome rather than the administrative zones that encompass unusually excessive rains that lead to significant erosion. three types of protected areas or conservation zones. The impact of climate change may not be felt for another 14 Tanzania’s Tourism Futures BOX 4.2.  A DESCRIPTION OF THE ANALYTICAL MODELING FRAMEWORK USED The three main users of the Serengeti are included in the issue that grows more pervasive with rising population densi- model: (i) tourists who are attracted by the abundance of wild- ties. The model allows for imperfect regulation with breaches life, (ii) trophy hunting ventures that are allocated a hunting of regulatory quotas and possible legal sanctions for poaching quota by the government, and (iii) local residents who engage and encroachment onto areas reserved for wildlife. in two types of activities; they hunt wildlife (bushmeat) for consumption and farm within the ecosystem under consid- The bioeconomic model is then linked to a CGE model. eration. At the core of the CGE is the SAM, whose architecture In keeping with existing literature, the focus is on a single reflects the main components of the Tanzanian economy. representative species, the wildebeest. This simplification The information for the SAM is drawn from the GTAP is reasonable in the context of the Serengeti and has been database which is augmented with other data to extend the adopted in the biological literature (for example, Holdo et al. natural resource component of the model. A CGE approach 2011). Wildebeest are widely regarded as the keystone species seems warranted in this context, given the size of the tour- in the Serengeti. They fulfill important ecological functions ism and wildlife sector and the importance of the Serengeti as ecosystem regulators and also have significant impacts on to the national economy of Tanzania. Tourism in Tanzania the local economy. Data on tourism also indicate that tourist is among the largest sources of foreign exchange, estimated numbers closely correlate with wildebeest populations, sug- at over US$1.28 billion and the overwhelming majority of gesting that they remain an important draw card for visitors, benefits derive from tourist visits to the Serengeti. Addition- especially because of the migration. As noted earlier, for the ally, the government earns significant revenue from fees and locals, the wildebeest are a primary source of protein. licenses for tourism and trophy hunting. A CGE approach is also useful in that it provides a consistent framework to It is hard to overstate the challenges of regulating an area assess the overall and distributional impacts of trade-offs as large as the Serengeti—an expanse extending over 25,000 between segments of the economy, such as ecosystem and km2 and spanning an international border. Poaching by the environmental losses in the Serengeti that occur as a conse- local population is a concern. Simultaneously, land conver- quence of gains in other parts of the economy (for example, sion and encroachment, especially in the buffer zones is an agriculture, mining, and so on). 25 to 30 years (Holdo et al. 2011). In contrast, human incidence in rural areas. There are also a host of other ­ population growth around the Serengeti is already high proposals involving intensifying tourism and intrusive and increasing. Understanding the economic role and activities or infrastructure that could either collectively linkages of the Serengeti ecosystem with sectors of the or individually lower the carrying capacity of the eco- economy is not without significance for an economy system, especially if they impede the wildebeest migra- so dependent upon natural-resource-based revenues. tion which helps sustain the high density of ungulates.20 Accordingly, this study has developed linked models to Finally, if increased tourism is to remain concentrated capture connections between renewable resource (wild- in the Northern Circuit, this will have repercussions for life) stocks and flows and the resulting micro and macro- the current high-value niche market. These effects are economic impacts. A summary of the models used is in explored first in the context of a bioeconomic (renew- box 4.2, with full technical details relegated to appendices able resource) model and followed by an assessment B and C. of the economy-wide impacts. Technical details are in appendix B. Reflecting current policy deliberations, the simulations explore three key issues: policies to boost agricultural productivity, a declining 20 A decline in numbers could be a result of restrictions on the ability of wil- carrying capacity from the interconnected suite debeest to track temporal shifts in high-quality forage resources across the landscape. In the most rigorous quantitative assessment available, Holdo et al. of pressures, and the effects of boosting tourist (2011) find that habitat fragmentation resulting from such structures (even with- numbers. Policies to intensify agricultural productivity out habitat loss) would lead to a projected median decline of 38 percent of the are a clear and necessary priority given the high poverty population. Tanzania’s Tourism Futures 15 TABLE 4.1.  EFFECTS OF POLICY CHANGES Combined 20% Increase 20% Increase in Agricultural Profits Combined + 20% Reduction in in Agricultural and 20% Reduction in Doubling of Baseline Carrying Capacity Profits Carrying Capacity Fines Wildebeest (#) 1,120,000 855,000 810,000 600,000 740,000 Harvest (#) 300,000 210,000 200,000 140,000 180,000 Tourists (#) 289,000 260,000 240,000 200,000 210,000 Land to wildlife (km2) 17,300 17,600 16,900 17,200 18,100 The results suggest that small and unconnected from agriculture rise, the amount of land devoted to agri- pressures to the ecosystem combine to deliver dis- culture increases. Once again, wildlife numbers decline by proportionately larger and unwelcome impacts. about 25 percent to 810,000, with a corresponding fall in In other words, combined pressures have synergistic tourist numbers and the wildebeest harvest (for example, effects, with one factor exacerbating the effects of the hunting off-take). other, so that the joint effects exceed the sum of the indi- vidual impacts. The outcomes are in table 4.1. The first The next column—termed the combined scenario—con- column summarizes the baseline case which describes the siders the combined effects of 20 percent higher agri- current situation. The baseline simulation tracks observed cultural profits together with a 20 percent decline in the outcomes with reasonable accuracy, projecting about 1.12 carrying capacity. This time there is a much more dra- million wildebeest in the steady state, which corresponds matic decline in wildebeest numbers (by about 50 percent) closely to an actual population of between 1.2 and 1.3 to 600,000 together with an equally significant reduction million animals. The projected (legal and illegal) hunting in the hunting off-take and tourist numbers by almost 30 off-take at 300,000 is somewhat larger than the estimated percent. The implication is clear. The combined pressures harvest, perhaps reflecting the clandestine nature of much have synergistic effects, with one factor intensifying the hunting, while projected tourist numbers at 282,000 are effects of the other, so that the joint effects exceed the sum within the current range of between 200,000 and 330,000 of the individual impacts. visitors a year. Could these negative consequences be reversed Consider first the effects of a decline in the carrying capac- through improved enforcement? The final column ity, which could occur for a number of reasons (examples considers the optimistic, though unlikely, case where all include the numerous intrusive structures that would penalties are doubled. While there is some improvement impede the migration, high intensity tourism, mining, or in wildebeest numbers, the decline in the population is other pressures). Suppose that carrying capacity declines still significant at 32 percent. Evidently, though increas- by (a modest) 20 percent, which is lower than median ing penalties may lead to improved compliance, this does predictions in the scientific literature (see, for example, little to address the root cause of the decline in wildlife Holdo et al. 2011).21 In such a case, wildlife numbers fall numbers—a lower carrying capacity resulting from a by about 22 percent to 850,000 and tourist numbers also degraded ecosystem. decrease. The next column explores the effects of a 20 percent increase in agricultural revenues. As the payoffs These results have striking implications for pol- icy and suggest the need to avoid damage in the first instance if the economic gains outweigh the 21 The detailed simulations by Holdo et al. (2011) based on a spatially explicit foregone benefits. They suggest the need to be alert model suggest a median population decline of 38 percent. To guard against exaggerating possible impacts, we consider a more modest reduction in carry- to potential synergisms, which may lead to unwelcome ing capacity. surprises when multiple impacts interact. Of greater 16 Tanzania’s Tourism Futures TABLE 4.2.  BOOSTING TOURIST NUMBERS need to be accompanied by a reduction in farmed area Combined 20% Combined (intensification) rather than the reverse. Agricultural Increase in Scenario expansion is often the stated rationale for reducing land Agricultural Profits with in and around protected areas, which is the opposite of and 20% Reduction Boosting the optimal response implied by this model. Conversely, if in Carrying Tourist the carrying capacity of the Serengeti ecosystem can be Capacity Numbers preserved or increased, the optimal response would sug- Wildebeest (#) 600,000 600,000 gest an expansion of agricultural land. Harvest (#) 140,000 150,000 Tourists (#) 200,000 218,600 Could the economic benefits of these changes Price change (%) 0 21% outweigh the potential costs? To address these issues, the results and model of the ecosystem are imbed- ded into a (macroeconomic) CGE model to assess the economy-wide consequences of the changes. A CGE c ­ oncern is that the standard policy instruments—fines approach is also useful in this context since it provides and enforcement of quotas—may do little to reverse the a consistent framework to assess the overall and distri- population decline when the carrying capacity and hence butional impacts of trade-offs between segments of the productivity of the ecosystem is diminished. This result economy, such as ecosystem losses in the Serengeti that has implications for the way intrusions into protected occur as a consequence of gains in other parts of the areas are managed. Often as an offset or compensation for economy. The introduction of wildlife in a CGE model is environmental damage, funds are provided for improved a novel feature of this work that has not been attempted environmental management. These results indicate that previously. this approach may not be highly effective once the engine of sustainability has been damaged. The framework is useful to investigate trade-offs between sectors. To explore a set of reasonable trade-offs, it is Increasing tourist numbers under the pressures assumed that agricultural profits (economy-wide) rise identified would be challenging, with possibly by 20 percent or about US$100 million and connectiv- adverse impacts on net tourist revenues. It is ity costs decline through the economy by 15 percent, instructive to consider the consequences of boosting tour- or about US$50 million, while there is a reduction in ist numbers in the combined scenario. Table 4.2 summa- carrying capacity of 20 percent. To guard against exag- rizes what might occur with attempts to increase tourist geration of impacts, the assumed benefits from the pro- arrivals with a diminished Serengeti ecosystem. The first posed changes in the Serengeti are considerably higher column outlines the baseline situation and the second the than suggested gains while assumed impacts on carrying outcome of the combined scenario. With a diminished capacity are lower than suggested by recent demographic tourism product on offer it would only be possible models.22 These changes would result in a reduction in to increase tourism numbers by reducing prices. proceeds from international tourists of US$552 million Column 4 records the outcome. To achieve a target close per year.23 To avoid overstatement of benefits, tour- to even a 10 percent increase in tourism numbers, price ist expenditures are significantly underestimated. Data would need to decline dramatically (by close to 20 per- reported in the WTTC suggest expenditures of about cent), suggesting that net revenues accruing from tourism US$300 per day in Tanzania while we assume a more would drop significantly. The reason is obvious: with a less modest US$200 a day. desirable product on offer, an increase in visitor numbers could only be achieved by lowering prices sufficiently. 