EA Mangrove Forests

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Economic Analysis

of

Mangrove Forests:

A case study in

Gazi Bay, Kenya

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UNEP promotes

environmentally sound practices

globally and in its own activities. This

publication is printed on 100% recycled paper

using vegetable based inks and other eco-

friendly practices. Our distribution policy aims to

reduce UNEPs carbon footprint.

This publication, Economic Analysis o Mangrove Forests: A case study in Gazi Bay, Kenya is prepared as part o the eorts othe United Nations Environment Programme o promoting coastal intertidal orests as a signicant green economy assetor Kenya which require consideration when calculating national accounts.

Published by the United Nations Environment Programme in September 2011

Copyright 2011, United Nations Environment Programme

ISBN: 978-92-807-3187-3Job Number: DEW/1230/NA

This publication may be reproduced in whole or in part and in any orm or educational or non-prot purposes withoutspecial permission rom the copyright holder, provided acknowledgement o the source is made. United NationsEnvironment Programme (UNEP) would appreciate receiving a copy o any publication that uses this report as a source.

No use o this publication may be made or resale or or any other commercial purpose whatsoever without prior permissionin writing o the United Nations Environment Programme.

Disclaimers

The views expressed in this publication are not necessarily those o the agencies cooperating in this project. Thedesignations employed and the presentations do not imply the expression o any opinion whatsoever on the part oUNEP or cooperating agencies concerning the legal status o any country, territory, city, or area o its authorities, or o thedelineation o its rontiers or boundaries.

Mention o a commercial company or product in this report does not imply endorsement by the United Nations EnvironmentProgramme. The use o inormation rom this publication or publicity or dvertising is not permitted. Trademark names andsymbols are used in an editorial ashion with no intention o inringement on trademark or copyright laws.

We regret any errors or omissions that may have been unwittingly made.

Maps, photos and il lustrations as specied.

Contributors and Reviewers

Author: Janis Hoberg, Department o Business and Economics, Free University o Berlin, Germany

UNEP Production Team: Mwangi Theuri, Jane Muriithi, Eugene Ochieng

UNEP Reviewers: Pushpam Kumar, Christian Lambrechts, Alberto Pacheco; Nick Bertrand, Derek Eaton, Ashbindu Singh,Johannes Akiwumi, Neeyati Patel

Field data support: Dr. J. G. Kairo (Kenya Marine and Fisheries Research Institute, Mombasa), Caroline Wanjiru (University

o Nairobi), A. Hamsa (Gazi Women Boardwalk, Gazi Village)

Citation

For bibliographic purposes, this document may be cited as:UNEP, 2011. Economic Analysis o Mangrove Forests: A case study in Gazi Bay, Kenya, UNEP, iii+42 pp.

Cover photos: Janis Hoberg

Design and layout UNEP: Audrey Ringler


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Economic analysis o mangrove orests: A case study in Gazi Bay, Kenya

Economic Analysis

of

Mangrove Forests:

A case study in

Gazi Bay, Kenya

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Source: Janis Hoberg*

____________________* Free University o Berlin, Department o Business and Economics


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Source: Janis Hoberg / UNEP


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Contents

E X E C U T I V E S U M M A R Y 1

I N T R O D U C T I O N 3

ECONOMIC ANALYSIS OF THE GAZI BAY MANGROVE FOREST 5

A. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

A1. General inormation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

A2. The study site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

A3. Methods & data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

A4. Research limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

B. RESULTS FOR DIRECT USE VALUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

B1. Fisheries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

B2. Wood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

B3. Eco-tourism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

B4. Research & education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

B5. Aquaculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

B6. Apiculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

C. RESULTS FOR INDIRECT USE VALUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

C1. Shoreline protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

C2. Carbon sequestration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21C3. Biodiversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

D. RESULTS FOR NON-USES VALUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

D1. Existence value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

E. TOTAL ECONOMIC VALUE (TEV) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

F. DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

G. OTHER STUDIES ON MANGROVES VALUATION IN AFRICA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

H. CONCLUSIONS AND RECOMMENDATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

A P P E N D I X 3 5

Mangroves and the emerging issue o climate change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

R E F E R E N C E S 4 0


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LIST OF TABLES

Table 1: Summary o the drivers o change in the Western Indian Ocean (WIO) regionTable A1: Overview o methods or ecosystem valuationTable B1: Projected sh capture development Gazi BayTable B2: Mangroves contribution to on- and oshore shery at dierent sitesTable B3: Projected sh price Kenya 2010 (Theoretical approach)Table B4: Catch composition & sh prices in Gazi (Empirical approach)Table B5: Costs o a shing vesselTable B6: Value o shery in Gazi Bay (related to the mangroves)Table B7: Revenues and costs o sustainable mangrove harvesting in Gazi (2010)Table B8: Income rom uel wood collection in GaziTable B9: Tourists visiting the Gazi Women Mangroves Boardwalk(2008-2010)Table B10: Revenues rom aquaculture ponds in GaziTable B11: Income rom aquaculture production in GaziTable C1: Calculation o the average house priceTable C2: Valuation shoreline protection

Table D1: Potential national non-use value or Egypts mangrovesTable D2: Potential visitors non-use value or Egypts mangrovesTable D3: Potential Kwale population non-use value or Gazi Bays mangrovesTable D4: Potential national non-use value or Gazi Bays mangroves (Empirical approach)Table D5: Potential visitors non-use value or Gazi Bays mangroves (Theoretical approach)Table D6: Potential visitors non-use value or Gazi Bays mangroves (Empirical approach)Table D7: Existence value o the mangroves in Gazi Bay (Theoretical approach)Table G1: Economic valuations o mangroves in AricaTable H1: Results assessment, recommendations and advices

LIST OF FIGURES

Figure 1: Kenya sh catch development 1975-2008Figure 2: Process o carbon sequestration in mangrovesFigure 3: Total Economic Value o the mangrove orest in Gazi Bay (TEV)Figure 4: Sea-level changes 1800-2100Figure 5: Projected global warming by 2100

LIST OF MAPS

Map 1: Gazi Bay

Map 2: Potential spread o a tsunami wave rom Karthala volcano lava owMap 3: Mangroves distribution in Eastern AricaMap 4: Mangroves distribution in Kenya


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EXECUTIVE SUMMARY

This study was undertaken as part o UNEP eorts o promoting orests as a signicant green economy asset orKenya. Forests should be taken into account when calculating the national accounts because the global rushor land and the increasing demand or agricultural products and urban inrastructure continue to intensiy thepressure on tropical and coastal orests. The act that orests provide goods and services which currently haveno valued assigned to in economic markets exacerbates the deorestation and land conversion.

Mangrove orests are among the most productive and valuable ecosystems on earth. However, the economicvalue o the diverse unctions they provide such as shoreline protection, nursery habitats and carbon storageare not accounted or by decision-makers. This study aims to demonstrate the economic value o mangroveorest services in Kenya, using the Gazi Bay mangrove orest ecosystem as an illustration.

The study quanties the Total Economic Value (TEV) o the Gazi Bay mangrove orest. The variables are dividedinto direct use, indirect use and non-use value. Direct use values include shery, timber, eco-tourism, researchand education, aquaculture and apiculture. They account or 20 per cent o the TEV. Indirect use values o themangroves are shoreline protection, carbon sequestration and biodiversity. They represent 25 per cent o the

TEV. The existence value, which represents the value o mangroves in an unharmed state, accounts or 55 percent o the TEV. The analysis results in a TEV o US$ 1,092 per hectare per year.

To quantiy the value o the goods and services, dierent methods were applied. Most o the direct uses werecalculated using the market value o the products. The Damage Costs Avoided Method was used to valuethe shoreline protection unction o the mangroves. Biodiversity and existence value were derived using theBenet Transer Method (BT).

It is acknowledged and stressed that this study suers rom research limitations. One reason is the lack oprimary data and appropriate peer reviewed studies. Application o the BT should also be considered withcaution. It is, however, recognized as one o the most widely used methodologies in the eld o environmentalvaluation and serves as a rst approach in determining non-marketable mangrove services. Thereore the

results o this analysis should be considered as a rst step towards quantiying the value o Kenyan mangrovegoods and services.

The results o the analysis are also compared with other economic analyses o mangroves in Arica, althoughonly a ew mangrove valuations have been conducted. Recommendations or uture research on mangrovevaluation are made.


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INTRODUCTION

Economic analysis o mangroves in Kenya aims to quantiy the value o the mangroves and the goods andservices they provide in order to promote their signicance in the Kenyan economy. The purpose o the studyis to demonstrate to local policy-makers the economic value o mangroves and to take into account their valuewhen making decisions on land uses and when calculating the national accounts. The specic objectives othis study include:

(a) Quantiying the value o alternative direct mangrove uses or the Kenyan economy;(b) Determining the non-marketable services o mangroves; and(c) Calculating the existence and biodiversity value o mangroves in their unharmed state.

The worlds coastal ecosystems are acing signicant pressure. A combination o geographical shits in humansettlements, an exponentially increasing population and climate change are causing considerable changes inland uses. Natural habitats are being converted into agriculture plantations and tourist destinations.

