Shrimp Farming and Mangrove Loss in Thailand This Page Intentionally Left Blank Shrimp Farming and Mangrove Loss in Thailand

Shrimp Farming and Mangrove Loss in Thailand This page intentionally left blank Shrimp Farming and Mangrove Loss in Thailand

Edited by Edward B. Barbier John S. Bugas Professor of Economics, Department of Economics and Finance, University of Wyoming, USA

Suthawan Sathirathai President, Good Governance for Social Development and the Environment Institute (GSEI), Bangkok, Thailand

Edward Elgar Cheltenham, UK • Northampton, MA, USA © Edward B. Barbier, Suthawan Sathirathai 2004 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher.

Published by Edward Elgar Publishing Limited Glensanda House Montpellier Parade Cheltenham Glos GL50 1UA UK Edward Elgar Publishing, Inc. 136 West Street Suite 202 Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library

Library of Congress Cataloguing in Publication Data Shrimp farming and mangrove loss in Thailand / edited by Edward B. Barbier, Suthawan Sathirathai. p. cm. Includes bibliographical references (p. ) 1. Shrimp culture—Environmental aspects—Thailand. 2. Shrimp culture— Economic aspects—Thailand. 3. Mangrove ecology—Thailand. 4. Endangered ecosystems—Thailand. I. Barbier, Edward, 1957– II. Suthawan Sathirathai. SH380.62.T5S48 2003 639′.58′09593—dc22 2003049352 ISBN 1 84376 601 9

Typeset by Cambrian Typesetters, Frimley, Surrey Printed and bound in Great Britain by MPG Books Ltd, Bodmin, Cornwall Contents

List of contributors vii Preface ix Map of Thailand indicating Phang-nga and Nakhon Si Thammarat provinces xii

1. Introduction: global mangrove loss and economic development 1 Edward B. Barbier and Mark Cox

PART INATIONAL TRENDS AND ANALYSIS OF MANGROVES

2. The importance of mangroves: ecological perspectives and socio-economic values 27 Sanit Aksornkoae, Ruangrai Tokrisna, Wattana Sugunnasil and Suthawan Sathirathai 3. Overview of shrimp farming and mangrove loss in Thailand 37 Sanit Aksornkoae and Ruangrai Tokrisna 4. Analysis of shrimp farm expansion and mangrove conversion in Thailand, 1979–96 52 Edward B. Barbier and Mark Cox

PART II CASE STUDIES: PHANG-NGA AND NAKHON SI THAMMARAT

5. Analytical background of the case studies and research sites: ecological, historical and social perspectives 73 Sanit Aksornkoae, Wattana Sugunnasil and Suthawan Sathirathai 6. Mangrove dependency, income distribution and conservation 96 Isra Sarntisart and Suthawan Sathirathai 7. Household use of mangrove and mangrove conservation decisions 115 Edward B. Barbier, Mark Cox and Isra Sarntisart

v vi Contents

8. The effects of mangrove loss on the labor allocation of households 131 Edward B. Barbier and Mark Cox 9. Analysis of shrimp farms’ use of land 154 Ruangrai Tokrisna 10. Coastal communities, mangrove loss and shrimp farming: social and institutional perspectives 191 Wattana Sugunnasil and Suthawan Sathirathai 11. Comparative returns of mangroves for shrimp farming and local direct and indirect uses in Surat Thani Province 210 Suthawan Sathirathai and Edward B. Barbier

PART III MANGROVE LOSS AND SHRIMP FARMING IN THAILAND: CONCLUSIONS

12. Conclusions of the study and policy recommendations 231 Edward B. Barbier and Suthawan Sathirathai

References 249 Index 260 Contributors

Sanit Aksornkoae, professor, Department of Silviculture, Kasetsart University, Bangkok, Thailand

Edward B. Barbier, professor, Department of Economics and Finance, University of Wyoming, USA

Mark Cox, Centre for Environment and Development Economics, University of York, UK

Isra Sarntisart, associate professor, Faculty of Economics, Chulalongkorn University, Bangkok, Thailand

Suthawan Sathirathai, Good Governance for Social Development and the Environment Institute (GSEI), Bangkok, Thailand

Wattana Sugunnasil, assistant professor, Department of Social Sciences, Prince of Songkla University (PSU), Pattani, Thailand

Ruangrai Tokrisna, associate professor, Department of Agricultural and Resource Economics, Kasetsart University, Bangkok, Thailand

vii This page intentionally left blank Preface

The following study was a collaborative effort between a team of Thai and international researchers to study the problem of shrimp farm expansion and mangrove loss in Thailand. To our knowledge, this is the first comprehensive study of economic, ecological and social causes and consequences of shrimp farm expansion and the corresponding impacts on coastal mangroves in any country of the world. Such study is long overdue. In recent decades scientists, mainly ecologists, have been alerting the global community to the problem of mangrove deforestation in tropical regions. The main activity thought to be responsible for the conversion of mangroves is the expansion of shrimp aquaculture production. In turn, the widespread destruction of mangrove ecosystems has entailed the loss of important ecological resources and services, including the role of mangroves in stabilizing shorelines, as storm barriers and as breeding grounds and nurseries for offshore fisheries. However, mangrove deforestation due to shrimp farm expansion is not just an ecological problem but also an economic one. Shrimp aquaculture is a very profitable financial investment and generates substantial export earnings. This is particularly welcomed in developing countries. For example, Thailand is currently the world’s leading exporter of cultured shrimp, which generates annually US$1–2 billion in foreign exchange. On the other hand, the loss of mangroves and other external costs, such as the release of untreated wastewater, generate substantial environmental damages. The financial gains to private investors, as well as the export earnings to the country, may therefore over-state the economic gains from shrimp farming. Mangrove loss is also a social problem. In many tropical countries, and certainly in Thailand, a significant number of local communities in coastal areas have always lived and thrived among the mangrove forests. The resources and ecological functions of these forests are not only valuable to the economic livelihoods of many communities but are also important to their culture and social institutions. It is these communities that bear the burden of the ecological, economic and social consequences of the widespread loss of mangrove forests due to shrimp farm expansion. The following study was conducted from July 1999 to January 2002, funded by the Population, Consumption and Environment Initiative of the Program on Global Security and Sustainability, of the John D. and Catherine

ix x Preface

T. MacArthur Foundation. The research involved both an international collaborative effort and interdisciplinary cooperation. There were many ways in which we could have approached this task. In the end, we decided on a two- dimensional approach. The first dimension involved providing some idea of the problems posed by shrimp farm expansion and mangroves loss at the global, national and local level. The second dimension was to go beyond just an economic analysis of these problems to provide some indication of the ecological and social aspects as well. With these two dimensions in mind, we structured the chapters of the study in the following way. Chapter 1 provides an overview of the global problem of mangrove loss, as well as an empirical analysis of a cross-section of 89 countries containing mangroves to assess the extent to which mangrove deforestation worldwide is associated with expansion of aquaculture production and primary sector (agricultural) activities more generally. Part I of this study focuses on shrimp farm expansion and mangrove conversion at the national level in Thailand. As noted in Chapter 2, in Thailand the loss of mangrove forests has meant the subsequent decline of important ecological services, especially to local coastal communities. Chapter 3 provides an overview of the scale of mangrove loss as well as shrimp farm expansion in Thailand over the past 35 years, with emphasis on the recent trends since 1989. To shed light on the role of the profitability of shrimp farming, as well as other economic factors, in determining both mangrove deforestation and shrimp farm expansion in Thailand over the critical 1979–96 period, Chapter 4 provides an in-depth empirical analysis of mangrove conversion in Thailand’s 21 coastal provinces. Part II switches the focus to detailed analyses of shrimp farm expansion, mangrove conversion and the resulting impacts on local communities in four representative case study sites, two from Nakhon Si Thammarat Province on the Gulf of Thailand and two from Phang-nga Province on the Andaman Sea coast. Chapter 5 provides the ecological, historical and social background to the four case study sites. Chapter 6 analyzes more extensively the consumption behavior of households in the four case representative village sites, and in particular the dependence of household income and consumption on local mangroves. Both Chapters 6 and 7 examine whether the degree of mangrove dependency of households in the case study sites influenced their willingness to participate in mangrove conservation, such as replanting activities. Chapter 8 investigates the extent to which the degree of the dependence of a household on local mangroves for income, as well as the loss of that forest, may affect the household’s decision to seek outside employment. Chapter 9 examines more broadly the development of shrimp farming in Muang and Pak Panang Districts, Nakhon Si Thammarat Province and Takua Thung and Muang Districts, Phang-nga Province, utilizing surveys of representative samples of Preface xi shrimp farmers from these two districts. Chapter 10 is an institutional analysis of the willingness and capability of stakeholders, consisting of both governmental officials and local communities, in effectively conserving the mangrove forests in the vicinity of the four case study sites. The chapter also examines whether appropriate laws and policies exist to provide the right incentives and an effective system of checks and balances for mangrove conservation and sustainable management. Finally, if there is to be a change in governmental policy towards mangrove management, then the impetus for this policy change may arise from the recognition that the economic benefits of mangroves to local communities may be substantial, and could possibly even outweigh the returns to intensive shrimp farming that lead to mangrove conversion. To address this issue, Chapter 11 assesses the local economic benefits of mangroves and compares them to the net returns from converting the mangroves to shrimp farming, using the example of Tha Po Village, Kanjanadit District, Surat Thanni Province on the Gulf of Thailand. Part III provides the conclusion of this study on mangrove conversion and shrimp farming in Thailand. Chapter 12 summarizes the main findings of the study, and offers a number of policy recommendations for improving the institutional and incentives framework for managing this problem. We also examine the implications of our conclusions and policy recommendations for other countries promoting the rapid development of their shrimp aquaculture industry. Finally, the editors and chapters authors who participated in this study would like to express our appreciation to a number of institutions and individuals who assisted us in our work. As mentioned above, the study was made possible through funding by the Population, Consumption and Environment Initiative of the John D. and Catherine T. MacArthur Foundation (Grant #98- 55147-GSS). We would like to express our gratitude to the MacArthur Foundation and the PCE Initiative Director, Dr Anu Kumar, for their support. We would like to thank our research assistant, Sathit Chanyaswad, and the survey team from the Faculty of Economics, Kasetsart University and the College of Population Studies, Chulalongkorn University for their invaluable assistance during the course of this study. We also appreciate the support of Professor Charles Perrings of the Environment Department, University of York, who did everything possible to facilitate this study from its inception until its completion. Finally, we are grateful to Margie Reis, Senior Office Assistant, Department of Economics and Finance, University of Wyoming for assistance in preparing the initial study report and the book manuscript for publication.

EDWARD B. BARBIER SUTHAWAN SATHIRATHAI Phang-nga

Map of Thailand indicating Phang-nga and Nakhon Si Thammarat provinces

xii 1. Introduction: global mangrove loss and economic development Edward B. Barbier and Mark Cox

INTRODUCTION

Mangrove, or ‘mangal’, systems are the sub-tropical and tropical equivalents of the temperate coastal and estuarine salt marsh system. They are essentially forest-based systems that tolerate salt and occupy the intertidal zone between land and sea. Although mangroves are generally found within 25° North and South of the Equator, they can be found in some northern latitudes as high as 32° (Maltby 1986). Mangroves line one-quarter of the world’s tropical and sub-tropical coastlines, covering an area of between 190 000 and 240 000 square kilometers (km2) globally (Kelleher et al. 1995). Approximately 117 countries and terri- tories have mangrove resources within their borders (WCMC 1994). Indonesia has the largest area of mangrove forest estimated at 4.5 million hectares (ha). Nigeria, Australia, Mexico and Malaysia have the next largest areas of mangrove forest, estimated at around 1 to 2 million ha (WRI 1996). Mangroves are very important to many tropical and sub-tropical countries, as they serve to protect coastlines from tidal waves, sea erosion and hurricanes. Furthermore, they are highly productive natural ecosystems, and provide nutrients and shelter for many commercially important aquatic organisms (Deegan et al. 1988; Mitsch and Gosselink 1993; Mooney et al. 1995; WCMC 1994; WRI 1996). Today, mangroves are one of the world’s most threatened ecosystems, and are rapidly disappearing in many tropical countries where they were once abundant. For example, Malaysia may have lost 17 per cent of its mangrove area between 1965 and 1985, India as much as 50 per cent between 1963 and 1977, and the Philippines as much as 70 per cent between 1920 and 1990 (WRI 1996). Many of the other countries in Asia, Latin America and Africa have lost between 30 and 70 per cent of their mangrove area in the last 30 to 40 years (Spalding et al. 1997; WRI 1996). In some countries, such as Thailand, the rate of mangrove loss has been more recent yet extremely rapid. Over 1975–93 the area of mangroves in Thailand has virtually halved, from 312 700 ha to 168 ,683 ha (Sathirathai 1998).

1 2 Introduction

While there are many reasons for the destruction of mangrove forests, including increasing population pressure and coastal development, the demand for land by key primary sector economic development activities, such as mining, conversion to salt ponds, agricultural and aquacultural expansion, and over-harvesting of the forests, has been the largest factor in recent years. By far the most important of these activities has been the expansion of aquaculture ponds, especially for shrimp production, into mangrove forests (Aksornkoae et al. 1986; Spalding et al. 1997; WRI 1996). Shrimp aquaculture has been responsible for mangrove deforestation in many countries, but is especially evident in South East and South Asia (Kongkeo 1997).1 The problem of mangrove conversion has been exacerbated over the past two decades, given the growing importance of shrimp farming to the export earnings of tropical countries. For example, in Bangladesh shrimp farming contributes 8 per cent to total export earnings (Raha and Alam 1997). In Thailand, the total value of export earnings for shrimp in the late 1990s was around US$1–2 billion annually (Jitsanguan et al. 1999; Tokrisna 1998). This recent trend of converting mangroves for commercially profitable land uses and development has led to massive mangrove loss worldwide. The result has been severe disruption to the important ecological and economic functions normally performed by undisturbed mangrove systems. In many countries and regions, mangrove deforestation is contributing to fisheries decline, degradation of clean water supplies, salinization of coastal soils, erosion and land subsidence, as well as release of carbon dioxide into the atmosphere (Barbier and Strand 1998; Ruitenbeek 1994; Sathirathai 1998; Spalding et al. 1997; WRI 1996). In Thailand, the welfare losses associated with the impacts of mangrove deforestation on coastal fisheries in Surat Thani Province were estimated to be around US$21 to 52 per ha (Sathirathai and Barbier 2001). Although the loss of mangroves and the resulting environmental effects are well publicized, there have been few studies of the economic causes of mangrove deforestation. In the following section, we develop a basic model of economic activity and mangrove conversion, in which the demand for land by converting activities leads to mangrove loss. From this model, a relationship is established between remaining mangrove area, the level of economic activity and other important causative factors. Mangrove area is expected to be a decreasing function of aggregate economic activities, such as aquaculture and agricultural expansion, that depend on the conversion or depletion of mangroves, and to be increasing with the amount of environmental protection. Ecological and coastal conditions, the accessibility of mangrove areas and institutional factors such as political stability should also have an influence. Although we would ideally like to conduct a pooled cross-sectional and time series analysis of mangrove deforestation across all countries, to date the best available data source on mangrove areas worldwide contains only a single-year Introduction 3 estimate of mangrove area by country (Spalding et al. 1997). We therefore estimate our mangrove area relationship empirically through a cross-sectional analysis of 89 countries. We also analyze two important sub-samples, middle and low-income economies and countries with mangrove areas greater than 25 km2.

A MODEL OF ECONOMIC ACTIVITY AND MANGROVE CONVERSION

Suppose that there are J different sectors, or activities, in the coastal area of an economy that depend in some way on the conversion or depletion of mangroves. For example, agriculture, aquaculture, salt production and residential or industrial construction would involve conversion of mangrove lands. Logging, charcoal making, tannin production and other activities that depend on depleting mangrove forest resources could also lead to a loss of mangrove areas. Although these activities may be highly diverse, their production relationships could be represented in a similar way, namely as a function of converted mangrove area and other inputs. Thus assume that the aggregate production of all J economic sectors that lead to mangrove loss can be represented by a single production relationship and total output, y. At any time t, the total stock of 1, . . . , K inputs (for example, labor and capital) available for producing this output can be represented by the vector, x. However, only x1 of these inputs are used directly in the production of y. The remaining x2 units are used to convert mangrove area, A, which of course are also an input for producing y. Thus the basic cost-minimizing level of production for y can be defined as:

C(w, y) = minx wx (1.1)

Subject to:

y = F(x1, A) (1.2)

A = A(x2, a) (1.3)

x = x1 + x2 (1.4)

Equation (1.2) is the aggregate production function for y, which is assumed to exhibit the standard properties with respect to its arguments, x1 and A. Equation (1.3) is the relationship for the level of mangrove conversion, A, which is an increasing function of the amount of inputs allocated to conversion, x2, 4 Introduction and a range of exogenous factors, a, that may influence the ‘accessibility’ of mangrove areas available for conversion, including roads, coastal infrastructure and concentration of populations in coastal areas. Equation (1.4) indicates that all inputs, x, can be used either directly in production of y or for mangrove conversion, with w being the corresponding vector of input prices. It follows from the above relationships that the conditional factor demand for any input, xik, can be defined as: ∂ ∂ ∂ xik xik xik x = x (w, y, a), –– < 0, –– > 0, –– > 0, i = 1,2 k = 1, ..., Kk ≠ 1. ik ik ∂ ∂ ∂ wik w1 y (1.5)

th That is, each k input used either directly for production, x1k or for mangrove conversion x2k, is decreasing in its own price, wk, but increasing with respect to other input prices, wl and output, y. The corresponding cost-minimizing vector of inputs that is used for mangrove conversion is defined as x2 = x2(w, y, a), and thus (1.3) can be rewritten as:

∂A ∂A A = A (w, y, a), –– > 0, –– > 0. (1.6) ∂y ∂a

Let the total amount of mangrove area that is remaining in any time period, t, be defined as M. Thus the total stock of mangrove area at time t available in a country, either for conversion or for preservation, can be denoted as N > A, or N = A + M. As this is a static model (for cross-sectional analysis) we will assume that N is a given stock, and will be affected by prevailing ecological and coastal conditions, b, of the country, such as length of coastline, rainfall, tidal conditions, temperature, water quality, and so forth. In addition, the remaining area of mangrove, M, may be influenced by the degree of conservation and protection effort, g, allocated to their preservation. It follows that

∂M A(w, y, a) + M(g) = N(b), –– > 0. (1.7) ∂g

Rearranging (1.7) yields

∂M ∂M ∂M M = M(w, y, a, b, g), –– < 0, –– < 0, –– > 0. (1.8) ∂y ∂a ∂g

Equation (1.8) indicates that the remaining mangrove area in a country should decrease with the aggregate output, y, of economic activities that depend on Introduction 5 mangrove conversion, as well as with factors that increase the accessibility of mangrove areas, a, but increase with the amount of environmental protection, g. Ecological and coastal conditions, b, and input prices, w, should also affect the extent of mangrove areas remaining in a country. Finally, in recent years, a variety of empirical analyses at both the country and cross-country level have explored the impact on deforestation of institutional factors, such as land use conflict, security of ownership or property rights, political stability and the ‘rule of law’ (for example, Alston et al. 1999, 2000; Deacon 1994, 1999; Godoy et al. 1998). The main hypothesis tested is that such institutional factors may have important independent influences on deforestation, separate from the effects of other explanatory economic variables. It seems reasonable that the same hypothesis may hold for our analysis, namely that prevailing institutional conditions may be an additional and independent influence on the amount of mangrove area remaining in a country. Denoting z as a vector of institutional indices, such as measures of political stability, ownership security, land use conflict and the ‘rule of law’, a modified version of (1.8) is

∂M ∂M ∂M M = M (w, y, a, b, g; z), –– < 0, –– < 0, –– > 0. (1.9) ∂y ∂a ∂g

Equation (1.9) is therefore the mangrove area relationship to be estimated through the following cross-country analysis.

DATA AND ESTIMATION APPROACH

To date, the most reliable source of international mangrove data is the World Mangrove Atlas (Spalding et al. 1997). This database contains estimates of mangrove area for 89 countries, based on various satellite imagery and map sources.2 However, the Atlas reports only a single-year estimate of mangrove area for each country. In addition, because different sources are used to provide this estimate, the year in which mangrove area is estimated varies greatly from country to country. Finally, the countries included in the database vary considerably in terms of the size of their mangrove area and their stage of economic development. For example, 22 countries in the sample contain mangrove forests of 2000 ha or less, whereas 28 countries have mangrove areas of 1.5 million ha or more. Although the vast majority of the countries are low and middle-income economies, 14 have GDP per capita ranging from US$7000 to around US$23 400. Table 1.1 lists the 89 countries from World Mangrove Atlas that were used in the following cross-country estimation of equation (1.9). The year of estimation 6 Introduction

Table 1.1 Countries from World Mangrove Atlas sample

Low income (< US$7000 per capita per year) Low mangrove (< 25 sq km)

Aruba (80) Grenada (80) Micronesia (69) St Vincent (80) Benin (89) Guam (76) Samoa (95) Tonga (72) Djibouti (85) Mauritania (95) St Kitts (80) Vanuatu (72) Dominica (80) Mayotte (85) St Lucia (84) High Mangrove (> 25 sq km) Angola (92) Ecuador (91) Indonesia (89) Senegal (85) Antigua (91) Egypt (92) Iran (70) Seychelles (78) Bangladesh (77) El Salvador (81) Kenya (95) Solomon Is. (95) Belize (92) Eq. Guinea (60) Madagascar (79) Somalia (92) Brazil (91) Fiji (85) Malaysia (86) South Africa (92) Brunei Dar (92) French Guiana (79) Mexico (92) Sri Lanka (92) Cambodia (88) Gabon (94) Mozambique (80) Sudan (92) Cameroon (85) Gambia (85) Myanmar (95) Surinam (78) Colombia (85) Guadeloupe (80) Nicaragua (91) Tanzania (89) Comoros (78) Guatemala (92) Pakistan (93) Thailand (87) Congo (92) Guinea (80) Panama (88) Togo (95) Costa Rica (88) Guinea-Bissau (90) Papua NG (70) Trinidad Tob. (80) Côte d’Ivoire (85) Guyana (96) Peru (91) Venezuela (82) Cuba (89) Haiti (82) Philippines (87) Vietnam (87) Dom. Rep. (84) India (86) Puerto Rico (78) Yemen (87) High income (>US$7000 per capita per year) Low mangrove (< 25 sq km) Bahrain (95) Bermuda (75) Qatar (92) Singapore (90) Barbados (75) Hong Kong (89) High mangrove (> 25 sq km) Australia (95) Cayman Is. (78) New Zealand (82) Saudi Arabia (85) Bahamas (92) Japan (86) Oman (88) UAE (82)

Note: For each country, the year in which mangrove area is estimated is indicated in parentheses.

Source: Spalding et al. (1997). of mangrove area for each country is indicated in parentheses. In addition, the table distinguishes between countries with large (> 25 km2) as opposed to small (< 25 km2) mangrove areas, and those with high (> US$7000) per capita income as opposed to middle or low income (< US$7000). To estimate equation (1.9), we required cross-country data for the key Introduction 7 variables in the regression that also matched as closely as possible the year of estimation of mangrove area for each country, as reported in Table 1.1. We were able to find data, or close proxies, for output of mangrove-dependent economic activity (y), accessibility of mangrove areas (a), ecological and coastal conditions (b), environmental protection (g) and institutional factors (z). Unfortunately, we were unable to obtain suitable data to represent our input price variable, w.3 For the remaining variables in (1.9) we used the following data sources. (Unless indicated otherwise, the data are for the same year of estimated mangrove area for each country reported in Table 1.1.)

Mangrove-dependent economic activity, y

As noted in the introduction, for most countries, mangrove loss is associated with key primary sector economic development activities, such as shrimp aquaculture, over-harvesting of forests, mining, salt production and agricultural expansion in coastal areas. From FAO (2000) we were able to obtain an estimate of total aquaculture production in metric tons of all shrimp and prawn species for the same year of estimated mangrove area for each country reported in Table 1.1. We average total shrimp aquaculture production over the total coastline length of a country.4 To represent production, or development, of other key primary economic activities that might cause mangrove loss we employed data on agricultural gross domestic product (GDP) per head of population engaged in agriculture, from World Bank (1998) and FAO (1997). However, mangrove deforestation may not just be related to certain primary sector economic activities but also be affected by the general level of economic development as well as the pace of economic growth in a country. To examine this hypothesis, we also included GDP per capita and GDP annual growth (from World Bank, 1998) in our analysis.

Accessibility of mangrove areas, a

The ‘accessibility’ of mangrove areas available for conversion may be affected by such factors as roads, coastal infrastructure and the concentration of populations in coastal areas. As an indicator of the state of development of a country’s road network, we employed data on the percentage of paved roads (World Bank 1998). For some countries, we were also able to obtain data on the population in coastal urban agglomerations, for 1980, and projections for the year 2000 (WRI 1994).

Ecological and coastal conditions, b

The abundance of mangroves found in any country will depend on a number of ecological and coastal conditions, including length of coastline, rainfall, 8 Introduction tidal conditions, temperature, water quality and so forth. Estimates of the total length of coastline (in kilometers) for 88 of the countries listed in Table 1.1 were obtained from WRI (1994) and National Geographic Society (1981).5 Data for only a limited number of countries on average annual rainfall, temperature and tidal range are available from Spalding et al. (1997).

Environmental protection, g

Our theoretical model suggests that the remaining mangrove area found in a country is likely to increase with the amount of environmental protection. Spalding et al. (1997) also provide an estimate of the total number of protected areas for each of the countries listed in Table 1.1. We employed this variable as our indicator of the degree of environmental protection in each country.

Institutional factors, z

As noted above, recent analyses have focused on the way a variety of institutional factors, such as land use conflict, security of ownership or property rights, political stability and the ‘rule of law’, may affect deforestation. The cross-country database on institutional factors that most closely matches the range of countries and the corresponding years for mangrove area estimates indicated in Table 1.1 is from Banks (1990). For selected countries in Table 1.1, the Banks data set contains data on the number of major cabinet changes (1985 only), constitutional changes (1985 only), government coups (1985 only), political purges (1985 and 1990), government crises (1985 and 1990), guerrilla warfare incidents (1985 and 1990), industrial strikes (1985 and 1990), political assassinations (1985 and 1990) and political revolts (1985 and 1990). The Banks data also include an index of party fractionalization (1985 only). All these institutional variables essentially reflect the degree of political stability in a country. Rather than include each variable separately, we combined them into three different single indicators of overall political stability for each country:

•apolitical stability index (PSI85) based on the variables for 1985 only (cabinet changes, constitutional changes and government coups plus the party fractionalization index);6 •apolitical stability index (PSI8590) based on a composite of the 1985 and 1990 observations for the relevant variables (purges, crises, guerrilla warfare, strikes, assassinations revolts and riots);7 •apolitical stability index (PSI) based on the average of the above two indices. Introduction 9

All three indices range from 0 (highest political stability) to 1 (lowest political stability).