22 The assumed changes are far above what is suggested might eventuate (see The results provide other instructive guidance GoT 2011; Holdo et al. 2011). for policy. Contrary to popular policy wisdom it suggests 23 Tourist numbers go from 750,000 to 550,000; expenditure per day is US$200 ­apacity that policies that diminish ecological carrying c with 10 days average stay. Tanzania’s Tourism Futures 17 TABLE 4.3.  CGE SIMULATIONS (IN US$, MILLIONS) Combined 20% Double Fines with 20% Reduction in 20% Reduction in Reduction 20% Increase Carrying Capacity, Carrying Capacity, in Carrying in Agricultural 20% Increase in 20% Increase Capacity and Profits and 15% Agricultural Profits, in Agricultural 15% Fall in Fall in Travel 15% Fall in Travel Profits, 15% Fall in Baseline Travel Costs Costs Costs Travel Costs Harvest (Value) 750 409.31 265.31 141.48 292 Tourism (Value) 578 458.28 427.21 285.56 341.52 Value added 26,461 25,233 25,451.23 24,429.4 24,946.44 Change in value added – –1,227.37 –1,009.77 –2,031.60 –1,514.56 (–4.6%) (–3.8%) (–7.7%) (–5.7%) Urban households (Change) – –434 –375.9 –730.5 –546.4 The effects are diffused through the economy and which typically considers impacts and issues separately especially large among poor rural households. and by sector. For instance, debates on the volume and The economy-wide effects emerge from the adverse impact of tourism and tourist infrastructure seldom con- exchange rate impacts associated with a decline in tour- sider effects emanating from the agriculture and land use ism. When tourism revenues fall, the exchange rate is or connectivity and vice versa. Managing this complex affected so that the effects are transmitted to most other natural asset calls for holistic and comprehensive plan- sectors of the economy. The simulations in table 4.3 show ning approaches. that even in a case when there is a very large positive shock on agriculture, to compensate for a loss of bush- meat, there is a net loss registered in the rural sector as B. DIVERSIFYING THE a result of economic contraction. Value added (a proxy TOURISM PRODUCT—THE for GDP) also changes by more than the flow of tourist revenue as a result of changes in the exchange rate effects. CASE OF RUAHA NATIONAL The simulation which considers the case of a combined PARK increase in agricultural profits (of 20 percent), a decline in Tanzania possesses a rich storehouse of tour- transport costs (of 15 percent), and a decline in carrying ist attractions and has the opportunity and poten- capacity (of 20 percent) indicates that value added (GDP) tial to diversify its tourism product by investing in the declines by about 7 percent. geographic comparative advantage of each part of the country. Recognizing that crowding diminishes the eco- In summary, the results suggest that the Seren- nomic value of tourism in the Serengeti, there would geti is a valuable economic asset and that policies need to be investments in building tourism at new which alter revenue flows will have wide-ranging destinations—a distinctive tourist experience, with a impacts that spill over to other sectors of the differentiation strategy. Coupled with its immense natu- economy. Understanding the direction and magnitude ral endowment, there is the potential for Tanzania to of these spillovers is crucial to policy analysis. The exer- solidify and consolidate its emerging position as Africa’s cise indicates that it would be difficult to compensate for premier wildlife tourism destination, similar to the sta- the economic losses from the ecosystem with other policy tus achieved by Costa Rica. interventions. In managing this asset it is also crucial to consider complementary impacts of disparate pressures A Southern Circuit exists, but the route is poorly as a result of possible synergistic effects. This suggests known and infrequently traveled. The RNP has long practical and conceptual challenges for policymaking been recognized as an ecological jewel with the potential 18 Tanzania’s Tourism Futures to become a major tourist destination in the Southern TABLE 4.4.  A 10 PERCENT INCREASE IN Circuit (Fox 2005). Established in 1910 as the Saba Game TOURISM VALUES Reserve, the RNP now covers an area of about 20,000 Baseline Absolute km2. It is the largest national park in Tanzania, the sec- (in 2010 Impact ond largest in Africa and serves as a vital watershed in its US$, (change in 2010 Percentage landscape. The RNP remains a central pillar in plans to millions) US$, millions) Impact diversify tourism in Tanzania through a Southern Circuit, Value added 26,001.97 239.35 0.92 aimed at relieving ever-increasing pressures in the North- Land 1,966.00 18.86 0.96 ern Circuit and the Serengeti. Yet, visitation rates are low, Labor 12,725.00 114.19 0.90 in part because of high travel costs. Capital 11,311.00 106.30 0.94 Urban 13,437.00 124.64 0.93 Spectacular landscapes around the Ruaha River Rural 509,961.00 130.27 0.03 combined with an abundance of charismatic spe- Tax and 1,241.00 15.54 1.25 cies make Ruaha an obvious tourist attraction. government The diversity and density of charismatic species is excep- revenue tionally high in the RNP, reflecting variations in flora and vegetation.24 Among its many accolades the Ruaha land- scape can boast the following: economy. However, the spatial distribution of benefits is »» 10 percent of all the lions left in the world, in a far from equitable, with the bulk of benefits accruing to period where they have vanished from over 80 per- urban households (as a result of the nature of linkages cent of their range of the sector and the exchange rate effects) and a smaller »» The third largest population of wild dogs fraction of benefits in the rural sector. This once again »» The second largest elephant population after highlights the importance of enhancing rural sector link- Botswana ages with tourist spending.25 »» Prominent endemics such as the newly discovered Kipunji monkey Commercializing Ruaha’s tourism potential has not been without challenges. Its many attrac- The protected area also encompasses two “important bird tions are largely unknown in the world of nature-based areas” and two potential Ramsar sites (WCS 2006). The tourism and few visitors to Tanzania arrive at this spec- RNP is deemed to be one of the most significant areas in tacular location. Table 4.5 compares tourism in Ruaha the world for large carnivores and their ungulate prey. to that in the Serengeti. In a typical year the Serengeti receives between 250,000 to 330,000 visitors, while If the Southern Circuit (including Ruaha) suc- Ruaha receives about 20,000. The constraints appear to ceeds in boosting tourism revenues by even 10 lie not in the availability of accommodation; there are percent, this would bring significant benefits to an adequate number of lodges in Ruaha (for the given the economy as a whole. Table 4.4 summarizes the visitation rates). Likewise the RNP entry fees are clearly macroeconomic consequences of a 10 percent increase in insignificant compared with total travel costs incurred by tourist revenues. Overall value added (a proxy for GDP) international tourists. The obstacles to Ruaha’s growth would rise by about 1 percent and government revenue must lie elsewhere. Visitor profiles, though sparse, suggest by about 1.25 percent. Most notably, benefits are equally that the typical Ruaha tourist seeks a more discerning and distributed between the primary factors of production— land, labor, and capital—suggesting that the sector may be a force for reducing aggregate inequalities in the 25 In comparing results, it is important to note that unlike the simulations in the previous section there is no assumed change in either trophy hunting or bushmeat hunting. As noted earlier, according to the simulations the latter has This is where Commiphora-Acacia vegetation communities merge with southern 24 extremely wide impacts on rural welfare because of the importance of bush- Zambezian Brachystegia-Isoberlinia (miombo) communities. meat as the primary source of protein. Tanzania’s Tourism Futures 19 TABLE 4.5.  COMPARING RUAHA TO THE and Ihefu wetland to the RNP. Downstream of the park, SERENGETI the Great Ruaha River joins the Little Ruaha to supply water to the Mtera and Kidatu hydropower plants. On Description Ruaha NP Serengeti NP average, the Great Ruaha provides 56 percent of run- Size 20,226 km2 14,763 km2 off to the Mtera and Kidatu hydropower stations, which (largest NP in (second largest in turn generate more than 50 percent of the country’s Tanzania) NP in Tanzania) electricity from hydropower. Significantly, the river is an Annual visitors 2011/12 2,100 330,000 (approx.) important livelihood resource and is used for domestic, Conservation fee for 24 livestock, and irrigation across the south and southwest hours—visitors above the of the country. age of 16 years (US$) ––Citizens 3 (TZS 5,000) 6 (TZS 10,000) Until the early 1990s, the Great Ruaha was a ––Residents (expatriates) 15 30 perennial river which flowed through the RNP ––Foreign 30 60 and into the Mtera Dam but has since become Bed capacity inside the NP seasonal. River flows indicate an increasing frequency (number) and extension of zero-flow periods in excess of 50 days ––Excluding TANAPA 222 1,633 between 1990 and 2004 (Kashaigili et al. 2007). Compe- camps tition over water resources between upstream irrigation ––Including TANAPA 302 1,863 and other users continues to escalate. The major irrigated camps areas are located upstream and have expanded dramati- cally in recent years (from 3,000 ha to over 115,000 ha (World Bank 2014). During the dry season, from July to November, the river is the only source of water for down- authentic wildlife experience and is either on a second trip stream users who include subsistence agriculture, live- to Tanzania (having done the obligatory Serengeti visit) or stock, the RNP, and hydropower in the Mtera Dam which arrives at Ruaha from the Serengeti.26 Attracting a larger has in the past relied upon dry season flows to augment proportion of the Serengeti tourists to Ruaha would do supplies (though the need for such supplies remains con- much to boost the park’s economic fortunes. However, tested; Kadigi et al. 2008; Machiba et al. 2003). despite efforts to promote Ruaha as part of the Southern Circuit, success has been elusive thus far, with an insignifi- cant increase in annual visitors from 19,721 in 2006/07 This has far-reaching consequences for the to 21,600 in 2011/12. immediate and long-term ecology of the park and its tourism potential. Lack of dry season flows There are three major challenges that constrain has had direct and observable effects as well as more sub- the development of tourism in Ruaha: competition tle indirect impacts on the downstream economy, water over water use, challenges of access, and the park’s obscu- quality, and ecology (see figure 4.1). Most immediately, rity in the public eye. lack of flows in the dry season lead to a decrease of buf- falo and other water-dependent species that have eco- nomic implications for the RNP. Buffalo are a high-profile WATER CONSTRAINTS species for photographic and hunting tourism. Currently, Water is the most-contested resource in the Ruaha’s tourism is confined to a small area along the river. area. The landscape and the economy of the region are As visitor numbers have increased, so has crowding along dominated by the Great Ruaha River, part of the Rufiji the Ruaha “River Drive,” leading to a decline in tourist Basin, the country’s largest. The river originates from the satisfaction (Fox, 2005). Therefore, to maintain the “wil- Usangu highlands and flows through the Usangu plains derness character” for which Ruaha is known, tourism must expand beyond its current area. However, drying 26 TANAPA officials, pers. comm. of the Ruaha River prevents expansion of tourism to the 20 Tanzania’s Tourism Futures FIGURE 4.1.  