Around 3.2 billion people occupy a coastal strip o 200 kilometers wide, which represents only 10 per cent o

the earths land surace. High urban population growth leads to competition or land in coastal regions. In thepast, mangrove orests have been the victim o this competition, leading to signicant degradation. Accordingto Giri et al. (2010), mangroves globally encompass an area o only 137,760 km. Approximately 75 per cent omangroves are concentrated in just 15 countries and barely 7 per cent o these lie in protected areas.

The situation in Eastern Arica is o special concern as people migrate rom rural areas to the coast in order tobenet rom the dynamic growth occurring in those areas. The population o coastal cities in Eastern Arica hasgrown by around 4 per cent per year (Hinrichsen, 1998). Since mangroves compete with urban developmentalong the Eastern Arican coast they are threatened with degradation and extinction. As one o the upcomingeconomies in Arica, Kenya aims at conserving indigenous traditions and values on one hand while keeping upwith the rapid social development and economic growth on the other. Kenyas natural resources oer attractivetourists destinations, rich biodiversity and a substantial array o goods and services. However, this natural asset

does not play a signicant part in Kenyas national accounts.

Mangroves are among the most productive ecosystems on earth, but since a large part o the mangroveservices do not have assigned market prices, the value o this unique ecosystem is generally underestimated.However, mangroves provide a broad array o goods and services to the local community. They play animportant role in on- and oshore shery, providing juvenile sh with nursery habitats and shelter. They arealso a source o timber and uel wood or the adjacent villages. Mangroves eature rich biodiversity; they canstore and sequester signicant amount o carbon; protect the shoreline rom soil erosion and tsunamis andattract unding or research and education.

Recreational activities in mangroves are also part o services. Ecotourism is becoming increasingly important

and mangroves oer a clear synopsis o the unctions and links between marine ecosystems and thereoreattract green-minded tourists. Alternative uses include apiculture (beekeeping) and aquaculture (shbreeding ponds). Bees use nectar rom the mangrove owers to produce honey while juvenile sh rom themangroves are used or breeding in commercial sh ponds. These benets show the high dependence o localcommunities on mangroves or their well-being.

Major drivers o environmental change which negatively impact on Kenyan mangroves include climatechange, population growth, urbanization and pollution o the environment. Climate change leads to a rise insea-level, which puts signicant pressure on mangrove orests rom the seaward side. Changes in precipitationpatterns, temperature surges and increase in the requency and intensity o heavy storms and tsunamisexacerbate the situation (see Appendix A). The rapid growth o population and the progress o urbanizationcauses competition or land since coastal areas are usually densely populated and demand or land conversion

into urban inrastructure continues to grow. This goes hand in hand with notable air and water pollution whichhampers valuable mangrove unctions such as water regulation and leads to loss o biodiversity. Table 1 showsa summary o drivers o change or the Western Indian Ocean region.


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Table 1: Summary o the drivers o change in the Western Indian Ocean WIO

Direct drivers Indirect drivers

LOCAL LOCAL

Changes in land uses & cover Poverty

Species introductions Community health

Habitat degradation

Overshing

Pollution

Agricultural practices

Erosion

NATIONAL NATIONAL

Natural disasters National policies

Migration Legislation

Industrial development Tourism development

Water quality Education

Catchment management Migration

Industrial development

GLOBAL GLOBAL

Climate change Globalization

Economics

Source: UNEP (2009)



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ECONOMIC ANALYSIS OF THE GAZI BAY MANGROVE FOREST

A INTRODUCTION

A1 GENERAL INFORMATION

The valuation o an ecosystem is a complex process that is reliant on the availability o relevant and accuratebiophysical data on ecosystem processes and unctions and the appropriate applications o economicvaluation (Morse-Jones et al., 2011). Resource economists approach the topic using dierent methods andmethodologies. In this study, the Utilitarian approach is applied. The Utilitarian approach searches or theoption that is the most valuable or the whole society in monetary terms. This study values the option o thewise use and conservation o mangroves. For example, it assumes that only a specic amount o timber anduel wood is extracted rom the mangroves so that they are able to recover rom the harvest and remain mostlyunharmed. This is a requirement or the provision o other ecosystem services.

The range o Total Economic Values (TEV) o mangroves determined in dierent studies show markedvariances (Spalding et al., 2010). Causes o these inconsistencies result rom the use o dierent approaches

and methodologies as well as insucient data collection. In addition emerging issues like climate changeaect the valuation (see Appendix A) in which some variables might increase in importance while others willeventually depreciate. For instance, the rise in sea-level could increase the value o shoreline protection in thelong run (Crabbe, 2009; IPCC, 2007).

Resource valuation can also be restricted when it comes to choosing the appropriate variables mainly dueto lack o unding. Some variables require highly sophisticated research approaches and methods, which arenot always aordable or have not even been invented. Regional or local specications may also inuence thevaluation. While Spurgeon (2002) derived the value o eco-tourism in Egyptian mangroves to be as high as US$130,000 per hectare per year (ha-1 y-1), Kairo et al. (2009) valued the same actor at US$ 9.3 ha-1 y-1 in Gazi, Kenya.The signicant dierence in value is simply based on the act that tourism is much more developed around themangroves o Egypt than in Gazi Bay. In addition, the mangroves in Spurgeons analysis are part o a greater

national park and thereore more attractive to tourists. This example shows how local dierences can inuencevaluation.

Since little research has been done in Arica, Benet Transer Method (BT, see section A3 or explanation) hasto be applied to calculate some o the values. Abundant economic data exist only or mangroves in SoutheastAsia (e.g. Ruitenbeek (1992); Sathirathai (1995); Leong (1999)). However, these studies are geographically tooar away rom Kenya to work as appropriate peer reviewed studies.

A2 THE STUDY SITE

In Kenya, several studies on mangroves have been conducted mainly ocusing on the region around Gazi Bay,although it belongs to the smaller mangrove sites in Kenya (see Appendix A or geographical distribution).Lamu district oers a much larger mangrove site and eatures about 67 per cent o the Kenyan mangroves.However, researchers choose the Gazi Bay area which is easily accessible than Lamu. Gazi Bay is located at thear Southern edge o the Kenyan coastline some 55km South o Mombasa (4025S and 39050E). According toMaina et al. (2008) Gazi Bay occupies an area o 18km2 and is sheltered rom storms by Chale Peninsula to theEast and a coral ree to the South. These two natural barriers support mangrove growth in the protected bay(Map 1). The area is surrounded by 6.2km2 o mangroves and the bay hosts approximately 180 dierent specieso shes and abundant bird lie (Kairo et al., 2010). Atmospheric conditions are typical or a tropical shorelinewith annual precipitation o 1000-1600mm and air temperature o 24-39oC (Kirui, 2007). Humidity ranges rom60 per cent to 100 per cent (Kairo et al., 2010).


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Map 1: Gazi Bay

Source: Survey o Kenya Map sheet 201/3, scale 1:50,000 (2000)

A3 METHODS & DATA SOURCES

A31 Methods or ecosystem valuation

Research in the eld o environmental economics has brought together an extensive array o methods orecosystem valuation. TEEB (2010) dierentiates between approaches based on market valuation, revealedpreerence and stated preerence. The methods dier signicantly rom each other in terms o their reliability,validity and applicability. In addition, some methods are much more costly and time-consuming than others.However, all methods have their merits and aws and it is let to the researcher to decide which method isbest to apply to the respective study site considering the limitations, local circumstances and environmentalsettings. Table A1 provides an overview o the methods commonly used or ecosystem valuation.


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Table A1: Overview o methods or ecosystem valuation

Approach Method Description Exemplary orest

good / service

Market

valuation

Market prices Market price o the good Timber

Avoided costs Costs that are avoided through the existence othis service

Shorelineprotection

Replacement costs Costs o establishing a construct that provides asimilar service

Freshwaterregulation

Restoration costs Costs o mitigation the eects o the loss o theecosystem service

Flood barriers

Productionunction

Contribution o the ecosystem service to thedelivery o another marketable good or service

Nursery habitat

Revealed

preerence

Travel costs Direct and opportunity costs o time o the

visitors

Recreation

Hedonic pricing Estimate o a demand unction or property Aesthetic views

Stated

Preerence

Contingentvaluation

Poll o beneters to determine their willingness-to-pay (WTP) or the preservation o the service

Biodiversity

Value

transer

Benet transer Transer o values rom a policy site to the studysite

Existence

Source: Modied rom TEEB (2010)

A32 Methods & data sources o this study

This study uses a variety o methods and methodologies to calculate the values o the dierent variables andto collect additional data. In some cases theoretical projections are combined with the evaluation o primarydata to prove their validity. On-site interviews were conducted to veriy theoretically calculated values onshery, research and education, aquaculture production and the potential benets rom the establishment oapiculture, one o the newest industries in Gazi. Data sources or indirect uses were obtained rom the KenyaMarine and Fisheries Research Institute (KMFRI) and available literature, as well as rom the application othe Benet Transer Method. However, main valuation tool was the application o market values or directecosystem goods and services.