Other economic and demographic variables

In addition to the various economic, ecological and economic factors identified in our model in the previous section that may determine the size of mangrove area found in a country, other demographic and economic influences may also affect mangrove conversion across countries. To represent these possible exogenous influences, we extended our data set for estimating (1.9) to include several additional variables. These were population density, rural population density, the percentage of the total labor force in agriculture, agricultural raw material exports as a percentage of total merchandise exports, total debt service (as a percentage of exports) and the real rate of interest. The source of all these variables was World Bank (1998).

Estimation approach

Given that our complete cross-country data set comprises observations for a single year only, estimation of the empirical relationship (1.9) across countries was conducted using ordinary least squares. The estimations were performed on the entire sample of all countries in Table 1.1, a sub-sample of countries with per capita income less than $7000 per person, and a sub-sample of countries with mangrove area greater than 25 km2. In all regressions, the Breusch–Pagan chi-squared test indicated the presence of heteroskedasticity, which was adjusted through using White’s robust correction of the covariance matrix. All regressions were also tested for the appropriate functional form: linear, semi-log and logarithmic. In every case the linear functional form was preferred. Finally, the independent variables were also examined for multi- collinearity, which was rejected in all cases. This was particularly important in ensuring that total shrimp aquaculture production per length of coastline, agricultural GDP per head of population engaged in agriculture, GDP per capita, GDP growth and total coastline length could be included together as independent variables in the estimation of equation (1.9). Table 1.2 lists the sub-set of variables from our full data set that were employed in the final cross-country regressions of the factors determining the remaining mangrove area of a country. Some of the variables in our complete data set, such as population in coastal urban agglomerations projected for 2000, tidal range, total debt service and the real rate of interest, proved to have too few observations across countries, and thus their inclusion reduced the sample sizes of the regressions significantly. In addition, none of these variables was found to be significant in the latter regressions, and the overall 10 Introduction explanatory power of these estimations was poor. Two other ecological variables, average annual rainfall and temperature, plus the remaining exogenous demographic and economic variables (that is, population density, rural population density, the percentage of the total labor force in agriculture and agricultural raw material exports as a percentage of total merchandise exports), were not significant in any regressions. In most cases the inclusion of one or more of these variables distorted the estimation results considerably, as well as reducing the overall explanatory power of the regressions. With the exception of average annual rainfall, none of the above variables was included in the final estimations of equation (1.9), and thus they are not listed in Table 1.2. Finally, of the three indices of political stability, PSI8590 performed consistently better in most regressions. This variable was therefore our preferred indicator of political stability. The 89 countries in Table 1.1 are drawn from five distinct global geographical zones (Spalding et al. 1997). These are East Asia, South East Asia and South Asia (zone 1); Oceania (zone 2); Latin America and the Caribbean (zone 3); Western (that is, Atlantic Coast) Africa (zone 4); and Eastern (that is, Indian Ocean and Red Sea Coasts) Africa and the Persian Gulf (zone 5). Countries located in zone 1 account for approximately 43 per cent of the total mangrove area of all countries listed in Table 1.1, and countries from zone 3 represent over 31 per cent of total mangrove area. Given that most of the world’s remaining mangrove areas are largely found in these two zones, we included dummy variables for countries from zone 1 and zone 3, respectively, in our cross-country regressions (see Table 1.2). The presence of dummy variables for these zones allows us to test the hypothesis that the mean (expected) values of remaining mangrove area in zones 1 and 3 are greater than in other geographical regions (that is, zones 2, 4 and 5). Finally, given that the data range for mangrove area estimates by country is from 1960 to 1996, alternative dummy variables for country observations from the earlier years of the sample were also employed. These included dummies for observations for years before 1975, 1981 and 1985. In addition, a year indicator variable was also included in alternative versions of the regressions. However, none of the dummy variables or the year indicator variable proved significant, nor did they improve the explanatory power of the regressions. These variables were therefore dropped from the estimations.

ESTIMATION RESULTS

The cross-country regressions of equation (1.9) for the sample of all countries are reported in Table 1.3, along with the relevant test statistics. Four different versions of the regression are indicated. Model 1 excludes both the GDP per Introduction 11

Table 1.2 Definitions of variables used in cross-country regressions

Variable Definition

MANGROVE Mangrove area (km2), year varies (Spalding et al. 1997). AREAS Number of protected areas, same year as MANGROVE (Spalding et al. 1997) AQUAS Total shrimp and prawn aquaculture production (metric tons), same year as MANGROVE, per length of coastline (km) (FAO 2000; WRI 1994) AGDPAP Agriculture value added divided by population engaged in agriculture (constant 1987 US$/person), same year as MANGROVE (FAO 1997; World Bank 1998) GDPG GDP growth (annual %), same year as MANGROVE (World Bank 1998) GDPPC GDP per capita (constant 1987 US$/person), same year as MANGROVE (World Bank 1998) ROADS Percentage of paved roads, same year as MANGROVE (World Bank 1998) COAST Length of coastline (km) (WRI 1994) CUP1980 Population in coastal urban agglomerations (’000s) (WRI 1994) PSI8590 Political stability indexa RAIN Mean monthly annual rainfall (mm) (Spalding et al. 1987) DUM1 Dummy for countries from zone 1 (Asia)b DUM3 Dummy for countries from zone 3 (Latin America and Caribbean)

Notes: a Based on Banks (1990); see text for explanation. b Includes countries from East Asia, Southeast Asia and South Asia. capita and growth variables. Model 2 includes GDP growth only, and Model 3 includes GDP per capita only. The fourth model displayed in Table 1.3 includes an additional ecological variable (RAIN) to Model 3.8 Model 4 is the preferred regression. The parameter estimate for GDP per capita (GDPPC) in the latter regression is significant and positive. Although average annual rainfall is significant only at the 10 per cent level, it is positively correlated with mangrove area across countries. In addition the explanatory power of Model 4, as measured by the adjusted R2, is the highest for all four regressions. In all four models the estimated coefficients for agricultural GDP per person employed in agriculture (AGDPAP) are highly significant and negative. In the Table 1.3 Cross-country regression of mangrove area, all countries (dependent variable: MANGROVE, mangrove area, km2)

Variables Model 1 Model 2 Model 3 Model 4

AREAS 4.233 × 101 4.210 × 101 4.956 × 101 5.371 × 101 (1.292) (1.282) (1.511) (1.712)† AQUAS –2.611 × 101 –2.531 × 101 –3.163 × 101 –3.577 × 101 (–1.595) (–1.534) (–1.996)* (–2.066)* AGDPAP –1.186 × 10–3 –1.184 × 10–3 –1.511 × 10–3 –1.651 × 10–3 (–3.261)** (–3.246)** (–3.255)** (–3.509)** 1 12 GDPG –1.729 × 10 (–0.420) GDPPC 2.209 × 10–1 2.962 × 10–1 (1.940)† (2.602)** ROADS 1.031 × 101 9.659 –1.494 –1.881 (0.682) (0.640) (–0.103) (–0.126) COAST 7.170 × 10–1 7.188 × 10–1 7.097 × 10–1 7.104 × 10–1 (8.242)** (8.215)** (8.378)** (9.013)** RAIN 4.049 × 10–1 (1.918)† CUP1980 –5.199 × 10–2 –5.276 × 10–2 –5.735 × 10–2 –5.769 × 10–2 (–1.291) (–1.307) (–1.501) (–1.576) , i F [ ** ** 3 2 3 3 10 10 * 10 10 = 14.63 × × = 0.886 ** × × 2 2 χ R (1.798)† 1.665 (–0.373) B–P –5.830 (–2.001) 2.218 (2.682) –2.878 = 45.85 F[11,37] adj. N = 49 ** ** 3 3 3 2 10 ** 10 10 10 = 13.63 × = 0.882 ** × × × 2 2 χ R -ratios are indicated in parentheses; N = number of observations. t –7.059 (–2.809) 2.491 (1.929)† 2.032 (3.365) 5.107 (0.927) F[10,40] = 38.38 adj. B–P N = 51 = Breusch–Pagan chi-squared test for heteroskedasticity. = Breusch–Pagan chi-squared test for heteroskedasticity. 2 χ ** ** 3 3 3 2 10 ** 10 10 10 = 15.87 × = 0.877 ** × × × 2 2 χ R –8.022 (–3.214) 2.094 (3.465) 8.044 F[10,43] = 38.89 B–P (1.834)† 2.061 (1.397) adj. N = 54 ** ** R -squared goodness of fit measure; B–P 3 3 3 2 10 ** 10 10 10 = 15.17 × = 0.880 ** = adjusted × × × 2 2 2 χ R 7.392 (–3.196) (1.773)† (3.495) (1.402) N = 54 F[9,44] = 44.12 adj. B–P 2.021 2.077 –7.851 †Significant at 10% level; *significant 5% **significant 1% : ] = F -test of model; adj. R j PSI8590 DUM1 Constant Notes DUM3

13 14 Introduction preferred regression (Model 4), as well as in Model 3, the parameter estimate for shrimp aquaculture production (AQUAS) is also significant and negative. Thus the hypothesis that an increase in primary sector activities reduces the remaining mangrove area of a country cannot be rejected. Model 2 indicates that GDP growth (GDPG) is not a significant variable in the regressions. Thus mangrove deforestation does not appear to be affected by a country’s rate of economic growth. In contrast, in the preferred regression of Model 4 GDPPC is significant and positive. This implies that the hypothesis that the general level of economic development (that is, GDP per capita) in a country influences mangrove deforestation cannot be rejected. Across the sample of all countries, an increase in GDP per capita tends to be associated with more remaining mangrove areas in a country. The most reasonable explanation is that, as an economy develops, manufacturing and tertiary economic activities are more prevalent, and these sectors are less likely to be responsible for widespread mangrove deforestation.9 Finally, the dummy variable for zone 3 was significant and positive in all four regressions of Table 1.3, and the dummy variable for zone 1 was positive and significant at the 10 per cent level. Thus we cannot reject the hypothesis that the mean values of remaining mangrove areas in zone 1 (East Asia, South East Asia and South Asia) and zone 3 (Latin America and the Caribbean) are greater than in other geographical regions. Of the remaining variables, the length of coastline and the political stability index were highly significant and positive across all four estimations, whereas the percentage of paved roads, the number of protected areas and coastal urban population in 1980 were not significant. Table 1.4 reports the two best regressions of equation (1.9) with respect to each of the two sub-samples of countries, those with per capita income less than $7000 per person and countries with mangrove area greater than 25 km2. Models 1 and 2 in Table 1.4 are for low and middle-income countries (that is, with GDP per capita less than $7000 per person). Models 3 and 4 in Table 1.4 are for countries with relatively large remaining mangrove areas (that is, with mangrove areas greater than 25 km2). Neither GDP per capita nor GDP growth proved significant in any of the regressions for low and middle-income countries, and the overall explanatory power of these estimations was poor. Thus these variables are excluded in the regressions reported in Table 1.4. The difference between the two reported regressions is that Model 2 includes RAIN, whereas Model 1 does not. However, RAIN appears not to be significant in Model 2, and so Model 1 is the preferred regression. In both Model 1 and Model 2 the estimated coefficient for shrimp aquaculture production (AQUAS) and the coefficient for agricultural GDP per person employed in agriculture (AGDPAP) are negative, but not significant. Thus for Table 1.4 Cross-country regression of mangrove area, all countries (dependent variable: MANGROVE, mangrove area, km2)

Countries with per capital income Countries with mangrove area less than $7000 per person greater than 25 km2 Variables Model 1 Model 2 Model 3 Model 4 AREAS 1.503 × 102 1.515 × 102 7.996 × 101 8.067 × 101 (5.763)** (5.808)** (5.598)** (5.891)** AQUAS –1.430 × 101 –1.806 × 101 –2.934 × 101 –3.386 × 101 (–1.085) (–1.276) (–2.405)* (–2.463)*

15 AGDPAP –8.622 × 10–4 –1.030 × 10–3 –2.228 × 10–3 –2.259 × 10–3 (–1.319) (–1.604) (–7.490)** (–8.087)** GDPPC 3.517 × 10–1 3.692 × 10–1 (2.139)* (2.410)* ROADS –2.683 × 101 –2.256 × 101 –2.589 × 101 –1.940 × 101 (–2.447)* (–1.995)* (–1.822)† (–1.288) COAST 6.994 × 10–1 7.012 × 10–1 7.035 × 10–1 7.059 × 10–1 (32.76)** (33.19)** (19.54)** (20.29)** RAIN 1.631 × 10–1 3.066 × 10–1 (0.827) (1.426) CUP1980 –1.099 × 10–1 –1.168 × 10–1 –1.016 × 10–2 –1.304 × 10–2 (–2.370)* (–2.332)* (–0.477) (–0.616) Table 1.4 (continued)

Countries with per capital income Countries with mangrove area less than $7000 per person greater than 25 km2 Variables Model 1 Model 2 Model 3 Model 4 PSI8590 –7.851 × 103 –4.908 × 103 –7.741 × 103 –7.067 × 103 (–2.322)* (–1.936)* (–3.019)** (–2.361)* DUM1 1.066 × 103 9.368 × 102 1.496 × 103 1.269 × 103 (1.198) (1.069) (1.352) (1.169) 16 DUM3 8.223 × 102 9.044 × 102 1.501 × 103 1.450 × 103 (1.304) (1.377) (2.691)** (2.528)* Constant 1.505 × 103 6.369 × 102 1.190 × 103 4.295 × 102 (2.850)** (1.819)† (2.021)* (0.504) N = 45 N = 44 N = 46 N = 45 F[9,35] = 99.38** F[10,33] = 85.62** F[10,35] = 59.72** F[11,33] = 53.26** adj. R2 = 0.953 adj. R2 = 0.952 adj. R2 = 0.929 adj. R2 = 0.929 B–P χ2 = 15.23** B–P χ2 = 15.21** B–P χ2 = 18.82** B–P χ2 = 16.50**

Notes: †Significant at 10% level; *significant at 5% level; **significant at 1% level; t-ratios are indicated in parentheses; N = number of observations; F[i, j] = F-test of model; adj R2 = adjusted R-squared goodness of fit measure; B–P χ2 = Breusch–Pagan chi-squared test for heteroskedasticity. Introduction 17 low and middle-income countries the hypothesis that an increase in primary sector activities reduces the remaining mangrove area of a country can be rejected. In sum, Models 1 and 2 suggest that neither primary production nor overall economic development and growth appear to be significant in influencing the remaining mangrove areas across all low and middle-income countries. In contrast, the key variables affecting mangrove areas for this group of countries appear to be the length of coastline, the number of protected areas, coastal urban population, political stability and the percentage of paved roads. The coefficients of these variables all have the same signs as predicted by our theoretical model. Coastline length is once again positively associated with remaining mangrove area. Mangrove areas increase with environmental protection, but decline as these forests become more accessible owing to an improved road network, as coastal urban populations rise or as political instability increases in low and middle-income economies. Finally, the zonal dummy variables were not significant in either Models 1 or 2 of Table 1.4, indicating that for low and middle-income countries there is no geographical difference across the five zones with respect to the regressions of remaining mangrove area. As noted above, Models 3 and 4 in Table 1.4 are the best regressions for countries with relatively large remaining mangrove areas (that is, with mangrove areas greater than 25 km2). In both regressions, GDP per capita is significant and is included.10 The main difference between the two reported regressions is that Model 4 includes RAIN, whereas Model 3 excludes this ecological variable. However, RAIN is not significant in Model 4, and so Model 3 is the preferred regression. In both models the estimated coefficients for both shrimp aquaculture production per length of coastline (AQUAS) and agricultural GDP per person employed in agriculture (AGDPAP) are significant and negative. Thus, for economies with mangrove areas greater than 25 km2, the hypothesis that an increase in primary sector activities reduces the remaining mangrove area of a country cannot be rejected. The parameter estimate for GDP per capita (GDPPC) in Models 3 and 4 is also significant and positive. For countries with large mangrove areas, one cannot reject the hypothesis that the general level of economic development (that is, GDP per capita) affects mangrove deforestation. Moreover, an increase in GDP per capita tends to be associated with more remaining mangrove areas in a country, suggesting that, as a country with large mangrove areas develops economically, less deforestation occurs. The dummy variable for zone 3 was significant and positive for both regressions for countries with large mangrove areas. Thus, for these countries, the hypothesis that the mean values of remaining mangrove areas in Latin America and the Caribbean (zone 3) are greater than in other geographical 18 Introduction regions cannot be rejected. Of the remaining variables, the number of protected areas, the length of coastline and the political stability index are significant in both Models 3 and 4, and the percentage of paved roads is significant at the 10 per cent level in our preferred Model 3. The signs are once again as predicted by our theoretical model. For countries with large mangrove areas, these areas are greater for countries with longer coastlines and more environmental protection, but decline for countries with increased political instability and easier forest access due to an improved road network. Table 1.5 indicates the elasticity estimates for the explanatory variables in the preferred regressions of mangrove area for all three samples of countries: (a) the sample of all countries (Table 1.3, Model 4); (b) the sub-sample of countries with per capita income less than $7000 per person (Table 1.4, Model 1); and (c) the sub-sample of countries with mangrove area greater than 25 km2 (Table 1.4, Model 3). The elasticity estimates facilitate comparisons across these three regressions. Across the entire sample of countries, and for countries with large mangrove areas, the estimated elasticities for both aquaculture production (AQUAS) and agricultural GDP per person employed in agriculture (AGDPAP) are highly significant and negative. Increases in overall agricultural GDP per person employed in agriculture have the larger impact on

Table 1.5 Estimated elasticities of the cross-country regressions of mangrove area

Variables All countries Countries with per Countries with (N = 89) capita income mangrove area less than $7000 greater than per person 25 km2 (N = 76) (N = 67)

AREAS 0.181† 0.347** 0.251** AQUAS –0.018* –0.007 –0.014* AGDPAP –1.089** –0.292 –1.046** GDPPC 0.647** — 0.486* ROADS –0.032 –0.349* –0.307† COAST 1.104** 0.889** 1.011** RAIN 0.351† — — CUP1980 –0.131 –0.200* –0.019 PSI8590 –0.165* –0.165* –0.195**

Notes: †Significant at 10% level; *significant at 5% level; **significant at 1% level; N = number of observations in full sample. Elasticities calculated using all the non-missing observations of the full sample for each variable. Introduction 19 mangrove loss. A 10 per cent rise in AGDPAP leads to around a 10.9 per cent fall in mangrove area for all countries, and a 10.5 per cent decline for countries with more than 25 km2 of mangroves. In comparison, a 10 per cent increase in shrimp aquaculture production is associated with 0.18 per cent and 0.14 per cent declines in the respective sub-samples. For all countries and for countries with large mangrove areas, the level of economic development, as represented by the GDP per capita of a country, is positively associated with greater mangrove area. A 10 per cent increase in GDP per capita will lead to a 6.5 per cent rise in mangrove area across all countries and a 4.9 per cent increase for countries with large mangrove areas. Several explanatory variables also have impacts on remaining mangrove areas, although, with the exception of length of coastline and political instability, most variables were not significant across the three regressions. However, in all cases the effects of the explanatory variables were the same as predicted by our theoretical model. The number of protected areas, coastline length and rainfall had positive effects on mangrove area, whereas the percentage of paved roads, coastal urban population and political instability had negative impacts. A country with a 10 per cent greater coastline length will have 11 per cent more mangrove area across all countries, 8.9 per cent more in low and middle- income economies and 10.1 per cent more in countries with large mangrove areas. A 10 per cent increase in political instability is associated with a 1.7 per cent decline in mangrove area across all countries and in low and middle- income countries, and a 2 per cent decline in countries with mangrove areas greater than 25 km2. A 10 per cent increase in environmental protection is associated with a 3.5 per cent increase in mangrove area in low and middle- income economies and a 2.5 per cent increase in countries with large mangrove areas. A 10 per cent rise in the percentage of paved roads and coastal urban populations lead respectively to 3.5 per cent and 2 per cent falls in mangrove area in low and middle-income economies. Finally, although the variable is significant only at the 10 per cent level, a country with 10 per cent more rainfall is likely to have 3.5 per cent more mangroves across all countries.

CONCLUSION

This chapter has sought to analyze the role of economic development, and in particular primary sector activities dependent on mangrove conversion, in causing the rapid decline in coastal mangrove areas across many countries of the world. From a theoretical model of economic activity and mangrove conversion, in which the demand for land by converting activities leads to 20 Introduction mangrove loss, we established a relationship between remaining mangrove area, the level of economic activity and other important causative factors. Mangrove area is expected to be a decreasing function of aggregate economic activities, such as shrimp aquaculture and agricultural expansion, that may involve the conversion or depletion of mangroves, and to be increasing with the amount of environmental protection. Ecological and coastal conditions, the accessibility of mangrove areas and institutional factors such as political stability should also have an influence. The mangrove area relationship emerging from our theoretical model was then estimated empirically through a cross-sectional analysis of 89 countries, as well as for sub-samples of middle and low-income economies and countries with mangrove areas greater than 25 km2. The main purpose of the empirical analysis was to examine the hypotheses that mangrove deforestation may be (a) due to certain mangrove-dependent primary sector economic activities (that is, aquaculture production and agricultural GDP per person employed in agriculture) and (b) affected by the general level of economic development and/or current rate of growth in a country (represented by GDP per capita and GDP annual growth, respectively). With regard to the first hypothesis, the regressions across all samples of countries and for countries with mangroves larger than 25 km2 provide some evidence that mangrove loss is associated with expansion of shrimp aquaculture production along coastlines and primary sector (that is, agricultural) activities generally. Of these two factors associated with mangrove deforestation, increases in overall agricultural GDP per person employed in agriculture have the larger impact on mangrove loss. With regard to the second hypothesis, there is some evidence that the level of economic development of a country affects the amount of its remaining mangroves. However, the relationship between mangrove area and the general economic performance of a country varies considerably depending on the sample of countries. For all countries and for countries with large mangrove areas, the level of economic development appears to be positively associated with greater mangrove area. GDP per capita may be associated with expanding manufacturing and tertiary economic activities, and these economic sectors are less likely to be responsible for widespread mangrove deforestation. However, GDP per capita is not significantly associated with mangrove loss in the sample of low and middle-income countries, and economic growth does not appear to influence mangrove area at all. The only ecological variable to have a consistent effect across regressions was length of coastline. As expected, a country with a greater coastline length will have more mangrove area. There was some evidence that a country with greater rainfall will also have more mangrove area, but this variable was significant only at the 10 per cent level and only for the regression sample for Introduction 21 all countries (Model 4 in Table 1.3). One interesting finding of the analysis was that political instability appears to be strongly associated with mangrove deforestation in all regressions. Other explanatory factors also influenced the mangrove area of a country, although not necessarily for all versions and samples of the regressions used to estimate equation (1.9). However, in all cases, the effects of these variables were the same as predicted by our theoretical model. For low and middle- income economies and for countries with large mangrove areas, an increase in environmental protection is associated with an increase in mangrove area, whereas a rise in the percentage of paved roads is linked to a decline in mangroves (see Table 1.5). For low and middle-income countries an increase in coastal population is also associated with mangrove loss. Overall, our analysis has been able to identify some economic conditions that are most likely to be associated with greater mangrove loss. We find some evidence that mangrove loss is associated with expansion of shrimp aquaculture production along coastlines and primary sector (that is, agricultural) activities generally, but not necessarily in all low and middle-income countries. Instead, it appears that countries with large mangrove areas are particularly susceptible to mangrove conversion from primary sector activities. Much of the current literature on global mangrove deforestation has focused on the influence of shrimp aquaculture expansion. Interestingly, however, our cross- country analysis suggests that increases in overall agricultural GDP per person employed in agriculture have the larger impact on mangrove loss. Nevertheless, from a policy perspective, there seems to be considerable scope for countries to reduce mangrove deforestation through mitigating the impacts of all primary sector activities in coastal areas, including shrimp aquaculture, on remaining mangrove areas. We also find some evidence that an increase in the level of overall economic development of a country, as reflected in its GDP per capita, may actually be associated with reduced mangrove loss. As a country develops economically, it will become more dependent on expanding manufacturing and tertiary economic activities, and these economic sectors are less likely to be responsible for widespread mangrove deforestation. Again, it appears that countries with large mangrove areas are particularly susceptible to this mitigating effect of overall economic development on mangrove loss. Our analysis suggests that some forms of economic development in some countries are likely to be associated with widespread mangrove loss. For example, a country endowed with large mangrove areas that is expanding its shrimp aquaculture production in coastal areas and is highly dependent economically on primary sector (that is, agricultural) activities generally is likely to experience greater mangrove deforestation. As that country develops economically, however, it may become less dependent on the latter activities 22 Introduction and thus reduce its mangrove loss. On the other hand, if the country is politi- cally unstable but has accessible mangrove areas, as the result of improved road networks, these factors will also contribute to increased mangrove loss. However, increased investment in environmental protection will counteract this loss to some extent. Perhaps this is one encouraging policy option emerging from our analysis. If the international community can provide low and middle-income economies with technical and financial assistance to increase their protection and conservation efforts, particularly of vulnerable coastal mangrove systems, this may be one way of slowing down rates of mangrove loss globally. Finally, there are a number of important caveats to this analysis, given the limited data set. It would have been preferable to have mangrove data for more than one year across countries, but unfortunately such time series observations are not available for many countries. The absence of such time series data limited our ability to employ more sophisticated panel analyses of changes in mangrove area over time. A second problem with the data set is that some key ecological variables, such as temperature and tidal levels, were incomplete for many countries, and other important ecological indicators, such as levels of coastal pollution, are not available. Other variables, such as rainfall, percentage of roads paved and number of protected areas, are national aggregates rather than specific to coastal areas where mangroves are located. Even key economic variables were not always available for all the countries in the sample for the years indicated in Table 1.1. As can be seen in Tables 1.3 and 1.4, the result was that the sample sizes of regressions were often smaller than the full sample of 89 countries. Given these limitations, the analysis and conclusions of this chapter regarding the potential impacts of economic development on mangrove deforestation across countries must be considered preliminary. Nevertheless, as this chapter represents a first attempt to develop a formal analysis of the economic factors determining mangrove loss worldwide, we hope that our analysis will lead to improved data collection and analysis for further work in this important area.