MAP SHOWING FORMAL IRRIGATION SCHEMES IN USANGU WETLAND Source: World Bank, Draft Hydropower Sustainability Assessment Report, 2015. downstream areas. Likewise, a lack of dry season water the Ruaha ecosystem. In the absence of data on the eco- adversely affects the subsistence farmers in the Wildlife nomic dimensions of the problem, the exercise can only Management Areas (WMAs) (Coppolillo et al. 2003) and be viewed as demonstrative and hypothetical. For policy reportedly leads to increased human-wildlife conflict as use there would be a need to calibrate the model with park predators prey on the livestock of nearby communi- actual data on livelihood attributes from the landscape, ties.27 None of this is conducive to attracting tourists in the which will require a minimalist, rapid data collection dry season when game-viewing is at its peak because of exercise. the concentration of wildlife around water sources. There is a general consensus that upstream The more subtle impacts include changes in the predator- abstraction of water, especially in the dry sea- prey balance and negative impacts on the livelihoods of son, induces water shortages among down- downstream users. While much attention has been given stream users.28 The irrigation schemes (for rice) are to the consequences on the energy sector, there has been located upstream of the hydropower plants. Water that is limited analysis of the effects on downstream users and not diverted upstream for irrigation or other purposes in the impacts on poverty levels in these areas. the Usangu flows naturally to downstream users, includ- ing the Mtera and Kidatu hydropower stations. There is Box 4.3 presents results from an illustrative assessment of the consequences of seasonal water deprivation in 28 However, there are dissenting views that the problem is independent of abstraction levels and is a consequence of alterations in land use and/or 27 A. Dickman, pers. comm. climate change. Tanzania’s Tourism Futures 21 BOX 4.3.  WATER SCARCITY IN THE RUAHA LANDSCAPE To better understand the linkages between water, the eco- ­eason is assumed to depend upon the availability of water. s system, and the economy, an analytical model was devel- The biology of the ecosystem is described by an extension oped for this report with the aim of identifying linkages that of the predator-prey model outlined by Fryxell et al. (2007). are often ambiguous and exploring trade-offs. Because of Carrying capacity depends essentially upon the availability of a lack of data on livelihoods in nearby communities, the dry-season water flows. results presented are based on assumed rather than actual The model illustrates how changes in water flow impact wild- parameters rendering the analysis limited for policy guid- life interactions and the incentives of subsistence farmers. As ance; however, results are illustrative. The formal model is the following figure shows, there are several key issues ema- in appendix B. nating from reduced water availability. With less water for The model incorporates the key economic decisions of the farming, there is an increase in bushmeat hunting, assumedly extremely poor residents who inhabit the lands downstream to replace missing calories. There is higher livestock mortal- and adjacent to the park (which are largely WMAs providing ity. In the short run, predator-prey imbalances favor predator joint management opportunities between state and communi- numbers as hunting becomes easier. However, this advantage ties) and survive through a combination of subsistence activi- quickly vanishes, not just because of reduced prey numbers ties: farming for domestic consumption; livestock rearing but also because of a diminished capacity to form prides. If for reasons that are well documented in the literature (cash, water shortages are significant and sustained, there is rapid store of value and tradition, food); bushmeat hunting which population decline as illustrated in the example below. There is a primary source of protein; and finally, the occasional is also an increase in predation on livestock, inducing greater lion hunt prompted by revenge killings as well as for ceremo- human-wildlife conflict in these equilibria. The figure shows nial purposes, usually as part of an initiation ceremony for how water constraints lead to proportionately lower lion adolescent males. Not unrealistically, farm output in the dry numbers in different equilibria. ­ Buffalo CC 100% Lion Buffalo CC 90% Lion Buffalo CC 80% Lion Buffalo CC 70% Lion Buffalo CC 60% Lion Buffalo CC 50% Lion Buffalo CC 40% Lion Buffalo CC 30% Lion Buffalo CC 20% Lion Buffalo CC 10% Lion 3.5 Lion 3.0 Numbers (× 1,000) 2.5 2.0 1.5 1.0 0.5 0.0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 an assumption that when optimally managed, average wet Kadigi et al. (2008) explore water allocation trade-offs in season flows are adequate for the needs of the Mtera res- greater detail and find that water used for hydropower ervoir (Lankford et al. 2007). However, when this assump- generates substantially higher economic benefits than tion does not hold, there remains a need to augment wet that used for agriculture. Their results are summarized in season flows with dry season supplies (Kadigi et al. 2008). table 4.6. In all scenarios examined, the economic value If so, this implies that there is a direct trade-off between of water for hydropower far exceeds that for agriculture. water used for irrigation and energy, suggesting that in the The result seems unsurprising as rice yields in the basin dry season water ought (in the optimum) to be allocated to are low and below the global average. Generally, water its highest valued use. productivity of rice in Sub-Saharan Africa ranges from 22 Tanzania’s Tourism Futures TABLE 4.6.  PAYOFFS FROM IRRIGATION TABLE 4.7.  APPROXIMATE ACCOMMODATION VERSUS HYDROPOWER AND TRAVEL COST AND Rice Hydropower TRANSPORTATION TIME Alternative Alternative Description Ruaha NP Chobe NP Description Scenarios Scenarios Average accommodation 390 580 Water used (mm3) 542–979 1,000–4,096 costs per person per Net value of water (US$/m3) 0.01–0.04 0.06–0.21 night full board—high Source: Kadigi et al. 2008. season (US$) Travel time by road from 11 hours (625 Chobe NP is nearest international km)—from located just next to airport Dar es Salaam Kasane Airport. 0.10 to 0.25 kg/m3, with an average yield of 1.4 tons/ha. Average price of one- 345 Chobe NP is China and some Southeast Asian countries have higher way air ticket from located just next to water productivities for rice, ranging from 0.4 to 0.6 kg/ nearest international Kasane Airport. m3 (Rosegrant et al. 2002). In contrast, in this basin, the airport (US$) equivalent figure is 0.11–0.19 kg/m3, with a correspond- ing value of US$0.01–0.04 per m3, reflecting lower yields and higher levels of water consumption (Kadigi et al. many ways unparalleled globally, offering a range of 2008). In contrast, the equivalent value for hydropower experiences. However, to be competitive it needs to offer varies from US$0.08 to US$0.21 per m3. a visitor experience that is no worse and preferably better than rivals in a similar category. A comparison of Ruaha However, a number of caveats are in order. First, the with Botswana and, in particular, the Chobe NP as a pos- results likely underestimate the benefits of transfers from sible rival destination is instructive. The products on offer irrigation as impacts on other downstream users (see are similar in many respects. Tourism (and the attractions, box 4.3) are not considered. Downstream water is needed scenery, and wildlife) in both locations are highly depen- by other users, including for livelihoods in WMAs and dent upon a river-based ecosystem. In the Chobe NP, as building tourism in the RNP. Second, alternative scenar- in Ruaha, the river in the dry season becomes the only ios that reverse these results are conceivable. For instance, source of water and survival for wildlife. Both parks are it could be assumed that there is an unexpected surge in renowned for their lions and large elephant herds. How- the availability of cheap supplies of oil and gas (perhaps ever, unlike Ruaha, Chobe is located close to the Victo- from recent exploration efforts or a further collapse of oil ria Falls and benefits from tourists who combine a visit to prices in global markets) that dramatically drive down the both attractions. marginal cost of thermal generation. This in turn would call for a switch on the margin from hydropower to ther- Table 4.7 compares accommodation and travel costs mal generation. Further, it is at times suggested that water as well as transportation times for both locations. The constraints derive entirely from climate change. Finally, it average cost of accommodation during the high season is arguable that in an idealized management system, the is US$580 in the Chobe NP and US$390 in the RNP. dams can be filled entirely with wet season flows and the The next tables show that arriving at Ruaha from vari- water stored for appropriate generation and use in the dry ous destinations in Tanzania is more time-consuming and season. expensive compared to the Chobe NP, which is located just next to an international airport. Thus, a more likely THE CHALLENGES OF ACCESS constraint for tourism development in the RNP is the To make Ruaha attractive to tourists, it must very high cost of traveling to the park, which on aver- be both accessible and affordable to its targeted age is US$345 for a one-way ticket (see table 4.9) or the market. Tanzania’s natural tourism products are in fact that it takes about 11 hours by road (see table 4.8) Tanzania’s Tourism Futures 23 TABLE 4.8.  APPROXIMATE DISTANCES BY ROAD From/To SNP (Seronera) Ruaha* Selous Dar es Salaam 965 km (14 hours) 625 km (11 hours) 230 km (6 hours) Arusha 335 km (5 hours) 700 km (14 hours) 1,000 km (14 hours) Selous – 855 km (17 hours) – SNP (Seronera) – 800 km (16 hours) 2,000 km (28 hours) Note: * Estimated transportation time during dry season. TABLE 4.9.  