For the contribution o mangroves to shery, projections o growth in annual catch were implemented (inaccordance with FAOs Fishstat+ 2010 Database). To conrm the results, two interviews with KMFRI and the

Beach Management Unit (BMU) in Gazi Bay were conducted.

The value o wood extractions, specically the collection o building poles and uel wood, was quantied usingprimary data. Inormation was provided by S. Shikeli, the wood concessionaire o Gazi, in particular on thegures or building pole prices, allowable amounts o harvest and costs.

Eco-tourism in Gazi Bay is only partially developed. The Gazi Women Boardwalk is the only community-basedgroup oering trips into the mangroves. The group provided data on the number o visitors and the respectiveincome. The operations manager o Gazi Retreat, the only tourist accommodation nearby, was interviewed onthe tourism potential in the region and its social responsibility or Gazi Village. That interview did not contributeto the data collection.

Research and education are a major component o mangrove services. A senior mangrove scientist, Dr. Kairo,who works or the Kenya Marine and Fisheries Research Institute has his research base in Gazi and is a resident


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o Gazi Village. He oers accommodation to oreign researchers and keeps record o the number o visitingresearchers and the amount o unding. Those data were used to quantiy the mangroves value or researchand education.

Aquaculture production is one o the newest, mangroves-related projects in Gazi. The ponds are mainlymanaged by C. Wanjiru, a researcher rom the University o Nairobi. She was able to provide data on potential

earnings and costs o the breeding ponds. Additional data came rom A. Hamsa, the director and manager othe Gazi Women initiative.

An apiculture (beekeeping) project was established by the Gazi Women initiative. Since the project wasestablished only recently, data provided by the manager, A. Hamsa, were used to predict potential incomerom the bee hives. Market values were used to calculate the value o income rom the honey production.

Indirect uses include shoreline protection, carbon sequestration and biodiversity values. For shorelineprotection the Damage Costs Avoided Method was applied. Data on the number o houses and house priceswere provided by Dr. Kairo. The rest o the required data was obtained rom ormer studies or simply projected.Due to the changing prices or carbon credits, the value o carbon sequestration is uctuating. This study uses

gures rom the Mikoko Pamoja project, a reorestation initiative, initiated by KMFRI, Earthwatch, EdinburghUniversity and Bangor University in 2010 (Kairo et al., 2010).

For the valuation o biodiversity in the Gazi mangroves the Benet Transer method (BT) was applied. BTincluded the comparison o the purchasing power parity GDP per capita or Kenya and Sri Lanka. UNEP/GPA(2003) used this approach to calculate the biodiversity value o mangroves in Sri Lanka. Non-use value in thisstudy only consists o the existence value. This study uses BT to value the existence o the mangroves in GaziBay. The peer study is the analysis o the mangroves in Egypt (Spurgeon, 2002) which is one o the very ewstudies conducted in Arica. It is so ar the only appropriate peer study that values biodiversity o mangrovesin Arica.

A4 RESEARCH LIMITATIONS

The variables o indirect use values and non-use values o this study lack primary data and appropriate peerstudies. This is due to the act that valuations o mangroves in Arica practically do not exist. Other reasonsinclude a limited time rame or the analysis and the lack o data records o important variables, limitedinrastructure to host and accommodate tourism as well as low publicity o the subject matter.

While the values o direct uses o the mangrove such as, shery, wood collection and apiculture are consideredto be accurate, the indirect and non-use values need to be conrmed by applying dierent methodologies.However, the results all into the global range o valuations. In addition, the study site has minimal development,which results in a comparably low Total Economic Value (TEV ). TEV represents the sum o all mangroves goodsand services. Further development o the tourism and research sector may increase awareness and in eectthe value o mangroves in Kenya.

Some o the assumptions made are based on studies rom Southeast Asia. The environmental settings inSoutheast Asia dier rom the settings in Eastern Arica and this has to be considered when examining theresults. Thereore, this study is seen as preliminary work and it is proposes that that the results, especially thoseo the indirect usage variables, are conrmed by applying a contingent valuation and conducting a survey inGazi Bay.

An economic analysis o mangroves encompasses an array o goods and services, which have to be valuatedindividually. Relevant variables or Gazi Bay can be divided into direct, indirect use and non-use values.


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B RESULTS FOR DIRECT USE VALUES

B1 FISHERIES

New shermen site in Gazi VillageSource: Janis Hoberg / UNEP

One o the major economic goods extracted rom mangroves and surrounding habitats is sh. Direct shingin the mangroves is relatively rare since mostly only juvenile sh are ound there hidden between the roots omangrove plants. Fishermen usually go oshore to the sea grasses or to the coral rees to sh. Onshore sheryis only done by locals who cannot aord the more expensive oshore shing gear (Kairo et al., 2009).

The most valuable direct use o mangroves is as a breeding and nursery habitat or juvenile sh. However,Kairo et al. (2009) assumed that shing in Gazi Bay is done in the estuary and mangrove area because oshoreshing equipment is too expensive or the shermen o Gazi Village. Thereore it was valuated as a direct usecomponent with 100 per cent contribution, although sea grasses and coral rees play an important part incoastal shery. A 100 per cent contribution assumed that the whole value o shery can be related directly tothe mangroves and can be added to their value. This study ranks sheries as a direct use o mangroves.

The contribution o mangroves to oshore and coral ree shery consists in protection and the provision onutrients rom allen leaves and nursery habitat. Since most shes grow up in the mangroves and then leave tooshore areas it is important to examine how much o the catch can be related to the mangroves. Studies oerdierent solutions regarding this issue.


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B11 Economic valuation: Amount o sh caught in Gazi in 2010

This study assumes a moderate contribution o mangroves to shery. Furthermore, the considered shing areabeneting rom the mangroves is limited to the shing grounds o the shermen rom Gazi Village.

The Indian Ocean along the Kenyan coastline is widely used or shing by local communities. Figure 1 shows

sh catch along the Kenyan coastline rom 1975-2008. The amount o sh caught has increased signicantlyin the last 33 years (Fishstat+, 2010). A total o 4531 tons was caught in 1975 and this increased to 7228 tons in2008. This corresponds roughly to an increase o 60 per cent in the last 33 years.

Figure 1: Kenya marine sh catch development 19752008

Source: Fishstat + 2010

To calculate the compounded annual growth rate (CAGR) or the Kenyan marine sheries industry theollowing ormula is applied:

Euation 1: Compounded annual growth rate

Where:CAGR = Compounded annual growth ratet

0= time 0

tn

= time nV (t

0) = Fish catch in time 0

V (tn) = Fish catch in time n

Using data rom Fishstat+ 2010 or Kenya, the CAGR (t1975

, t2008

) becomes:

The result shows that the sh capture in Kenya has increased on average by 1.425 per cent annually. Thisis mainly the result o a growing population, globalization and the increasing wealth o the population.

Furthermore, shing gear has improved, which makes capture o sh on- and oshore easier. Since mangrovesare the nursery habitat o most o the sh caught, their importance or the Kenyan ood supply and exporteconomy is crucial.

12,000

10,000

8.000

6,000

4,000

2,000

01970

Marineshcatch(tons)

1975 1980 1975 1990

Year

1975 2000 2005 2010

CAGR (t0,tn) = 1V(tn)

V(t0)

1

tn -t0

CAGR (t1975,t2008) =

= 0.01425 = 1.425%

17228

4531

1

2008 - 1975


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Kairo et al. (2009) ound using data rom CORDIO EA that in 2006 the amount o sh caught in Gazi Bay wasas much as 66.235 tons. Assuming that the catch composition and an annual growth rate o 1.425 per cent isapplicable to and representative o Gazi Bay, one can calculate the projected amount o sh caught in Gazi(Table B1).

Table B1: Projected sh capture development Gazi Bay

2006* 2007 2008 2009 2010

66235 67.179 68.136 69.107 70092

*Source: Kairo et al. (2009)

Following this projection the annual amount o sh caught in Gazi Bay is estimated at 70.092 tons. In order toconrm the sheries data in Gazi Bay, in particular the amount o sh caught, current sh prices and shingcosts, two interviews were conducted with the Beach Management Unit (BMU) and with E. Myanchoka, aresearcher and Laboratory Technician (KMFRI) respectively, on 02 and 04 March 2011. The BMU is responsibleor the management o sheries in Gazi village and keeps records o shing data. According to E. Myanchoka

the total amount o sh caught in 2009 was 72 tons and 69.8 tons in 2010 (Myanchoka (KMFRI), pers. comm).This corresponds roughly to the projected gure. For urther calculations 698 tons o total catch in 2010 isused.

B12 Contribution o mangroves to sheries

Kairo et al. (2009) projected that the mangroves in Gazi Bay contribute 100 per cent to shery income; howeverother studies show that sheries in this coastal ecosystem are not entirely dependent on the mangroves. Forexample, Spurgeon (2002) suggests a 5-25 per cent contribution o mangroves to oshore shery. Aburto-Oropreza (2008) calculated that 31.7 per cent o the capture production is related to the mangroves. Table B2represents a global overview o estimates o mangroves contribution to on- and oshore shery.