NOTES

1. Mangrove swamps are considered very suitable for shrimp farming because the areas are flooded with brackish, stagnant water that is ideal for aquaculture (Kongkeo 1997). 2. Although the list of countries covered by the World Mangrove Atlas is fairly comprehensive, there are a couple of notable omissions, such as Nigeria, which has one of the largest areas of mangroves in the world (WRI 1996), and the United States. Curiously, the Atlas does not report mangrove area for the entire United States but only for Florida. 3. Our preference was to use rural wage rates across countries as our main input price variable, as the available evidence suggests that in many countries rural labor is a major input in both the clearing of mangroves and in activities such as aquaculture and agriculture that depend Introduction 23

on mangrove conversion (Spalding et al. 1997; WCMC 1994; WRI 1996). However, obtaining a cross-country data set on rural wage rates for the year of estimation of mangrove area for each country, as reported in Table 1.1, was not possible. Similar problems occurred for other input price data, such as for fertilizers, insecticides and other key agricultural inputs. 4. As noted in the introduction, extensive shrimp and prawn aquaculture production in coastal areas is most likely to be responsible for conversion of mangroves. If a country’s shrimp aquaculture production is small relative to its coastline then there is likely to be less impact on the total mangrove area of that country. 5. The one exception is Micronesia. 6. The number of cabinet changes, constitutional changes and coups were each converted into a weighted index variable using the formula Xi/Max |X|, where Xi is the observation for the ith country and Max |X| is the maximum observation in the cross-country sample. The three resulting weighted index variables, along with the party fractionalization index, were then averaged into the single political stability index variable, using the standard formula SXij/Nj th th where Xij is the index value of the j political variable for the i country and Nj is the number of political variables. 7. The composite 1985 and 1990 data set for each of the political variables (purges, crises, guerrilla warfare, strikes, assassinations, revolts and riots) was created by selecting the observation from either 1985 or 1990, depending on which year more closely corresponded to the single-year estimate of mangrove area for each country in Table 1.1. The resulting data set for each variable was then converted into a weighted index using the formula Xi/Max |X|, and then all the indexed variables were averaged into the single political stability index variable, using the standard formula SXij/Nj. 8. Other variants than the four models depicted in Table 1.3 were also estimated. For example, including both GDP per capita and GDP growth did not improve upon Model 3, and the coefficient for GDPG was insignificant. Including a GDP per capita squared term in Model 3 did not improve the regression results, and the coefficient for the squared GDPPC term was also not significant. Thus an ‘environmental Kuznets curve’ income effect can be rejected in this analysis. 9. This finding and explanation is consistent with some cross-country studies of deforestation, especially for tropical countries, which also report a negative relationship between forest loss and GDP per capita. For recent reviews, see Kaimowitz and Angelsen (1998) and Barbier and Burgess (2001). 10. Replacing GDP per capita with GDP growth, or including both variables together, in Models 3 and 4 did not improve the explanatory power of the estimations, and the coefficient for GDPG was always insignificant. This page intentionally left blank PART I

National Trends and Analysis of Mangroves This page intentionally left blank 2. The importance of mangroves: ecological perspectives and socio-economic values Sanit Aksornkoae, Ruangrai Tokrisna, Wattana Sugunnasil and Suthawan Sathirathai

THE ECOLOGICAL AND ENVIRONMENTAL IMPORTANCE OF MANGROVES

Mangroves serve as a link between marine and terrestrial ecosystems. These communities are clearly important to the stability and maintenance of various adjoining ecosystems, for example, seagrass beds, coral reefs and marine life. Mangroves represent a unique habitat for a diverse variety of marine and terrestrial animals. The amount of organic matter produced by mangroves will support not only the mangrove ecosystem itself but also other related ecosystems. Moreover, mangroves also play an important role in stabilizing shorelines in coastal streams and estuaries by protecting them against tidal bores and soil erosion. It is firmly believed that, if the mangrove communities along the banks of estuaries and coastlines were disturbed, or were to be completely cut down, there would be no habitats or adequate food to support the organisms in these areas. Consequently, the loss of these mangrove-related ecosystems would disturb the natural ecological systems over a considerable area. Thus mangrove forests are recognized as having significant ecological and environmental values. However, it is difficult to quantify these values. Details of ecological and environmental values of mangroves can be discussed as follows.

Feeding and nursery ground for fisheries

Mangroves play a very important role as habitat, nursery and a source of food for both commercial fishery species and other marine fauna. Several studies of mangrove-associated fish populations in Thailand provide evidence that Thai mangrove forests are used by fish, crustacean and mollusks (a) as nursery

27 28 National trends and analysis of mangroves grounds, (b) as permanent habitats, or (c) as breeding grounds in the case of some coastal species (Angsupanich and Aksornkoae 1996; Wattayakorn et al. 1994; Monkolprasit 1994; Nishihira 1997). Several studies have examined the ecological relationship between mangroves and fisheries in Thailand. Watanachai (1979) reported that the species composition and abundance of fish eggs and larvae in the Laem Pak Biak mangroves (Phetchaburi) were dependent on the nutrient supply in the area. More than 30 families of fish that include species of economic importance such as Lates calcarifer and Chanos chanos were recorded from the area. Larval fish of several species of economic importance including tarpon (Megalops cyprinoides, M. atlantica), lady fish (Elops hawaiensis, E. saurus), groupers (Epinephelus tauvina) and snappers (Lutianus johni) were recorded from the mangrove forest in Ban Khlong Wan, Prachub Khiri Khan Province. On the Andaman coast, Janekarn and Boonruang (1986) have carried out a fish larval survey in mangrove areas of Phang-nga Bay located on the Andaman coastline. Forty-four families of fish larvae were present, gobiids being the most abundant, accounting for 64 per cent of all specimens; engraulid and clupeid larvae were also relatively common. Janekarn and Sawangarreruk (1987) reported on the fish larvae collected along the west coast of Thailand (Andaman Sea of the Indian Ocean) from Phuket to Satun Province. More than 60 families were recorded, the major ones being Carangidae, Gobiidae, Clupeidae, Monacanthidae and Callionymidae. Macintosh et al. (1991) found that fish larval diversity in the Ranong mangrove forest was as high as that described in other mangrove forests along the coast of Thailand. It is believed that the early life stages of fish require access to rich food sources to support their high rate of metabolism and growth. They also require shelter from predators. The mangroves bordering the many creeks and waterways adjoining Khlong Ngao seem to offer an ideal habitat for these purposes. The export of organic matter during the wet season and the high abundance of planktonic larvae released by the mangrove intertidal fauna are the important food sources for these young fish stages. Another important feature of the Ranong mangroves is that the entire forest is flooded by the high tides each month. This means that fish have complete access to the intertidal mangrove zone at these times, a situation which must increase opportunities for feeding and allow wide dispersal of young fishes through the mangrove ecosystem.

Shoreline stability

Mangroves typically establish themselves on sheltered accreting shores. Thus the role of mangroves in protecting coastal stability against erosion and storms is widely recognized. Their tangled root system is important in land building The importance of mangroves 29 because they trap sediment and the mangroves are extended. The physical and chemical studies of mangrove forests conducted in Khlong Ngao, Ranong Province under the UNDP/UNESCO Regional Mangrove Project (1991) showed that the Ranong mangroves serve two key functions in the coastal ecosystem: (a) the mangroves trap fine sediments carried into the coastal zone by flood waters, and (b) there is a significant net export of nutrients from the mangroves into the coastal zone, which acts as a source of enrichment for the marine environment. It was demonstrated that the bulk of fine sediments washed into the Khlong Ngao mangroves by local floods settled rapidly and were trapped by the mangrove vegetation. Only about 12 hours were required for sediment-laden water in the estuary to become clear. High rainfall areas with significant sediment displacement, such as the Ranong mangroves, act as natural sedimentation tanks, protecting other coastal environments from the harmful consequences of sediment discharge. In areas suffering from inland deforestation and soil erosion, this role of the mangroves becomes even more vital.

Water quality control

Mangrove ecosystems play an important role in sequestering inorganic dissolved nutrients and other potential pollutants from coastal streams and rivers that would be discharged into neighboring nearshore ecosystems. A study by Aksornkoae et al. (1999), under the Royal Leam Pakbia Environmental Research and Development Project at Phetchaburi Province, Thailand, demonstrated that mangrove forests can be used as tertiary treatment sites for sewage to remove inorganic and toxic materials from domestic and industrial effluents. Mangroves can also remove nutrients, reduce suspended solids, remove heavy metals and absorb toxic hydrocarbons. Wattayakorn et al. (1999) found that mangrove soils were good traps for immobilizing waste water-borne phosphorus and heavy metals. In some areas along the coastline, severe coastal erosion and storm damage can be found, resulting from mangrove removal. This is one of the important reasons why various countries have legislation to protect mangroves as ‘buffer zones’ along the coastline.

Foraging areas for birds and wildlife habitats

Mangrove forests serve as the feeding and nursery grounds for many species of birds and as important habitats for a variety of invertebrates, reptiles and some mammals. A survey of vertebrates, excluding fish, carried out by Sittilert et al. (1976), identified 42 species of birds, seven species of mammals, two species of reptiles and one amphibian. These animals were mainly found living at the edge of the mangrove swamp, entering it to feed on mangrove 30 National trends and analysis of mangroves fauna. Four species of migrating birds moved in during different seasons of the year. Nabhitabhata’s (1982) ecological study of birds in Songkhla Lake, Southern Thailand revealed that there were 25 families with 90 species of birds in the area. Of these, 70 per cent and 20 per cent, respectively, were residents and seasonal migrants. Most birds observed in the area tended to feed on open grazed land. Birds of the families Bucerotidae, Picidae and Pittidae, often found in the natural mangrove forests, were absent from the exploited mangrove forest. Bhovichitra et al. (1982) reported sightings of 42 bird species from the Ranong mangroves.

THE SIGNIFICANCE OF MANGROVE FORESTS TO COASTAL COMMUNITIES

In Thailand, as is true elsewhere in South East Asia, mangrove forests and the coastal ecosystem have played an important role for coastal human settlements. These settlements in mangrove and coastal areas range from small fishing communities to large cities. The latter often include ports, harbors, industrial estates and residential developments. In Southern Thailand, where most mangrove forests are concentrated, major cities with high population densities are usually located in coastal areas that offer ease of access, supplies of fresh water and fertile land. These also often happen to be the best habitats for mangrove development. Besides accommodating industrial, commercial and social activities, mangrove ecosystems also serve as the base for a significant number of people living in communities who depend on mangrove forests and coastal waters for their livelihood. Many of these coastal residents who live in or earn their living from the mangrove environments utilize the areas for timber, poles, woodfuel and thatch, for capture and culture fisheries, for salt production and for other agricultural land uses. Generally, the main form of coastal human habitation in Southern Thailand is in permanent fishing villages, varying in size from a small cluster of 20–50 households to several hundred families. In 1998, for the total mangrove areas of the remaining 1 200 000 rai,1 it was estimated that a million people were local residents living in at least 2000 coastal communities located within or near to mangrove forests, scattered along coastal areas (Plathong and Sitthirach 1998; Boonchuwong 1995). Mangrove populations mostly live in small communities within or at the edge of the mangrove or along channels inside the estuary. These communities depend upon mangrove forests for a variety of direct and indirect benefits. Many household necessities of coastal communities, including agricultural lands, fishing gear, firewood, charcoal, construction materials, herbal plants for traditional medicines and other minor products are provided by mangroves. The indirect benefits of mangroves arise largely from The importance of mangroves 31 their other ecological functions, such as controlling shoreline erosion and sedimentation, acting as windbreaks and providing a habitat for marine wildlife. Life in most coastal communities revolves around fishing in coastal areas (for details, see Sugunnasil 1995; Ruohomaki 1999; Priebprom 1986; Rougrujipimon 1985). Fisheries in the mangrove areas are usually on a small scale. Most local fishermen exploiting the area use stationary or simple gear such as fixed traps, hook and line, cast nets and some gill nets. Consequently, there is a low level of production per person. Sometimes local villagers fish in the mangrove creeks or canals. Some of the marine species found in mangrove canals, such as mud crabs, mantis shrimps, mullet, sea bass and groupers are high-priced. Besides fishing, coastal residents derive additional income by cutting and extracting wood from mangrove forests for either firewood, charcoal wood or poles. There are some whose livelihoods depend solely on harvesting mangrove forest products such as fuelwood, charcoal wood, fishing stakes, poles and nypa for thatching. In many coastal communities, working as mangrove wood-cutters for charcoal production or concessions has been an important source of income for local villagers (Miprasart 1996). It is also not uncommon to find that mangrove areas in Southern Thailand have been converted into paddy fields, coconut, rubber and palm plantations by local villagers (Aksornkoae 1993). Furthermore, coastal and marine resources are also important for providing employment opportunities for poor and landless farmers and other groups of people living on society’s fringes. Unable to find work in growing sectors of the national economy, many have moved to the coasts to exploit comparatively free, commonly owned resources. Compared to inland forests, very few mangrove forests are under private ownership. Most mangrove forests have been declared reserved mangrove forests, which makes any land occupancy illegal. Nevertheless, large areas of reserved mangrove forests have been illegally occupied by coastal residents for a long period of time. The increased pressure on, and demand for, forest resources, agricultural lands and other uses have led to widespread degradation of the mangrove forests. Historically, many coastal communities in Southern Thailand were highly dependent on the mangrove forests and they have become well adapted to the environment, and their habitation has had minimal negative effects on the forest ecosystem (Chansanoh 1994; Sugunnasil 1997). To a large extent, local residents’ traditional pattern of fishery–forestry utilization, mainly for their subsistence needs, was in line with the ecological requirements of the mangrove ecosystem, as their survival depended on the sustainability of the coastal environment. However, the development process and the emergence of a market for mangrove and coastal resources, as well as modern consumer products, have created new incentives that are affecting coastal residents’ social and economic interests and their way of life. Particularly since the early 1960s, increases in urbanization, industrialization, population, land scarcity, 32 National trends and analysis of mangroves infrastructural development and commercialization in the South and Thailand in general have resulted in an increasingly intensive use of coastal resources (Sugunnasil 1995). This development pattern, which has relied heavily on intensive resource uses, has also constantly encroached upon the remaining mangrove areas and severely affected the state of mangroves and other coastal and marine resources. Approximately two million rai of mangroves were estimated to exist in 1960. Since then, the area of the mangrove forest has decreased at an alarming rate (see also Chapter 3). Three decades later, only about half remained (Plathong 1998). Consequently, the exposure to a variety of man-made and natural pressures has taken its toll on the mangrove forests and coastal ecosystem. These pressures have resulted in the rapid depletion of mangroves and the drastic decline in fisheries. All the major bays in the country have now been overfished. Destructive fishing activities such as trawls and push nets have resulted in the degradation of marine and coastal ecosystems. Charcoal concessions, mining, shoreline development and shrimp farming expansion, particularly since the 1980s, have been further identified as leading factors in the continued mangrove deforestation and degradation of the coastal marine environment and the consequent conflicts among different resource user groups in coastal areas (Plathong and Sitthirach 1998). Changes in the ecology of coastal areas have several important consequences for people living in coastal communities. As the area of mangroves declines, the growing number of coastal residents are forced to concentrate on a smaller forest area, leading to further degradation through over-use, and frequently they must travel greater distances to obtain basic necessities. Of major concern to many local fishermen in a number of coastal communities is the impact of mangrove loss and wastewater from shrimp farms on the productivity of inshore and offshore fisheries. Many mangrove-dependent marine species are important for the consumption and livelihood of coastal residents, and many commercially important kinds of fish, crabs, prawns and mollusks use mangrove areas as nursery grounds and shelter during the juvenile stages of their development. Local fishers in many coastal communities have reportedly observed the relationship between the destruction of coastal mangroves and a general decrease in fish stocks (Priebprom 1986; Chansanoh 1992; Rithibhonbhun et al. 1993). The prospect of declining fish stocks is particularly worrisome in most fishing communities, as their coastal waters are already being over-fished by an increasing number of small-scale fishermen and by the large commercial trawling industry. Despite the fact that marine fish stocks have come under increasing pressure and continued to decline, for many small-scale coastal fishermen, fishing is the only way of life that they have known, and they persist in it even though it provides only a very marginal livelihood. The importance of mangroves 33

Poverty in these coastal communities has also been pointed out as a source of mangrove and marine ecosystem degradation. A large number of small- scale fishing families in these communities is believed to be living below the poverty line. As these coastal residents are dependent upon the mangrove and coastal ecosystem for their livelihood, degradation of mangroves and increased pressure and competition for other land and water uses have led to conflicts among themselves and between local residents and government officers and outsiders. In other cases, resouce degradation has forced many of them to intensify and diversify their income-generating activities. In situations where an alternative livelihood is limited, as is true in most of the cases, this could lead to a cycle of resource destruction and depletion. Coastal villagers, like rural villagers elsewhere, have been increasingly driven by the same market incentives and economic imperatives that drive urban people, government officers and private investors. An intensified process of commodification of natural resouces has increasingly blurred the distinction between traditional and commercialized, market-oriented patterns of coastal resource exploitation. Subsistence ethics and traditional limited use of resources appear to have been declining and differentiation in employment, education, socio-economic status and standard of living in many coastal communities has been noted (Prachuabmoh 1996; Sugunnasil 1997). Such changes may have been induced by increasing resource scarcity, rising expec- tations and changing consumption patterns. In other words, the increased heterogeneity among coastal residents, together with the urgency of their resource constraints, appears to have been eroding the image of coastal communities living in harmony with their mangrove and marine environment. Nevertheless, despite evidence indicating the complexity and difficulties of the problem, there are also a number of coastal communities which are now working on community mangrove forest projects to protect their local resources and use them in a more sustainable way (Rithibhonbhun et al. 1993; Sathirathai 1998). It is against this background of a changing and dynamic situation in coastal areas that the proliferation of shrimp ponds with its devastating impact on the ecology of mangrove forests and the emergence of conflicts among different resource users in many coastal communities must be understood.

THE ECONOMIC VALUE OF MANGROVES IN THAILAND: A REVIEW OF LITERATURE

The economic value of mangroves comprises two main values: use and non- use values. Use values can be categorized into direct use values, indirect use values and option values. 34 National trends and analysis of mangroves

Direct use values come from the outputs from mangroves that can be directly consumed. They are values from mangrove wood and wood products, brackish water catches from fishing grounds in the mangroves, animals captured from mangroves, and natural collection from mangroves (such as honey and herb collection). Indirect values are mainly functional benefits. They are more concerned with ecological functions such as nutrients, flood and flow control, water quality maintenance, sediment retention, shoreline stabilization, storm protection, shoreline navigation, habitats for fauna and flora, and carbon sequestration. These indirect values are usually interrelated and difficult to quantify. Option values are those future values from direct or indirect use of mangroves once the mangroves have been maintained. They can be values from biodiversity, which if maintained can be of use in the future. Culture/heritage values are also option values of maintaining mangroves for the next generations. Non-use values are usually existence or bequest values. They can be aesthetic values and biodiversity values from the existence of mangroves. Economic valuation techniques have been developed as a means of assessing the value of natural resources and the environment, including mangroves. Nevertheless, the complicated ecological function of mangroves makes it difficult for them to be valued. Attempts that have been made to calculate the mangrove values in Thailand are described below. Direct use values may have been the values that can be most conveniently quantified. Often market values can be estimated for the direct consumption of produce from mangroves. Pongthanapanich (1995) attempted to quantify the values of benefits from mangroves in order to estimate the optimum use of mangroves in Trang Province, a province on the Andaman Coast of Thailand. In her study, based on various scientific studies on the benefits derived from mangroves, she was able to estimate the direct use values from mangrove woods and brackish water catches. The wood values ranged from 14 038 to 25 250 baht/ha/yr, while the figure for brackish water catches was 25 625 to 96 406 baht/ha/yr, depending on the fertility of the mangroves.2 The wood values were estimated from the present value of net returns on reported wood- cuts from concession areas, while aquatic catch volumes were based on various scientific studies. Catches included shrimps, sergistid shrimps, fish and crabs. Market value was employed in assigning values to these outputs. As for the indirect use values, data were available only for nutrient retention values. Using a market value approach, nutrient retention value was estimated to be 4 498 baht/ha/yr.3 In spite of underestimation on mangrove values, this study found that, for the optimum allocation of mangroves in Trang, only 12 per cent of the area should be converted into shrimp farms. As a result, the net present value from mangroves in Trang would be 52 731 billion baht, of which 22 per cent could be from shrimps. At this optimum allocation, the annuity of net The importance of mangroves 35 present value per hectare of mangroves would be 130 069 baht, at a discount rate of 8 per cent over a life span of 30 years.4 In 1999, the Department of Agricultural and Resource Economics at Kasetsart University undertook a study on the estimation of environmental costs from shrimp farming. In this study, estimation of direct and indirect use values of mangroves was again attempted. This study used a different source of information on wood productivity, mainly based on charcoal wood. By using a market value approach, the wood productivity was estimated to be 76 782 baht/ha/yr. In contrast, the estimation of fishery catches was estimated to be only 7394 baht/ha/yr. Indirect use values in this study included nutrient retention, shoreline stabilization, carbon fixation and oxygen release. In estimation of nutrient retention the source of physical information was the same as the study in 1995, but the price estimation was based on a different source. Nevertheless, the estimated value of nutrient retention was about the same as before, at 4567 baht/ha/yr.5 For the sake of shoreline stabilization, a preventa- tive cost was employed. From the construction cost of 475.9 million baht for 1046 ha of mangrove, at a discount rate of 8 per cent and a capital recovery factor of 0.1018, the shoreline stabilization value was estimated to be 46 338 baht/ha/yr. For carbon fixation and oxygen release, the total value was estimated to be 43 825 baht/ha/yr from 58.4 ton/ha of carbon dioxide and 44.9 ton/ha of oxygen. The price of oxygen was obtained from the Department of Pollution Control in Thailand, while the price of carbon dioxide was provided by the World Bank. Adding up these values, the estimated mangrove value comes to 178 915 baht/ha/yr.6 The above studies employed a market value approach and replacement cost in the estimation of mangrove values and worked out only some direct and indirect use values of the mangrove. Attempts have not been made to calculate option values and non-use values. There are still other approaches, including surrogate market, contingent valuation, the individual choice model, conditional value of information which can be applied. Nevertheless, in estimating the values, it is important that ecological function be thoroughly understood, otherwise the estimation can be either under- or over-valued. The benefits of mangroves to local communities have been highlighted by a recent study conducted by a team led by Suthawan Sathirathai, of the Centre for Ecological Economics, Chulalongkorn University, Bangkok, with the support of the Economy and Environment program for South East Asia (EEPSEA) (Sathirathai 1998; Sathirathai and Barbier 2001). The study looked at the case of Surat Thani Province of Southern Thailand, where substantial areas of mangrove have been cleared for shrimp farming. The case study examined two hypotheses: first, the full conversion of mangroves into commercial shrimp farms may not be worthwhile if the real forgone benefits of mangroves are taken into account; and second, the benefits from mangroves 36 National trends and analysis of mangroves may provide incentives for local communities to protect the ecosystems. Full details of the study are provided in Chapter 11.

NOTES

1. A‘rai’ is the common measure of land area used in Thailand. The conversion rate is 6.25 rai = l hectare of land. 2. 40 baht = approximately 1US$. 3. This was based on Aksornkoae (1998). The volumes of nitrogen, phosphorus, potassium, calcium, magnesium and sodium were 8.9, 0.7, 8.4, 18.2, 3.9 and 8.9 kg/0.16 ha/yr for the Andaman mangroves in Ranong. 4. More details are available from Pongthanapanich (1995) and Tokrisna and Pongthanapanich (2001). 5. Average volumes of nutrients in Ranong on the West Coast and Chanthaburi on the East Coast. 6. See details in Department of Agricultural and Resource Economics (1999) and Tokrisna and Pongthanapanich (2001). 3. Overview of shrimp farming and mangrove loss in Thailand Sanit Aksornkoae and Ruangrai Tokrisna

THE PRESENT STATUS AND LOSS OF MANGROVE FOREST

The Present Status of Mangrove Forest

The mangrove ecosystem is totally different from most other ecosystems. Mangroves are unique and have special, highly complex characteristics. They are transitional ecosystems between land and sea and between freshwater and seawater. In Thailand, the existing mangrove forest can be found mainly in six provinces along the Andaman Sea Coast and in 16 provinces along the Gulf of Thailand coast (see Figure 3.1).1 Mangroves are present on approximately 50 per cent of the 2614 km coastline of the country. In a recent survey, Charuppat and Charuppat (1997) estimated the total existing mangrove forest to be approximately 167 582 ha, using Landsat-5 data. Of the estimated total mangrove forest area, approximately 80 per cent can be found along the Andaman Sea coast, which is the western part of the Southern Thailand peninsula. However, the mangrove forest in Thailand was approximately 367 900 ha in 1961. Thirty-five years later, the mangrove area has been reduced to slightly more than half its original size.

Mangrove Forest Loss

Mangrove forest areas in Thailand have been destroyed or degraded at an alarming rate. They have been reclaimed for different purposes such as aquaculture, agriculture, resettlement areas, urbanization, salt production, road and transmission lines set-up, mining, construction of ports and harbors, dredging, build-up of various industries and power plants. It was estimated that, between 1961 and 1996, an estimated area of 204 865 ha of mangrove forests was converted for such purposes. Changes of mangrove forest areas in Thailand and by regions between 1961 and 1996 are shown in Tables 3.1 and 3.2, respectively.