AVERAGE AVIATION PRICES Circuit, but does not mention Ruaha, and on the official (ONE WAY, US$) home page Ruaha is ranked eighth among the top ten destinations and below several with less to offer in terms From/To SNP (Seronera) Ruaha Selous of attractions.29 An Internet search can be uninforma- Dar es Salaam 450 330 175 tive also. A search with key words such as “Tanzania, Arusha 200 330 420 wildlife tourism, and lions” fails most often to bring up Zanzibar 335 420 210 any links to Ruaha, and when Ruaha is mentioned, it is Selous – 320 – typically in academic work from the Carnivore Project. SNP (Seronera) – 520 575 With such limited global recognition, it is no surprise that Ruaha’s tourist numbers lie far below potential. There needs to be a concerted effort to increase aware- from the closest i ­nternational airport (Dar es Salaam). ness and information about Ruaha’s many attractions. Moreover, despite the fact that the road network in the The branding of Tanzania as “The land of Kiliman- RNP has been ­ prioritized for improvement by TANAPA, jaro, Zanzibar, and the Serengeti” clearly warrants almost all the lodges inside the park are closed during the reconsideration to be made more inclusive to reflect the rainy season (April–May) as the roads are impassable dur- diversity of unspoiled destinations and what each has ing that period. The tourist experience is not measured by to offer. the product on offer alone but by the whole continuum of interactions that include travel time and costs. Consumers A marketing strategy is needed that fits the are becoming better informed. Price, quality of accom- range of attractions on offer with market pref- modation, and the product on offer are critical deter- erences. It is unclear without further research whether minants when selecting a destination. They increasingly Ruaha is better suited to the generic traveler or more seek destinations that offer “value for money.” Given that specialized segments such as experiential travelers and Ruaha offers a less attractive experience, especially during the growing adventure travel market. The length of dry periods when river flows have ceased, and is the more stay of the average visitor in Tanzania is 11 days. The expensive destination to reach, competing with the Chobe most cost-effective way to increase tourist revenue is NP in Botswana may be difficult. to increase the length of stay, such as through offering additional attractions. The private sector has a clear In summary, the transport infrastructure and quality of role to play in leading this process, with the state pro- experience may not match the prices that the tourists have viding regulatory support to ensure that developments to pay in competing markets. do not erode the economic or ecological value of the park. Finally, the form of marketing will also be critical. RUAHA—AN UNKNOWN DESTINATION? Internet-based marketing offers the most cost-effective Despite its many attractions, Ruaha receives lit- opportunity, but other vehicles need to be considered tle publicity in the official media and, more gen- erally, it is widely overlooked in travel media. http://www.tanzaniatouristboard.com/places-to-go/southern-circuit/ viewed 29 The Tanzania Tourist Board publicizes the Southern on August 3, 2014, 6 A.M. EST. 24 Tanzania’s Tourism Futures depending upon targeted ­ market and strategy. Consum- reviews and experiences of destinations and products) ers have always taken advice from other travelers when are extremely popular. The two most significant sources selecting a destination, and the Internet has increased of information when selecting a long-haul holiday are possibilities and the range of opinions available. Web- previous experience (that is, the traveler has been there sites such as Trip Advisor (where travelers post their own before) and recommendations (Frias et al. 2012). Tanzania’s Tourism Futures 25 CHAPTER FIVE WAY FORWARD Tanzania’s natural assets have catalyzed a buoyant and robust tourism industry that has served the country well, especially in times of economic volatility and recession. Its natural assets also play a pivotal role in sustaining the livelihoods of the rural poor, who are highly dependent upon ecosystem services such as bushmeat, hydrological flows from water-sheds, and fuelwood. The CGE analysis has demonstrated that the effects of natural resource depletion in the Serengeti have a disproportionate impact on the rural poor through the impact on tourism flows and the availability of livelihood resources. This suggests that degradation of the natural asset base could precipitate a downward spiral of poverty when alternative sources of employment are limited. The macroeconomic simulations reported in this study also suggest that the economic impact of the sector is often underestimated. The benefits are stronger than might appear, with cross-sectoral spillover effects and linkages that dominate those of other traditional sectors of the economy. Tourism as a labor-intensive industry has become an important source of employment in Tanzania and provides good quality jobs, especially to women30 who often have few other opportunities for well-paid employment. All of this has emerged as a consequence of the HVLD approach that has built a resilient sector. To build upon this success, Tanzania needs to play to the comparative advantage of each region and attraction. This calls for a strategy that maximizes tourism revenue and not tourist numbers. The latter, as demonstrated in this report, could prove to be counterproductive. However, with a high incidence of rural poverty there are opportuni- ties to further build the industry and strengthen linkages with the rural poor. BENEFIT SHARING AND BUILDING LINKAGES WITH THE LOCAL ECONOMY There is a need to strengthen linkages with the local economy and develop policies and incentives to share benefits with the poorest who often live close to tourist attractions. Current benefit-sharing policies (summarized in box 5.1) have had limited impact in 30 Respectively 22 percent and 24 percent of permanent Tanzanian employees in managerial and non-managerial posi- tions in hotels are female (Survey prepared for the HAT, 2014). Tanzania’s Tourism Futures 27 BOX 5.1.  THE WILDLIFE MANAGEMENT AREAS AND OTHER BENEFIT SHARING IN TANZANIA As a result of past failures, traditionally centralized wildlife ­ overing an area of 28,389 km2 or about 3 percent of Tanza- c management policies and the crisis facing wildlife popula- nia, have successfully completed the required 12-step partici- tion the community-based natural resource management patory process leading to WMA gazettement and 22 others (CBNRM) approaches and Wildlife Management Areas are in various stages of development. Considerable progress (WMAs) emerged during the reform process in the 1990s. has been made during the past decade in terms of creating a Through direct involvement of local communities in manag- basic legal and institutional framework for WMAs; support- ing wildlife for tangible local benefits WMAs was recognized ing communities to establish the basic management structures as the best option for conserving wildlife outside. Protected and land use patterns required to form and oversee WMAs; Areas (PAs). Passage of the 1998 Wildlife Policy (revised 2007) and building broad support for WMAs as a key component of laid out the legal underpinnings of Tanzania’s approach to both conservation and natural resource-related development CBNRM through the establishment of WMAs. This policy policies and approaches in Tanzania. promoted wildlife management at the village level by allow- However, despite this significant progress, major challenges ing “rural communities and private land holders to manage remain, particularly in the economic and governance realms. wildlife on their land for their own benefit” and “devolving A U.S. Agency for International Development (USAID) eval- management responsibility of the settled and areas outside unsettled protected areas to rural people and the private sec- uation report of WMAs performance (USAID 2013) found many critical issues threatening the success and sustainability tor.” New WMA Regulations under the 2009 Act were issued of WMA namely: (i) lack of transparency and accountabil- in 2012, which contain a number of key changes, including ity among WMA stakeholders; (ii) incomplete devolution of strengthening the communities’ involvement and influence responsibilities to WMAs; (iii) costs of establishing and run- over trophy hunting concession allocations in WMAs, as well ning WMAs are too high and payments from government too as providing greater clarity around benefit-sharing. unpredictable; (iv) lack of diversified (and sustainable) reve- WMAs began to be formally implemented in 2003 and the nue streams; and (v) benefits to communities are low and are first WMAs were gazetted in 2006. Currently 17 WMAs, not perceived to be adequate at the household level. inducing a greater integration of the industry into the especially when revenues are captured by community local economy. This arguably reflects the large gap that leaders and the elite. prevails between the industry’s needs and the available supply capacity in the surrounding rural areas. Economic Building local capacity. Another promising model participation by the poor would be difficult when they entails building supply chains into local communities to are unable to provide the goods and services that are of strengthen economic linkages. Agriculture is an obvious value to the industry. The challenge for policy is to create entry point because of the availability of land. However, a set of commercial incentives for tourism operators to constraints would likely arise as a result of a lack of local strengthen local linkages while remaining commercially knowledge, capacity, and work culture, all of which com- profitable. A number of schemes merit consideration. bine to limit the ability to generate reliable supplies to the industry. To address these issues would require intensive Community conservancies. Box 5.2 describes the programs of capacity building to develop partnerships Namibian experience of Community Conservancies. and a mutual understanding of priorities between the These are an extension of the more familiar CBV between industry and local communities. communities and private tour operators, where pieces of community reserved land are subleased to private tour- A. MAINTAIN AND ism investors for direct, annual set sub-lease base fee; bed- night fees; and in some cases, extra activity fees per day STRENGTHEN THE HVLD that are paid directly to the village governments. Evidence SEGMENT suggests (Platteau 2004, Wong 2010) that problems often The HVLD approach has been the default strategy that communities, arise with the distribution of benefits within ­ has served as a robust source of employment and growth. 28 Tanzania’s Tourism Futures BOX 5.2.  NAMIBIA COMMUNAL CONSERVANCIES AND TOURISM Communal conservancies in Namibia grew out of the recogni- a committee representative of community members. Con- tion that wildlife and other natural resources had disappeared servancies are also required to draw up a clear plan for the in many parts of the country and that the livelihoods of rural equitable distribution of conservancy benefits to members. communities could be improved if these losses were reversed. Once registered by the MET, the conservancies gain user The Namibian CBNRM approach is based on devolving user rights to sustainably use wildlife and tourism and retain rights over natural resources and management authority to 100 percent of the revenues generating from hunting and community institutions established in terms of national legis- tourism. lation. The policy and legislation provide an incentive-based The CBNRM program has become one of Namibia’s most approach to conservation—enabling communities to earn effective forms of rural development and is considered the income and other benefits from their sustainable manage- most successful in the region. There are currently 79 regis- ment of natural resources. Moreover, by linking conservation tered conservancies in Namibia, which occupy 15.4 million to poverty alleviation, conservancies provide livelihood and ha equivalent to 19 percent of the country. The total pro- employment opportunities while at the same time unlocking grammatic investment of N$1.2 billion from 1990 to 2011 great tourism development potential. has produced an estimated net national income of N$2.8 Conservancies are self-selecting social units or communities billion, while the Namibia CBNRM program has attained of people that choose to work together and become regis- a net present value of N$451 million, or the equivalent of tered with Namibia’s Ministry of Environment and Tourism an economic internal rate of return of 21 percent (NACSO (MET) and are in turn provided with technical advice and 2012). However, despite the success achieved to date, sev- support by the Namibian government and nongovernmental eral challenges confront the CBNRM program, namely, the organizations (NGOs). To meet the conditions for registra- financial dependency of conservancies on donors and govern- tion, a conservancy must have a legal constitution and clearly ment; weak institutional capacity of conservancies; increas- defined boundaries that are not in dispute with neighboring ing threats from commercial poaching; and lack of long-term communities. It must also have a defined membership and cost-effective and efficient support systems. The HVLD is an inelastic segment of market demand Address the Litany of Pressures on