Table B2: Mangroves contribution to oshore shery at dierent sites

Study year Mangroves contribution to shery

AburtoOropreza 2008 31.7%

Spurgeon 2002 5-25%

Naylor and Drew 1999 90%

Singh 1994 30%

Bennett and Reynolds 1993 10-20%

Lal 1990 56%

Hamilton and Snedaker 1984 67%

Macintosh 1982 49%

Source: Modied rom Roennbaeck (1999)

Since the result rom the study o Aburto-Oropreya (2008) gure is based on accurate background research itis applied here to calculate a more valid gure or the value o mangrove contribution to oshore shery inGazi Bay.

Assuming a mangroves contribution to shery o 31.7 per cent in Gazi Bay, the amount o sh caughtattributable to the mangrove is as ollows:

The total amount o sh caught in 2010, related to the mangroves in Gazi Bay, is: 221538 tons

69.8 * .0317 = 22.1583


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B13 Fish prices

Kairo et al. (2009) set the sh price per kg at Kenya shillings 100.00 (Ksh 100). Table B3 shows the ination rateor Kenya rom 2006 to 2010 (IMF, 2010).

Table B3: Projected sh price Kenya 2010 Theoretical

Year Average annual infation rate Projected Fish price Ksh

2006 6.0360% 100.00

2007 4.2560% 104.26

2008 16.1810% 121.13

2009 9.2510% 132.33

2010 4.1050% 137.76

In two interviews the prices or dierent sh species were determined. Table B4 shows the catch composition

o Gazi Bay (Maina et al., 2008), the results rom the two interviews, conducted in Gazi Village in March 2011and the total average sh price. The numbers represent the prices quoted by the shermen selling their sh toa dealer.

Table B4: Catch composition & sh prices in Gazi Empirical

Taxonomic group Species Price Ksh /

kg1

Price Ksh /

Kg2Average

price

Ksh/Kg

Catch

composition

Gazi Bay3

Contribution

to total

average sh

price Ksh / Kg

Scombridae Mackerel, tuna 110-120 100 107 24.00% 25.68

Scaridae

Monacanthidae

Acanthuridae

Labridae

Marine shes ~110 ~110 110 22.50% 24.75

Siganidae Rabbitshes 130-150 100-120 125 15.10% 18.875

Lethrinidae Emperors ~110 100-120 110 8.70% 9.57

Spyraendae Barracudas 100-110 100-120 107 7.40% 7.918

Octopodidae Octopuses 100 150 125 4.20% 5.25

Carangidae Amberjacks ~100 ~110 105 4.00% 4.2

Lutjanidae Snappers 150-180 120 140 3.40% 4.76

Haemulidae Grunts ? 100-120 110 2.80% 3.08

Mullidae Mullets 100 80-100 95 2.10% 1.995

Loligidae Various squids 100 120 110 0.50% 0.55

Others - ~110 ~110 110 5.30% 5.83

TOTAL / Average - ~115 112.5 113 100.00% 112458

Using these gures, the average price o sh in Gazi Bay is: Ksh112458 / Kg

____________________1

Myanchoka (KMFRI), personal communication2 Beach Management Unit Gazi Village, personal communication3 Maina et al. (2008)


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B14 Costs o shing gear

The cost o shing gear or local shermen consists, or the most part, o the cost o acquiring and maintainingboats, nets and other shing gear. There are 26 vessels permanently based in Gazi. I maintained properlyvessels last around 6 years (Myanchoka (KMFRI) and BMU, pers. comm.). The cost o a new vessel is calculatedas ollows:

Table B5: Costs o a shing vessel

Part Costs Ksh

Material 30,000

Building costs 37,500

Transport 15,000

Manpower 17,500

Total Costs 100,000

Source: Myanchoka (KMFRI), pers. comm.

Assuming a price o Ksh 100,000 or a new vessel, a lie o 6 years or each vessel and 26 permanent vessels inGazi, the total annual costs or vessels are about Ksh 430,000.

In addition, nets have to be changed every year since most o them are not o good quality. The most widelyused gear is the shing line (Kairo et al., 2009). The nets are usually used by three shermen at a time workingin a group. Assuming 100 shermen who work and live permanently in Gazi (some shermen come rom othersites, such as Zanzibar) approximately 33 shing lines are needed every year. Common prices or shing linesrange rom Ksh 5,000 to Ksh 10,000. Assuming a price o Ksh 8,000 the annual costs or the shing lines addsup to Ksh 264,000.

Since the revenue attributable to the mangroves is assumed to be 31.7 per cent o the total revenue, the sameassumption has to be applied to the costs. The total shing costs attributable to the mangroves are thereoreKsh 220,000. To justiy this result a rough estimate rom the Beach Management Unit came up with an annualincome o Ksh 72,000 per sherman per year. Assuming 31.7 per cent contribution, 100 shermen and 620hao mangroves the value totals to Ksh 3681.29 ha-1 y-1, which conrms the value derived when consideringrevenues and costs. Since the rst approach is more accurate the contribution o mangroves to shery in Gaziis calculated at Ksh 3,664ha-1y-1, or an equivalent oUS$ 44 ha1y1.

Table B6 : Value o shery in Gazi Bay related to the mangroves

Parameter Amount

Revenues (Ksh / year) 2,491,372

Costs or vessels (Ksh / year) 136,310

Costs or nets (Ksh / year) 83,688

Income ( Ksh / year) 2,271,374

Mangroves ( ha) 620

Fishery value o mangroves (Ksh / ha / year) 3,664


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B2 WOOD

This section includes the harvest o building poles and the collection o uel wood in the mangroves. It isassumed that market prices are reasonable and that the harvest is sustainable. It is necessary to dierentiatebetween clear-elling, which would destroy the whole ecosystem and all its depending goods and services, andsustainable harvesting. For sustainable subsistence orestry Bann (1997) suggests to introduce an imposition

o a maximum allowable harvest rate that does not exceed the orests capacity to regenerate and developnaturally in order to ensure sustainability. In the past, especially between 1970 and 1980, the industrial sectorand the local community clear-elled signicant parts o the mangrove orest in Gazi Bay. However, the recentpast has brought about some innovative projects where the local community is supported to replant an areaand giving the people economic incentives especially through carbon credits trading (e.g. Kairo et al., 2010).This study assumes a sustainable harvesting o the mangroves which is secured by the strict harvesting andcollecting rules or Gazi Bay established by the Kenyan government. No illegal cutting or collection o timberand uel wood is taken into account in this study.

B21 Building poles

In Gazi Bay the only person allowed to cut mangrove trees or building poles is the concessionaire Mr. S. Shikeli.He is allowed to harvest 500 scores o building poles per year (1 score = 20 poles). This guarantees long-termconservation o the mangroves since only designated classes o poles are harvested. The concessionaire candecide or himsel how to divide the 500 scores between the dierent tree classes. The prices or poles dierdepending on their diameter. The industry dierentiates between the Boriti, Mazio, Pau, Fito and Fingiclasses.Harvesting o the Fito poles is no longer allowed. Depending on the class the concessionaire has to pay dierenttax rates. He also employs wood cutters who are paid per score and class. The annual charge or the license isKsh 10,000 and an additional Ksh 1,000 charged as application ees. Table B7 shows revenue and costs or theconcessionaire in 2010:

Table B7: Revenues and costs o sustainable mangrove harvesting in Gazi 2010

Parameter Class

Fingi Boriti Mazio Pau

Price (Ksh / score) 2400 2000 1600 500

Salary costs (Ksh / score) 900 700 500 150

Taxes (Ksh / score) 600 500 400 110

Income (score / class) 900 800 700 240

Scores harvested per class (2010) 50 50 100 300

Income per class (Ksh) 45,000 40,000 70,000 72,000

Income (all classes) 227,000

license ees (Ksh) 10,000

Application ees (Ksh) 1,000

Total income 2010 (ksh) 216,000

Source: Shikeli, pers. comm. March 2011

The annual income rom sustainable harvesting was Ksh 216,000 in 2010. Assuming 620 hectares o mangroves,the harvesting income in Gazi is Ksh 348.4 ha -1y-1, which is equivalent to US$ 42 ha1y1. This gure appears tobe very low, but considering the tough restrictions or the concessionaire the low value is justiable. 500 scoresper year is equivalent to 10,000 stems. This results in a harvest limit o only 16 trees ha-1y-1. Acknowledging

these limitations, which ensure conservation o the orest and taking into consideration the act that all othervariables depend on a sustainable mangroves orest the limited amount o income potential rom mangrovescutting can be justied.


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B22 Fuel wood

Inhabitants rom villages close to the mangroves are allowed to collect one bundle o uel wood per day. 50villagers, mostly women, take permanent advantage o this opportunity. Assuming those 50 people go tocollect uel wood 22 days per month (every day excluding weekends), the annual total amount o collecteduel wood is:

50 collectors * 22 days per month (1 bundle per day) * 12 months = 13,200 bundles / year

The collecting ees are Ksh 100 / month / person. The total ees are thereore Ksh 60,000 / year. Fuel wood canbe sold at Ksh 70 per bundle (Shikeli, pers. comm.). Table B8 shows the villagers income rom gathering omangrove uel wood.