37 38 National trends and analysis of mangroves

BANGKOK Samut Sakhon Samut Prakan Samut Songkhram Chon Buri Phet Buri Rayong

Chantha Buri CAMBODIA

Trat

BURMA Prachuab Kirikhan

Gulf of Thailand

N Chumphon

Ranong Mangroves areas Andaman Sea

Surat Thani

Phang-Nga Nakorn Srithmmarat

Krabi

Trang Pattalung

Songkhla

Pattani

Saturi Narathiwart

MALAYSIA

Figure 3.1 Distribution of mangroves in Thailand rai/yr 2 292.00 24 643.00 39 675.00 81 136.00 33 076.00 21 056.00 16 057.00 366.72 ha/yr 3 942.88 6 348.00 5 292.16 3 368.96 2 596.12 12 981.76 Average destruction area Average % 1.23 6.82 4.27 1.82 1.39 1.04 55.76 14.81 24.38 rai 6 876.00 42 113.00 42 113.00 32 115.00 28 425.00 99 230.00 354 000.00 158 700.00 567 951.00 1 280 410.00 Rate of change – 96 ha 4 548.00 6 738.08 5 138.40 1 100.16 55 200.00 25 392.00 90 872.16 15 876.80 204 865.60 rai 2 327 800.00 2 299 375.00 1 954 375.00 1 795 675.00 1 227 724.00 1 128 494.00 1 086 381.00 1 054 266.00 1 047 390.00 Mangrove forest ha 372 448.00 367 900.00 312 700.00 287 308.00 196 435.84 180 559.04 173 820.96 168 682.56 167 582.40 Changes in mangrove forest area in Thailand, 1961 area forest Changes in mangrove Charuppat and (1997). ear otal able 3.1 T Y Before 1961 1961 1975 1979 1986 1989 1991 1993 1996 T : Source

39 Table 3.2 The extent of existing mangrove forests and other land uses, by different regions in 1996

Total area 1996 Total original Location Mangrove Shrimp Resettlement Other mangroves forest pond areas uses before 1961

Eastern region (ha) 12 658.0 24 295.3 3 957.1 13 934.6 54 845.0 (rai) 79 112.5 151 845.8 24 731.7 87 091.3 342 781.3 Central region (ha) 5 449.0 15 629.2 3 099.9 42 803.7 66 981.8

40 (rai) 34 056.8 97 682.5 19 374.5 267 523.2 418 636.3 Eastern coast of (ha) 16 517.4 21 919.6 1 001.1 16 957.0 56 449.2 the peninsula (rai) 103 570.0 136 997.5 6 257.0 105 981.2 352 807.4 (Gulf of Thailand) Western coast of (ha) 132 904.0 5 153.8 742.3 55 371.9 194 172.0 the peninsula (rai) 830 650.3 32 211.0 4 639.3 356 074.5 1 213 575.0 (Andaman Sea) Total (ha) 167 582.4 66 997.9 8 800.4 129 067.2 372 448.0 (rai) 1 047 390.0 418 736.8 55 002.5 806 670.2 2 327 800.0

Source: Charuppat and Charuppat (1997). Shrimp farming and mangrove loss in Thailand 41

A 1996 survey into the loss of the country’s mangrove forest (Table 3.2) showed that approximately 204 865 ha of mangrove forest were completely cleared for other purposes, which is about 56 per cent of the original mangrove area in 1961. Of the total area of mangrove lost, 32.7 per cent was converted into shrimp ponds, 4.3 per cent into resettlement areas and 6.30 per cent were put to other uses, including agriculture, urbanization, ports and harbors, mining, salt pans, transmission lines, power plants and road construction. Table 3.3 indicates the extent of mangrove loss in Southern Thailand (that is, the Eastern and Western Peninsula provinces). Over the period 1961–96, mangrove forests in Southern Thailand declined by about 1 181 985 rai (189 117 ha), or about 56.5 per cent of the original mangrove area. Mangrove loss in the Eastern Peninsula (Gulf of Thailand Coast) was approximately 541 430 rai (86 628 ha), or 83.9 per cent of the total area and about 615 600 rai (98 496 ha) or 42.5 per cent of the total mangrove area in the Western Peninsula (Andaman Sea coast). According to a survey in 1996 (Table 3.4), 55 per cent of mangrove conversion in the Eastern Peninsula was for shrimp ponds, 2.5 per cent for resettlement and 42.5 per cent for other uses, while, in the Western Peninsula, 8.4 per cent of mangrove loss was for shrimp ponds, 1.2 per cent for resettlement areas and 90.4 per cent for other uses. Over the period 1961–96, mangrove loss was approximately 541 430 rai (86 628 ha), or 83.9 per cent of the total area, along the Gulf of Thailand and about 615 600 rai (98 496 ha), or 42.5 per cent of the total area, along the Andaman Sea. According to the 1996 survey (see Table 3.4), mangrove conversion on the Eastern Peninsula was largely due to shrimp ponds (55 per cent), followed by other land uses (42.5 per cent) and then finally resettlement (2.5 per cent), whereas on the Western Peninsula mangrove loss was mainly the result of other land uses (90.4 per cent), then shrimp ponds (8.4 per cent) and finally resettlement areas (1.2 per cent).

THE DEVELOPMENT OF SHRIMP FARMING IN THAILAND

Shrimp farming in Thailand started from traditional extensive farming along the coastline in the inner Gulf of Thailand, benefiting from the abundant natural larvae of banana shrimp (Peneaus merguiensis) and school shrimp (Metapenaeus sp.). In the early days, shrimp was a by-product of salt pens. Returns from this by-product induced the development of extensive shrimp farming along the coast where there used to be plenty of salt pens. The early shrimp farms were located in three provinces, Samut Sakhon, Samut Songkram and Samut Prakarn, which were not too far from Bangkok and the central seafood market. Lower salt prices in the late 1940s resulted in an increasing Table 3.3 Mangrove forest in southern Thailand, 1961–96

Province Mangrove forest (rai) 1961 1975 1979 1986 1989 1991 1993 1996

Total Eastern Peninsula 645 000 221 875 221 100 122 767 106 725 87 375 102 657 103 570 Chumphon 50 625 46 250 43 300 22 662 14 156 11 363 20 587 19 698 Sura Thani 160 000 23 125 36 300 26 774 23 544 13 775 19 775 19 586 Nakhon Si Thammarat 382 500 96 875 80 200 55 219 53 256 50 156 49 975 52 601 Pattalung 8 750 11 875 10 200 656 525 375 800 881 Songkhla 8 125 36 875 32 400 6 031 4 300 1 431 3 425 3 896

42 Pattani 35 000 6 875 8 700 11 425 10 944 10 275 8 095 6 906 Total Western Peninsula 1 446 250 1 197 125 1 113 475 923 746 888 564 927 193 836 585 830 650 Ranong 191 250 151 250 141 200 135 097 132 388 121 688 120 675 120 229 Phang-nga 358 750 318 375 304 475 227 625 222 583 209 427 191 976 190 265 Phuket 28 750 19 375 17 800 12 034 11 163 9 722 9 675 9 448 Krabi 335 625 206 250 198 500 189 540 185 289 193 469 178 292 176 709 Trang 243 750 212 500 205 400 164 225 156 560 198 206 152 050 150 596 Saturi 288 750 289 375 246 100 195 243 180 581 194 681 183 877 183 402 Total in southern Thailand 2 091 250 1 420 000 1 324 575 1 046 446 994 339 1 014 596 939 219 934 220 Total in Thailand 2 229 375 1 954 375 1 795 625 1 227 674 1 128 494 1 085 050 1 054 266 1 047 390

Source: Charuppat and Charuppat (1997). Shrimp farming and mangrove loss in Thailand 43 number of extensive shrimp farms in this area. In this early era, farming with black tiger shrimp (Peneaus monodon) was largely unknown in Thailand. The extensive shrimp farming usually converted salt pens into shrimp farms or used parts of the pens for shrimp farming. In the late 1960s, the number of shrimp farms increased as a result of better shrimp prices and a higher return as compared to salt farms. These farms used a large area: approximately 8–16 ha/farm. They had to be located near the coastline, on the banks of the canals for the convenience of pumping water into the ponds. They relied solely on natural larvae and feed abundance. At the early stage of development, water would be changed on a weekly basis. As the number of shrimp farms increased, water change became more frequent.The main cost of extensive shrimp farming was for pond construction and fuel for pumping water into the ponds. The establishment of successful hatcheries for P.merguiensis and P.monodon in 1973, along with high returns, led to more farming. In 1983, a large multinational company, the President Feed Industry from Taiwan, entered into a joint venture with local investors. They introduced intensive black tiger shrimp (P.monodon) farming. This shrimp species had a better survival rate than banana shrimp in aquaculture, and thus a better return. High returns from such farming led to a rapid increase in farming areas in the inner Gulf which soon spread to the eastern and southern coasts of the Gulf. There was a change from extensive to intensive farming, with semi-intensive farms also in existence. For intensive farming, farmers stocked the larvae from the hatcheries. With such stocking density, additional feed was required. The farmers could no longer rely on natural abundance. Nevertheless, they need water from natural water sources. A high density of shrimp could lead to a lower quality of water, especially with a lack of a proper water management system and management of pond effluence including the water and sludge from shrimp ponds. Farmers solved the problem by adding aerators to improve water quality in their rearing ponds. Because of its higher tolerance and better survival rate, the black tiger species rapidly became popular among shrimp farmers. It was possible to transport the larvae longer distances. Shrimp farming quickly spread to the coast in the Eastern Region and the coast of the Gulf of Thailand, further down in the south. Finally, the areas extended to the coast of the Andaman Sea, on the West side of the Southern area of Thailand. In 1973, the Department of Fisheries reported that there were 1462 shrimp farms in Thailand over a cultivated area of 11 468 ha, with a production of 1635 metric tons, an average of 7.8 ha/farm at an average yield of 143 kg/ha. The farms mainly practiced extensive farming. After 1983, shrimp farming became more intensive. There was a transition during the second half of the 1980s. By 1988, the number of shrimp farms had increased to 10 246 farms over 54 778 ha. The average farm size fell to 5.3 ha/farm at an average yield of 1016 kg/ha.2 Table 3.4 Different land use patterns in mangrove areas of southern Thailand in 1996

Land-use in mangrove areas (rai, 1996) Province Mangrove Shrimp Resettlement Other Total forest ponds areas uses

Total Eastern Peninsula 103 570.50 136 997.50 6 257.00 105 981.25 352 806.25 Chumphon 19 698.75 19 506.75 800.00 26 444.50 66 450.00 Sura Thani 19 586.25 39 610.00 221.50 14 351.00 73 768.75 Nakhon Si Thammarat 52 601.00 65 479.25 445.25 16 580.75 135 106.25 Pattalung 881.25 2 368.50 93.75 12 475.25 15 818.75 Songkhla 3 896.50 7 905.25 3 671.50 22 520.50 37 993.75 44 Pattani 6 906.75 2 127.75 1 025.00 13 609.25 23 668.75 Total Western Peninsula 830 650.25 32 211.00 4 639.25 346 074.50 1 213 575.00 Ranong 120 229.00 2 088.75 3 202.50 43 442.25 168 962.50 Phang-nga 190 265.25 5 958.25 75.00 78 570.25 274 868.75 Phuket 9 448.00 1 322.00 70.50 6 472.00 17 312.50 Krabi 176 709.25 7 910.50 87.50 64 780.25 249 487.50 Trang 150 596.75 5 656.75 0.00 93 077.75 249 331.25 Saturi 183 402.00 9 274.75 1 203.75 59 732.00 253 612.50 Total in southern Thailand 934 220.00 169 208.50 10 896.25 452 055.75 1 566 381.20 Total in Thailand 1 047 390.00 418 736.75 55 002.50 806 670.75 2 327 800.00

Source: Charuppat and Charuppat (1997). Shrimp farming and mangrove loss in Thailand 45

Before 1990, intensive shrimp farming was a highly profitable investment thanks to high yield and the high price of the produce. Suitable coastal areas including mangrove areas were converted into shrimp farms. In 1991, there was a Cabinet Resolution not to allow shrimp farming in conserved and fertile mangrove areas. Shrimp farming in mangrove areas was restricted to deteriorated mangrove areas. During this period most shrimp farming had become intensive, using a smaller area with high stocking density and application of ready-mixed feed. Actually, intensive shrimp farmers did not prefer mangroves. The necessary area was usually small, but with a high operating cost for feed, fuel and larvae. The high cost of land clearing, and a lack of infrastructure (including electricity and road access) deterred intensive shrimp farmers from converting mangroves for shrimp farms. During this period the rate of mangrove conversion to shrimp farming fell, unlike the early stage of development when there had been more extensive farms. Nevertheless, throughout the 1990s, the remarkably high return from intensive shrimp farming continued to attract more investors. The number of shrimp farms along the coasts increased, although not always at the expense of mangrove forests. The success of black tiger shrimp hatcheries, together with the development of the shrimp feed industry and the intensive culture technique, and the high price in the international market promoted the rapid development of shrimp farming in Thailand. Shrimp culture expanded from coastal intra-tidal zones to inter-tidal zones and inner coastal areas as shrimp farming was no longer dependent on wild larvae and natural feed. Soon shrimp farms were crowded along the coastal areas. The density of farms in the earlier developed areas was beyond the carrying capacity of the environment. Without careful management of effluence from shrimp farms, environmental conditions were degraded. Water quality deteriorated, leading to a lower yield, and finally widespread problems with the outbreak of disease. There were at least three factors involved in the periodic shrimp disease outbreaks of the 1990s: poor water quality, the weak and infected shrimp larvae, and the lack of good farm management (that is, overstocking and over- feeding). These were the results of too rapid a development in the shrimp farming industry. Farmers responded to the disease problem by shifting the location of shrimp cultivation. This contributed to the spread of shrimp farm expansion. In 1992, the largest shrimp farm areas were in the Southern Region along the Gulf of Thailand coastline. Thereafter, however, owing to the outbreak of disease, the shrimp farm area along the south east coast decreased. By 1998, it had recovered, but the area was still smaller than in 1992. In contrast, over the period 1997–8, the shrimp farm area on the Andaman Sea 46 National trends and analysis of mangroves coast gradually increased, indicating a shifting to the west coast. However, since 1996, there has been a steady increase in the number of shrimp farming areas away from the coast, such as the rice-growing areas of the Central Region in Thailand. Because of the deteriorating environmental conditions along the coastline, shrimp farmers have invented a ‘closed system’ for intensive aquaculture for use in low salinity areas such as the Central Region. In this system, once the water is introduced into the pond, there is very little water exchange. The farmer has to monitor carefully water condition, and water treatment is employed only to maintain the salinity and water quality at designated levels. Such operations require skillful pond management. The farmers import seawater from the coastal area to the Central Region using truck transportation. The water is treated before being introduced into the rearing pond in order to make sure that it is not infected and has the proper salinity level. This closed water system developed rapidly in the Central Region and quickly spread to other agricultural zones. In November 1998, the National Environmental Board banned shrimp farming in freshwater areas (particularly in the Central Region) as there was concern that too many rice farmers were converting their paddy fields to closed shrimp farming systems. By 1998, there were 25 977 farms in Thailand, with a total area of 76 019 ha. The average farm size in 1998 was 2.9 ha and the average yield per farm was 3325 kg/ha; 84 per cent of shrimp farms were classified as intensive farms, 12 per cent as extensive and 4 per cent as semi-intensive. The extensive and semi-intensive farms were found mainly in deserted, former aquaculture areas, where the environmental conditions had been degraded and were no longer profitable for intensive farming.

PROBLEMS AND CONSTRAINTS IN AREA UTILIZATION

The shrimp culture in Thailand has been mainly based on intensive systems since the early 1990s. The shrimp farm area reached its peak of 75 332 ha in 1991 and then declined. In 1998, it increased again, to 76 019 ha, mainly owing to the expansion of the closed intensive culture system in the Central Region. The number of shrimp farms in Thailand reached its height in 1995, at 26 145 farms, fell in 1996 and 1997, but increased again in 1998 as a result of the expansion in the Central Region. However, following the November 1998 ban on shrimp farms in freshwater areas, it is likely that Thailand has reached its peak in terms of shrimp culture area and number of farms. Table 3.5 and Figure 3.2 summarize the trends since 1989 for shrimp farming in Thailand. Table 3.5 Number of shrimp farms, farm area, production, farm size, yield in Thailand

Item 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Number of shrimp farms Intensive 6 228 9 089 13 961 14 768 15 474 17 707 22 001 19 284 19 992 21 924 Semi-intensive 3 836 3 417 2 218 1 629 1 522 1 247 1 172 1 036 894 1 069 Extensive 2 481 2 566 2 819 3 006 3 031 3 244 2 972 3 093 2 837 2 984 Total 12 545 15 072 18 998 19 403 20 027 22 198 26 145 23 413 23 723 25 977 Farm area (ha) Intensive 25 771 23 468 38 104 36 338 36 569 38 631 44 711 42 123 44 416 44 611 Semi-intensive 24 480 20 458 15 778 12 459 10 908 8 450 8 091 7 399 6 440 4 851 Extensive 20 915 20 680 21 450 23 999 24 410 26 167 22 140 23 142 22 264 26 557 Total 71 166 64 606 75 332 72 796 71 887 73 247 74 942 72 664 73 120 76 019 47 Shrimp production (metric tons) Intensive 71 665 98 409 145 194 173 542 216 514 256 159 253 182 231 551 221 752 245 767 Semi-intensive 14 274 13 064 11 608 5 808 3 750 3 128 2 902 3 427 1 941 2 477 Extensive 7 555 6 754 5 267 5 534 5 250 4 159 3 457 4 522 3 867 4 487 Total 93 494 118 227 162 069 184 884 225 514 263 446 259 541 239 500 227 560 252 731 Average farm size (ha/farm) Intensive 4.14 2.58 2.73 2.46 2.36 2.18 2.03 2.18 2.22 2.03 Semi-intensive 6.38 5.99 7.11 7.65 7.17 6.78 6.90 7.14 7.20 4.54 Extensive 8.43 8.06 7.61 7.98 8.05 8.07 7.45 7.48 7.85 8.90 Total 5.67 4.29 3.97 3.75 3.59 3.30 2.87 3.10 3.08 2.93 Average yield (kg/ha/yr) Intensive 2 781 4 193 3 810 4 776 5 921 6 631 5 663 5 497 4 993 5 509 Semi-intensive 583 639 736 466 344 370 359 463 301 511 Extensive 361 327 246 231 215 159 156 195 174 169 Total 1 314 1 830 2 151 2 540 3 137 3 597 3 463 3 296 3 112 3 325 48 National trends and analysis of mangroves

Number of shrimp farms 30 000 25 000 20 000 15 000 Intensive 10 000 Semi-intensive Extensive 5 000 TOTAL 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Farm area (ha) 80 000 70 000 60 000 50 000 40 000 Intensive 30 000 Semi-intensive 20 000 Extensive 10 000 TOTAL 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Shrimp production (ton) 300 000 250 000 200 000 150 000 Intensive 100 000 Semi-intensive Extensive 50 000 TOTAL 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Average farm size (ha/farm) 10.00 8.00 6.00 Intensive 4.00 Semi-intensive 2.00 Extensive TOTAL 0.00 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Average yield (kg/ha) 8 000 6 000 4 000 Intensive Semi-intensive 2 000 Extensive TOTAL 0 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Figure 3.2 Number of shrimp farms, farm area, production, farm size and yield in Thailand, 1989–98 Shrimp farming and mangrove loss in Thailand 49

Recently, the conversion of mangroves into shrimp farms has decreased. This could be explained by the exhaustion of suitable mangrove areas. Starting shrimp farms in mangrove areas requires a large amount of upfront investment for clearing the land. In addition, without adequate infrastructure, electricity and road access, it is often unprofitable to convert the mangroves for shrimp farming. There is evidence that shrimp yields in ponds in crowded mangrove areas tend to be low because of soil conditions. Mangrove soil usually contains sulfuric acid and a low pH. Once exposed to the air, it could easily be contaminated for shrimps. Mangrove mud is also soft, thus contributing to the high cost of pond construction and maintenance. Along the coastal areas of Thailand there are also numerous paddy fields and plantations. Such land has also tended to be converted into shrimp farms, leading to conflicts over coastal resource utilization. Rice paddies require fresh water, while shrimp farms require a higher level of water salinity. Given the high returns from shrimp farms, many coastal paddy fields have been converted irreversibly into shrimp farms. Many coastal plantations, such as, plantations of coconut, cashew nut, rubber and oil palms, have also been converted to shrimp farms. In addition, in some coastal zones, deserted mining areas and idle land have been converted into shrimp farms. As noted above, shrimp farming also imposes considerable externalities, or negative impacts, on the other coastal activities and populations. In coastal areas, lack of good management of effluent discharge has led to water quality degradation. Among shrimp farmers themselves, water discharged from one farm could affect other farms, as the source of water intake and water discharge can be the same. During an outbreak of infection, the disease could be rapidly spread through this common water supply. The higher salinity in coastal water supplies also leads to conflicts with other coastal agricultural activities, especially paddy farms and freshwater aquaculture in the area. The productivity of other agricultural activities could be worsened once the coastal areas have been converted into shrimp farms. For the Central Region, such negative impacts finally led to the prohibition of black tiger shrimp farms in freshwater areas. For those shrimp farming in the mangroves, the mangrove deforestation impairs other benefits derived from mangroves. Habitats for aquatic life deteriorate, thus leading to less fish abundance and lower income for the coastal fishermen. The loss of mangroves along the coastlines also affects negatively various ecological functions including, for example, spawning and nursery grounds for aquatic life, windbreaks, shoreline protection, a filter for water from, as well as to, the sea, and carbon sequestration. Important wood and wood products from the mangroves and collection of shellfish are also affected by mangrove deforestation, which can have important impacts on the livelihood of local communities. Figure 3.3 50 National trends and analysis of mangroves

Ethnic Culture

Community- based Local management community

Community Infrastructure development development

High shrimp Investment Influx of Conversion of price in shrimp migrants coastal areas farms into shrimp farms

Occupational Income from mobility shrimp farm

Mangrove values • Direct use values (wood, fisheries, animal captures, natural collections) • Indirect use values (nutrients, flood Degraded and flow control, water quality fishery maintenance, sediment retention, abundance shoreline stabilization, storm protection, shoreline navigation, habitats for flora and fauna, carbon sequestration, etc) • Option values (biodiversity, culture/heritage) • Non-use values (aesthetic values, biodiversity)

Figure 3.3 Shrimp farming and mangrove conversion Shrimp farming and mangrove loss in Thailand 51 summarizes the important linkages and trade-offs between coastal shrimp farming and mangrove conversion.

NOTES

1. In Thailand, the Indian Ocean is called the Andaman Sea. 2. As calculated from Statistics from Shrimp Culture (1998), Royal Fisheries Department, Thailand. 4. Analysis of shrimp farm expansion and mangrove conversion in Thailand, 1979–96 Edward B. Barbier and Mark Cox

INTRODUCTION As previous chapters have made claim, there are many reasons for the destruction of mangrove forests, including increasing population pressure, coastal development, mining, conversion to salt ponds and agriculture, and over- harvesting of the forests. The largest factor in recent years has been the expansion of aquaculture ponds into mangrove forests (see also Aksornkoae et al. 1986; Spalding et al. 1997; WRI 1996). Shrimp production has been the primary aquaculture activity and has been responsible for mangrove deforestation in many countries, but is especially evident in Thailand and other Asian countries (Kongkeo 1997). Mangrove swamps are considered very suitable for shrimp farming because the areas are flooded with brackish, stagnant water that is ideal for aquaculture (Hassanai 1993). The problem of mangrove conversion has been exacerbated in recent years given the growing importance of shrimp farming to the export earnings of tropical countries. For example, in Bangladesh, shrimp farming contributes 8 per cent of total export earnings (Raha and Alam 1997). In Thailand, the total value of export earnings for shrimp in the late 1990s was around US$1–2 billion annually (Jitsanguan et al. 1999; Tokrisna 1998; Vandergeest et al. 1999). This preference for short-term exploitative economic gains, rather than longer-term sustainable exploitation, has led to massive mangrove loss worldwide (see Chapter l). In many countries and regions, mangrove deforestation is contributing to fisheries decline, degradation of clean water supplies, salinization of coastal soils, erosion and land subsidence, as well as release of carbon dioxide into the atmosphere (Barbier and Strand 1998; Ruitenbeek 1994; Sathirathai and Barbier 2001; Spalding et al. 1997; WRI 1996). In Thailand, the welfare losses associated with the impacts of mangrove deforestation on coastal communities in Surat Thani Province were estimated to be around $27 264 to $35 921 per hectar (see Chapter 11; also Sathirathai and Barbier 2001).

52 Shrimp farm expansion and mangrove conversion 53

Although the loss of mangroves and the resulting environmental effects are well publicized, there have been few studies of the economic causes of mangrove deforestation. The present chapter is concerned with such an analysis for Thailand. As mangrove deforestation has many parallels with that of tropical deforestation, approaches applied in case studies of tropical forest conversion in Thailand are relevant (Cropper et al. 1999; Panayotou and Sungsuwan 1994). Here we assume that the clearing of mangroves by shrimp farmers is the major cause of mangrove loss. A model of this coastal land use conversion decision is therefore developed, which leads to a reduced-form relationship for the aggregate equilibrium level of cleared mangrove land for all shrimp farmers. The relationship is tested through a pooled cross-sectional and time series analysis of mangrove deforestation and shrimp area expansion in 21 of Thailand’s coastal provinces over 1979–96. This allows us to investigate the role of the profitability of shrimp farming, the pressures of population change and in-migration as well as the role of overall economic development and ‘accessibility’ of coastal areas in determining mangrove loss through conversion to shrimp farms over this period in Thailand. The structure of the chapter is as follows. The next section provides a brief background to the problem of mangrove deforestation and shrimp aquaculture expansion in Thailand’s coastal provinces. The third section develops the formal model of the mangrove clearing decisions of shrimp farmers under open access conditions. The fourth section presents the panel analysis estimation of the reduced-form relationship for mangrove conversion, while the fifth section discusses the results. A final section provides an overall conclusion.