the Northern that has exhibited resilience and steady growth over eco- Circuit. Congestion, as it occurs in the Massai Mara nomic cycles. It attracts customers who are willing to pay Reserve or the Ngorongoro Crater, is not conducive to high prices for the experiences they desire. Nonetheless, a high-value tourism experience. Intrusive developments this is a market segment that is difficult to attract and one and over-building—a feature common in other tour- that can easily be lost if the product fails to meet expec- ist areas—is also certain to undermine the value of the tations. Forgoing this much-sought-after market niche product. Likewise, policies within and outside the eco- would likely be economically imprudent if the intention system that damage the carrying capacity and hence is to maximize revenues from tourism. the wilderness value of the ecosystem would also have counterproductive economic consequences that erode Preserve the Jewel in the Crown of Tourism. The the earning potential of this natural asset. The implica- allure and iconic status of the Serengeti has been pivotal tion is that there is a need to preserve and strengthen in allowing the country to maintain its status as an exclu- the status of the Serengeti as an HVLD destination that sive HVLD tourist destination. The Serengeti is the last caters to a different market segment to that of the Massai intact, fully functioning savanna wilderness ecosystem in Mara Reserve. This will allow the country to maximize Africa and its central attraction is the vast herds of wil- revenues from this market without entering into direct debeest that migrate north from their calving grounds in competition with a more volatile (and elastic) segment of the southern part of the ecosystem. There are risks that the market. current trends could undermine the earning potential of the Serengeti with adverse consequences that would be For HVLD tourism to succeed, the product on offer must transmitted widely through the economy. be rare, exclusive, or unique. The Serengeti clearly falls Tanzania’s Tourism Futures 29 into this category. The wildebeest migration is obviously ­ imply, in the absence of enforceable regulations, if water s unique and the authentic and uncrowded wilderness is made available to upstream farmers, it will be used so experience on offer is exceptional and atypical. By con- long as there are benefits from additional use (irrigation) trast, the experience (congestion and location) and prod- that exceed the opportunity costs of the users.31 Address- uct (wildlife observable) on offer at NPs would not be able ing this problem will be especially challenging given to attract the HVLD market segment. Second, since such the number and diversity of users and the regulatory HVLD assets are rare, by implication, there is less compe- ­constraints. tition, which allows for higher prices to be charged for the experience. Third, HVLD tourism attracts people who There are three ways in which water use can be con- care more about experience (wilderness) and less about trolled: through quotas (quantity controls); water pricing price (that is, more inelastic demand). This group might schemes; and payments to reduce water use (payment include the so-called high-net-worth individuals but also for environmental services). The first approach involves includes interest groups (hobbyists, birdwatchers, climb- regulating water use through physical quotas. However, ers, and so on). Hence, not every destination in Tanzania in the absence of water monitoring and measurement will fit into the HVLD category. systems and a transparent, credible system of sanctions for breaches, quotas will inevitably be unenforceable. Cul- B. DIVERSIFY THE PRODUCT tural and rights-based beliefs are other common reasons why registering for “water rights” is not seen as legitimate There is a need for a differentiated strategy that plays to in many communities. The second and more complex the economic strengths of each attraction and asset. alternative is to impose a price (fee) for water use. This is Going forward, the approach would need to build and often difficult to implement and resisted by users accus- differentiate tourism by location (for example, Seren- tomed to free water supplies. Finally, there is the possibil- geti versus Arusha NP versus the South); product (wild- ity to pay current users to reduce the amount of water life, beach, culture, adventure); and market segment extracted from the system, a Payment for Environmental (domestic, international, conference). Service (PES) scheme. This is more likely to gain com- munity acceptance so long as the payments cover oppor- The focus of tourism on the Northern Circuit has meant tunity costs. that Tanzania’s vast endowment of other tourist assets remains underused. The country has failed to adequately PES schemes are typically complex and call for consid- leverage the opportunities for employment, growth, and erable investment in monitoring and enforcement, and poverty reduction that these assets offer. Building tourism where institutional capacity is weak, it would be necessary in the Southern Circuit has not been easy in a market that to outsource implementation of the program. A prob- grows more competitive and better informed each day as lem with such schemes is determining the right price. If a consequence of improved connectivity and globaliza- payments are too small, users will have little incentive to tion. There are four preconditions that will need to be participate in the scheme (also part of the “additionality met to make the Southern Circuit a competitive offering problem”) and a payment too large will be both waste- for tourists who can choose between an array of similar ful and risk attracting new entrants, thus worsening the products. problem. In essence, the problem is that of asymmetric information—information on the opportunity costs of Address the challenge of water constraint. If the participation is private. A typical solution in such situa- RNP is to become one of the central attractions there is tions is to use auction schemes to extract private infor- a need to address the problem of dry-season water flows in the basin and restore flows to the NP. The problem 31 More formally, it is well known that each user will extract water to maximize is especially challenging because water use in this basin his or her payoffs, but overall entry will ensure that all rents from resource use is treated as an open access, common property resource, are depleted. In short, there is economic overuse of the resource, which is inef- where the number of users is difficult to control. Put ficient. 30 Tanzania’s Tourism Futures mation and generate more efficient outcomes.32 Without ­ arketing and packaging of these products. However, m adequate investment in water management and control, they receive little publicity. Tanzania’s marketing slogan as none of this will be feasible. “The land of Kilimanjaro, Zanzibar, and the Serengeti” simply reinforces the current bias in favor of the much- Common to all of these schemes is the need for greater visited Northern Circuit. A coherent and well-funded investment in administrative and institutional capac- marketing plan would need to be an essential part of the ity to build measurement and monitoring systems with diversification process. adequate enforcement capabilities. A system of property rights is needed that identifies users, defines their legal Develop a marketable product. The product on rights, and limits new entrants. Monitoring systems are offer must be competitive in both price and experience. needed to identify violations while effective penalties and Beach tourism is perhaps the most-competitive and well- rewards provide the incentives for compliance with the informed segment of the market, with models that cover rules. the entire range of prices. The price-conscious tourists are largely indifferent about location but sensitive to price, Access and costs. Inadequate infrastructure results in travel cost, and travel times. With a long coastline, there higher transportation times and costs to reach the RNP are opportunities to compete in many of the segments of from international airports compared to NPs in the the sun-sea-sand holiday destinations. Northern Circuit as well as the Chobe NP in Botswana. Moreover, lodges inside the RNP are forced to close down In summary, the tourism industry is central to the econ- during the long rainy season during the months of April omy of Tanzania with significant contributions to govern- and May as roads are impassable during that period. To ment revenues, employment, and the external balance. allow the RNP to become an alternative wildlife destina- Expanding the sector will require building on the coun- tion throughout the year and be attractive in terms of try’s distinctive strengths and the comparative advan- price, the road network both inside the park and the road tage of its many tourism assets. HVLD tourism is both to the park from the closest larger city, Iringa, need to be necessary and has done well in the past to build a niche upgraded. and robust industry in the iconic Serengeti. Dramatically expanding tourist numbers in the Serengeti will inevitably Branding and publicity. The Southern Circuit needs call for more competition in the less lucrative spectrum of to define and develop a brand to distinguish itself from the market. rivals. There is much that is unique to offer prospective tourists. Ruaha alone can boast 10 percent of all the lions There are also considerable opportunities elsewhere left in the world, the third largest population of wild dogs, to build a more diversified tourism product. This will the second largest elephant population after Botswana, call for combined efforts across sectoral boundaries, to and prominent endemics. The Selous Game Reserve is address the challenges of infrastructure, contests over a World Heritage Site with an impressively large array water resources, policies to strengthen linkages with the of wildlife that includes the endangered black rhinoc- rural poor, and finally, the need for a sound marketing eros. There are considerable opportunities for r ­ esourceful strategy. 32 This established result from the Theory of Contracts is being increasingly used in determining land-use decisions in environments with limited enforcement capacity (Laffont and Tirole 1999). Competition is the driving force behind this so-called “revelation mechanism.” In formulating a bid, participants face a trade-off between a higher net gain from raising the asking price and a reduced chance of winning (being selected). Competition thus reduces overcompensa- tion and increases cost-effectiveness. Auctions have the added advantage of act- ing as a price discovery mechanism for environmental services for which there are no well-established markets and thus no prices. Tanzania’s Tourism Futures 31 REFERENCES Arcese, P., J. Hando, and K. Campbell. 1995. “Historical and Present-Day Anti- Poaching Efforts in Serengeti,” edited by A. R. E. Sinclair and P. Arcese. Serengeti 11: Dynamics, Management, and Conservation of an Ecosystem. Chicago: University of Chicago Press. Baird, S., C. McIntosh, and B. Özler. 2001. “The regressive demands of demand- driven development.” Journal of Public Economics. 106: 27–41. Bank of Tanzania Quarterly Economic Bulletin. September 2013. Survey prepared for the Hotel Association of Tanzania (HAT) 2014. Barrett, C. B., and P. Arcese. 1995. “Are Integrated Conservation-Development Proj- ects (ICDPs) Sustainable? On the Conservation of Large Mammals in Sub-Saha- ran Africa.” World Development. 23 (7): 1073–1084. ———. “Wildlife Harvesting and ICDPs.” Land Economics. 74: 449–65. Coppolillo, P. B., L. Kashaija, D. Moyer, and E. Knapp. 2003. “Technical Report on Water Availability in the Ruaha River and State of Usangu Game Reserve, November 2003.” Wildlife Conservation Society and WWF-Tanzania Program. Fox, B. 2005. An Overview of the Usangu Catchment, Ifehu Wetland and Greater Ruaha River Ecosystem Environment (Mimeo). Frias, D. M., M. A. Rodriguez, J. A. Castaneda, C. M. Sabiote, and D. Buhalis. 