Table B8: Income rom uel wood collection in Gazi

Parameter Amount

Collected uel wood ( bundles / person / year) 264

Number o collectors 50Total amount o collected bundles / year 13,200

Price per bundle ( Ksh) 70

Revenues (Ksh) 924,000

Fees (Ksh) 60,000

Income (Ksh) 864,000

Source: Shikeli, pers. comm. March 2011

The total income rom uel wood collection is Ksh 864,000 or Ksh 1,394 per hectare (equivalent toUS$ 168 ha1y1). This gure is higher than the value o the building poles because collecting uel wood is aday-to-day activity and many more people are involved. In addition, the limitations are not as strict as they areor the harvesting o building poles.

B3 ECO-TOURISM

Tourism has always been a major source o income or any coastal population and since mangroves providerich biodiversity and an impressive landscape, tourism could represent a reasonable part o the economic valueo mangroves. Prerequisite or tourism is a well-established inrastructure to host and accommodate tourists.Tourism in Gazi Bay is only moderately developed. Additional inrastructure and a change o consciousnessamong ordinary tourists might lead to an increase in the value o this variable. Gazi Retreat lodge provideshigh-class services and acilities or afuent tourists. The Gazi Women Boardwalk is responsible or visits

to the mangroves. The Operations Manager o Gazi Retreat, S. Fernandez, said that every visitor is stronglyencouraged to visit the Boardwalk to support the local community.

This study uses the income / market value method to estimate the tourism value o the mangroves in Gazi. TableB9 shows the number o tourists visiting the Boardwalk rom 2008 to 2010 . This study assumes that the incomeor the Gazi Women Boardwalk is an appropriate gure to apply to the value o eco-tourism. This gure willincrease i mangroves are marketed more widely, especially in Diani, where a lot o international tourists spendtheir holidays. The study also recommends applying the Travel Costs Method (TC), which could increase thevalue o this variable signicantly. Lack o primary data prevented the application o TC in this study.


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Table B9: Tourists visiting the Gazi Women Mangroves Boardwalk 20082010

Months No o Visitors

2008 2009 2010

Jan 14 60 68

Feb 8 66 175

Mar 10 160 196

April 87 83 38

May 131 3 101

June 31 144 161

July 244 325 335

Aug 140 178 167

Sept 27 38 102

Oct 95 43 119

Nov 195 89 75

Dec 162 135 136

TOTAL 1144 1324 1673

Source: Gazi Women Boardwalk

Since 2008 the number o visitors has increased steadily. In 2010 the Boardwalk registered 1673 visitors. Theentrance ee is generally Ksh 100 and students usually pay a little less. The womens group also oers ood atthe entrance to the Boardwalk at a cost o Ksh 200 per person. It is assumed that 50 per cent o the visitors take

this opportunity.

The total income or the Gazi Women Boardwalk is thereore:

Euation 2: Ecotourism income in Gazi 2010

1,673 x Ksh 100 + 837 x Ksh 200 = Ksh 334,700

Costs or running the boardwalk are nearly non-existent and the Gazi Women do not keep records o theircosts. The income rom eco-tourism in Gazi in 2010 attributable to the mangroves is Ksh 334,700y-1 or Ksh 540ha-1y-1, which is equivalent to US$ 65 ha1y1.

B4 RESEARCH & EDUCATION

Mangrove sites around the world attract a lot o researchers, students and school classes who want to learnmore about this intertidal habitat. Although research on the Arican mangroves has a great potential it hasbeen rather low up to now. Kairo et al. (2009) and Spurgeon (2002) added the unds or PhD and MSc studentsto their valuation. This study assumes that the amount o unding or mangrove research can be applied toquantiy the research and education value o the mangroves to some degree. It is acknowledged that moreresearch has to be done and various methods applied to nally come up with a more accurate value.


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Students visiting the mangroves in GaziSource: Janis Hoberg / UNEP

There have been a number o research projects in the Gazi Bay mangroves during the period 2007 and 2010.Funding or those projects was as ollows (Kairo, pers. comm.):PhD = 5 * US$ 10,000 / yearMsc = 9 * US$ 6,000 / yearBsc = 4 * US$ 2,500 / yearTOTAL = US$ 114,000 / year

The unding and research value per year is thereore US$ 114,000 or US$ 1844 ha1y1.

B5 AqUACULTURE

Combining the eorts o KMFRI, UNDP and The Gazi Fishermen Group in January 2011 one o the newestinitiatives in Gazi is the aquaculture project. Four ponds were established each eaturing dierent sizes andsettings. 20 people were involved in the project and the ngerlings and juvenile shes were captured romthe mangroves. The study assumes that all income rom the aquaculture production can be related to themangrove valuation since the ponds were established as a mangroves related project.

The sh species is milksh and the eed is maize jam, which costs Ksh 2,000 per bag (270 Kg). The shes areed on a daily basis. For the 4 ponds, 5 Kg o maize jam are used every day. The total cost o 1,825Kg o maizejam per year is therewith Ksh 13,518. The milksh takes 5 months to grow, which results in 2.4 intakes peryear. The milksh is sold at Ksh 100. According to A. Hamsa (pers. comm.) the costs o construction o the twoUNDP ponds were Ksh 397,245 including the repair o the two other ponds. The total cost or the KMFRI pond

was Ksh 175,000. The construction o the communal pond was Ksh 70,000 (Wanjiru, pers. comm.). The totalconstruction costs were thereore Ksh 642,245. It is also assumed that the ponds have to be rebuilt ater 8 years,which results in annualized construction costs o Ksh 80,280. The revenue rom the ponds is as ollows:


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Table B10: Revenues rom auaculture ponds in Gazi

Pond SizeFish population

density

Potential number

o shes / yearRevenues Ksh

KMFRI 180m2 2 shes / m2 864 86,400

UNDP1 180m2 2 shes / m2 864 86,400

UNDP2 180m2 3 shes / m2 1296 129,600

Communal 80m2 2 shes / m2 384 38,400

TOTAL 620m2 - 3408 340,800

Source: Wanjiru, Aquaculture Management Gazi, pers. comm. March 2011

Income rom the ponds is derived as ollows:

Table B11: Income rom auaculture production in Gazi

Parameter Amount

Revenues (Ksh / year) 340,800

Feeding costs (Ksh / year) 13,518

Construction costs (Ksh / year) 80,280

Income ( Ksh / year) 247,002

Mangroves (ha) 620

Value o aquaculture ( Ksh / ha / year) 3984

The value o aquaculture production in Gazi Bay is Ksh 398.4 ha-1

y-1

, (US$ 48 ha1

y1

). Although quite low a realpotential exists. Up to now only 4 ponds have been built and the revenues are distributed over 620 hectares omangroves. The concept is new and requires more research and practical application until it becomes a steady,alternative income source besides the oshore shing.

B6 APICULTURE

The rst mangroves-related apiculture project in Gazi was introduced in 2010. Ater some problems withcolonisation the rst harvest was completed in the beginning o 2011. Apiculture is usually implementedthrough the establishment o bee hives. Since the apiculture project was introduced as a new way o creatingbenets rom the Gazi mangroves, this study assumes that the income rom the bee hives can be added in itswhole to the valuation. In addition, the bees get the nectar rom the mangroves owers and no other valuable

sources are available in Gazi.

A total o 24 hives were built, each with 9 columns. Each column produces 3Kg o honey in 3 months. Thisresults in 108Kg o honey / hive / year. The 24 hives are able to produce 2,592Kg o honey in one year. Thehoney can be sold at Ksh 300/Kg. The total potential annual revenue is thereore: Ksh 777,600 per year. Theconstruction costs were Ksh 122,690 (Hamsa, pers. comm.). Without a protective shade a hive can last 10 years.Annualizing the construction costs results in annual costs o Ksh 12,269. The potential total annual incomeis thus: Ksh 765,331 per year or Ksh 1234.4ha -1y-1, which is equivalent to US$ 147 ha1y1. I this business isexpanded successully it will constitute an important alternative source o income. However, problems ariserom an insucient amount o owers and reshwater. Articial sources have to be provided to keep the beesrom using owers and reshwater wells close to the village which could create problems or the communityand visiting tourists.