BACKGROUND

The issue of coastal land conversion for commercial shrimp farming is a highly debated and controversial topic in Thailand. Frozen shrimps are a major export product of Thailand, earning more than $1.6 billion each year, and the government has been keen to expand these exports (Tokrisna 1998), yet expansion of shrimp exports has caused much devastation to Thailand’s coastline and had knock-on effects in other valuable commercial sectors, such as fisheries. Thailand’s coastline is vast, stretching for 2815 kilometers (km), of which 1878 km is on the Gulf of Thailand and 937 km on the Andaman Sea (Indian Ocean) (Kaosa-ard and Pednekar 1998). In recent years, the expansion of intensive shrimp farming in the coastal areas of southern Thailand has led to rapid conversion of mangroves (CORIN 1995). Over 1975–93, the area of mangroves was virtually halved, from 312 700 ha to 168 683 ha. Although the rate of mangrove deforestation has slowed, in the mid-1990s the annual loss was estimated to be around 3000 ha/year (Sathirathai 1998). 54 National trends and analysis of mangroves

Although mangrove conversion for aquaculture began in Thailand as early as 1974, the boom in intensive shrimp farming through mangrove clearing began in 1985, when the increasing demand for shrimps in Japan pushed up the border-equivalent price to $100 per kilogram (kg) (Bantoon 1994). For example, over the 1981–85 period in Thailand, annual shrimp production through aquaculture was around 15 000 metric tonnes (KMT), but by 1991 it had risen to over 162 KMT and by 1994 to over 264 KMT (Kaosa-ard and Pednekar 1998). Shrimp farm area expanded from 31 906 ha to 66 027 ha between 1983 and 1996. A more startling figure is the increase in the number of farms during that period, from 3779 to 21 917. In general, this reflects a rapid shift from more extensive to more small-scale, intensive and highly productive aquaculture systems of on average two or three ponds with each pond comprising up to one hectare (ha) in size (see Chapter 3; also Goss et al. 2001; Kongkeo 1997; Tokrisna 1998). However, much of the semi-intensive and intensive shrimp farming in Thailand is short-term and ‘unsustainable’: water quality and disease problems mean that yields decline rapidly and farms are routinely abandoned after five or six years of production (Dierberg and Kiattisimkul 1996; Flaherty and Karnjanakesorn 1995; Thongrak et al. 1997; Tokrisna 1998; Vandergeest et al. 1999). Shrimp farm expansion has slowed in recent years, but unsustainable production methods and lack of know-how have meant that more expansion still takes place every year simply to replace unproductive and abandoned farms. Estimates of the amount of mangrove conversion due to shrimp farming vary, but recent studies suggest that up to 50–65 per cent of Thailand’s mangroves have been lost to shrimp farm conversion since 1975 (Dierberg and Kiattisimkul 1996; Tokrisna 1998). In provinces close to Bangkok, such as Chanthaburi, mangrove areas have been devastated by shrimp farm developments (Raine 1994). More recently, Thailand’s shrimp output has been maintained by the expansion of shrimp farming activities to the far southern and eastern parts of the Gulf of Thailand, and across to the Andaman Sea (Indian Ocean) coast (Flaherty and Karnjanakesorn 1995; Sathirathai 1998; Vandergeest et al. 1999). Shrimp farming does not necessarily have to pose any environmental threat, provided that wastewater from the farm has been treated before being released. In addition, it is possible to design shrimp aquaculture systems in coastal areas that do not involve removal of vegetation and areas naturally fed by tidal conditions. However, the establishment of these farm systems is too expensive for the type of small-scale pond operations found in much of Thailand, which are dependent on highly intensive and untreated systems through rapid conversion of mangrove and coastal resources (Thongrak et al. 1997; Tokrisna 1998). Much of the financial investment in coastal shrimp farms is from wealthy individual investors and business enterprises from Shrimp farm expansion and mangrove conversion 55 outside the local community (Flaherty and Karnjanakesorn 1995; Goss et al. 2000, 2001). Although some hiring of local labor occurs, in the past shrimp farm owners have tended to hire Burmese workers as their wage rates are much lower. Ill-defined property rights have exacerbated the rapid conversion of mangroves to shrimp farms. Although the state, through the Royal Forestry Department, ostensibly owns and controls mangrove areas, in practice they are de facto open access areas onto which anyone can encroach. Mangrove deforestation in southern Thailand has also been affected by the increase in tourist infrastructure, agricultural expansion and urban developments in coastal areas (Dierberg and Kiattisimkul 1996; Tokrisna 1998). Until recently, government policy considered mangroves as areas of wasteland that could be freely reclaimed for development and highly profitable economic activities (Sathirathai 1998). There has also been considerable debate over the recently imposed ban on shrimp farming in rice and fruit-growing areas. In the one or two years before the ban was imposed, shrimp farmers had been shifting from converted mangrove areas on the coast to rice paddy and fruit plantations in the Central Region of Thailand. The exodus from coastal to inland rice and fruit-growing areas took place because of a major outbreak of shrimp disease along the coastal areas, which was put down to poor water quality induced by shrimp farming itself. Because current shrimp farm practices are very unsustainable and as a result of a high incidence of conflicts between rice farmers and shrimp farmers, the government has decided to ban the use of rice and fruit-growing areas for shrimp farming. With this ban, there is a distinct possibility that shrimp farmers may shift back to coastal areas, although now the target might include the remaining pristine mangrove on the Andaman (Indian Ocean) coast.

A MODEL OF MANGROVE CONVERSION FOR SHRIMP FARMING

If shrimp farm expansion is a major cause of mangrove deforestation, the resulting mangrove loss in any period, rt, is directly related to the amount of land area converted by shrimp farms:

Mt–1 – Mt = rt = Nt – Nt–1, (4.1) where M represents mangrove area, and N is the amount of land cleared and used for shrimp farming. Equation (4.1) states that the land available for shrimp farming in the current period, Nt, equals the amount of productive land 56 National trends and analysis of mangroves left over from a previous period, Nt–1, plus any newly cleared land, rt. Equally, the decline in mangroves between the current and previous periods Mt–1 – Mt, equals the amount of land newly converted for shrimp farming, rt. Equation (4.1) implies a direct link between mangrove deforestation and land conversion for shrimp farm area expansion, with the latter activity determined by the commercial profitability of aquaculture operations. As noted in the previous section, mangrove areas in Thailand are largely open access resources freely available to shrimp farmers who can gain access to these areas and claim them. By modeling the land clearing decisions of commercial shrimp farmers under such open access conditions, it is possible to determine the key economic factors influencing mangrove conversion for aquaculture expansion. In any time period, t, let the profit function of a representative shrimp farm be the profits gained by choosing a profit-maximizing level of inputs:

max p(p, w, wN) = Max pf (xj, Nj) – wxj – wNNj, (4.2) Nj , xj where the variable inputs include the amount of mangrove area cleared by the th j farm, Nj, and a vector, xj, of other i,... ,k inputs (for example, labor and feed/fertilizer) used in production of shrimp. The corresponding vector of input prices is w, and p is the price of shrimp. Finally, wN is the rental ‘price’ of land. If shrimp farmers clear their own land of mangroves, this is an ‘implicit’ price, or opportunity cost (Panayotou and Sungsuwan 1994). However, if the farm purchases or rents additional cleared land from a market, wN would be the market rental price of cleared mangrove land (Cropper et al. 1999). Utilizing Hotelling’s lemma, the derived demand for cleared land by the jth shrimp farm, Nj, is therefore ∂ ∂ ∂ p Nj Nj N = N (p, w, w ) = – ––, –– < 0, –– > 0. (4.3) j j N ∂ ∂ ∂ wN wN p

As (4.3) is homogeneous of degree zero, it can also be rewritten as a function of relative prices, using one of the input prices, wi, as a numeraire:   ∂ ∂ pw wN Nj Nj N = N  —, —,–– , –––– < 0, ––– > 0. (4.4) j j  ∂ ∂ wi wi wi (wN/wi) (p/wi)

Equations (4.3) and (4.4) depict the derived demand for cleared mangrove area by the representative jth farm. Either of these relationships could be aggregated Shrimp farm expansion and mangrove conversion 57 into the total demand for converted mangrove by all J shrimp farms. To simplify the following analysis, we will work with the derived demand relationship (4.3). In aggregating the demand for cleared land across all J shrimp farms in a province or coastal zone, it is important to consider other factors that may influence the aggregate level of conversion, such as income per capita, population, land area and the aggregate number of farms. Thus, allowing Z to represent one or more of these exogenous factors and N the aggregate demand for cleared mangrove area in a province or coastal zone, the latter can be specified as

N = N(p, w, wN; Z). (4.5) As shrimp farms generally provide their own ‘supply’ of cleared mangrove land, N, one can view this type of ‘own’ supply as a kind of ‘production’ of cleared land, which is governed by the following conditions. The source of the ‘cleared land’ (that is, a mangrove swamp) is an open access resource, so that land is cleared up to the point where any producer surpluses (rents) generated by clearing additional land are zero. The principal input into clearing land is labor, L, which is paid some exogenously determined wage rate, wL, and the production function is assumed to be homogeneous. This ‘production’ of cleared land may also be affected by a range of exogenous factors, a, that may influence the ‘accessibility’ of pristine mangrove areas available for conversion, including, roads, infrastructure and closeness to major cities and towns. Thus one can specify a cost function, based on the minimum cost for the shrimp farm of producing a given level of cleared mangrove area, N, for some fixed levels of wL and a, as:

Cj = Cj(wL, N; a). (4.6)

Under open access conditions, each shrimp farm will convert mangrove area up to the point where the total revenues gained from converting Nj units of land, wNNj, equal the total costs represented by (4.6). If a shrimp farm clears its own mangrove area, then wN is now the household’s implicit ‘rental’ price, or opportunity cost, of utilizing additional converted land. However, as the shrimp farm is essentially supplying land to itself, in equilibrium the implicit price ensures that the farm’s costs of supplying its own land will be equated with its derived demand for converted mangrove area. Then for the jth representative household the following cost conditions for supplying its own cleared land must hold:

∂ ∂ ∂ cj cj cj w = c (w , N ; a) –– > 0, –– > 0, –– < 0, j = 1, . . . , J. (4.7) N j L j ∂ ∂ ∂ wL Nj a 58 National trends and analysis of mangroves

The right-hand side of (4.7) is the average cost curve for clearing land, which may be increasing with the amount of land cleared as, among other reasons, one must venture further into the mangrove swamp to clear more land (Angelsen 1999). That is, in equilibrium, the shrimp farm’s implicit price for cleared land will be equated with its per unit costs of mangrove conversion. Together with the farm’s derived demand for converted land (4.3), equation (4.7) determines the equilibrium level of mangrove clearing by the shrimp farm as well as its implicit price. Although the latter variable is not observed, it is possible to use (4.3) and (4.7) to solve for the reduced-form equation for the equilibrium level of cleared mangrove area. Substituting (4.7) for wN in equation (4.3), and then rearranging to solve for Nj yields

Nj = Nj(p, w, wN [wL, a]), ∂ ∂ ∂ ∂ ∂ dNj Nj Nj wN dNj Nj wN –– = –– + –– ––, –– = –– –– > 0. (4.8) ∂ ∂ ∂ ∂ ∂ dwL wL wN wL da wN a Note that the overall impact of a change in the wage rate on mangrove clearing by a shrimp farmer is ambiguous, owing to two possible counteracting effects. Given equation (4.7), we would expect that a higher wage would make it more costly for the farmer to clear mangrove area, thus reducing the equilibrium amount of land converted; that is,  ∂ ∂  Nj wN  –– –– < 0  ∂ ∂  wN wL However, as labor is also used in shrimp production, equation (4.3) indicates that the wage rate is included in the vector of input prices, w, that influence the demand for cleared land. If land and labor are substitutes in shrimp farm production, we would also expect a rise in the wage rate to increase the use of converted mangrove land in aquaculture; that is, ∂  Nj  –– > 0 . ∂  wL Thus whether the equilibrium level of cleared land will increase or decrease in response to a rise in the wage rate will depend on the relative magnitude of these two effects. Aggregating (4.8) across all J shrimp farms in a province or coastal zone that convert their own land from mangrove areas, and including exogenous factors Z, leads to a reduced-form relationship for the aggregate equilibrium level of cleared mangrove land: Shrimp farm expansion and mangrove conversion 59

* dN dN N = N(p, w1, wL; a, Z), –– > 0, –– > 0, (4.9) dp da where the wage rate, wL, is now distinguished from the vector of prices for inputs other than labor, w1. The amount of mangrove land converted should increase with the price of shrimp and accessibility of the mangrove forest. However, as in the case of (4.8), the impact of a change in the wage rate or other input prices is ambiguous. Returning to (4.1), for a relatively long time period [t, t–1], it is possible to establish a direct link between mangrove loss, shrimp farm expansion and the equilibrium land-clearing relationship (4.9). In equation (4.1), let Mt–1 represent the amount of mangrove area available in a previous period before much shrimp farming has occurred. Thus compared to the current period, t, in the previous period, t–1, mangrove area will be relatively abundant, and very little of it will have been cleared for shrimp farming:

Nt–1 –– ≈ 0. Mt–1

Thus, dividing equation (4.1) by Mt–1, we obtain:

Mt–1 – Mt Nt – Nt–1 Nt –––– = –––– = –– . (4.10) Mt–1 Mt–1 Mt–1 The left-hand side of (4.10) is a measure of the long-run proportionate change in mangrove area. It therefore represents a long-run indicator of mangrove loss. The right-hand side of (4.10) is the ratio of current shrimp farm area to mangrove area in a previous base period. It therefore represents a long-run indicator of relative shrimp farm area expansion. Equation (4.9) defines an * equilibrium reduced-form relationship between current shrimp farm area, Nt , and the output and input prices for shrimp farming, the accessibility of mangrove areas and other economic and demographic factors. Thus it follows that our long-run indicator of relative shrimp farm area expansion, Nt /Mt–1, will also be determined by equation (4.9). As equation (4.10) suggests that our long-run indicators of mangrove loss and shrimp farm expansion are equivalent, our measure of long-run mangrove loss, Mt–1 – Mt /Mt–1, is also determined by (4.9). Thus both indicators of mangrove loss and shrimp farm expansion can be estimated, using appropriate data for the shrimp output price, p, the wage rate, wL, other input prices, wI, the ‘accessibility’ of mangrove areas, a, and other economic and demographic factors that may affect the mangrove clearing decision, Z. 60 National trends and analysis of mangroves

EMPIRICAL ESTIMATION AND RESULTS

Table 4.1 lists the variables that were used in the panel analysis estimation across the coastal provinces of Thailand and over the period 1979–1996. Although data were collected for all 22 coastal provinces of Thailand for this period, only 21 coastal provinces were used in the analysis. As no mangrove area data were recorded by the Royal Forestry Department for the coastal province of Narathiwat, we excluded this province from the analysis. To use either our mangrove loss or shrimp farm expansion indicators as a dependent variable requires first choosing an appropriate base year for mangrove area, Mt–1. We chose 1979 as the base year for two reasons. First, both economic and mangrove data in Thailand prior to that date were not complete for all coastal provinces and, second, even though shrimp farming

Table 4.1 Definitions of variables and sources of data for the panel analysis of mangrove clearing and shrimp farm area expansion, 1979–96

Variable Definition

MBASE Proportion of mangrove area cleared in current year relative to mangrove area in the base year (1979) [(M1979 –Mt)/M1979] (provincial level, km2)a STMBASE Proportion of shrimp farm area in the current year relative to mangrove area in the base year (1979) [St/M1979] (provincial level, km2)b PRICE Average farmgate price of shrimp (provincial level, Thai baht/kg, constant 1990 values)b MINWAGE Minimum wage (provincial level, baht/day, constant 1990 values)c AMPB Ammonium phosphate price (national level, baht/kg, constant 1990 values)d DISTANCE Average distance of a province from Bangkok (provincial level, km)e POPG Annual change in population (provincial level, numbers)e NFARML Number of registered shrimp farms per total land area (provincial level, farms/km2) b GPP Gross provincial product per capita (baht per person, constant 1990 values)f

Sources: aRoyal Forestry Department; bDepartment of Fisheries; cDepartment of Labor Protection and Welfare; dOffice of Agricultural Economics, eDepartment of Local Administration and Department of Highways; fOffice of National Economics and Social Development Board. Shrimp farm expansion and mangrove conversion 61 began prior to 1979, the major period of shrimp farm establishment and expansion in Thailand occurred over 1979 to 1996. Thus our dependent variable for mangrove loss is the proportion of mangrove area cleared relative to the 1979 area of mangroves (MBASE in Table 4.1), and our dependent variable for relative shrimp farm expansion is the proportion of shrimp farm area in the current year relative to 1979 mangrove area (STMBASE). According to equations (4.9) and (4.10), the explanatory variables in our regression should include the price of shrimp (p), the input prices (wI and wL), other economic and demographic factors (Z) and factors that affect the accessibility of mangrove areas (a). As indicated in Table 4.1, output price, p, was represented by the provincial price of shrimp in Thai baht/ton (PRICE).1 The two input prices chosen for wL and wI, respectively, were the minimum provincial wage (MINWAGE) and the price of ammonium phosphate (AMPB). The latter is a proxy for the price of feed used in shrimp aquaculture, with which it is highly correlated (Thongrak et al. 1997). As equation (4.4) 3 indicated, the output and input prices could be expressed either as absolute values or in terms of relative prices with respect to one of the input prices. We found that the estimations performed better where shrimp price and the feed price proxy were expressed as relative prices to the minimum wage (that is, PRICE/MINWAGE and AMPB/MINWAGE). The distance of each province from Bangkok (DISTANCE) is included as our measure of the ‘accessibility’ of provincial mangrove resources. Finally, several exogenous factors, Z, were chosen to represent both economic effects and demographic changes at the provincial level that might influence mangrove conversion: gross provincial product (GPP) per capita, population growth (POPG), and the number of shrimp farms per total provincial land area (NFARML).2 The general approach advocated for panel analysis was followed in estimating equation (4.10), involving a comparison of pooled ordinary least squares (OLS) and one-way and two-way fixed and random effects models (Baltagi 1995; Greene 1997). Log-log and semi-log forms of the regression were also tested but the linear form performed best. Inclusion of the DISTANCE variable in the models meant that any fixed effects regression would be collinear. We tested the models with and without the DISTANCE variable, and in all cases the one-way random effects models including the DISTANCE variable performed best. We also tested for the possible endogeneity of the NFARML variable in the regressions of MBASE and STMBASE through applying the modified Hausman simultaneity test to the panel analysis.3 The null hypothesis that NFRAML is an exogenous variable could be rejected for the MBASE regression but not for the STMBASE estimation. However, the standard instrumental variable (IV) technique could not be employed to correct for the endogeneity of NFARML in the STMBASE estimation. The IV technique in panel analysis requires using a two-stage fixed 62 National trends and analysis of mangroves effects procedure (Baltagi 1995; Greene 1997) but, unfortunately, fixed effects is incompatible with our preferred regression that includes the DISTANCE variable.4 As an alternative, we therefore report two versions of our panel analysis of STMBASE, one with the NFARML variable and one without.5 The preferred panel analysis estimations of mangrove clearing (MBASE), and shrimp farm expansion (STMBASE) with and without the shrimp farm density variable, are presented in Table 4.2, along with the relevant test statistics.6 These statistics show that the one-way random effects model is preferred over the OLS panel analysis model.7 The results reported for mangrove loss in Table 4.2 show that all variables have the predicted signs. In addition, the only explanatory variable that has no significant impact on long-run mangrove loss in Thailand is shrimp farm

Table 4.2 Thailand: one-way random effects estimation of mangrove loss and shrimp farm area expansion, by province, 1979–96

MBASE STMBASE STMBASE (with (without NFARML) NFARML)

PRICE/MINWAGE 4.081 × 10–2 1.795 × 10–1 2.089 × 10–1 (5.524)** (4.941)** (3.769)** AMPB/MINWAGE –2.620 × 10–3 –8.102 × 10–3 –9.031 × 10–3 (–6.982) (–7.244)** (–5.313)** DISTANCE –5.013 × 10–4 –1.331 × 10–3 –1.681 × 10–3 (–3.314)** (–2.033)* (–2.316)* POPG 5.808 × 10–7 5.915 × 10–6 6.548 × 10–6 (1.769)† (2.431)* (1.741)† GPP 8.466 × 10–7 –2.875 × 10–6 –1.546 × 10–6 (2.428)* (–2.587)** (–0.919) NFARML 1.071 × 10–3 2.380 × 10–2 (0.945) (5.086)** CONSTANT 0.773 1.536 1.780 (7.882)** (3.715)** (3.733)** Number of observations 294 315 315 Re-estimated R2 0.345 0.501 0.340 F-test 25.22** 51.43** 31.83** Breusch–Pagan (LM) Test 356.64** 1765.35** 1743.87** ≡ ≡ Notes: MBASE % mangrove area cleared relative to 1979 (M1979–Mt)/M1979; STMBASE % shrimp farm area relative to 1979 mangrove area, St/M1979. †significant at 10% level or less; *significant at 5% level or less; **significant at 1% level or less; t-ratios are indicated in parentheses. Shrimp farm expansion and mangrove conversion 63 density (NFARML). The relative price of shrimp (PRICE/MINWAGE) has a significant and positive effect on mangrove deforestation across the coastal provinces of Thailand, whereas mangrove loss declines for those coastal provinces that are further from Bangkok (DISTANCE). A rise in the relative feed price (AMPB/MINWAGE) has a significant and negative impact on long- run mangrove loss. Provincial economic development (represented by GPP) causes mangrove deforestation, as does population growth (POPG), although the latter variable is significant only at the 10 per cent level. The two regressions for relative shrimp farm area expansion in Thailand vary little with respect to the sign and significance of the coefficients of three main variables: relative shrimp price (PRICE/MINWAGE), relative feed price (AMPB/MINWAGE) and the accessibility of mangrove areas (DISTANCE). All three variables are significant and have the predicted signs (see Table 4.2). Shrimp farm area expansion increases with the relative price of shrimp, but declines with the relative feed price and for those coastal provinces further from Bangkok. Population growth is significant in explaining relative shrimp farm expansion in both regressions, but only at the 10 per cent level in the estimation that excludes shrimp farm density (NFARML). Provincial economic development has a significant and negative impact on shrimp farm expansion in the regression that includes NFARML, but is insignificant in the estimation without NFARML. Finally, NFARML appears to be a significant factor in shrimp farm expansion, but, as discussed above, this variable is likely to be endogenous in the regression.

DISCUSSION

The panel analysis regressions of mangrove loss and relative shrimp farm area expansion reported in Table 4.2 are consistent with the theoretical model of mangrove conversion for shrimp farming developed in the third section, above, and with each other. Further insights into the causes of mangrove loss and shrimp farm expansion can be gained from the estimated elasticities, which are indicated in Table 4.3. The variables with the largest impacts on mangrove loss (MBASE) are distance from Bangkok and the price of ammonium phosphate (AMPB), followed by the minimum wage (MINWAGE), shrimp price (PRICE), gross provincial product per capita (GPP) and population growth (POPG). In both regressions of relative shrimp farm area expansion (STMBASE), the variables with the largest effects are again distance from Bangkok and ammonium phosphate price, followed by the minimum wage and shrimp price.8 In the estimation that includes shrimp farm density, the remaining impacts are attributed to GPP, shrimp farm density and population growth. In the estimation that 64 National trends and analysis of mangroves

Table 4.3 Thailand – estimated elasticities for mangrove loss and shrimp farm area expansion, by province, 1979–96a

Explanatory Mangrove Shrimp farm Shrimp farm variables loss area expansion area expansion (MBASE) (STMBASE) (STMBASE) with without NFARML NFARML

PRICE/MINWAGE 0.158** 0.402** 0.468** PRICE 0.156** 0.397** 0.462** MINWAGEb 0.302** 0.421** 0.450** AMPB/MINWAGE –0.460** –0.824** –0.918** AMPB –0.445** –0.796** –0.887** DISTANCE –0.626** –0.963* –1.216* POPG 0.014† 0.080* 0.089† GPP 0.097* –0.190** –0.103 NFARML 0.014 0.185** —

Notes: a Calculated using all 378 non-missing observations; bpositive elasticity as the coefficient for AMPB is greater in absolute terms than the coefficient for PRICEWAG in all regressions; †significant at 10% level or less; *significant at 5% level or less; **significant at 1% level or less. excludes shrimp farm density, only population growth has a modest, but barely significant, impact on shrimp farm expansion. As expected, the effects of changes in the explanatory variables on relative shrimp farm expansion are always greater than on mangrove loss.9 Overall, these results reaffirm the hypothesis that the profitability of shrimp farming is a very important underlying cause of mangrove deforestation in Thailand. Intensive shrimp farming utilizes considerable amounts of feed, the costs of which represent anywhere from 30 to 60 per cent of the total costs of shrimp aquaculture in various systems across Thailand (Kongkeo 1997; Thongkrak et al. 1997; Tokrisna 1998). Thus it is not surprising that a change in the price of ammonium phosphate – our proxy for feed price – causes a relatively large impact on shrimp farm expansion and mangrove clearing. As indicated in Table 4.3, if ammonium phosphate and thus feed prices across Thailand were to rise by 10 per cent, the relative decline in shrimp farm area would be 8–9 per cent and mangrove clearing would decrease by around 4.5 per cent. Our results indicate that shrimp farm area expansion and mangrove loss are also responsive to changes in the price of shrimp. As discussed in the second section of the chapter, expansion of shrimp farming in Thailand has occurred rapidly since 1985, which was when a rapid rise in world demand and prices for shrimp occurred. The elasticity estimates suggest that, if the Shrimp farm expansion and mangrove conversion 65 price of shrimp were to rise by 10 per cent, relative shrimp farm area would increase by 4–5 per cent and mangrove deforestation would expand by 1.6 per cent. The analysis also confirms that the ‘accessibility’ of mangrove areas is an important determinant of mangrove clearing for shrimp farming in Thailand. This is an expected result, given that Bangkok is the major domestic market as well as the key port and terminus for both Thailand’s export market and many regional domestic markets. In addition, many investors in shrimp farming operations are from outside the coastal provinces, and in particular from Bangkok. The elasticity estimates suggest that coastal areas that are 10 per cent further from Bangkok have 10–12 per cent less relative shrimp farm area and have 6.3 per cent lower mangrove clearing rates. Distance from Bangkok appears to be an important factor determining the accessibility of coastal resources, the profitability of shrimp farming and therefore mangrove conversion. The historical pattern of mangrove loss in Thailand is consistent with this result. Mangrove deforestation began initially in the coastal provinces near Bangkok, spread down the southern Gulf of Thailand coast towards Malaysia and is now beginning on the Andaman Sea (Indian Ocean) coast (Flaherty and Karnjanakesorn 1995; Raine 1994; Sathirathai 1998). Table 4.3 indicates that the provincial minimum wage variable has a positive elasticity in the panel regressions. A 10 per cent rise in the rural minimum wage causes relative shrimp farm area to increase by over 4 per cent and mangrove clearing by 3 per cent.10 As discussed in the third section, our theoretical model would suggest that the amount of mangrove land converted should decrease with the cost of labor, which is the principal input involved in clearing operations, but this effect may be counteracted by an opposite impact of a rise in the wage rate on mangrove conversion, if land and labor are substitutes in shrimp farming. Our elasticity results suggest that this latter substitution effect might be the stronger influence. As the costs of labor use in production rise, shrimp farmers may be induced to move from more intensive aquaculture operations that employ relatively more labor than land to more semi-intensive and extensive systems that require relatively more land. For example, in Thailand extensive shrimp farms (5–7 ha) have average labor costs of only $13.5/ha, semi-intensive farms (3–4 ha) have labor costs of $239/ha and intensive farms (2–3 ha) have labor costs of $922/ha (Tokrisna 1998). Thus a rise in wages may lead some shrimp farmers to expand shrimp farm area and switch to less intensive operations in order to save on overall labor costs (Goss et al. 2001). Shrimp farm expansion and mangrove loss may also be influenced somewhat by demographic pressures, such as provincial population change, although the significance of this impact is weak in two of the three regressions (see Tables 4.2 and 4.3). A 10 per cent rise in population growth will cause 66 National trends and analysis of mangroves shrimp farm area to expand by 0.8–0.9 per cent, and mangrove clearing also increases by 0.1 per cent. A 10 per cent rise in gross provincial product per capita increases mangrove loss by about 1 per cent but the impact of GPP on relative shrimp farm area is less clear, given the problem of the endogeneity of shrimp farm density in the regressions of STMBASE (see Tables 4.2 and 4.3). As noted above, mangrove loss is increasingly occurring in coastal areas owing to provincial economic development activities other than shrimp farming, such as urbanization, agriculture, tourism and industrialization (Dierberg and Kiattisimkul 1996; Tokrisna 1998).11 Such coastal economic developments are likely to lead to increases in gross provincial product per capita while at the same time putting greater pressure on remaining mangrove areas.