2012. “The Formation of a Tourist Destinations Image via Information Sources: The Moderating Effect of Culture.” International Journal of Tourism Research. 14: 437–50. Fryxell, J. M., A. Mosser, A. R. E. Sinclair, and C. Packer. 2007. “Group Formation Stabilizes Predator-Prey Dynamics.” Nature. 449.7165 (2007): 1041–1043. Grinnell, J., C. Packer, and A. E. Pusey. 1995. “Cooperation in Male Lions: Kinship, Reciprocity or Mutualism?” Animal Behaviour 49.1: 95–105. Government of Tanzania. 2012. Tanzania Tourism Survey, March 2012. Hayward, M. W., J. O’Brien, and G. I. H. Kerley. “Carrying Capacity of Large Afri- can Predators: Predictions and Tests.” Biological Conservation. 139 (1): 219–229. Holdo, R. M., J. M. Fryxell, A. R. E. Sinclair, A. Dobson, and R. D. Holt. 2011. “Pre- dicted Impact of Barriers to Migration on the Serengeti Wildebeest Population.” PLoS ONE 6(1): e16370. doi:10.1371/journal.pone.0016370. Ikiara, M., and C. Okech. 2002. “Impact of Tourism on Environment in Kenya: Sta- tus and Policy.” KIPPRA Discussion Paper Number 19. Kenya Institute for Public Policy Research and Analysis. Jarman, P. J., and M. V. Jarman. 1979. “The Dynamics of Ungulate Social Orga- nization.” In Serengeti: Dynamics of an Ecosystem, edited by A. R. E. Sinclair, and M. Norton-Griffiths. 185–220. Chicago: University of Chicago Press. Jolles, A. E., D. V. Cooper, and S. A. Levin. 2005. “Hidden Effects of Chronic Tuber- culosis in African Buffalo.” Ecology 86 (9): 2358–2364. Jolles, A. E. 2007. “Population Biology of African Buffalo (Syncerus caffer) at Hluhluwe- iMfolozi Park, South Africa.” African Journal of Ecology. 45 (3): 398–406. Tanzania’s Tourism Futures 33 Kadigi, R. M. J., N. S. Y. Ndoe, G. C. Ashimogo, and S. Morardet. 2008. “Water for Irrigation or Hydropower Generation? Complex Questions Regarding Water Allocation in Tanzania.” Agricultural Water Management. 95 (8): 984–992. Kashaigili, J. J., M. McCartney, and H. F. Mahoo. 2007. “Estimation of Environmen- tal Flows in the Great Ruaha River Catchment, Tanzania.” Physics and Chemistry of the Earth, Parts A/B/C 32 (15): 1007–1014. Kideghsesho, J. R., J. W. Nyahongo, S. N. Hassan, T. C. Tarimo, and E. N. Mbije. 2006. “Factors and Ecological Impacts of Wildlife Habitat Destruction in the Serengeti Ecosystem in Northern Tanzania.” African Journal of Environmental Assess- ment and Management. 11: 17–32. Knapp, E. J. 2012. “Why Poaching Pays: A Summary of Risks and Benefits Illegal Hunters Face in Western Serengeti, Tanzania.” Tropical Conservation Science. 5(4): 434–445. ———. 2007. “Who Poaches? Household Economies of Illegal Hunters in Western Serengeti, Tanzania.” Human Dimensions of Wildlife. 12: 195–196. Landscan. 2009. http://web.ornl.gov/sci/landscan/. Laffont, J. J., and J. Tirole. 1993. A Theory of Incentives in Procurement and Regulation. Cam- bridge, MA: MIT Press. Lankford, B., and T. Beale. 2007. “Equilibrium and Non-equilibrium Theories of Sustainable Water Resources Management: Dynamic River Basin and Irrigation Behaviour in Tanzania.” Global Environmental Change. 17.2: 168–180. Leakey, M. D., and R. L. Hay. 1979. “Pliocene Footprints in the Laetoli Beds at Lae- toli, Northern Tanzania.” Nature. 278: 317–323. Lunogelo, H. B., A. Mbilinyi, and M. Hangi. 2010. Paper 20: Tanzania Phase 2. Global Financial Crisis Discussion Series. London: Overseas Development Institute (ODI). Machibya, M., B. Lankford, and H. F. Mahoo. 2003. “Real or Imagine Water Com- petition? The Case of Rice Irrigation in the Usangu Basin and Mtera/Kidatu Hydropower, Tanzania.” In a paper presented during the RUAHA +10 Seminar— 1993–2013: Ten Years of the Drying U of the Great Ruaha River, ICD, Sokoine University of Agriculture, Morogoro, Tanzania, 11–12 December, and quoted in Kadigi et al (2008). McComb, K., C. Packer, and A. E. Pusey. 1994. “Roaring and Numerical Assess- ment in Contests between Groups of Female Lions.” Panthera leo. Anim. Behav. 47: 379–387. Mduma, Simon A. R., A. R. E. Sinclair, and R. Hilborn. 1999. “Food Regulates the Serengeti Wildebeest: A 40-Year Record.” Journal of Animal Ecology. 68.6: 1101–1122. McNaughton, S. J. 1984. “Grazing Lawns: Animals in Herds, Plant Form, and Coevo- lution.” American Naturalist. 863–886. Mesochina, P., O. Mbangwa, P. Chardonnet, R. Mosha, B. Muti, N. Drouet, W. Cros- mary, and B. Kissui. 2010. Conservation status of the lion (Panthera leo Linnaeus, 1758) in Tanzania. Paris: Fondation IGF. Ministry of Natural Resource and Tourism, Tourism Division. 2012. Tanzania Tour- ism Statistical Bulletin 2012. Moehlman, P. D. 1986. “Ecology of Cooperation in Canids.” In Ecological Aspects of Social Evolution: Birds and Mammals, edited by D. I. Rubenstein and R. W. Wrang- ham. Princeton: Princeton University Press. 34 Tanzania’s Tourism Futures ———. 2014. “4. Ecology of Cooperation in Canids.” Ecological Aspects of Social Evolu- tion: Birds and Mammals. 64. Platteau, J. P. 2004. “Monitoring Elite Capture in Community-Driven Development.” Development and Change. 35.2: 223–246. Rentsch, D., and A. Damon. 2013. “Prices, Poaching, and Protein Alternatives: An Analysis of Bushmeat Consumption around Serengeti National Park, Tanzania.” Ecological Economics. 91: 1–9. Rosegrant, Mark W., X. Cai, and S. A. Cline. 2002. World Water and Food to 2025: Deal- ing with Scarcity. Intl Food Policy Res Inst. Sinclair, A. R. E. “Serengeti past and present.” Serengeti II: Dynamics, Management, and Conservation of an Ecosystem. 2 (1995): 3. Sinclair, A.R.E., and M. Norton-Griffiths, eds. 1995. Serengeti: Dynamics of an Ecosystem. Chicago: University of Chicago Press. Sinclair, A.R. E, and P. Arcese, eds. 1995. Serengeti II: Dynamics, Management, and Conser- vation of an Ecosystem. Vol. 2. Chicago: University of Chicago Press. Sinclair, A. R. E., C. Packer, S. A. R. Mduma, and J. M. Fryxell. 2008. Serengeti III: Human Impacts on Ecosystem Dynamics. Chicago: The University of Chicago Press. ———. 2009. Serengeti III: Human Impacts on Ecosystem. Chicago: University of Chicago Press. Stander, P.E. 1991. “Demography of Lions in the Etosha National Park, Namibia.” Madoqua. 18.1: 1–9. Tanzania Tourism Statistical Bulletin. 2012. Tourism Division, MNRT. UN World Tourism Organization and ILO. 2001. Economic Crisis, International Tour- ism Decline and its Impact on the Poor. Madrid, Spain: World Tourism Organization (UNWTO). USAID (U.S. Agency for International Development). 2013. Tanzania Wildlife Manage- ment Areas Evaluation. Prepared by Tetra Tech ARD and Maliasili Initiatives. WCS (Wildlife Conservation Society). 2006. “Current Wetlands Management Prac- tices in the Usangu Sub Catchments: A Review of Drivers, Pressures, State, Impacts and Responses.” Wong, S. 2010. “Elite Capture or Capture Elites? Lessons from the ‘Counter-Elite’ and ‘Co-Opt-Elite’ Approaches in Bangladesh and Ghana.” World Institute for Development Economics Research Working Paper: 82. World Bank. 2010. Kenya’s Tourism: Polishing the Jewel. World Bank and M. Critchley. 2014 (Draft). Earth Observation of the Mtera Catchment. WTTC (World Travel and Tourism Council). 2013. Travel and Tourism Statistics. ———. 2014. Economic Impact. Tanzania’s Tourism Futures 35 APPENDIX A TREND OF VISITORS ARRIVALS AT NPS FOR FY2006/07–2011/12 TREND OF VISITORS ARRIVALS AT NPS FOR FY2006/07–2011/12 Financial Year Sl. No. National Park 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 1 Arusha 55,098 56,076 56,393 52,907 65,645 78,636 2 Gombe 888 1,012 1,393 2,261 1,708 2,792 3 Katavi 1,746 2,041 2,359 2,137 3,128 3,003 4 Kilimanjaro 40,599 42,715 41,967 46,856 52,641 64,467 5 Kitulo 98 175 340 503 229 328 6 Lake Manyara 143,916 158,019 143,504 146,573 171,606 181,621 7 Mahale 1,235 1,293 1,048 710 1,239 3,688 8 Mikumi 29,462 33,574 34,912 35,539 42,292 45,535 9 Mkomazi n.a. n.a. 887 833 1,175 1,230 10 Ruaha 19,721 20,958 19,786 17,374 22,703 21,600 11 Rubondo 377 432 593 643 1,156 754 12 Saadani 2,224 3,711 4,159 4,564 7,490 13,533 13 Saa Nane n.a. n.a. n.a. 4,131 4,600 5,416 14 Serengeti 272,035 288,185 262,122 271,901 507,432 330,412 15 Tarangire 102,693 122,631 104,864 80,927 130,041 158,687 16 Udzungwa 3,003 3,602 4,648 4,027 5,942 8,870 Total 673,095 734,424 678,975 671,886 1,019,027 920,572 Source: Tanzania Tourism Statistical Bulletin 2012, Tourism Division, Ministry of Natural Resources and Tourism. Tanzania’s Tourism Futures 37 APPENDIX B SERENGETI BIOECONOMIC MODEL 1. THE BENCHMARK MODEL to hunting outside protected areas (Rentsch and Damon 2013).34 WITH A SOCIAL PLANNER This appendix begins by presenting a simplified bench- Because of the paucity of quantitative information, in mark model of the social planner’s problem and obtains what follows, functional forms are used that economize closed form solutions that are compared to second-best on data requirements. Accordingly, tourists are assumed outcomes under imperfect regulation. There are three to visit the area to view wildlife and their numbers Tt , main users of the Serengeti who are the agents in the depend on the stock of wildlife. As noted above, wildlife model: tourists who are attracted by the abundance of stocks are proxied by wildebeest population W (Sinclair et wildlife, trophy hunting ventures that are allocated a al. 2008). The number of tourists is then given by:35 hunting quota by the government, and locals who engage AW b ; 0 < b < 1. Tt = A 1 (1a) in two types of activities—they hunt wildlife (bushmeat) for consumption and farm within the ecosystem under The other main agents in the model are the trophy hunt- consideration. ing concessionaires who are granted an allocation Ω by the government.36 The harvest of wildebeest allocated to In keeping with the existing literature, the focus is on a sin- trophy hunting is: gle representative species, the wildebeest. It is important to emphasize that this simplification is reasonable in the Th = ΩW . (1b) context of the Seregenti and has been widely adopted in Finally, locals in the model engage in farming and hunting the biological literature (for example, Holdo et al. 2011). for bushmeat.37 Numerous empirical studies confirm that Wildebeest are widely regarded as the keystone species in bushmeat remains an important source of protein for the the Serengeti. They fulfill important ecological functions (mainly) poor households that live in the Serengeti ecosys- as ecosystem regulators and also have significant impacts tem. In some parts of the ecosystem, bushmeat hunting on the local economy. As the keystone species wildebeest numbers regulate biomass growth, tree dynamics, preda- tor populations, and ungulate competitors (Sinclair et 34 As noted earlier, this species is disproportionately affected by hunting, leading al. 2008). Reducing their numbers from habitat patches to concerns that this could result in wider trophic changes with impacts across the food chain (Holdo et al. 2011). results in marked changes in biodiversity and community 35 Note that it is possible to interpret this formulation as the outcome of a util- structure. All of this suggests that as a first approxima- 1 ity maximizing problem such that tourist utility U (T ) = (WT ) − PT where b tion a focus on the dominant species is reasonable in a b 1  W b  1−b modeling context. Data on tourism also indicate that P is price per tourist day, which upon maximization yields Tt =   ; In 1  P  tourist numbers closely correlate with wildebeest popu-  1  1−b equation (1) this implies that A =   and b = b/1− b, or equivalently b = b/ P lations, suggesting that they remain an important draw (1+b ). Hence, ∂T 1 (W/P )(b/1-b) and finally for completeness, we note that =− card for visitors, especially because of the migration.33 For ∂P 1− b the price elasticity of T is –P/(1−b). the locals, the wildebeest are a primary source of protein, 36 Trophy hunting in Tanzania is largely outsourced to commercial organiza- and the migration periodically brings large numbers into tions who market the hunting experience as an elite and high-end activity often proximity of humans and increases their vulnerability with “guaranteed” kills (Kideghsesho et al. 2006). The aim here is not to