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C RESULTS FOR INDIRECT USE VALUES

C1 SHORELINE PROTECTION

Studies show that where mangroves are intact they work as an eective buer against tsunamis (UNEP-WCMC 2006). The death toll ater the 2004 tsunami was signicantly lower in areas where mangroves hadremained unharmed (Das et al., 2008). Mangroves also prevent soil erosion and damage rom the rise in sea-level. This study ocuses only on the valuation o mangroves as a protection against extreme weather eventssuch as tsunamis, cyclones or hurricanes. While some researchers generalized the protective unction omangroves to entire coastlines others have ocused on the apocalyptic nature o these events and thereoreminimized the contribution o mangroves to shoreline protection (see Walters et al., 2008). Kairo et al.(2009) valued shoreline protection as a major service o mangroves with close to 55% o the total economicvalue. In other studies (Spurgeon, 2002; Leong, 1999) the proportion is less. Other valuations range romUS$ 32 ha-1y-1 to US$ 3,679 ha-1y-1 (Bann, 1997, Sathirathai et al., 2001). Barbier et al. (2008) claims that shorelineprotection is one o the most undervalued mangrove ecosystem services yet mangroves can provide protectionto coastal communities up to 5km inland. The study also points out that beneters can be dierent dependingon the use o the land. While outside investors may benet rom converting mangroves into uses such as

shrimp arms, local communities mostly gain prots rom protection and wise use o mangroves.

The valuation itsel is complex since a number o actors and aspects have to be incorporated and dierentmethodologies applied. The most widely used method is the Replacement Cost Method (RC) which derives thevalue o a man-made seawall as having the same protective eect or the shoreline. The value is then applied tothe mangroves (Kairo et al. 2009, Spurgeon 2002). The alternative is the Damage Cost Avoided Method whichcalculates the potential damage a tsunami would have on the urban inrastructure or losses in agriculture imangroves did not exist (Ruitenbeek, 1992). This study applies the damage cost avoided method.

Studies show that 30 trees per 100m2 in a 100m wide belt may reduce tsunami ow rate by as much as 90% (EjF,2006). Dierent studies on the impact o the tsunami in 2004 indicated that in an area with an intact mangrovebelt only 7 per cent o the villages were severely aected, while in areas where the mangrove orests were

degraded, damage reached 80-100 per cent (Dahdouh-Guebas, 2006). Taking 80 per cent as representative,this corresponds to an additional protection o 73 per cent o the villages due to mangroves.

The impacts o a potential tsunami on the Kenyan coast are likely to be severe (Ngunjiri, undated). Since anyextreme weather event occurs randomly and likelihood predictions do not exist, gures here have to beinterpreted cautiously. As o 2011 only the 2004 tsunami which hit the Southeast Asian coastlines aectedKenya.

The greatest threat or the Kenyan coastline, however, is the Karthala volcano on the Comoros. It is active andhas had our diering scale eruptions since 2005. Another large scale outbreak could lead to lava owing intothe ocean and trigger a tsunami which would eventually cause havoc along the Eastern Arican coastline. The

increasing requency o eruptions rom the Karthala volcano since 2005 raises concerns about the potential othe volcano to produce a major eruption, which could have severe consequences. A tsunami caused by lavaow into the Indian Ocean rom the Karthala volcano, could reach Mombasa in less than 30 minutes (Hartnady,2005) (Map 2). According to Hartnady (per. comm.) the Karthala represents a possible tsunami hazard due tolarge-scale ank collapse on its western side. Taking into account recent developments this study assumesthat the probability o an eruption o Karthala and other threats, including or example an accompanyingtsunami caused, could lead to damage in Gazi Bay roughly estimated at 5 per cent per year. This gure includesall possible weather events that occur rom the sea and which could aect Gazi Bay. It is pointed out that theassumptions o 73 per cent additional protection through mangroves and 5 per cent likelihood o a severeweather event are limited in their validity. The value or shoreline protection as it is quantied in this study isonly a preliminary result and requires urther investigations.


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Map 2: Potential spread o a tsunami wave rom Karthala lava fow

Data source: Giri et al. (2010); Hartnady (2005). Map redrawn by UNEP/DEWA

Gazi mangroves protect two nearby villages: Gazi and Makongeni. According to Dr. Kairo (KMFRI, pers. comm.)there are about 700 houses around the bay o which 500 are in Gazi and 200 in Makongeni. The average houseprice is as ollows:

Gazi Bay

I n d i a n

O c e a n

Karthala

volcano

< 30 Min

Tanzania

Kenya

Madagascar

Mozambique

300'0"E

00'0"

150'0"S

300'0"S

In di an

O c e a n

Eastern AfricaEastern Africa

Legend

Mangroves

Tsunami waves0 500250

Kilometers


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Table C1: Calculation o the average house price

Status o house Village compositionHouse price

US$

Contribution to total avg

house price US$

Permanent 15% 5000 750

Semipermanent 70% 2000 1400

Temporary 15% 500 75

TOTAL 100% - 2225

Source: Kairo, pers. comm. March 2011

Assuming 700 houses (with an average house price o US$ 2,225), 5 per cent likelihood or a severe weatherevent and an additional protection o 73 per cent, the shoreline protection value o the mangroves can becalculated as ollows:

Table C2: Valuation o shoreline protection

A Number o houses ~700

B Average house price(US$) 2,225

C Value houses (US$) (A*B) 1,557,500

D Likelihood o any severe weather event at the Kenyan coastline per year 5%

EValue shoreline protection(C*D*0.73 in US$)

56,848.75

F Mangroves in Gazi Bay (ha) 620

G

Value shoreline protection

( US$ / ha / year ) 917

Following this approach the value o shoreline protection rom any possible severe weather events becomesUS$ 917 ha1y1. At Gazi Bays western coast, signs o signicant coastal erosion are obvious. Stones had tobe brought to the beach to prevent urther soil erosion. These stones could represent the value o a sea wall.

C2 CARBON SEqUESTRATION

Due to climate change carbon sequestration by orests continues to gain in value. Due to their high biomassdensity and productivity mangroves play a signicant role in carbon sequestration. According to Giri et al.(2010) mangroves, including associated soil, could sequester approximately 22.8 million metric tons o carbon

each year. Covering only 0.1 per cent o the earths continental surace, the orest would account or 11 percent o the total input o terrestrial carbon into the ocean and 10 per cent o the terrestrial dissolved organiccarbon exported to the ocean. Another study calculated net photosynthetic rates o 155 kg C ha -1day-1 in a22-year old Rhizophora apiculata orest in Malaysia (Walters et al., 2008). This study assumes a carbon price oUS$ 7 per ton and a biomass o 18 t C ha -1y-1. These assumptions limit the validity o the results, since priceschange signicantly over time.

Sequestration itsel is complex, since many dierent actors inuence the intensity o sequestration. Figure 2gives an overview o the complexity o the process.


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Figure 2: Process o carbon seuestration in mangroves

Source: Bouillon et al. (2008)

A number o attempts to measure the ability o Gazi mangroves to sequester carbon have been undertaken.While most o these attempts were rather based on ecological approaches, Kairo et al. (2010) came up witha straightorward result o 18 tC ha -1y-1 carbon benet potential. Carbon prices change depending on thelocation o the market, the type o market (e.g. Voluntary market) and supply and demand. This study assumesa price o US$ 7 per ton. These assumptions result in an additional mangrove value oUS$ 126 ha1y1

C3 BIODIVERSITY

Few studies have measured the value o biodiversity in mangroves. Nonetheless, mangroves in their

undisturbed state are regarded as a reuge or rich biodiversity. Valuing biodiversity in monetary termsis one o the newest approaches in the eld o environmental economics. The current discussion is stucksomewhere between ethical concerns about trying to put a value on lie, and complex analysis models thattry to quantiy its value. Ruitenbeek (1992) denes the capturable biodiversity benet as the potentialbenet which the country might be able to obtain rom the international community in exchange ormaintaining its biodiversity base intact. Biodiversity value combines direct, indirect and non-use valueand is a valuation o human preerence rather than actual value (UNEP/GPA, 2003).

The greatest challenge is the non-use or non-marketable character o biodiversity. This problem has led tothe act that most attempts to value biodiversity apply the Contingent Valuation Method (CV). It is the mostwidely used method or estimating non-use values. It is based on the Willingness to Pay (WTP) concept,which includes surveys o the local and regional communities, asking them to place a monetary value on the

mangroves and say, what they are willing to pay to conserve the biodiversity. The advantages o this methodare its exibility and has wide acceptance. However, CV is costly. Oten, researchers use the Benet TranserMethod (BT). The procedure estimates the value o an ecosystem service by transerring an existing valuationestimate rom a similar ecosystem (TEEB, 2010). According to TEEB (2010) BT is the second most appliedmethodology to estimate services o wetlands. Thereore its application here to calculate the biodiversity valueis justied.

In reality, what valuation studies normally measure is the economic value o biological resources rather thanbiodiversity (Bann, 1997). Other studies suggest that the value o biodiversity should be expressed as or shouldat least include the value o medicinal and pharmaceutical extracts rom the orest (Abeysinghe, 2010). Thisindicates that mangroves might be a source o dierent medicinal properties such as specic antibacterial

eatures. Following this approach Ruitenbeek (1992) came up with a biodiversity value o US$ 15 ha-1

y-1

,measuring mainly the pharmaceutical value o the mangroves. UNEP/GPA (2003) used the ollowing benettranser ormula to calculate the value o biodiversity o mangroves in Sri Lanka:

faunal assimilation

and respirationsediment-atmosphere

and sediment-water

CO2 exchange

sediment

burial exchange

of POC, DOC

and DIC

root production

wood production

water-atmosphere

CO2 eux

litter fall

direct herbivory


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Euation 3: Benet Transer Method

Valuey

= Valuex

(PPP GNPy

/PPP GNPx)E

Where:PPP GNP =Purchasing power parity GNP per capita

E = Elasticity o values with respect to real income (UNEP/GPA (2003) assumed E=1.00)E = 1.00 implies a 1 per cent change in WTP relative to a 1 per cent change in real income.