CONCLUSION

Mangroves are widely recognized as one of the most highly threatened global ecosystems, with the principal cause being conversion to shrimp aquaculture (Spalding et al. 1997; WRI 1996). Despite this serious worldwide problem, to our knowledge, this chapter represents the first attempt at an economic analysis of the factors influencing shrimp farm expansion and mangrove conversion. Our choice of Thailand is also appropriate, given that, since 1975, the area of mangroves in Thailand has virtually halved and the majority of this conversion is attributable to shrimp farming (Dierberg and Kiattisimkul 1996; Sathirathai 1998; Tokrisna 1998). Previous studies of tropical deforestation in Thailand have shown that the factors determining agricultural expansion are the major underlying causes of forest conversion (Cropper et al. 1999; Panayotou and Sungsuwan 1994). Evidence presented in this chapter indicates that this is also the case for the production of shrimp and mangrove loss in Thailand. We have therefore modeled the way this coastal land use conversion decision is determined by the profit-maximizing decisions of a representative commercial shrimp farmer, which in turn allowed us to develop a reduced-form relationship for the aggregate equilibrium level of cleared mangrove land for all shrimp farmers. Our theoretical model suggests that this relationship will be a function of the shrimp output price, p, the wage rate, wL, other input prices, wI, the ‘accessibility’ of mangrove areas, a, and exogenous economic and demographic factors that may affect the mangrove clearing decision, Z. Moreover, since land clearing by shrimp farmers leads to mangrove deforestation, we have derived from our model either a long-run indicator of mangrove loss or relative shrimp farm area expansion that could be empirically estimated, using appropriate data for the above variables. Shrimp farm expansion and mangrove conversion 67

Both relationships were tested through a panel analysis of mangrove deforestation and shrimp area expansion in 21 of Thailand’s coastal provinces over the period 1979–96. This enabled us to investigate the role of the profitability of shrimp farming, the accessibility of mangrove areas, the pressures of population growth and the role of economic growth in determining both mangrove loss and shrimp farm expansion over this period in Thailand. The regression results provide strong empirical evidence that the output and input prices associated with shrimp farming are significant determinants of mangrove loss. In particular, the shrimp price and ammonium phosphate (that is, feed) price play a very important role in the development of shrimp farming and therefore mangrove loss, as our theoretical model would suggest. We also obtained the result that an increase in the minimum wage rate increases shrimp farm expansion and mangrove conversion, indicating that land and labor may be substitutes in aquaculture production. There is evidence in Thailand that a rise in wages may lead some shrimp farmers to expand shrimp farm area and switch to less intensive operations in order to save on overall labor costs (Tokrisna 1998; Goss et al. 2001). Given that increasing global demand for shrimp will continue to ensure the profitability of shrimp aquaculture for some time, our results suggest that these economic incentives for shrimp farm expansion will continue to put pressure on the remaining mangroves in Thailand and other tropical regions. The accessibility of mangrove areas, that is, how far coastal provinces are from Bangkok, also has an important influence on mangrove deforestation. This result may have captured the historical pattern of coastal economic development in Thailand: shrimp farm expansion and accompanying mangrove deforestation began initially in the coastal provinces near Bangkok, spread down the southern Gulf of Thailand coast towards Malaysia and is now beginning on the Andaman Sea (Indian Ocean) coast (Flaherty and Karnjanakesorn 1995; Raine 1994; Sathirathai 1998; Vandergeest et al. 1999). This geographical ‘spread’ of coastal development and mangrove clearing for shrimp farming is not unique to Thailand. We would expect to see similar patterns of shrimp farm expansion and mangrove deforestation in other tropical countries where large-scale mangrove destruction is taking place. We also found evidence that coastal economic activities other than shrimp farming, such as agriculture, tourism, industrialization and urbanization, are contributing to mangrove conversion. This coastal development effect may have been captured by the positive impact of gross provincial product per capita on mangrove loss in our analysis. In addition, population growth in the coastal provinces of Thailand may be contributing to mangrove deforestation. Although we believe that our analysis has captured many of the important trends in and causes of shrimp farm expansion and mangrove loss in Thailand over the period 1979–96, several recent developments could greatly influence 68 National trends and analysis of mangroves the impacts of shrimp farming on mangrove conversion. First, the availability of new mangrove areas suitable for conversion to shrimp farming is becoming increasingly scarce. Of the 62 800 ha of mangrove areas considered suitable for shrimp farms in 1977, between 38 per cent and 65 per cent were already converted by shrimp farms between 1975 and 1993 (Dierberg and Kiattisimkul 1996). Thus expansion of shrimp farms is increasingly occurring on coastal land formerly used for rubber and palm plantations and, until the recent ban, in rice paddy areas. Second, it is still too early to gauge the effect of the ban on shrimp farming in the rice and fruit-growing areas in the Central Region of Thailand. One result is likely to be greater conversion of remaining areas of coastal mangrove forests, especially the remaining pristine mangrove on the Andaman (Indian Ocean) coast. On the other hand, to prevent this from happening, recent policy initiatives have been proposed to promote the conservation of mangroves and the participation of local communities in their management (Sathirathai 1998). For example, the Royal Forestry Department is considering banning mangrove forest concessions and regulating the use of mangrove areas, particularly those affected by shrimp farming. Furthermore, new legislation on community management of forests has been introduced, which offers the hope that the right of local communities to protect mangrove forests may receive legal recognition. The motivation for this potential change in policy arises from the recognition that the economic benefits of mangroves to local communities may be substantial, and could possibly even outweigh the returns to intensive shrimp farming that lead to mangrove conversion. However, it remains to be seen whether Thailand will become a model of sound management of coastal mangrove development and protection for other tropical countries to emulate, or continue to be an example of the way uncontrolled shrimp farm expansion can lead to extensive destruction of mangrove resources.

NOTES

1. In the regressions of this chapter, all price variables as well as gross provincial product per capita (GPP) are expressed in local currency (Thai baht) and in real terms (1990 values), using the GDP deflator for Thailand. 2. The exchange rate and real interest rate were also included as additional exogenous variables in the analysis. However, these variables are not represented at the provincial level. Neither variable was significant, and their inclusion distorted the original regression results. Both variables were therefore dropped from the final regressions. Population growth was used instead of population density as the latter was highly correlated with GPP and shrimp farm density (NFARML). 3. The Hausman simultaneity test involves a two-step procedure (Nakamura and Nakamura 1981). In the first step, NFARML was regressed on the remaining exogenous variables to obtain the estimated residuals and the predicted values of NFRAML. In the second step, the two dependent variables, MBASE and STMBASE, were regressed respectively on the Shrimp farm expansion and mangrove conversion 69

predicted values of NFARML and the estimated residuals obtained in step one. If for each regression the estimated coefficient for the residuals is statistically significant, there is a simultaneity problem between the respective dependent variable and NFARML. 4. We did employ the instrumental variable fixed effects method to correct for the endogeneity of NFARML, excluding the DISTANCE variable from the analysis. This regression performed poorly, with none of the coefficients being statistically significant in the instru- mented regression. 5. One possible reason why shrimp farm density may be endogenous in the regression of relative shrimp farm area expansion is that our variable, NFARML, is the total number of registered shrimp farms per total provincial land area. In Thailand, once a shrimp farm is established and registered, it will remain officially registered as a shrimp farm even long after it is abandoned, provided that it is not converted and registered to some other land use. The latter happens rarely, given the toxic and unproductive state of the abandoned shrimp farm land. Thus total registered shrimp farms are likely to include both productive and abandoned shrimp farms. 6. Significant autocorrelation was detected in the panel analysis estimation of mangrove loss. Thus the regression was re-estimated using an autocorrelated error structure following standard Cochrane–Orcutt transformation procedures for panel analysis (Greene 1997). As a result of the transformation, which leads to a reduction in the total number of observations, the significance of the regressions and of the estimated coefficients of individual variables were affected, but only slightly. Thus the one-way random effects estimation of mangrove loss with the autocorrelated error structure was generally preferred, and it is this corrected estimation that is reported in Table 4.2. 7. As indicated in Table 4.2, for all regressions an F-test was performed to verify the null hypothesis of zero individual effects across all 21 provinces. As the test was highly significant, this hypothesis can be rejected, which in turn implies that pooled OLS is not an efficient estimator, and the random effects model employing generalized least squares (GLS) is preferred. The Breusch–Pagan Lagrange multiplier (LM) statistic is also highly significant, which suggests rejection of the null hypothesis of zero random disturbances. Thus the test statistics reported in Table 4.2 argue in favor of the random effects model over OLS for all panel analysis regressions. 8. As Table 4.3 indicates, in the regression without shrimp farm density, the impact of the shrimp price on relative shrimp farm area expansion is slightly larger than the impact of the minimum wage rate. 9. As noted in the second section of the chapter, mangrove deforestation in southern Thailand has also resulted from tourism, and agricultural, industrial and urban developments in coastal areas, and thus is not completely explained by mangrove clearing for shrimp farming. 10. By employing relative prices in each regression, and using minimum wage as the numeraire, the impact of a rise in the wage rate will depend on the relative impacts of the PRICE/MINWAGE versus AMDIS/WAGE variables on the dependent variable. As reported in Table 4.3, in all regressions the negative impact of the latter variable has the greater absolute effect, which is the reason why the elasticity associated with MINWAGE is positive. 11.Tokrisna (1998) provides some evidence of these changing trends in the rate of mangrove utilization by various coastal economic activities. Before 1980, an average of 7 per cent of all mangrove areas in Thailand were converted to shrimp ponds. In 1986, the rate of mangrove conversion to shrimp ponds was estimated to be 30 per cent, but declined to 17 per cent by 1994. In contrast, the rate of mangrove conversion due to other coastal economic activities, such as urbanization, agriculture, tourism and industry, has increased rapidly, from 15 per cent before 1980 to 17 per cent in 1986 and 36 per cent by 1994. In terms of cumu- lative impacts on mangrove loss, over the entire 1979–96 period, shrimp farming is still thought to have had the greatest effect, even though the rate of mangrove conversion due to shrimp aquaculture has tended to vary over this period. As reported in the second section of the chapter, estimates suggest that up to 50–65 per cent of Thailand’s mangroves have been lost to shrimp farm conversion since 1975 (Dierberg and Kiattisimkul 1996; Tokrisna 1998). This page intentionally left blank PART II

Case Studies: Phang-nga and Nakhon Si Thammarat This page intentionally left blank 5. Analytical background of the case studies and research sites: ecological, historical and social perspectives Sanit Aksornkoae, Wattana Sugunnasil and Suthawan Sathirathai

SELECTION OF CASE STUDIES

In order to understand better the local issues concerning shrimp farm expansion and mangrove loss, we selected two research sites for further case study. Two principal research sites were selected: two representative villages in Nakhon Si Thammarat Province (on the Gulf of Thailand) and two representative villages in Phang-nga Province (on the Andaman coast) (Figure 5.1). In Nakhon Si Thammarat Province, Ban Gong Khong in East Pak Panang Subdistrict, Pak Panang District and Ban Khlong Khut in Pak Nakhon Subdistrict, Muang District were selected. As for Phang-nga Province, Ban Sam Chong Tai in Kalai Subdistrict, Takua Thung District and Ban Bang Pat in Bang Toey Subdistrict, Muang District were chosen. The criterion for selecting these research sites was mainly based on the condition of mangrove forest depletion. Mangroves in Nakhon Si Thammarat have been depleted extensively, whereas in Pang-ngha the rate of destruction has been much slower and pristine forest still exists. The two sites were further compared in terms of the economic background and use of mangroves; the conversion of mangrove areas into other uses including commercial shrimp farms; conflicts of resource uses in the areas; and conservation of mangroves. This chapter provides an ecological, historical and social perspective on the four villages.

Phang-nga Province

Ban Sam Chong Tai in Kalai Subdistrict is located in the middle of a mangrove forest with limited road access. Villagers rely heavily on mangroves in terms of direct and indirect uses. For direct use they collect timber and non-timber

73 74 Case studies: Phang-nga and Nakhon Si Thammarat

Samut Sakhon Bangkok Prachinburi Ratchaburi Chachaengsao

Samut Prakan Chon Buri Samut Phetchaburi Songkhram Rayong Chanthaburi Cambodia Trat Myanmar

Prachuap Khiri Khan

Gulf of Thailand

Andaman Chumphon Sea

Ranong

Surat Thani Ban Khlong Khut Nakhon Si Thammarat Phang-nga Ban Gong Khong Ban Sam Chong Tai Krabi

Phuket Pattalung Ban Bang Pat Trang

Songkhla

Saturi Pattani

Yala Narathiwat

Malaysia

Figure 5.1 Map of Thailand indicating Phang-nga and Nakhon Si Thammarat provinces products in the form of fishery products and wood for fuel and timber. Indirectly, these villagers are offshore fishermen who also have a better understanding of the linkages between mangroves and capture fisheries. It is also interesting to note that the village is located in Phang-nga Bay where fishing villages are quite conservative and not that attracted to modernization. Villagers do not engage in shrimp farming and rather oppose the venture. Conflicts also exist in terms of polluted water from shrimp farms causing damage to fish culture along the coast. Moreover, there is also damage done to Ecological, historical and social perspectives 75 rice paddies and public water resources. Conflicts between shrimp farming and mangroves are not clearly established. However, it is well known that local fishermen in Phang-nga Bay are opposing shrimp farming in their forest areas. In the past, the mangrove areas in Ban Sam Chong Tai were degraded mainly by the logging activities of forest concessions. According to law, any owner of a forest concession is required to replant after cutting down trees. In reality, reforestation has never taken place. Although the mangrove forests have not been completely cleared, many areas have been destroyed. Finally, the Cabinet Resolution of 19 November 1996 abolished forest concessions in mangrove areas all over the country. It is interesting to observe that in Kalai Subdistrict when forest concessionaires were granted rights to cut down trees, they did not choose the areas belonging to the local community. They appear to have recognized the de facto rights of the local community to the mangroves, since the villagers in Kalai Subdistrict have long used these areas in common and consider the areas as their mangrove forest community. While villagers in Ban Sam Chong Tai in Kalai Subdistrict are mainly small-scale and medium-scale fishermen who have a simple lifestyle, villagers in Ban Bang Pat in Bang Toey Subdistrict have diversified professions ranging from fishermen to commercial shrimp farmers and owners of rubber plantations. The latter village is far wealthier than the former. Ban Bang Pat in Bang Toey Subdistrict is located on the main highway. The level of commercialization and modernization is quite high. Villagers engage in various commercial enterprises. Members of the same household may own both rubber plantations and commercial shrimp farms. From casual observation, they seem to be less dependent on mangroves. The mangrove forests in Bang Toey Subdistrict were first cleared by tin mining concessions. These activities not only destroyed the forests but also created enormous water pollution in the area. After the prices of tin fell drastically, coupled with the severe decline of mangroves, the Cabinet Resolution of 23 July 1991 abolished tin mining in mangrove forests all over the country. However, as the villagers in Bang Toey Subdistrict do not depend much on mangroves, they became open access areas upon which anyone can encroach. Parts of these forests were also converted into shrimp farming. However, the mangrove conversion in these areas is still not as extensive as along the east coast (the Gulf of Thailand). According to experts, much of the west coast (Andaman Sea) is steeply sloped and therefore not very suitable for shrimp farming. However, according to a villager in Bang Toey Subdistrict, the water quality is much better along the Andaman Sea coast and people can use the areas continuously for the cultivation of shrimp farming for as long as 10 years without serious disease problems. This is quite different from the Gulf of Thailand where the life span of shrimp farms is only four to five years. It is 76 Case studies: Phang-nga and Nakhon Si Thammarat also interesting to note that the more suitable areas for shrimp farming along the west coast are now rubber plantations which are located next to mangrove forests. Farmers normally cleared the plantations before establishing shrimp ponds and pumped seawater from the adjacent mangrove areas. What is a real concern is whether water pumping has any ecological impacts on the mangrove forests. In Ban Sam Chong Tai in Kalai Subdistrict, the local community is quite active in the conservation of mangroves. They consider an area of 300–400 rai (which legally belongs to the state) as their own community forest.1 These villagers are small-scale fishermen who recognize the important linkages between mangrove areas and capture fisheries. They have set up rules for wood collection and now replant some degraded areas, with some support from a government project. However, it is important to note that the village leader has initiated the idea of reforestation himself and asked for support from outsiders. In Bang Toey Subdistrict, the local community also participates actively in the replanting of mangroves. However, the project was originally initiated by non-governmental organizations (NGOs) who encouraged the villagers to replant the degraded areas. As mentioned earlier, the villagers do not rely much on mangroves. However, they would like to reforest the denuded mangroves as they realize the important role of forest conservation.

Nakhon Si Thammarat Province

Even though Ban Gong Khong in East Pak Panang Subdistrict is also located in the middle of rather pristine mangrove forest, and villagers extensively collect wood and fishery products, the level of urbanization and commercialization in the area is relatively high compared to that of Ban Sam Chong Tai in Phang-nga. Commercial shrimp farming is extensively practiced, posing a threat to the existing mangrove area. Ban Khlong Khut in Pak Nakhon is far more urbanized. However, villagers still engage in offshore fisheries. Although the mangrove forest nearby is in a rather poor condition, villagers go and collect wood from the forest in East Pak Panang Subdistrict for making their fishing instruments. There are a lot of factories in which villagers are employed. Many villagers are also hired as labourers in commercial shrimp farms, most of which are owned by outsiders. Generally, the remaining mangrove areas in Nakhon Si Thammarat are only in small patches. Pristine mangrove forest surrounding Ban Gong Khong in East Pak Panang Subdistrict is quite an exception. The major cause of the conversion of the mangrove areas along the Gulf of Thailand has been shrimp farming. Historically, commercial shrimp cultures have long been established on the Gulf; in the past, road access was better than on the Andaman side and, geographically, the mangrove areas could be easily cleared. More importantly, Ecological, historical and social perspectives 77

Table 5.1 Research sites and sample sizes

District Survey sites Number of sampled households

Phang-nga • Ban Sam Chong Tai, Kalai Subdistrict, 55 Takua Pa District • Ban Bang Pat, Bang Toey Subdistrict, 42 Muang District Total for Phang-nga 97 Nakhon Si • Ban Gong Khong, East Pak Panang 53 Thammarat Subdistrict, Pak Panang District • Ban Khlong Khut, Pak Nakhon 51 Subdistrict, Muang District Total for Nakhon Si Thammarat 104 TOTAL 201 local communities depend less on mangroves as the level of commercialization and urbanization is quite high. The mangrove forests are therefore like an open access resource, despite the fact that the areas legally belong to the state. Conflicts in terms of resource use are prevalent since there are a number of factories in Pak Nakhon. The problem of water pollution from these factories is quite serious, especially for aquaculture, including shrimp farming. Conflicts between shrimp farmers and rice farmers have also been observed. Mangrove conservation activities in the two villages in Nakhon Si Thammarat are limited as compared to such activities in the two villages in Phang-nga. Replanting has been carried out mostly by the Royal Forestry Department, with villagers participating only as hired labor. For quantitative and in-depth analysis, household surveys were conducted with sampled sizes, as indicated in Table 5.1.

ECOLOGICAL BACKGROUND

Phang-nga

Mangrove status in Phang-nga Mangrove forests in Phang-nga can be found in Muang District, Takua Thung District, Takua Pa District, Kuraburi District, Taimuang District, and Kor-yao 78 Case studies: Phang-nga and Nakhon Si Thammarat

Table 5.2 Mangrove forests in districts in Phang-nga (1989) and Nakhon Si Thammarat, 1999

Mangrove forests Province ha rai % Phang-nga Provincea 35 613.28 222 583.00 100.00 Muang District 6 706.72 41 917.00 18.83 Takua Thung District 6 313.12 39 457.00 17.73 Takua Pa District 5 087.68 31 798.00 14.29 Kuraburi District 14 549.76 90 936.00 40.85 Taimuang District 2 722.88 17 018.00 7.65 Kor-yao District 233.12 1 457.00 0.65 Nakhon Si Thammarat Provinceb 11 275.50 70 472.00 100.00 Muang District 590.88 3 693.00 5.24 Pak Panang District 8 483.83 53 024.00 75.24 Khanom District 1 984.00 12 400.00 17.59 Thasala District 126.88 793.00 1.12 Sichol District 89.91 562.00 0.81

Source: aCharuppat and Charuppat (1997); bNakhon Si Thammarat Regional Forest Office (2000).

Figure 5.2 A pristine mangrove forest in Phang-Nga Province Ecological, historical and social perspectives 79

District, with a total area of about 35 613 ha, as shown in Table 5.2. The mangrove forests in this area are rich and productive plant communities. At present they are mainly located in the Marine National Park (see Figure 5.2). More than 24 species of trees were found in the mangrove forests of Phang- nga. The most common species found are Rhizophora apiculata, R. mucronata, Avicennia alba, A. officinalis, Bruguiera cylindrica, B. parviflora, Ceriops tagal, Sonneratia alba, S. griffithii and Xylocarpus granatum. The conversion of mangrove forests in Phang-nga is very limited with the area of mangrove loss at only 26 958 ha between 1961 and 1996 (Table 5.3). Mangrove forests in this province are mainly converted through mining (particularly in Takua Pa District), agriculture and the construction of ports and roads. Shrimp ponds are operated in a small area of about 826 ha (5166 rai) as shown in Table 5.4. The average stand density of mangrove forest in Phang-nga (Table 5.5) was about 778 trees/ha with a stem volume of approximately 43.6 m3/ha (Table 5.6). Natural regeneration of mangrove forests in Phang-nga as regards densities of saplings and seedlings is quite good, with a total density of 10 749 seedlings/ha (Table 5.7).

Mangrove status in the study area

Bang Toey Subdistrict Mangrove forests in Bang Toey Subdistrict, Muang District, Phang-nga mainly occupy areas along the banks of rivers and canals (see Figure 5.3) and are scattered around the village and shrimp

Table 5.3 Change in mangrove forest area in Phang-nga and Nakhon Si Thammarat Provinces, 1961–96

Mangrove forests (rai) Phang-nga Nakhon Si Thammarat Year ha rai ha rai

1961 57 400.0 358 750 61 200.0 382 500 1975 50 940.0 318 375 15 500.0 96 875 1979 48 716.0 304 475 12 832.0 80 200 1986 36 420.0 227 625 8 835.0 55 219 1989 35 613.3 222 583 8 521.0 53 256 1991 33 508.3 209 427 8 025.0 50 156 1993 30 716.2 191 976 7 996.0 49 975 1996 30 442.4 190 265 8 416.2 52 601

Source: Charuppat and Charuppat (1997). 80 Case studies: Phang-nga and Nakhon Si Thammarat

Table 5.4 Total area of mangrove forest land use in Phang-nga and Nakhon Si Thammarat Provinces, 1993 and 1996

Total mangrove land use 1993 1996 rai % rai %

Phang-nga 274 868.75 100.0 274 868.75 100.0 Mangrove forests 191 976.00 69.9 190 265.25 69.2 Shrimp ponds 5 166.00 1.8 5 958.25 2.2 Resettlement areas none — 75.00 0.1 Other 77 726.76 28.3 78 570.25 28.5 Nakhon Si Thammarat 135 106.25 100.0 135 106.25 100.0 Mangrove forests 49 975.00 37.0 52 601.00 38.9 Shrimp ponds 63 620.25 47.1 65 479.25 48.5 Resettlement areas none — 445.25 0.3 Other 21 511.00 15.9 16 580.75 12.3

Source: Charuppat and Charuppat (1997).

Table 5.5 The stand density of trees with a diameter at breast height (dbh) exceeding 4cm at three study sites: Bang Toey Subdistrict in Muang District, Ban Sam Chong Tai in Takua Thung District, Phang-nga Province

Species Average stand density, tree/ha Bang Toey Ban Sam Phang-nga Subdistrict Chong Tai Province Muang Takua Thung District District

Avicennia spp. 14.9 7.8 15.6 Bruguiera spp. 24.0 120.8 43.7 Ceriops tagal 24.9 195.1 103.1 Excoecaria agallocha — 4.0 10.9 Rhizophora apiculata 193.8 382.4 269.1 Rhizophora mucronata 11.4 24.8 183.0 Sonneratia spp. 0.9 17.8 3.8 Xylocarpus spp. 128.2 201.5 117.8 Other species 32.0 18.6 31.2 Total 430.1 972.8 778.2 Ecological, historical and social perspectives 81

Table 5.6 The stem volume of trees with a diameter at breast height (dbh) exceeding 4cm at three study sites: Bang Toey Subdistrict in Muang District, Ban Sam Chong Tai in Takua Thung District, Phang-nga Province

Species Average stem volume, m3/ha Bang Toey Ban Sam Phang-nga Subdistrict Chong Tai Province Muang Takua Thung District District

Avicennia spp. 6.65 0.74 3.96 Bruguiera spp. 7.02 1.34 2.12 Ceriops tagal 0.26 2.03 1.01 Excoecaria agallocha — 0.34 0.79 Rhizophora apiculata 5.40 5.89 5.33 Rhizophora mucronata 0.15 0.33 5.47 Sonneratia spp. 0.67 2.27 0.59 Xylocarpus spp. 32.73 39.18 23.44 Other species 0.54 0.47 0.85 Total 53.42 52.59 43.56

Figure 5.3 Mangrove forests with Avicennia spp. at Bang Toey Subdistrict, Muang District, Phang-nga Province 82 Case studies: Phang-nga and Nakhon Si Thammarat

Table 5.7 Sapling and seedling density for natural mangrove regeneration at three study sites: Bang Toey Subdistrict in Muang District, Ban Sam Chong Tai in Takua Thung District, Phang-nga Province

Species Average sapling and seedling density, tree/ha Bang Toey Ban Sam Phang-nga Subdistrict Chong Tai Province Muang Takua Thung District District

Avicennia spp. 286.7 19.5 107.6 Bruguiera spp. 4 537.8 1 358.7 1 510.8 Ceriops tagal 1 754.5 3 816.2 2 606.2 Excoecaria agallocha — 25.9 28.7 Rhizophora apiculata 5 535.5 4 315.2 4 012.1 Rhizophora mucronata 648.7 295.4 253.0 Sonneratia spp. 0.4 86.0 17.3 Xylocarpus spp. 1 667.0 1 921.7 1 118.9 Other species 2 843.0 74.4 1 095.0 Total 17 273.4 11 913.0 10 749.6

ponds. The main species are Avicennia spp, Bruguiera spp, Rhizophora apiculata, Rhizophora mucronata, Ceriops tagal, Sonneratia spp, Excoecaria agallocha and Xylocarpus spp. The species of Avicennia Rhizophora and Sonneratia generally cover areas along the banks of rivers and canals, while the species of Excoecaria agallocha and Xylocarpus prefer inland areas. The stand density of mangrove forests in Bang Toey Subdistrict is about 430 trees/ha (Table 5.5) with a stem volume of approximately 53.4 m3/ha (Table 5.6). Natural regeneration is rather good, as based on 17 273 trees/ha of densities of saplings and seedlings (Table 5.7). The local people in Bang Toey Subdistrict use mangrove swamps for catching fish, crustaceans and mollusks. They also use mangrove trees for firewood.