exam- ine the bioeconomics of trophy hunting but to explore the interactions of mul- tiple uses, so we abstract from more detailed industrial organization concerns 33 A regression yields the following log tourist numbers = 0.5 log (wildebeest) in what follows. + 0.211 time trend, with an R2 = 0.879 though the correlation need not imply 37 In an extension, we explicitly model labor supply decisions. This adds real- causality. (2.45) (0.81) ism but does not alter the qualitative conclusions, so is ignored in what follows. Tanzania’s Tourism Futures 39 is legal though subject to controls. If N is the legal allo- where r is the intrinsic growth rate, q is a parameter that cation of bushmeat, the model subsumes the case where measures the carrying capacity per unit of land available all hunting is illegal (N = 0) and allows for poaching and for wildlife and Ω and N are the harvest of trophy hunt- noncompliance in subsequent sections. Farming in this ers and locals respectively. We begin by deriving the social context could represent either livestock rearing (the tra- planner’s optimal allocations in an idealized situation of ditional Maasai activity) or crop production (dominant full compliance, with control variables Ω, N, L w, subject among other groups). An important feature of the model to the dynamics of W in (5). The Hamiltonian can be is that there is competition for land used either for farm- defined as: ing or wildlife. Let L = L w + Lg be the total amount of land allocated to wildlife and agriculture respectively and FW s Ω h [ p N N H = FW W + p L L g ]J NW further assume that L w = Lp + L wnp, where, Lp denotes land W + m[ rW (1 − ) − ΩW − N NW W ], (3a) in the protected national park and L wnp is land outside the q( L − Lg ) national park used by wildlife. Finally let Lnp = L wnp + Lg be land outside the protected areas. Utility to locals from where m is the co-state variable. hunting and farming is given by: The first-order conditions for a maximum are: V ( Π ) = [( r − c )(WN ) + ( P − k )(( L − Lw )]J = [ p N WN + p L ( L − Lnp − L p )]J ; J < 1, (1c) ∂H U = h − mW = 0, (3b) ∂Ω Ω where r and c define the benefits and costs respectively ∂H U from the harvest of wildebeest38 and pN = (p – c), while = J p N − m = 0, (3c) ∂N Π pL = (P – k) are unit profits from land used in agriculture, Lg = L – L w. ∂H U W2 = J p L − mr = 0, (3d) ∂L g Π q ( L − L g )2 Social welfare which is maximized by the planner is sim- ply the aggregate utility of the three agents and takes a • ∂H U p Cobb-Douglas specification, defined as: dm = − m − dm = −s − JU N N ∂W W Π W AW b )a ( B ( ΩW )g )q [ p N WN U = Tta Thg Πl = ( AW WN + p L L g ]J − m r − 2m r +m Ω + mN , (3e) q( L − Lg ) = FW s Ωh [ p N WN + p LW ( L − Lw )]J , where d is the discount rate. (2a) Using equations (3d) and (3e) and recalling that Lg ≤ Lnp, ba + g where ba + gq + J = f < 1 , s = ba q = f − J and gq a q the optimal allocation of land to wildlife is: F=A B . The stock of wildebeest evolves according to the usual rp N Lw = L − L g = W , logistical differential equation. This functional form has qp L been parameterized for the Serengeti wildebeest (Stratton np and Lw = L p otherwise. if L g ≤ Ln (4) 2012) and is used to proxy the evolution of this keystone species: Thus the ratio between the land allocated to wildlife and dW W the stock of wildebeest at the optimum is independent of = rW (1 − ) − ΩW − N NW , (2b) wildlife non-consumptive use and directly proportional to dt qLw the relative payoffs to hunting, relative to farming (pN /pL ) with an adjustment for the carrying capacity of land (q) 38 Note that r and c can be derived from the primitives of a Cobb-Douglas utility and the intrinsic growth rate (r). Observe that L w is declin- function. We avoid this step to economize on space. ing in q since a higher carrying capacity implies that less 40 Tanzania’s Tourism Futures land needs to be allocated to wildlife to achieve any given Finally, for later use, we note that solving for the steady- payoff.39 Combining equations (3b)–(3e) yields the optimal state values yields: change in the stock of wildlife: h pL Ωss = [ r (2 − 1) + d ] (7a) W • pL ab qr p N = r (1 − )−Ω− N. (5) W qr p N J pL p L rp L N ss = [ r (2 − 1) + d ] − L + ). (7b) By equation (5) it is clear that non-negative growth ab qr p N p NW qp N requires that the relative profitability of farming is suf- ficiently low for an equilibrium to be sustained (that is, In the steady state, hunting levels decline with the benefits derived from tourism (ab ) but increase with the profitabil- W p q > 0 → L < [ r − ( Ω − N )]2 ). ity of agriculture and with the rate of discount, suggesting W pN r a higher preference for current consumption (or a longer The optimal growth paths of the control variables are path of accumulation of natural capital). From expression given by: (5) in the steady state, the combined value of the harvest • pL Ω 1 pL Ω must equal r (1 − ). Using expressions (7a) and (7b) = [ r (1 − 2 ) − d ]+ and (6a) rqp N Ω ab rqp N h • W with the equilibrium condition, = 0, yields the steady- • state stock of W: W N 1 pL [1 − (2w N − 1)h = [ r (1 − 2 ) − d ]+ Ω N w N (a b ) rqp N h wN ab pL L 2w − 1 pL f pN −( N )[ r (1 − ) − N ]. (6b) Wss = , (8a) wN rqp N rp L (f − a b ) p N [2 −r + d) ] qr p N f pL The results under perfect regulation are intuitive. A higher value of tourism (ab ) or a lower regenerative capacity (r) where f = ab + h + J < 1 is a measure of the scale diminishes growth of both types of hunting, whereas a parameter of the welfare function. higher carrying capacity (q) unambiguously leads to higher harvest rates in both sectors.40 The intuition is straight- Expression (8a) reveals that in the steady state, the stock forward: greater tourism benefits and a lower regenera- of wildlife will be larger the smaller the relative profit- tive capacity of wildlife favor non-consumptive tourism. ability of hunting compared to farming. Conversely, the While in (6b), the rate of increase in bushmeat hunting steady state values of land in the benchmark model are rises with the level of trophy hunting (Ω), suggesting com- given by: plementarity, when h is sufficiently small. ab pL L f pN w = Lss . (8b) 39 Since agriculture occurs only on non-park land Lnp, this can be stated as: qp N (f − a b ) 2− [r − d] Lw = L p + ( Lnp − L g ) = ( L − Ln rp N rp L f p ) +W np . qp L  Ω N  Ω N  Ω In the steady state, the optimal level of land allocated to d  d  d  d  d   Ω   N   Ω   N   Ω 40 By inspection, < 0 and < 0, < 0 and <0 0, , d ( pq ) > a wildlife is positively related to factors that increase their d (a b ) d (a b ) dr dr relative payoffs, such as the value of non-consumptive uses of wildlife and the relative profit of trophy hunting. N N d  d  These results are largely predictable and provide a bench- N N Lg 0 and > 0 and > 0 if h < . d ( pq ) dΩ wL mark for comparison with outcomes under regulatory imperfections. Tanzania’s Tourism Futures 41 2. IMPERFECT REGULATION excess of these allowable limits.41 Further, t > 0 if N > Na and t = 0 if N ≤ Na and n > 0 if Lg > La and n = 0 if Lg ≤ La. In this section, we take a step toward realism by extend- Note that the expected penalty is assumed to be increas- ing the benchmark model to include imperfect enforce- ing in the misdemeanor, reflecting the common judicial ment of hunting quotas and land allocated to farming. convention that the punishment should fit (rise with) the It is hard to overstate the challenges of regulating an crime. area as large as the Serengeti, an expanse extending over 25,000 km2 and spanning an international bor- Maximizing equation (9a) yields the first-order conditions der. Poaching by the local population is a widespread which define the reaction functions of the local popula- problem, estimated at over 10 percent of the wildebeest tion: population in certain years (Rentsch and Damon 2013). 1 1 Simultaneously, land conversion and encroachment, N = Na + and L g = La + (9b) 2t 2v especially in the buffer zones is a problem that grows more pervasive with rising population densities. This Observe that ∀∞ > t > 0, N > Na; thus, harvest levels section extends the core model by allowing for breaches will always exceed the allowable quota by an amount of regulatory quotas and possible legal sanctions for that is inversely proportional to the fine for noncompli- poaching and encroachment onto areas reserved for ance (unless the fine is infinite). This is arguably a realistic wildlife. There is limited evidence of trophy operators feature of the model. If the allowable quota (Na) is zero, violating their quotas; perhaps a reflection of the large the fine coincides with a tax levied on the whole amount hunting blocks that are leased to operators over signifi- of hunting. A similar result applies to the land allocation cant periods together with generous hunting allocations, decision. Note too that since 0 ≤ N ≤ 1, and 0 ≤ Lg ≤ Lnp, which are likely more incentive compatible. Allowing fines must meet the conditions: violations by trophy hunters in the model would be 42 straightforward but is ignored in what follows as it is not 1 Lnp t≥ ,v≥ . considered to be a problem. 2(1 − N a ) 2(1 − La ) With regulatory imperfections, the timing of events Substitute (9b) in (9a) to define the indirect utility func- becomes significant. It is assumed that the government tion: is the first mover and defines the policy parameters, tak- V ( Π ) = [ p N W ( N a + 1 / 2t ) − tp N W ing account of the downstream responses (the reaction functions) of other agents where relevant. Observing × ( N a + 1 / 2t − N a )2 + p L ( La + 1 / 2v ) these policies, the local population responds by setting −vp L ( La + 1 / 2v − La )2 ]J = ΠJ = the level of hunting (N) and the land allocated to farming 1 1 = [p NW ( N a + ) + p L ( La + )]J . (9c) (Lg). Lacking property rights, the local population ignores 4t 4v resource dynamics and they myopically maximize short- term expected utility, given the observed policy param- eters. In contrast, the government maximizes long-term 41 The expected penalty can be interpreted as the product of the probability of welfare taking account of resource dynamics. Thus, the detection (say z); the probability of conviction conditional upon being detected local population maximizes: (say c); and the penalty once convicted (say e). Thus t = zce. Introducing cor- ruption and bribe giving drives a wedge between the probability and cost of Max u = {p N WN WN − tp N W ( N − N a )2 detection and conviction but does not alter the analysis. 42 For example, if the quota on hunting is 5 percent of the stock of wildebeest, } J +p L L g − vp L ( L g − La )2 , (9a) the minimum tax that would yield a value of the actual hunting share not exceeding 100 percent would be 52 percent of unit profits. Another interpre- where Na and La are the legally permissible allocations tation is also possible. Consider, however that the tax is levied such that tn is of hunting and agricultural land determined by the gov- obtained by equating: t v p NWN = tp NW ( N − N a )2 →t v = t ( N − N a )2 . Thus, N ernment and tpNW and npL represent the expected fines for example, for t = 50, Na = 0.05, the optimum value of N would be 0.06 and which are levied, respectively, on hunting and farming in the marginal ad valorem tax rate tn = 0.01. 42 Tanzania’s Tourism Futures As the first mover, the government will take account of the The amount of land allocated to farming increases with downstream responses of agents as defined in the reaction the profitability of farming, declines with the stock of wild- functions in equation (9b). Thus, the modified Hamilto- WM life, and increases with the carrying capacity q = nian is given by: (L − Lg ) of wildlife since the payoffs from wildlife-related activities H =F FWW s ΩhV ( Π ) + m (rW increase with resource abundance.43 Further note that as W  1 v declines, the amount of land allocated to farming also × (1 − − ΩW −  N a +  W . (10a) declines.  