This method was adopted in this study or estimating non-use benets o mangroves. Using this ormula,UNEP/GPA (2003) estimated a value o US$ 18 ha -1y-1 or biodiversity. The data or the PPP GNP are as ollowsaccording to the World Bank (2011):

PPP GNPSri Lanka 2009

= US$ 4,720PPP GNP

Kenya 2009= US$ 1,570

Applying the gures gives the ollowing result:

US$ 18 [US$ 1570 / US$ 4720]1.00 = US$ 5 ha1y1

Due to the relatively low PPP GNP o Kenya the value o biodiversity o the Kenyan mangroves, using BT, is onlyUS$ 5 ha-1y-1. This value might change signicantly, i a dierent methodology, such as WTP, is applied. Thisrequires extensive eld work and it is put orward as a recommendation to conrm the theoretically calculatedresults.

Rhizophora Mucronata



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D RESULTS FOR NON-USES VALUES

D1 EXISTENCE VALUE

The simple acknowledgement o the existence o the mangroves can also be valuated. This expresses theintrinsic value o mangroves, considering cultural, aesthetic, heritage and landscape aspects (Ghani, 2006). Inthis case, all direct or indirect uses o the mangrove orest are not considered and the ecosystem is let withoutharming or using it. To come up with a monetary valuation o the existence o an ecosystem, Willingness ToPay (WTP) is applied by asking aected people how much value they would put on the simple existence andconservation o the relevant ecosystem. In other words the existence value o a natural resource is identiedwith the member o societys WTP or the preservation or the use o the recreation value o orests and naturalecosystem (Deghani et al., 2010).

This study uses BT values rom Spurgeon (2002) in Egypt. The limitations o the validity o this approach areacknowledged. Dierences in environmental settings, societys dependence on mangroves and in the wealtho the population can inuence the WTP signicantly. It is thereore strongly recommended that contingentvaluation should be applied in Gazi Bay in order to quantiy the existence value more accurately. Table D1 and

D2 show the estimates or the non-use value o the mangroves in Egypt. The data were obtained rom nationalstatistics.

Table D1: Potential national nonuse value or Egypts mangroves

Parameter Low Best High

National population (2002) - 66,000,000 -

% population willing to pay (WTP) 1% 2.5% 10%

WTP US$/year 0.1 1 5

Area of mangroves (ha) - 500 -

Total value of mangroves (US$/year) 66,000 1,650,000 33,000,000

Value of mangroves (US$/ha/year) 132 3,300 66,000

Source: Spurgeon, 2002

Table D2: Potential visitors nonuse value or Egypts mangroves


Visitors to Sinai and Red Sea (2002) - 2,400,000 -

% visitors willing to pay (WTP) 5% 20% 40%

WTP US$/person 1 10 20

Area o mangroves (ha) - 500 -

Total value o mangroves (US$/year) 120,000 4,800,000 19,200,000

Value o mangroves (US$/ha/year) 240 9,600 38,400

Source: Spurgeon, 2002


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Using the same approach or Kenya leads to the ollowing results:

Table D3: Potential Kwale population nonuse value or Gazi Bays mangroves

Parameter Low Moderate High

Population Kwale district (2010) 650,000 650,000 650,000% o population willing-to-pay (WTP) 1%* 2.5%* 10%*

WTP US$ / year 0.1* 1* 5*

Area o mangroves in Gazi (ha) 620 620 620

Total value o mangroves (US$/yr) 650 16,250 325,000

Value o mangroves (US$/ha /yr) 1.05 26.21 52419

*Assuming distribution rom Spurgeon (2002)

People along the Kenyan coastline depend heavily on mangrove products. Thereore, consciousness o

mangroves in Kenya can be assumed to be higher than in Egypt. Conclusively the parameter column high canbe stated as being representative or Kenya. This results in a US$ 524.19 ha-1y-1 mangrove existence value whenusing the theoretical approach. Gazi Bay is home to around 3,000 inhabitants (Kairo, pers. comm.). Table D4 isa proposal or uture use.

Table D4: Potential national nonuse value or Gazi Bays mangroves Empirical approach


Population in Gazi Bay 3,000 3,000 3,000

% o Gazi Bay population willing-to-pay ? ? ?

WTP US$ / yr ? ? ?Gazi Bay (ha) 620 620 620

Total value o mangroves (US$/yr)

Value o mangroves (US$/ha/yr)

? Questionnaire / Survey needed

On average round about 4,000,000 tourists per year visit the coastline o Kenya (KBS, 2010). Kenya as a wholeeatures around 57,000 hectares o mangroves.

Table D5: Potential visitors nonuse value or Gazi Bays mangroves Theoretical approach


Visitors o the Kenyan coastline 4,000,000 4,000,000 4,000,000

% o coastal visitors willing-to-pay ( WTP) 5%* 20%* 40%*

WTP US$ / yr 1* 5* 20*

Area o mangroves in whole Kenya (ha) 53,000 57,000 61,000

Total value o mangroves (US$/y) 200,000 800,000 3,200,000

Total value o mangroves (US$ / ha /y) 3.8 702 524.6

*Assuming distribution and WTP rom Spurgeon (2002)


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Since coastline tourists are usually only moderately interested in mangroves and most o them stay in hotelsclose to Diani Beach or Mombasa, the column Moderate is assumed to be appropriate. The existence value othe mangroves or visitors is thereore US$ 702 ha1y1. Table D6 is a proposal or uture use.

Table D6: Potential visitors nonuse value or Gazi Bays mangroves Empirical approach, WTP


Visitors in Gazi Bay (2010) 1,673 1,673 1,673

% of Gazi Bay visitors willing-to-pay (WTP) ? ? ?

WTP US$ / year ? ? ?

Gazi Bay (ha) 620 620 620

Total value of mangroves in Gazi Bay (US$/y) ? ? ?

Total value of mangroves in Gazi Bay (US$/ha/y) ? ? ?

? Questionnaire / Survey needed

Table D7: Existence value o the mangroves in Gazi Bay Theoretical approach

Parameter Result

Existence value o mangroves or nationals ( US$ / ha / yr ) 524.19

Existence value o mangroves or visitors ( US$ / ha / yr ) 70.2

Total existence value o mangroves US$ / ha / yr 59439

It is a well-known act that this approach is greatly inuenced by local and regional circumstances such aswealth, education and awareness o the matter. For instance, Leong (1999) derived a signicant existence value

o US$ 26.439 ha-1

y-1

. In addition, since Kenya eatures a much higher amount o mangroves than or exampleEgypt, per hectare values in Kenya must be lower because the total amount o WTP is distributed over a largerarea o mangroves.



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E TOTAL ECONOMIC VALUE (TEV)

The Total Economic Value consists o the three components: Direct Use Value, Indirect Use Value and Non-UseValue (Sathirathai, 1995). Thus TEV is made up o use value and non-use value. By denition, use values deriverom the actual use o the environment while non-use values are non-instrumental values which are in the realnature o the thing but unassociated with actual use, or the option to use the thing. Instead such values aretaken to be entities that reect peoples preerences, but include concern or, sympathy with, and respect orthe rights or welare o non-human beings. The TEV value or the mangrove orest o Gazi bay is summarizedin Figure 3.

Figure 3: Total Economic Value mangrove orest Gazi Bay TEV

TOTAL ECONOMIC VALUE

US$ 1,092.3 / hectare / year

Direct Use Value

US$ 275.2 / ha / year

FisheryUS$ 44 / ha / year

Building polesUS$ 4 / ha / year

Fuel woodUS$ 16.8 / ha / year

Eco-tourismUS$ 6.5 / ha / year

ResearchUS$ 184.4 / ha / year

ApicultureUS$ 14.7 / ha / year

AquacultureUS$ 4.8 / ha / year

Indirect Use Value

US$ 217.7 / ha / year

Shoreline protectionUS$ 91.7 / ha/ year

Carbon sequestrationUS$ 126 / ha / year

BiodiversityUS$ 5 / ha / year

Non-Use Value

US$ 594.4 / ha / year

Existence valueUS$ 594.4 / ha / year


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F DISCUSSION

The Total Economic Value (TEV) o the mangroves in Gazi Bay is US$ 1,092.3 ha-1y-1. Direct uses account oraround 25 per cent o the TEV. Mangroves should be used in a sustainable way to guarantee preservationor uture generations and the conservation o the indirect uses, particularly shoreline protection and carbonsequestration. These uses will diminish in value i the orest is not managed sustainably.

Indirect uses represent 20 per cent o the TEV. This share is likely to increase in the uture as the issue o carbonsequestration becomes more and more important. The market or carbon credit is expanding rapidly andcould become the biggest global commodity market in the near uture. Additionally, sea-level rise threatensthe distribution o mangroves, leading to an increase in the value o shoreline protection.