Ban Sam Chong Tai Mangrove forests at Ban Sam Chong Tai cover areas along the coastline and the banks of rivers and canals (Figure 5.4). The common species of mangrove forest in this area are Avicennia, Bruguiera, Rhizophora, Ceriops, Excoecaria, Sonneratia and Xylocarpus. Avicennia and Sonneratia are dominant species in coastal areas. Species of Rhizophora, Ecological, historical and social perspectives 83

Figure 5.4 Mangrove Forests with Rhizophora spp and Avicennia spp, along the coastline at Ban Sam Chong Tai, Takua Thung District, Phang-Nga Province

Bruguiera and Ceriops are found beside the Avicennia–Sonneratia community. Xylocarpus and Excoecaria generally cover the banks of rivers and canals. Mangrove forests at Ban Sam Chong Tai are of a higher productivity than those at Bang Toey Subdistrict, with a stand density of about 972 trees/ha (Table 5.5) and a stem volume of 52.6 m3/ha (Table 5.6) respectively. The total density of saplings and seedlings with the value of approximately 11 913 trees/ha indicates good natural regeneration (Table 5.7). The local people at Ban Sam Chong Tai prefer to conserve mangrove forests to increase fishery products, rather than harvesting trees for firewood.

Nakhon Si Thammarat

Mangrove status in Nakhon Si Thammarat Mangrove forests in Nakhon Si Thammarat cover a large area close to the coastline. They also occupy a narrow strip along the coastline and are scattered around and within shrimp ponds (Figure 5.5). The mangrove forests are distributed in five districts with a total area of about 70 472 rai (11 275 ha) 84 Case studies: Phang-nga and Nakhon Si Thammarat

Figure 5.5 Narrow strips of mangrove forest along the coastline and replanted mangroves in shrimp ponds, Pak Poon, Nakhon Si Thammarat Province including 3693 rai (590 ha) in Muang District, 53 024 rai (8483 ha) in Pak Panang District, 12 400 rai (1984 ha) in Khanom District, 793 rai (126 ha) in Thasala District and 562 rai (89 ha) in Sichol District, respectively (see Table 5.2). Mangrove forests in these areas are composed of various species but the dominant ones found are Avicennia, Bruguirea, Lumnitzera, Rhizophora, Sonneratia, Xylocarpus and Excoecaria agallocha. The stand density is rather thick, mainly comprising small-sized trees, with about 1130 trees/ha. The stem volume is approximately 45m3/ha. Natural regeneration of mangrove forests in this area is quite good, with the total densities of saplings and seedlings at 21 450 trees/ha. Stand density, stem volume and natural regeneration are presented in Tables 5.8. 5.9 and 5.10, respectively. The mangrove forest in Nakhon Si Thammarat was once rich with a large area of about 382 500 rai (61 200 ha) in 1961, but the total area remaining was only 52 601 rai (8416 ha) in 1996 (Table 5.3). A 1996 survey revealed that the conversion of mangrove forests in this area (see Table 5.4) was mainly into shrimp ponds (65 480 rai). This accounted for approximately 49 per cent of the total mangrove loss. However, with the planting mangrove promotion of the government, NGOs and local communities, the total mangrove forest in Nakhon Si Thammarat Province increased to approximately 70 472 rai in the year 2000 (see Table 5.2). Ecological, historical and social perspectives 85

Figure 5.6 Mangrove forests along the river at Ban Khlong Khut, Nakhon Si Thammarat Province

Mangrove status of the study areas

Ban Khlong Khut Mangrove forests at Ban Khlong Khut occupy an area along the banks of canals and rivers. The dense forest is mainly found in areas near to the village (Figure 5.6). However, mangrove trees are also planted along the river bank for soil erosion control. The common mangrove species are Avicennia, Bruguiera, Lumnizera, Rhizophora and Sonneratia. Mangrove forests in this area are mainly composed of small-sized trees with a density of 962 trees/ha (see Table 5.8) and a stem volume of approximately 41.6 m3/ha (Table 5.9). The natural regeneration is quite good, with the total densities of saplings and seedlings at about 26 000 trees/ha (Table 5.10). The majority of mangrove trees in this area are secondary growth due to heavy harvesting for firewood in the past.

Ban Gong Khong Mangrove forests at Ban Gong Khong are situated mainly along the banks of canals and the mouth of Gong Khong Canal. The rich and productive mangrove forests are found near to the village (Figure 5.7). Some species, like Lumnizera, are also planted around houses for the construction of crab traps and firewood. Mangrove forests in this village show a high stand density and stem volume, with values of 1078 trees/ha and 55.6 m3/ha respectively (Table 5.8 86 Case studies: Phang-nga and Nakhon Si Thammarat

Table 5.8 The stand density of trees with a diameter at breast height (dbh) exceeding 4cm at three study sites: Ban Khlong Khut in Muang District, Ban Gong Khong in Pak Panang District, Nakhon Si Thammarat Province

Species Average stand density, tree/ha Ban Khlong Ban Gong Nakhon Si Khut in Muang Khong in Pak Thammarat District Panang District Province

Avicennia spp. 285 315 272 Bruguiera spp. 112 180 210 Lumnitzera sp. 84 — 45 Rhizophora apiculata 121 210 185 Rhizophora mucronata 102 195 160 Sonneratia spp. 160 140 165 Xylocarpus spp. — — 38 Other species 98 38 55 Total 962 1 078 1 130

Table 5.9 The stem volume of trees with a diameter at breast height (dbh) exceeding 4cm at three study sites: Ban Khlong Khut in Muang District, Ban Gong Khong in Pak Panang District, Nakhon Si Thammarat Province

Species Average stem volume, m3/ha Ban Khlong Ban Gong Nakhon Si Khut in Khong in Pak Thammarat Muang District Panang District Province

Avicennia spp. 28.6 25.5 10.5 Bruguiera spp. 1.2 2.5 2.1 Lumnitzera sp. 2.0 — 3.1 Rhizophora apiculata 1.1 5.1 4.2 Rhizophora mucronata 1.8 3.5 3.2 Sonneratia spp. 4.5 14.0 6.5 Xylocarpus spp. — — 12.1 Other species 2.4 5.0 3.4 Total 41.6 55.6 45.1 Ecological, historical and social perspectives 87

Table 5.10 Sapling and seedling density for natural mangrove regeneration at three study sites: Ban Khlong Khut in Muang District, Ban Gong Khong in Pak Panang District, Nakhon Si Thammarat Province

Species Average sapling and seedling density, trees/ha Ban Khlong Ban Gong Nakhon Si Khut in Khong in Pak Thammarat Muang District Panang District Province

Avicennia spp. 10 000 11 000 9 500 Bruguiera spp. 4 000 4 500 3 700 Lumnitzera sp. 1 600 — 625 Rhizophora apiculata 400 2 500 1 800 Rhizophora mucronata 800 1 500 1 200 Sonneratia spp. 1 200 4 800 3 200 Xylocarpus spp. — — 325 Other species 8 000 3 500 1 600 Total 26 000 27 800 21 950

Figure 5.7 Mangrove forests along the Khlong (canal) and village, Ban Gong Khong, Nakhon Si Thammarat Province and Table 5.9). The natural regeneration is quite good, with the total densities of saplings and seedlings at 27 800 trees/ha (Table 5.10). The mangrove forests at Ban Gong Khong are richer and more productive than those at Ban Khlong Khut. 88 Case studies: Phang-nga and Nakhon Si Thammarat

BACKGROUND AND ECOLOGICAL HISTORY OF THE CASE STUDIES Ban Khlong Khut and Ban Gong Khong communities of Pak Panang Bay

Pak Panang Bay is located on the eastern coast of the Gulf of southern Thailand, covering Muang and Pak Panang Districts in Nakhon Si Thammarat Province. The bay is also a growing commercialized and urbanized area. The coastline is now dotted with urban centers and communities of various sizes engaged in diversified activities, including coastal and off-shore fisheries, seafood processing, commerce and services, rice growing and fruit orchards. Shrimp farming is a growing industry in the area. Large tracts of mangrove forests along the coastline have been converted to commercial, industrial and residential areas. Ban Khlong Khut and Ban Gong Khong are two coastal communities located on Pak Panang Bay. Ban Khlong Khut is a community of 278 households and a population of 1200, all of whom are Thai. The community is connected to Pak Nakhon municipality, a town center located in Muang District west of the bay where mangrove forests of approximately 30 000 rai (4800 ha) used to exist. Ban Khlong Khut is a relatively large and heteroge- neous community. Ban Gong Khong, another study site, is located within and surrounded by the reserved mangrove forest on the western coast of Talum Puk Cape, east of Pak Panang Bay in Pak Panang District. The community has about 700 villagers living in 150 households which are scattered along the canal leading to Pak Panang Bay. The use and conservation of mangrove, including resource conflicts in both Ban Khlong Khut and Ban Gong Khong can be summarized in a chronologi- cal order of events as below.

Ban Khlong Khut

From 1950 to 1960 Thick mangrove forests largely covered the area around the village. Houses were built along the canal. Rice growing was the main occupation. Smaller crabs and shrimps in the mangroves were collected for sale. Fishing (using cast nets, hook and line) was mostly for personal consumption. Villagers depended heavily upon the mangroves for direct uses (for example, timber for house poles, fishing boats, fuel; nypa for thatching) and indirect uses (for example, harvesting smaller crabs and shrimps).

Early and mid-1960s Resource uses became more commercialized. Villagers started using motorized boats for fishing/catching large shrimps in Ecological, historical and social perspectives 89

Pak Panang Bay and sold them to local markets. Mangrove trees were increasingly cut down by villagers and outsiders for sale, mostly using the trees for the construction of popular fishing gear called Yor Peek, a large stationary liftnet with a wing.

Mid-1970s Rice fields were heavily flooded in 1975. Salinity and irregular rainfall forced an increasing number of rice growers to shift into coastal fishery.

Early and mid-1980s In the early 1980s, extensive shrimp farming started making inroads into Ban Khlong Khut. Mangrove forests were cleared and abandoned rice fields sold. Shrimp farms initially located on the periphery began to expand into rice-growing areas. In the mid-1980s, problems of salinity and seepage of brackish water forced more villagers to sell their cultivated lands. Villagers, however, claimed they were better off from the profit earned from shrimp farms and land sale. The mangroves in Ban Khlong Khut had been heavily degraded and the mangrove trees completely cleared. Many Ban Khlong Khut residents were increasingly engaged in coastal fishery in Pak Panang Bay as their main source of income.

Late 1980s and early 1990s Intensive shrimp farming made its appearance in Ban Khlong Khut. More mangrove areas were cleared. Initially many local residents turned their extensive methods into semi-intensive or intensive methods, but they soon faced diminishing returns and rising debts and started rent- ing out their ponds. Most intensive practices were later taken over or operated by outside investors. Problems of shrimp diseases and polluted water discharged into canals became widespread. Serious conflicts, however, never occurred as most residents were all implicated directly as owner-operators or indirectly as rentiers.

Mid- and late 1990s Intensive shrimp farms were completely abandoned. Many residents were still heavily indebted. Some switched back to an extensive method of shrimp aquaculture. Mud crabs and small crabs were reportedly disappearing from Ban Khlong Khut. Land price was as high as 100 000 baht per rai.2

2000 Local residents increasingly depend upon and compete for their catch from the dwindling marine stock in Pak Panang Bay. The total catch of shrimp, for example, has decreased by four to five times. This decreasing marine stock, some Ban Khlong Khut residents believed, could be attributed to the increasing number of fishermen and polluted wastewater discharged into the bay from thousands of rai of shrimp farms located along the bay’s coastline. 90 Case studies: Phang-nga and Nakhon Si Thammarat

Many Ban Khlong Khut residents increasingly rely upon illegally cutting down mangrove trees from reserved forests located on Talum Puk Cape, since there are no mangroves available nearby and their popular Yor Peek fishing gear requires constant replacement of wood and poles.

Ban Gong Khong

From 1950 to 1960 Pioneer families moved into the area. Houses were built along canals leading to Pak Panang Bay. The vegetation consisted of dense mangrove forests, mostly large trees. Wood cutting for nearby charcoal factories was the major source of income for early settlers. Harvesting small shrimps and crabs in mangrove canals and areas along the shores around estuaries provided supplementary income. Pioneer families also depended heavily upon the mangrove for materials used for house construction and firewood. New families were able to clear the mangrove areas as much as they needed, mostly for their own residences.

Early and late 1960s In 1960, the demand for shrimp from local markets at Pak Panang District increased. Villagers intensified their catch, using simple fishing gear such as paddle boats and small push nets. More landless and poor people, many of whom were related to early settlers, moved in as wage earning from wood cutting and income from fishing provided more stable and secure livelihoods. Some families started expanding their residential areas and clearing more mangrove forests. In 1965, the whole mangrove area on Talum Puk Cape was declared a reserved forest. Authorities regarded Ban Gong Khong residents’ occupancy as illegal. The village head failed to notify the residents earlier. Since then, threats of eviction have been carried out on various occasions. Another charcoal factory, owned and operated by a Chinese merchant, was opened nearby, providing another source of wage earning from wood cutting.

Mid-1970s Villagers continued harvesting mud crabs and small crabs which were still abundant in mangrove canals. Forestry authorities came in to warn villagers not to encroach further on mangrove forests, particularly those opposite the canal, as they were all declared reserved forests.

Early 1980s The Forestry Department started replanting programs on reserved forests. As charcoal factories were closing down, Ban Gong Khong villagers began working for replanting programs instead. More people moved in and made their living as hired labor in the replanting program and fishing. Collecting small crabs in the mangroves still provided a substantial income for villagers. A dirt road connecting villagers to main roads was constructed. Ecological, historical and social perspectives 91

Late 1980s A shrimp farm using an intensive method was first operated in Ban Gong Khong by a local resident in 1987. Using mostly human labor, mangrove forests were cleared, and large trees burnt down. The high profit encouraged more villagers to turn their lands into shrimp ponds. The village head applied for a land title for everyone living in Ban Gong Khong, but this was rejected on the grounds that the land was in reserved forests. Forestry authorities came in to designate the community boundary, and put up signs indicating reserved forests. The availability of electricity and gas reduced the local need for firewood.

Early 1990s Some residents used the profit from shrimp farming to build new and modern houses. Shrimp farming in Ban Gong Khong expanded rapidly. Bulldozers were used to clear mangrove areas and dig up shrimp ponds. Villagers claimed to have given some money to the village head, who was a pioneer shrimp farmer himself, and authorities as bribes. Many fishermen used savings or borrowed capital to invest in shrimp farming. Harvesting marine life in the mangroves was still an important source of income for some who did not own much land or lacked sufficient capital.

Late 1990s Many local shrimp farmers went bankrupt. Most returned to their fishing and faced the fact that the fish stock had already declined. Small crabs in mangrove canals were harder to find. Many villagers claimed shrimp farm investors on the east coast of Ta Lum Puk Cape had dumped effluents and polluted wastewater into mangrove forests on the west side of the cape, thereby destroying the fishery’s habitats. Water in canals, along which many shrimp farms were located, became polluted. Forestry authorities came to survey and record the number of shrimp ponds and declared that no more new ponds were allowed. Temporary occupation rights for villagers were also granted, but transfer of rights was prohibited. However, some 20–30 outside shrimp investors reportedly bought the ponds and land from villagers. The replanting program in honor of His Majesty the King was extended to areas along the sides of Ban Gong Khong’s road, covering about 3000 rai (480 ha).

2000 Key informants claim that mangrove forests around the village and in reserved areas are much denser, thicker and healthier than they were 20 years ago, as a result of the replanting program. Villagers are still harvesting timber and wood to be used in constructing board walks and poles. For some, collecting grapsid crabs, although they are increasingly hard to find, remains an important source of income. However, villagers’ access to mangrove areas close to shrimp ponds is prohibited. 92 Case studies: Phang-nga and Nakhon Si Thammarat

Villagers also complain about the quality of water in canals which have become polluted since the coming of shrimp farms.

Ban Sam Chong Tai and Ban Bang Pat communities of Phang-nga Bay

Phang-nga Bay is a small gulf of the Andaman Sea along southern Thailand’s west coast. Its terrestrial borders comprise three provinces: Phuket, Phang-nga and Krabi. The bay, being one large estuarine ecosystem, is one of the most biologically productive bays in the Andaman Sea (Limpsaichol et al. 1998) and is home to some 13 000 small-scale fishermen in 114 coastal villages. An abundance of mangrove areas is one of several factors contributing to the bay’s high productivity (Nickerson-Tietze, 2000). The study area is located in the western part of Phang-nga Bay, Phang-nga, which is well known for its abundant and pristine mangrove forests. The case studies cover two villages, each from the two districts along Phang-nga Bay, namely, Sam Chong Tai in Takua Thung District and Bang Pat in Muang District. Approximately 70 per cent of the village households in both communities are dependent on coastal resources. The remaining households derive their income from aquaculture, agriculture and working as wage laborers. Ban Sam Chong Tai is located near the mouth of the estuary. The community has around 54 households. All residents are Muslims. The village is surrounded by mangrove forests with streams and canals to north and west. The other village in this study area of Phang-nga Bay, Ban Bang Pat, used to be part of a larger Ban Klang community in Bang Toey Subdistrict. The community has approximately 50 households, most of which are also Muslim. The ecological history of Sam Chong Tai and Ban Bang Pat can be summarized as below.

Ban Sam Chong Tai

From 1950 to 1960 The village was surrounded by dense mangrove forests, consisting mostly of large trees. Villagers depended heavily on the forests for their direct and indirect uses. They also had to travel to inland communities to exchange their fish products for other necessities, mainly rice. Cutting down trees for charcoal production for Chinese merchants to be exported to Penang was practiced by most villagers.

The 1960s Acetes, locally called Koey, was plentiful in the area, and harvesting Koey in mangrove canals provided the main source of income for local residents. Other important marine species included mantis shrimp, mud crabs and mullet. Simple fishing gear was used such as sails, stake traps, cast nets, hook and line, and small push nets. Ecological, historical and social perspectives 93

An area of 2000 rai (320 ha), including Ban Sam Chong Tai, was declared a National Park.

The 1970s In the early 1970s, mining activities started to operate in the area, followed by charcoal factories in the late 1970s. Some villagers were hired as wood cutters. Thick mangrove forests, as charcoal concession areas, covering 3000–4000 rai, were rapidly degraded. In 1973 and 1975, large tracts of the mangrove areas, including those where Ban Sam Chong Tai is located, were declared a reserved forest. Villagers began using motorized boats and other modern fishing gear such as gill nets, but their fishing activities were still mostly confined to the near shore and mangrove canals. A decrease in the number of mud crabs began to be noticed.

Mid- and late 1980s In 1985, charcoal factories began hiring illegal migrants as wood cutters, and using a non-selective method of cutting down mangrove trees. In the late 1980s, shrimp farms started to appear in watershed areas to the north and discharged wastewater into canals flowing to coastal waters around Sam Chong Tai. A variety of marine species in mangrove canals and around nearby shores decreased noticeably. In 1989, authorities came to evict villagers, but they refused to leave.

Early and late 1990s Dwindling coastal marine resources forced local fishermen to venture further from the shoreline and consequently spend more time on their fishing. Charcoal concessions were cancelled and degraded mangrove forests began to regenerate, attracting more marine life. However, mangrove streams, creeks and canals became more polluted as an increasing number of shrimp farms began discharging wastewater into them. In the mid-1990s, villagers began their conservation activities, focusing on replanting mangrove trees and setting up a community forest in degraded areas. They declared the replanted area a local sanctuary, prohibiting any kind of exploitation for five years. In 1997, the first dirt road connecting villagers to outside networks was constructed.

2000 Villagers continue their conservation activities. A local committee and rules regulating the use of the community forest have been set up. Authorities are more sympathetic to their right to occupy the land in the National Park. Facing the continuous decline of marine resources, most villagers consider shrimp farming as the real threat to their livelihood. 94 Case studies: Phang-nga and Nakhon Si Thammarat

Ban Bang Pat (and Ban Klang)

Before 1960 In the early 1950s, a small group of families moved to settle in the area known today as Ban Bang Pat. At that time, Ban Bang Pat was part of a larger Ban Klang community, Bang Toey Subdistrict. Early settlers in Ban Bang Pat, along with residents of other coastal communities, were highly dependent upon the mangroves, which formed dense, diverse forests surrounding the community. Rice growing was the main occupation of local residents while fishing was carried out mainly for personal consumption. Fish and Acetes, locally known as Koey, were plentiful in the area, and harvesting Koey in mangrove areas provided a supplementary source of income. Simple fishing gear such as sails, paddling boats, set bags, cast nets, and hook and line were used.

The 1960s The outside demand for shrimps increased. Fishing became more commercialized. Charcoal concessions in mangrove forests, covering 2000–3000 rai (320–480 ha), east of the community were granted to outside investors. Some local residents were hired to cut wood for charcoal factories. Villagers could still harvest timber from the forests as their needs were limited.

The 1970s Improved transportation and profits from selling their catch, especially shrimps, enabled many residents to build their houses using more durable materials such as plank woods, tiles and cement from the town market. In the mid-1970s, mining corporations began operating in areas upstream and in the northern portions of the community. The clearing of mangrove forest, together with heavy sedimentation and turbidity, reportedly took their toll on marine life in the coastal waters of Bang Toey Subdistrict.

The 1980s Facing declining marine resources near the shoreline, local residents were forced to use improved fishing gear, such as motorized boats and push nets, to venture offshore. Some had turned to cutting down timber for sale in markets, thereby accelerating mangrove degradation. Rice growing had declined and villagers increasingly bought rice from the market. Many had turned their rice fields into small oil palm plantations. In the late 1980s, shrimp farming by outsiders began to operate in neighboring villages north of Ban Bang Pat and Ban Klang.

The 1990s In the early 1990s, villagers began conservation efforts to prevent the expansion of shrimp farming in degraded mangrove areas. With cooperation from outside agencies and local authorities, they set themselves the target of replanting 1000 rai (160 ha) from 1993 to 1996. An area of 100 rai (16 ha) was designated as a community forest, protected and managed by a local committee. Ecological, historical and social perspectives 95

Aquaculture, particularly that of oysters and green mussels, had been successfully introduced to coastal waters around the area. Ban Bang Pat was the first to venture into aquaculture. As shrimp farming expanded and more wastewater was discharged into canals and creeks upstream, local villagers began to feel its impacts. These included the high salinity of their drinking wells, salt water seepage into nearby rice fields, and high mortality of their aquaculture. They voiced their concerns to the authorities, but no serious efforts were made to solve the problems. In 1996, Ban Bang Pat was administratively separated from Bang Toey Subdistrict but relationships and communication among residents of these two villages continued, and many communal activities were shared.

2000 The life of local residents has become more modern and therefore dependent upon the mangroves indirectly more than directly. Nevertheless, efforts have been made by local villagers to protect and conserve the mangrove forests for their children. The conservation activities of local residents in Phang-nga became well- known, attracting media attention and funds from donors. The influx of external funds to support conservation activities is becoming a challenging problem for local management, not to mention the time-consuming process of community-based resource management.

NOTES

1. 6.25 rai = 1 ha. 2. 40 Thai baht = US$1. 6. Mangrove dependency, income distribution and conservation Isra Sarntisart and Suthawan Sathirathai

BACKGROUND

This chapter analyzes the consumption behavior of households in the four case study coastal villages. Data from 201 households were sampled randomly from the total of 434 households in the four villages of which 55, 42, 53 and 51 households were from Ban Sam Chong Tai and Ban Bang Pat in Phang-nga Province, and Ban Gong Khong and Ban Khlong Khut in Nakhon Si Thammarat Province, respectively (Table 6.1). These households are generally dependent on mangrove forests. Some of the households derive their income directly from the forest, in terms of collection of fishery products, wood products and firewood. Some of them benefit indirectly from the existence of the forest through coastal fisheries of demersal and shell fish. Some also engage in aquaculture. These activities have different degrees of dependency on mangrove forest. Consequently, the degree to which the existence of mangrove forest affects their income and economic well-being differs across households and villages. Table 6.2 summarizes the average annual gross income of households in the four villages. The average annual gross (money and non-money) income of households in these villages was around 104 227, 179 776, 264 936, and

Table 6.1 The number and size of households in the four villages

Village Number of Household Number of samples Population size earners

Total 201 434 4.67 1.89 Ban Sam Chong Tai 55 55 4.73 1.65 Ban Bang Pat 42 51 4.02 1.90 Ban Gong Khong 53 100 4.64 1.94 Ban Khlong Khut 51 228 5.18 2.08

96 Mangrove dependency, income distribution and conservation 97

Table 6.2 Gross income of households in the four villages

Village Gross income Money income Imputed income

Ban Sam Chong Tai 104 227 (100.00) 97 040 (93.11) 7 186 (6.89) Ban Bang Pat 179 776 (100.00) 170 446 (94.81) 9 329 (5.19) Ban Gong Khong 264 936 (100.00) 253 523 (95.69) 11 413 (4.31) Ban Khlong Khut 260 311 (100.00) 247 936 (95.25) 12 375 (4.75)

Note:Income in baht per year; figures in parentheses are percentage shares.