1   2t  q  L − − La   2v  Using (10c) and (10d) the steady-state allocation of trophy Since there are two instruments (the fine and the quota) hunting is given by: and one objective (the optimal allocation), one of the h rp L 1 instruments can be set arbitrarily while the other is Ωss = [(2 − r) + +d ] (12a) ab qp N 4t defined through the optimization of equation (10a). In what follows, we focus on defining optimal quotas (Na and Equation (12a) is analogous to the familiar fundamen- La) taking the expected penalties (t and v) as given. This tal equation of renewable resources, with an adjustment is perhaps a realistic description of institutional reali- reflecting imperfect compliance. As compliance declines, ties. Typically, the conservation authorities have limited so does the stringency of regulations, in recognition of jurisdiction over criminal sanctions and their authority is the limits of governance. Hence, the allocation to trophy restricted to determining issues directly related to wildlife hunting rises. This simply reflects the fact that the optimal management such as quotas and allocations. The ultimate stringency of regulations depend upon levels of enforce- penalties for violating regulations are usually determined ment. by other layers of government involving the judiciary, over which conservation authorities have little direct con- Turning next to bushmeat hunting, the steady-state allo- trol. For policy purposes, these parameters are given. The cation is defined by: first-order conditions are defined by: J rp L 1 dH J Up N N ass = [(2 − r) + + d ] + J1 , (12b) = −m =0 (10b) ab qp N 4t dN a Π rp L 1 pL L 1 dH hU where J1 = − − (1 − ) . = − mW = 0 (10c) q p N 4t p N W 4v dΩ Ω The share of bushmeat hunting is: dH JU p L mrW 2 = − =0 (10d) dLa Π  1  2 1 J rp L 1 q  L − − La  N ss = N ass + = [(2 − r) + + d ] + J2 , (12c)  2v  2t a b qp N 4t • m s 1 rp L 1 p L 1 = d + (1 − )Ω − ( N a + ) where J2 = + − L (1 − ). m h 4t q p N 4t p N W 4v 1 2W + ( N a + ) − r[1 − . (10e) 2t 1 q ( L − − La ) 2v 43 Note that a greater carrying capacity allows for higher levels of agriculture. Contrary to popular policy wisdom, this result suggests that policies that dimin- Using (9b), (10b), and (10d), the allocation of land is given ish ecological carrying capacity need to be accompanied by a reduction in by: farmed area (intensification) rather than the reverse. Agricultural expansion is 1 rp N rp N often the stated rationale for these policies (for example, water abstraction and La = L − − W → Lg = L −W (11) intrusive infrastructure) in and around protected areas, which is the opposite of 2v qp L qp L the optimal response implied by this model. Tanzania’s Tourism Futures 43 The equilibrium level of bushmeat hunting includes a respectively, under perfect (p) and imperfect compliance non-compliance factor J2, which rises as the penalties t (I ) in the steady state and let Wssp , WssI be the respective and v decline. Intuitively, in regimes with weak penalties, steady stocks of wildlife. Then: there is less compliance, and knowing this the government allows for a higher legal amount of bushmeat hunting, Lemma 1a. With finite penalties, the proportion of wildlife harvested ceteris paribus. under imperfect compliance by trophy hunters and bushmeat hunters always exceeds the proportion harvested under perfect compliance. Wildlife stocks in the steady state are defined by: That is, Ωss P < ΩssI , and p and N ss < N ss I . ab pL 1 [ (1 − )]L f pN 4v Wss = , (12d) h pL rp L (f − a b ) f  Proof: From (7a) Ω p ss = [ r (2 − 1) + d ] {2 −r + d+  ab qr p N qp N f 4t  h rp L 1 and from (12a) Ω I ss = [(2 − r) + + d ]. where f = ab + h + J < 1 is a measure of overall convex- ab qp N 4t ity of the social welfare function. 1 Thus Ωss P − Ωss I =− < 0 ∀ 0 < t < ∞. From (7b) 4t Note that a steady state with positive values requires that J pL p L rp L both the numerator and denominator are positive.44 p N ss = [ r (2 − 1) + d ] − L + ) ab qr p N p NW qp N Land allocated to wildlife in the steady state is J rp L 1 ab pL 1 and by (12c) N ss I = a b [(2 qp − r ) + 4t + d ] + J2 . [ (1 − )]L N f p 4 v ss = Lw (12e) N qp (f − a b ) f  1 J p L  1 2 + ( N )1/2 {−r + d+  Thus N ss p − N ss I = − − L rp L f 4t  4t (a b + 1) p N W   4n   < 0 ∀ 0 < t < ∞ and 0 < v < ∞. ■ The following Lemmas summarize and compare the two equilibria. They suggest that the proportion of stock har- Lemma 1b. In a steady state, wildlife stocks under imperfect com- vested under imperfect regulation is always higher than pliance are always lower than under perfect compliance. That is under perfect regulation (for finite fines) and as a result, Wssp >WssI . wildlife stocks are always lower under imperfect regula- tion. This reflects the inability to fully control harvesting and land use in an environment where compliance cannot ab pL L be assured. In contrast, Lemma 2 asserts that as regula- f pN Proof: From (8a) W p ss = tory compliance improves, the amount of land devoted to rp L (f − a b ) p N [2 −r + d) ] agriculture declines since in a better-regulated economy, qr p N f pL it is easier to ensure compliance with regulations. Finally, Lemma 3 demonstrates how land allocations need to vary ab pL 1 [ (1 − )]L with changes in carrying capacity and relative payoffs. f pN 4v and (12d) W I ss = . rp L (f − a b ) f  Let ΩssP , Ωss I p , N ss I , N ss be the proportion of wildlife {2 −r + d+  qp N f 4t  harvested by trophy hunters and bushmeat hunters, Consider first the numerators of these expressions. ab pL 1 ab pL 1 44 To see why, note that the numerator needs to be positive to ensure that shares Clearly: [ (1 − )]L – L=– f pN 4v f pN 4v of hunting are non-negative but less than unity and therefore the denominator needs to be positive. < 0 ∀ 0 < v < ∞. 44 Tanzania’s Tourism Futures Consider next the denominators: Recognizing this, where compliance is weak, a greater rp L amount of land is devoted to agriculture. It is interesting rp L (f − a b ) p N 2 −r + d) – {2 −r + to note that this result emerges even without incorporat- qr p N f pL qp N ing monitoring costs in the model. (f − a b ) f  f d + = – < 0, ∀ 0 < t < ∞. Thus, the f 4t  4t Lemma 3. As carrying capacity declines, the optimum steady-state numerator of (33) is smaller and its denominator larger allocation of land to wildlife increases and as the relative payoffs so that Wssp > WssI . ■ to hunting increase, the optimum steady-state allocation of land to ∂Lw ∂Lw wildlife declines. That is, ss < 0 and and ss < 0. Note also that the difference in wildlife stocks vanishes ∂q ∂p N only if penalties are infinite. For future discussion of policy issues we note the following properties of the equilibria: Proof: From (12e) ab  2 BL Lemma 2. As regulatory compliance improves, the amount of land ∂L w   f   =− ss < 0; where dL dL ∂q  1 1  2 devoted to agriculture declines. That is g > 0 and g > 0.  qp N    qp N  2 2 dt dv 2r  B + 2     rp L   rp L    ∂L g  rp    Note that using (11) we have = −  N  < 0 and ∂W  qp L  f (f − a b )  B =  −r + d  and upon simplifying ∂W c  4t f  from (12d) we have = > 0, where wher ∂t  1 2   4t  V +  2  4t      rp L (f − a b )  ab pL 1 ∂Lw  pL Bq  V= −r + d  and Χ = [ (1 − )]L ss = − +  < 0. ■ qp N f   f pN 4v ∂p N  p N 1  1  2   qp  2  qp  2  2r p N  N   B  N  + 2  ∂W c dL g ∂L g ∂W   rp L    rp L    and = > 0. Hence, = >0     ∂v  1 dt ∂W ∂t 4v 2  V +   4t  In policy terms, Lemma 3 seems especially instructive. ∂L g ∂W dL g and = >0. ■ Activities that lower carrying capacity (q) call for an dv ∂W ∂v increase in land allocated to wildlife, often the reverse of Thus, the optimal allocation of land for conservation is what is observed. Intuitively, as q increases (decreases), larger in situations with greater compliance. Intuitively, wildlands become more (less) productive, so any given in situations of weak governance, stricter regulations payoff from W can be obtained with less (more) land (limits on agricultural expansion) cannot be enforced. devoted to wildlife. Tanzania’s Tourism Futures 45 APPENDIX C RUAHA MODEL The following is a brief description of the models used The Hamiltonian of the problem is thus: in the simulation. Let L be the total annual endowment   C  of labor available in a representative household. Let Lf H = U + l  rC 1 −  − (1 − d Lc )G GDC  , (6)   C  denote labor devoted to farming, Lc labor devoted to cattle herding, Lb bushmeat hunting and Lg lion hunting. Then: where l is the costate variable. Farm output is given by: The solution to be used for the simulations includes the labor supply variables, which when substituted into the Q = Laf W , (1) production functions give the hunting levels and farm out- where W is the amount of arable land and could be made put (not of critical interest at this stage). dependent on water availability in the dry season. The solutions are as follows: Lion hunting is: 1  a P f W  1−a H = Lgg G , Lf =  (7) (2)  qX   where G is the given stock of lions taken from the predator 1 prey model.  g Pg G  1−g Lg =  (8)  qX   Bushmeat hunting is linear in effort: Cq r CqX C= (9) B = qXLb. (3) r−D Xqr GPc d C DGP Cattle are set to graze on open pastures with no inputs. r (q qXX ( r + r ) − DG (qXr +dr qXr rPPcC − DGd PcC Labor is expended protecting the herd. Cattle growth is Lc = , (10) d DG ( DGP qXr ) DGPcC d − qXr given by a logistical function: where r (rho ) is the eiinter nterest rat = 0.05 approximately. nterest rate  C rC 1 −  − (1 − d Lc )G C = rC GDC , (4) Modified Predator-Prey Model:  C X = Y + Z, where Y is African buffalo where C is the herd size and C is the carrying capacity. numbers and Z is Giraffe numbers. (11) G is the number of lions and GDC the number consumed without protection. Lc is protection time which reduces the dY  Y  = S y Y 1 − YG − 0.5q − a y YG qYL YLb , (12) dt  KY   deaths by a factor d. where Sy = average calf survival rate for buffalo, KY = The household maximizes: carrying capacity for buffalo, and ay = probability that U = P f Laf W + PcC + Pg Lgg G + q qX ( ) X L − L f − Lc − L g , (5) encounter between lions and buffalo will result in removal of buffalo individual. Labor for bushmeat hunting is subject to equation 4. assumed to be equal for both prey species (that is, 0.5). dZ  Z  The terms Pi (i = f, g, c) are prices or weights given by = S z Z 1 − ZG − 0.5q − az ZG qZL ZLb , (13) households to each of the outputs dt  KZ   Tanzania’s Tourism Futures 47 where Sz = average calf survival rate for giraffe, KZ = This value uses density estimates of 0.34 per km2 for the carrying capacity for giraffe, and az = probability that RNP during the dry period from Barnes and Hamilton encounter between lions and giraffe will result in removal 1982 and current estimate of park area of 20,226 km2 of giraffe individual. (including recent annexation of Usangu Game Reserve). dG e (YG + ZG + CG ) g az = 0.18 (from Stander 1991) = RG + − L gG , (14) dt 1 + 0.5G Initial numbers used in model: where R = intrinsic growth rate of lions or cubs per year per adult female. This value is negative because cubs die Buffalo = 19,843 in the absence of prey animals. e = lion efficiency of con- verting food into fertility. This value is the ratio of number This value is the sum of estimates from RNP and Usangu of cubs (1.5) to number of kills per adult lion (4.5) times Game Reserve from the 2006 Tanzania wildlife aerial the ratio of adult females to the pride (0.375). survey. Giraffe = 1,556 Parameter values: This value is the sum of estimates from RNP and Sy = 0.73 (from Jolles et al 2005 and Jolles 2007) Usangu Game Reserve from the 2006 Tanzania wildlife KY = 36,407. aerial survey. This value uses density estimates of 1.8 per km2 for the Lion = 580 (from Mesochina et al. 2010) RNP during the dry period from Barnes and Hamilton 1982 and current estimate of park area of 20,226 km2 This value refers to RNP with area of 14,507 km2 but is (including recent annexation of Usangu Game Reserve). a best estimate. ay = 0.115 (from Hayward et al. 2011) Sz = 0.41 (from Sinclair et al. 1995) KZ = 6,877. 48 Tanzania’s Tourism Futures E n v i ronment and N atural R esour c es G lobal P ra c t i c e P ol i c y N ote W O R L D B A N K G R O U P R E P O R T N U M B E R 96150-TZ 1818 H Street, NW Washington, D.C. 20433 USA Telephone: 202-473-1000 Internet: www.worldbank.org/environment