The non-use value contributes the biggest share to the TEV o about 55 per cent. This gure should bereconsidered since no primary data is available. The application o the contingent valuation method (CV) couldresult in a more accurate gure.

The contribution o mangroves to on- and oshore sheries in Gazi is valued at US$ 44 ha-1y-1. This is signicantly

less than the value that Kairo et al. (2009) derived or the reorested area, which was US$ 113.09 ha-1

y-1

. This isdue to the act that this study assumes a contribution o mangroves to shery o 31.7 per cent, while Kairo etal. (2009) assumed 100 per cent. It is a well-known act that sea grasses and coral rees play a signicant role incoastal sheries. This justies the assumption o a close to one third contribution. Spurgeon (2002) estimated avalue o US$ 18,150 ha-1y-1, assuming that the 500 hectares o mangroves support shery along the whole RedSea coast. This study assumes that mangroves only support shery around Gazi Bay. The Bay itsel is protectedby Chale Island and thereore creates a rather isolated ecosystem with the adjacent coral ree in the South.Most o the shing is done close to the coral ree. The limitation o the mangroves contribution to shery inGazi to the bay is thereore acceptable.

Global estimates or the shery value o mangroves range rom US$ 84 ha-1y-1 (Sathirathai, 1995) to US$ 39,750ha-1y-1 (Aburto-Oropeza et al., 2008). The wide range is due to the variability o the actors included in the

analysis. For instance, the extent o the area that is considered to belong to the range o inuence o themangroves diers signicantly between the studies. Secondly, the contribution o mangroves to shery ishandled dierently (see Table B2). Thirdly, the amount o catch is subject to local environmental conditions,the provision o shing gear and the richness o the shing grounds. This study uses a rather strict assumptionregarding the contribution o mangroves to shery and the value ranges at the lower end o the spectrum.

This study also uses a conservative approach when calculating the allowable amount o harvestable wood.The value or building poles and uel wood amounts to US$ 20.8 ha-1y-1. According to Spalding et al. (2010) theglobal range o timber/uel wood value is US$ 10 - 1,093 ha-1y-1. Kairo et al. (2009) valued the building polesat US$ 360.67 ha-1y-1 or the replanted area. In recent years the cutting o mangroves in Gazi has been highlyrestricted and only one person is issued with a license. The allowable amount is limited to 500 scores, each

consisting o 20 stems. This is equivalent to only 16 stems ha-1

y-1

. In comparison, Kairo et al. (2009) assumeda total amount o harvestable wood o 241 scores or 4819 stems ha-1y-1. The reorested area is planted with adensity o one tree per 1- 1.5m2. Thereore the amount o trees per hectare is estimated to be around 8,000.Using the gures rom Kairo et al. (2009), one would cut 60 per cent o all trees every year. This cannot beclassied as sustainable harvesting and is thereore not the appropriate gure or the valuation. This studyinstead relies on primary data o the concessionaire, who stated that he is only allowed to cut 500 scores peryear. Considering these strict limitations a value o US$ 4 ha -1y-1 or the building poles is reasonable.

Fuel wood is valued at US$ 16.8 ha-1y-1. This is close to the value o US$ 18.5 ha -1y-1 that Kairo et al. (2009)calculated or the reorested area. It is still a bit less, which can be explained by the act that the reorested areais more densely planted than the natural orest surrounding it.

Eco-tourism in Gazi is valued at US$ 6.5 ha-1y-1. Kairo et al. (2009) valued it with US$ 9.3 ha-1y-1. A global overviewprovided by Spaldings et al. (2010) presents a range o US$ 43 152,100 ha-1y-1 or mangrove-related tourism.The value o tourism in Gazi is low because o the act that tourism in Gazi Bay is really in its inancy. The only


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income rom tourism related to the mangroves comes rom the Gazi Women Boardwalk that had ~ 1700visitors in 2010 and charges only Ksh 100 per person. Nonetheless there is potential or more tourism in Gazi,especially i tourists rom the nearby Diani-Beach are made aware o eco-tourism at Gazi.

Research and education in the Gazi mangroves is valued at US$ 184.4 ha-1y-1. This is less than the US$ 770.23 ha -1y-1 that Kairo et al. (2009) obtained, but that study distributed the whole amount o current unding over only

7 hectare o replanted mangroves, which naturally led to a higher per hectare value. Globally, little researchhas been on the research and education value o mangroves. Spurgeon (2002) estimated US$ 18,000 ha -1y-1,based on the setting that less mangroves exist in the Egypt than in Kenya, which obviously leads to higher perhectare value.

Aquaculture production is valued at only US$ 4.8 ha -1y-1 since it is in early stages o establishment in Gazi.No comparable estimates have been done so ar, which makes the project in Gazi a pilot project or othermangroves sites, with aquaculture as an alternative income source or the local community. It is importantto stress that no mangroves should be harvested to make space or the ponds. Only the juvenile sh or theponds should be obtained rom the mangroves so that they actually contribute to the aquaculture production.Once well established, the ponds in Gazi can be expanded. Thereore there is a high potential or the value to

appreciation in the uture.

What is true or aquaculture production is also valid or apiculture in Gazi. As a project that has been establishedonly recently, the current value ranges at US$ 14.8 ha-1y-1. However, it is higher than the value derived bySpurgeon (2002), which is US$ 0.8-1 ha-1y-1, since no noteworthy beekeeping had been established in theEgyptian mangroves by then.

Indirect usage o the Gazi mangroves consists o shoreline protection, carbon sequestration and biodiversity.This study suggests a value o US$ 91.7 ha-1y-1 or the shoreline protection unction o the mangroves. Kairoet al. (2009) used the sea wall replacement method, which resulted in US$ 1,586.66 ha-1y-1. This study uses theDamage Costs Avoided Method, since the replacement method does not consider the dierences o space o amangrove orest and a sea wall. In addition, a sea wall does not eature the same costs and characteristics when

assumed to be replaced at a completely dierent site. However, even the Damage Costs Avoided Method islacking accuracy, since the prediction o a severe weather event aecting Gazi Bay is highly speculative. It isthereore recommended that urther research on the actual protection value o mangroves rom erosion andtsunamis be conducted.

Carbon sequestration is one o the major unctions o mangrove orests. Since markets or carbon credits arestarting to emerge, the ocus o research on mangrove services is shiting towards their ability to sequestercarbon. The ability depends on the productivity o the ecosystem which is varies rom site to site depending onlocal precipitation patterns, salinity and solar intensity. Eastern Arica belongs to the region where mangroveseature less productivity than or instance, in Southeast Asia. However, they are still able to sequester signicantamounts o carbon by producing new biomass while storing carbon in the above and below biomass.In Gazi Bay, the reorestation project dubbed Mikoko Pamoja (Kairo et al., 2010) provided reliable data oncarbon sequestration o Gazi mangroves. Using those gures, this study derives a value o US$ 126 ha-1y-1. Thisrepresents an increase in value compared to the value o the reorested area rom Kairo et al. (2009), althoughthis study uses a price o US$ 7 per metric tonne o Carbon (tC), instead o US$ 10 per tC, which is what Kairo etal. (2009) assumed. Up to now, only ew valuation studies world-wide have integrated carbon sequestration intheir analysis. UNEP/GPA (2003) derived a value o US$ 85 ha-1y-1 (Spalding et al., 2010).

This study values biodiversity at US$ 5 ha-1y-1. The concept o biodiversity valuation is a relatively new eature inenvironmental economics (TEEB, 2010). The most accurate procedure to calculate it is to conduct a survey andask locals or their Willingness to pay (WTP). This study uses the widely accepted Benet Transer Method(BT) instead, which is much easier to apply. The global valuation overview o Spalding et al. (2010) rangesbiodiversity value at US$ 1-21 ha-1y-1.

Existence value as the only non-use value component o the TEV in this study is valued atUS$ 594.4 ha-1y-1. Since this value is calculated with BT rom the study in Egypt (Spurgeon, 2002), it is highly


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recommended that a questionnaire is designed and a survey conducted to derive a more appropriate gureor the non-use value.

The TEV o this study results in US$ 1,092 ha-1y-1. Kairo et al. (2009) valued the replanted area o 7 hectares oRhizophora mucronata at US$ 2902.9 ha-1y-1. However, this study ocuses much more on a sustainable use othe mangroves, which is the reason or the comparably low TEV. Global estimates range rom ~ US$ 1,000

ha-1y-1 to ~ US$ 22,000 ha-1y-1 (Spalding et al., 2010). Although the study provides values at the very lowerend o the valuation range this can be justied by several actors. Gazi Bay is just at its inancy in terms otourism development, strict limitations or harvesting are in place, and the abundance o mangroves along theKenyan coastline diminishes the per hectare value considerably. This means that tourism income, WTP or themangroves and research unds are distributed over a larger area.

This study shows that mangrove orests are a signicant natural asset in a given economy. Decision-makersare encouraged to consider these non-marketable goods and services when calculating the national accounts.Acknowledging the value o mangroves as

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