260 311 baht. The major part of their income was derived from the selling of agricultural, mangrove forest and fishery products. Less than 7 per cent of the gross income was imputed from their consumption of home-produced goods. The rest was from wage earnings. Income earned directly from mangrove forest was more important to households in Ban Sam Chong Tai and Ban Gong Khong than households in the other two villages (Table 6.3). The share of the direct income from mangrove forest in the gross money income of households in the two villages (approximately 41 and 24 per cent) was more than that of Ban Bang Pat and Ban Khlong Khut (approximately 8 and 6 per cent). However, it should be noted that the major source of household income in Ban Gong Khong was not mangrove forest but other agricultural products, that is, shrimp farming, that provided more than 50 per cent of households’ gross money income. The major source of household income in Ban Sam Chong Tai was indirect income from coastal fisheries that provided around 56 per cent of their gross money income. Thus, although the existence of mangrove forest seems to be important for the well-being of households in Ban Gong Khong, they still have another alternative source of income when compared to the villagers in Ban Chong Tai. Households in the four coastal villages also consumed some of the output of their own production (Table 6.4). The imputed value of home-produced goods from households in Ban Khlong Khut, Ban Gong Khong, Ban Bang Pat and Ban Sam Chong Tai was around 12 375, 11 413, 9329 and 7186 baht per year, respectively. Of this, 27, 74, 28, and 57 per cent was the consumption of products from fishery in mangrove forest, and the collection of wood products and firewood from the forest. Thus, in terms of consumption, the direct dependency on mangrove forest of households in Ban Gong Khong and Ban Sam Chong Tai was more than that of households in the other two villages. In terms of income that they earned indirectly from the existence of mangrove forest, that is, coastal fishery of demersal and shell fish, and aquaculture, households in Ban Khlong Khut earned this type of income more than Table 6.3 Sources of gross money income of households in the four villages

Gross total Direct use of Indirect use of mangroves Off-farm Village money mangroves Agriculture work income Fishery Coastal fishery Aquaculture Demersal Shellfish Demersal Shellfish

Total 191 935.68 4 710.25 28 706.15 8 393.15 75 262.05 17 918.94 41 589.05 15 356.09

98 (100.00) (2.45) (14.96) (4.37) (39.21) (9.34) (21.67) (8.00) Ban Sam Chong Tai 97 040.36 9 460.55 29 862.46 8 660.15 39 684.75 6 133.27 490.91 2 748.27 (100.00) (9.75) (30.77) (8.92) (40.90) (6.32) (0.51) (2.83) Ban Bang Pat 170 446.46 3 262.75 10 463.55 6 321.90 75 444.07 56 044.67 8 547.62 10 361.90 (100.00) (1.91) (6.14) (3.71) (44.26) (32.88) (5.02) (6.08) Ban Gong Khong 253 523.31 5 460.27 56 081.47 5 834.16 38 529.86 339.62 127 660.38 19 617.55 (100.00) (2.15) (22.12) (2.30) (15.20) (0.13) (50.36) (7.74) Ban Khlong Khut 247 936.08 0.00 14 033.60 12 470.28 151 652.50 17 500.00 23 674.51 28 637.06 (100.00) (0.00) (5.66) (5.03) (61.16) (7.05) (9.55) (11.55)

Note:Income in baht per year; figures in parentheses are percentage shares. Table 6.4 Imputed value of home-produced consumption goods

Total Direct use of mangroves Indirect use of mangroves Village imputed value Wood Firewood Fishery Coastal fishery Aquaculture Products Demersal Shellfish Demersal Shellfish

Total 10 065.04 1 799.64 341.34 1 437.96 1 136.14 1 490.47 3 207.83 651.55

99 (100.00) (17.88) (3.39) (14.29) (11.29) (14.81) (31.87) (6.47) Ban Sam Chong Tai 7 186.18 1 614.09 602.73 730.00 1 153.98 503.36 1 869.29 712.73 (100.00) (22.46) (8.39) (10.16) (16.06) (7.00) (26.01) (9.92) Ban Bang Pat 9 329.04 1 518.14 0.00 265.70 785.98 2 462.62 2 397.50 1 899.10 (100.00) (16.27) (0.00) (2.85) (8.42) (26.40) (25.70) (20.36) Ban Gong Khong 11 412.89 1 738.68 659.62 4 224.36 1 780.82 1 568.85 1 440.56 0.00 (100.00) (15.24) (5.78) (37.01) (15.60) (13.75) (12.62) (0.00) Ban Khlong Khut 12 374.65 2 294.90 9.80 271.18 735.29 1 672.94 7 155.25 235.29 (100.00) (18.55) (0.08) (2.19) (5.94) (13.52) (57.82) (1.90)

Note:Imputed value in baht per year; figures in parentheses are percentage shares; 40 Thai baht = US$1. 100 Case studies: Phang-nga and Nakhon Si Thammarat households in other villages did. The indirect mangrove income of an average household in this village was around 9063 baht/year. This was more than twice the indirect income of households in the other villages which was 138 597 baht/year (Ban Bang Pat), 58 464 baht/year (Ban Sam Chong Tai) and 48 013 baht/year (Ban Gong Khong).1 It should be noted that, although the fishing area of fishermen from Ban Khlong Khut was relatively far from their village, it was nearer to mangrove forest in Ban Gong Khong’s area. With respect to their inputs of production, households in Ban Sam Chong Tai tended to employ family workers (labor from their own family members) more than households in the other three villages (Table 6.5). Around 37 per cent of their input cost was allocated to household workers. The share of Ban Bang Pat, Ban Gong Khong and Ban Khlong Khut was relatively less, around 16, 21 and 21 per cent of their total production cost respectively. This could be explained by the non-labour cost and the net profit (net income less the value of family workers) of households in Ban Sam Chong Tai that were considerably lower than those of households in the other three villages.

MANGROVE DEPENDENCY AS RELATED TO POVERTY AND CONSERVATION ACTIVITIES

The Simple Models

As discussed earlier, the present study is interested in the importance of mangroves to local economy and villagers’ well-being. We would like to understand the linkages between mangroves and poverty problems in these coastal villages. Moreover, we would like also to investigate the possible correlation between mangrove dependency and the participation in mangrove conservation activities of the local people. Firstly, we need to define mangrove dependency. In this study, the household mangrove dependency model is a modified version of the well-known Linear Expenditure System (LES) pioneered by Stone (1954). In this model, households are assumed to be utility-maximizing agents. The utility of a household is assumed to depend on three factors, namely the committed level of consumption of goods i (gi), the marginal budget share of goods i (bi), and the level of consumption of goods i. Four categories of goods are defined here: leisure time, goods that the household can buy from a market, goods that are produced directly from mangrove forest and consumed partly by the members of the household, and goods that are produced indirectly from mangrove forest and consumed partly by members of the household. For simplicity, in the case of leisure time and three goods, the model can be illustrated as follows: Table 6.5 Net income and cost structure of production

Cost structure

Village Gross Total Depreciation Opportunity Cost of Net income cost and intermediate cost of household hired labor income cost labor

Total 202 000.72 130 349.81 81 199.33 45 547.24 3 603.24 71 650.91

101 (100.00) (64.53) (40.20) (22.55) (1.78) (35.47) Ban Sam Chong Tai 104 226.54 71 854.25 33 071.48 38 318.49 464.28 32 372.29 (100.00) (68.94) (31.73) (36.76) (0.45) (31.06) Ban Bang Pat 179 775.50 111 276.78 81 098.99 28 385.40 1 792.39 68 498.72 (100.00) (61.90) (45.11) (15.79) (1.00) (38.10) Ban Gong Khong 264 936.20 167 964.58 109 649.59 56 936.10 1 378.89 96 971.62 (100.00) (63.40) (41.39) (21.49) (0.52) (36.60) Ban Khlong Khut 260 310.73 169 099.79 103 618.57 54 689.93 10 791.29 91 210.94 (100.00) (64.96) (39.81) (21.01) (4.14) (35.04)

Note:Unit in baht per year; figures in parentheses are percentage shares; 40 Thai baht = US$1. 102 Case studies: Phang-nga and Nakhon Si Thammarat

bu bI Maximize utility = (Lu – gu) P (Qi – gi) , (6.1) subject to

0 0 Budget constraint wLs + P2Q 2 + P3Q 3 = P1Q1 + P2Q2 + P3Q3 (6.2)

Time constraint L = Ls+ L u + L2 + L3, (6.3)

Where w = market wage rate,

L = total time available, Lu = household’s leisure time, Ls = time working as wage earners outside the household, 0 L2 = labor input into the production of Q 2, 0 L3 = labor input into the production of Q 3, and ∀ Pi, Qi = the price and household consumption of goods i, i.

Equation 6.2 simply states that total income equals total expenditure; that is, savings are not included in this model. Equation 6.3 states that the household spend their time on three activities: leisure, working as wage earners, and 0 production of Q 2 (goods that are produced directly from mangrove forest) and 0 0 0 Q 3 (other goods). The output of the two goods (Q 2 and Q 3) are functions of L2 and L3, respectively, and are also functions of other factors of production such as intermediate inputs and mangrove area. Using a simple mathematical technique, the first- and second-order conditions of maximization, three equations are derived. Equation (6.4) explains a time trade-off between wage earning and the leisure of households. Equation (6.5) states that the minimum level of consumption that the household allocates to the goods is equal to the committed level of consumption of the goods. Equation (6.6) explains how the household allocates its available time to the production of all goods in such a way that the value of the output and the pre- determined wage rate of household members are equal, that is, marginal revenue product of labor equals wage rate.

0 WLu = G(w, gu, Ls, bu, Q 2, Pi, gi). (6.4)

0 PiQi = H(w, Ls, bi, Q 2, Pi, gi). (6.5)

∂ 0 ∂ ∂ 0 ∂ w = P2( Q 2/ L2) = P3( Q 3/ L3). (6.6)

The mangrove dependency ratio of a household can be defined as a ratio between the total income that the household derives directly from mangrove2, Mangrove dependency, income distribution and conservation 103

P2Q2, and the total committed expenditure of the household, wgu + P1g1 + P2g2. The higher value of the ratio indicates a higher dependency of households on mangrove forest. The value of more than one indicates that the household use mangrove forest more than they actually need to maintain the minimum level of economic well-being. In order to investigate the role of various factors, including the degree of a household’s dependency on mangrove forest in its participation in conservation activities, a simple model is proposed, as follows. As for the mangrove conservation practices in the survey areas, the number of conservation activities includes four major types: (1) voluntary replanting of the forest (without payment); (2) taking care of the forest (for example, guarding saplings); (3) setting up rules for the community use of the mangrove; and (4) protection of the forest (including reporting to authorities in cases of forest encroachment). Let D1 and D2 be two dummy variables that explain the household’s participation in conservation activities. Their values are 0 (not participating) and 1 (participating). When Y is the effective level (or aggregation measure) of a household’s participation in mangrove conservation activities, K1, K2, and r are constant terms. The effective level (Y) can be explained by the following CES (constant elasticity of substitution) function:

–r –r 1/r Y = [K1D 1 + K2D 2] . (6.7)

The degree of complementarity and substitution between D1 and D2, (ss) equals 1/(1 + r); ss > 0 when the two activities are complementary and < 0 when they are substitutes. Because of limited information, this chapter assumes that K1 and K2 equal one. The sign of r is determined from correlation between the activities. A positive correlation suggests that they are complementary while a negative correlation points to substitutability between the two activities. The degree of correlation is used to guess the magnitude of r. Table 6.6 presents the correlation coefficient of four conservation activities in the four villages. As shown in the table, these activities are found to be complementary: each household tended to participate in many activities. The value of ss is assumed to be greater than 0. Based on the value of Y, a regression of Y on variables such as mangrove dependency ratio, household size, education background (average schooling years of the household), the number of household members who were not less than 60 years old, total net income and the household’s awareness of an external support for conservation activities, is used to clarify which factors play major roles behind the household’s participation in mangrove conservation activities. It should also be noted that there are two sources of external support on the conservation activities. These are governmental agencies and 104 Case studies: Phang-nga and Nakhon Si Thammarat

Table 6.6 Various conservation activities and sources of external support

1 2 3 4 5 6

1. Government support 1.00 –0.36** — — — — 2. NGO support –0.36** 1.00 — — — — 3. Mangrove replanting — — 1.00 0.18* 0.02 0.38** 4. Taking care of mangrove — — 0.18* 1.00 0.13 –0.07 5. Awareness of community — — 0.02 0.13 1.00 0.16* mangrove utilization rules 6. Mangrove protection — — 0.38** –0.07 0.16* 1.00

Notes: *Significant at 95%, **significant at 99%. non-governmental organizations. A similar CES function is also used to combine the household’s awareness of the support from the two sources. As shown in Table 6.6, the awareness of the two sources of support were significantly negatively correlated and tended to be substitutes. The value of ss is assumed to be less than 0 in this case.

THE ESTIMATED RESULTS AND THEIR LIMITATION

Based on a nonlinear optimization technique,3 the household’s committed level of consumption of goods i (gi) and the household’s marginal budget share of goods i (bi) are estimated. As summarized in Tables 6.7 to 6.10, the total committed expenditure of an average household was highest in Ban Khlong Khut (around 73 310.50 baht/year), followed by that of an average household in Ban Sam Chong Tai (68 043.26 baht/year), Ban Bang Pat (64 729.83 baht/year) and Ban Gong Khong (63 313.15 baht/year). These figures tend to indicate that the standard of living of households in Ban Khlong Khut was relatively higher than that of households in the other three villages. Considering the marginal expenditure of households in these villages (Tables 6.11 to 6.14), the life of an average household in Ban Bang Pat was less dependent on the outside economy than other households. Less than 87 per cent of their additional income was spent on goods that they did not produce and had to purchase from markets. Households in this village also placed a high value on their leisure time. For every additional income of 100 baht, they were happier to sacrifice 2 baht in exchange for leisure time. This explains why the value share of household labor input of this village was relatively lower than that of the other villages. In the cases of Ban Sam Chong Tai, Mangrove dependency, income distribution and conservation 105

Table 6.7 Committed level of expenditure of households in Ban Sam Chong Tai

Good g t-stat P P·g

Leisure time of males 0.82 3.91 13.12 10.75 Leisure time of females 0.11 1.96 6.88 0.79 Leisure time of children 0.61 5.08 10.00 6.14 Demersal fish 54.33 12.38 94.04 5 108.98 Shellfish 28.78 4.09 110.32 3 175.16 Aquaculture products 86.07 80.75 141.00 12 135.36 Wood 339.19 10.84 5.10 1 731.07 Firewood 794.06 25.44 6.29 4 994.22 Other goods 40 880.80 6.17 1.00 40 880.80 Total 42 184.76 NA 387.75 68 043.26

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1.

Table 6.8 Committed level of expenditure of households in Ban Bang Pat

Good g t-stat P P·g

Leisure time of males 0.38 2.76 49.61 18.63 Leisure time of females 0.13 2.43 25.61 3.36 Leisure time of children 0.10 1.26 10.00 1.01 Demersal fish 64.80 6.75 35.06 2 272.00 Shellfish 42.80 4.76 67.70 2 897.49 Aquaculture products 85.95 71.59 60.47 5 197.23 Wood 365.69 11.37 6.00 2 194.13 Firewood 1 016.59 35.47 6.93 7 044.97 Other goods 45 101.02 7.63 1.00 45 101.02 Total 46 677.45 NA 262.38 64 729.83

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1.

Ban Gong Khong and Ban Ban Khlong Khut, households spent more than 90 per cent of their extra income on goods that they had to buy from markets. But they valued their leisure time much less than half a baht for every additional 100 baht that they earned. The three following sections will focus more on the issue of mangrove dependency, poverty and conservation participation. 106 Case studies: Phang-nga and Nakhon Si Thammarat

Table 6.9 Committed levels of expenditure of households in Ban Gong Khong

Good g t-stat P P·g

Leisure time of males 0.85 3.99 37.10 31.51 Leisure time of females 0.13 2.07 24.19 3.09 Leisure time of children 0.64 5.30 10.00 6.41 Demersal fish 60.03 7.08 41.78 2 507.96 Shellfish 28.94 4.21 84.78 2 453.91 Aquaculture products 86.10 83.63 80.54 6 934.48 Wood 338.56 11.60 5.05 1 709.42 Firewood 896.58 31.25 8.00 7 172.67 Other goods 42 493.70 6.94 1.00 42 493.70 Total 43 905.53 NA 292.44 63 313.15

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1.

Table 6.10 Committed levels of expenditure of households in Ban Khlong Khut

Good g t-stat P P·g

Leisure time of males 0.86 3.98 42.46 36.59 Leisure time of females 0.13 2.12 31.17 4.09 Leisure time of children 0.68 5.34 10.00 6.78 Demersal fish 62.58 7.29 42.11 2 635.13 Shellfish 28.94 4.19 114.84 3 323.85 Aquaculture products 86.09 82.44 200.00 17 218.86 Wood 352.99 11.71 5.83 2 057.29 Firewood 897.78 30.20 5.00 4 488.91 Other goods 43 539.00 6.99 1.00 43 539.00 Total 44 969.05 NA 452.41 73 310.50

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1.

Mangrove Dependency Ratio

In terms of the degree of dependency on mangrove forest, the ratio between the income that they derive directly from mangrove and their total committed expenditure indicates that households in Ban Gong Khong depended heavily on mangrove forest. Their mangrove income was around 71 per cent of their total committed expenditure. Households in Ban Sam Chong Tai came second Mangrove dependency, income distribution and conservation 107

Table 6.11 Marginal budget shares of households in Ban Sam Chong Tai

Good Marginal expenditure t-stat

Leisure time of males 0.2809E-4 0.18 Leisure time of females 0.0032 0.85 Leisure time of children 0.4135E-15 0.40E-7 Demersal fish 0.0181 4.42 Shellfish 0.0669 7.77 Aquaculture products 0.4152E-18 0.19E-7 Wood 0.0082 2.98 Firewood 0.7411E-18 0.20E-7 Other goods 0.9036 NA Total 1.0000 NA

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1.

Table 6.12 Marginal budget shares of households in Ban Bang Pat

Good Marginal expenditure t-stat

Leisure time of males 0.0002 0.21 Leisure time of females 0.0027 0.70 Leisure time of children 0.0171 0.51 Demersal fish 0.0249 4.26 Shellfish 0.0830 8.14 Aquaculture products 0.2649E-18 0.13E-7 Wood 0.0053 1.65 Firewood 0.1010E-15 0.39E-6 Other goods 0.8668 NA Total 1.0000 NA

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1. as their mangrove income was around 49 per cent of their total committed expenditure. The existence of mangrove forest is an important factor behind the well-being of households in these two villages. On the opposite side, households in Ban Bang Pat and Ban Khlong Khut tended to be more dependent on income from the indirect use of mangrove forest in terms of offshore fisheries. The mangrove dependency ratio for households in these two villages was much less, only around 17 and 15 per cent of their total committed expenditure, 108 Case studies: Phang-nga and Nakhon Si Thammarat

Table 6.13 Marginal budget shares of households in Ban Gong Khong

Good Marginal expenditure t-stat

Leisure time of males 0.2060E-4 0.15 Leisure time of females 0.0039 0.92 Leisure time of children 0.1038E-13 0.22E-6 Demersal fish 0.0191 4.25 Shellfish 0.0668 8.43 Aquaculture products 0.1474E-14 0.11E-5 Wood 0.0079 2.89 Firewood 0.1287E-19 0.40E-8 Other goods 0.9023 NA Total 1.0000 NA

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1.

Table 6.14 Marginal budget shares of households in Ban Khlong Khut

Good Marginal expenditure t-stat

Leisure time of males 0.7531E-5 0.84E-1 Leisure time of females 0.0036 0.83 Leisure time of children 0.7824E-17 0.79E-8 Demersal fish 0.0191 4.09 Shellfish 0.0691 7.49 Aquaculture products 0.2673E-17 0.44E-7 Wood 0.0067 2.29 Firewood 0.1564E-16 0.12E-6 Other goods 0.9015 NA Total 1.0000 NA

Note:NA= not available; all figures in Thai baht/year; 40 Thai baht = US$1. respectively. These are presented in Table 6.15. However, if we calculate their income derived from captured fisheries, a form of indirect use of mangrove, as a percentage of their committed expenditures, the ratio became approximately 103 and 159 per cent, respectively. In addition to the local communities’ heavy dependence on mangrove forest, empirical evidence suggests that the distribution of dependency on mangrove of households was different across villages. Households in Ban Gong Khong and Ban Sam Chong Tai were both more dependent on mangrove Mangrove dependency, income distribution and conservation 109

Table 6.15 The committed level of expenditure (S Pigi), mangrove 0 dependency income (P2Q 2) and mangrove dependency ratio 0 (P2Q 2/(S Pigi) of households in the four villages

0 0 Village S Pigi P2Q 2/S Pigi P2Q 2/S PigI Mean SD CV

Ban Sam Chong Tai 68 043 32 848 0.49 0.45 0.91 Ban Bang Pat 64 730 11 050 0.17 0.23 1.35 Ban Gong Khong 63 313 45 447 0.71 0.76 1.07 Ban Khlong Khut 73 311 10 836 0.15 0.28 1.87

Note: SD = standard deviation, CV = coefficient of variation; all figures in Thai bhat; 40 baht = US$1. forest than households in the other two villages. The coefficient of variation (CV) of their mangrove direct dependency ratio was around 1.07 and 0.91, respectively. Thus the degradation of mangrove forest will affect the economic well-being of households in the two mangrove-dependent villages quite equally. Nevertheless, the adverse impact could be relatively stronger on households in higher-income brackets. Reasons were that the dependency ratios were positively correlated to net income of households in Ban Sam Chong Tai, and significantly positively correlated to the net income of households in Ban Gong Khong (Table 6.16). This was because of the poorer conditions of the fishing tools of low-income households in Ban Sam Chong Tai and the extensive use of wood products from mangrove forest by high-income shrimp farmers in Ban Gong Khong, respectively. In the case of Ban Khlong Khut and Ban Bang Pat, the degradation of mangrove forest affected the economic well-being of each household unequally and the impact tended to be more severe on households in lower- income brackets. This is explained by the coefficient of variation of mangrove

Table 6.16 The correlation between dependency ratio and net income

Village Direct dependency ratio Correlation

Ban Sam Chong Tai 0.49 0.169 Ban Bang Pat 0.17 –0.136 Ban Gong Khong 0.71 0.479* Ban Khlong Khut 0.15 –0.185

Note: *Significant at 99% level; all figures in Thai bhat; 40 Thai baht = US$1. 110 Case studies: Phang-nga and Nakhon Si Thammarat dependency ratio that was relatively high (1.87 and 1.35) and the correlation between the ratio and their net income that was slightly negative.

Mangrove Dependency and the Incidence of Poverty

This section focuses on the impacts of mangroves on poverty in the coastal communities. In order to investigate such impacts, two points will be analyzed: the incidence of poverty or the percentage of poor in the total population in the four villages and the degree of relationship between poverty incidence and direct income that households derived from products collected out of mangrove forest. A poor person is defined as an individual whose income falls below a minimum standard level or a poverty line. Indirect income, that is, income from coastal fisheries, is not included in this case. The incidence of poverty in these coastal villages was found to be significantly different from the national level. By applying the old World Bank rural poverty line (Astra Meesook 1979), around 7160 baht/person/year, the incidence of poverty in Ban Khlong Khut was found to be the least and much less than those in the other three villages (Table 6.17). The percentage of poor people in the population of Ban Khlong Khut was 3.41 per cent while in Ban Sam Chong Tai, Ban Bang Pat and Ban Gong Khong it was 9.62, 11.83, and 11.79 per cent, respectively. The overall incidence of poverty in the rural areas of Thailand was around 8 per cent in 1999.4 As a source of households’ income, the utilization of mangrove forest has brought a considerable number of people in these villages out of poverty. Had there been no income from the direct uses of mangrove forest, poverty incidence in these four villages would have been more severe than it actually was. Excluding income from the direct uses of mangrove forest, the percentage of the poor in the total population of Ban Gong Khong and Ban Sam Chong Tai would have been 55.28 and 48.08 per cent, respectively. This was around five

Table 6.17 The incidence of poverty in the four villages

Village Direct Head count Head count dependency ratio ratio1 ratio2

Ban Sam Chong Tai 0.49 48.08 9.62 Ban Bang Pat 0.17 20.71 11.83 Ban Gong Khong 0.71 55.28 11.79 Ban Khlong Khut 0.15 13.64 3.41

Notes: 1. Based on net income excluding net direct income. 2. Based on net income including net direct income. Mangrove dependency, income distribution and conservation 111 times the actual levels of the incidence of poverty in the two villages. As already mentioned, households in these villages depended heavily on mangrove forest. Similarly, the incidence of poverty would have been 20.71 per cent for Ban Bang Pat and 13.64 per cent for Ban Khlong Khut, respectively. This was also more severe than the national poverty incidence. Direct income from forest area had reduced the incidence of poverty in these two villages by around 9–10 per cent. Nevertheless, it should be noted that, with some possible substitution effect, the actual impact on poverty alleviation by mangrove might be lower than the above results suggest. With no mangrove forest, some poor villagers may find jobs elsewhere and earn more income in order to bring themselves out of poverty. At this point, however, it might not be an over-exaggeration to conclude that mangrove forests act as a social safety net for poor coastal communities.

Conservation Activities and Mangrove Dependency Ratio

It is believed that many factors have played important roles behind households’ participation in various conservation activities. These include their dependency on mangrove forest, their awareness of external supports, and the elderly in each household who saw the benefit of living near mangrove forest. Their education background, household income and household size could also have impacts on households’ participation in conservation activities. However, because these variables are highly correlated with the mangrove dependency ratio and have potential to create some estimation problems, they were excluded from this analysis. Despite low explanatory power, regression results point to the roles of many factors behind the decision of households to participate in conservation activities (Table 6.18). First, households’ awareness of external support was found to be a significant determining factor in the decision of households in Ban Gong Khong and Ban Khlong Khut to participate in mangrove conservation activities. In the other two villages, although insignificant, the role of external support was also positive. Thus the existence of external support, from both government agencies and NGOs, could activate the participation of households in various conservation activities. Second, in terms of households’ dependency on mangrove forest, the relationship differed among villages. For villages in which households were heavily dependent on income from mangrove forest, that is, Ban Sam Chong Tai and Ban Gong Khong, households that were more dependent on mangrove forest were more likely to participate in one or more conservation activities. High dependency on mangrove forest leads to a greater appreciation of the long-term benefit of the forest by households. The opposite was true for households in the other two villages, Ban Bang Pat and Ban Khlong Khut, 112 Case studies: Phang-nga and Nakhon Si Thammarat

Table 6.18 Determinants of households’ participation in conservation activities

Variable Ban Sam Ban Bang Ban Gong Ban Khlong Chong Tai Pat Khong Khut

Constant 1.492* 2.087** 0.043 0.235 (2.309) (2.731) (0.135) (1.286) Awareness of external 0.614 0.215 0.930** 0.893** supports (1.075) (0.372) (2.787) (3.641) Dependency ratio 0.159 –0.093 0.067 –0.327 (0.398) (–0.108) (0.377) (–0.739) Members aged not less 0.187 –0.112 –0.427 –0.098 than 60 years old (0.571) (–0.171) (–1.422) (–0.501) R2 0.029 0.005 0.153 0.237

Notes: *Significance at 95 per cent. **Significance at 99 per cent. The degree (elasticity) of substitution between various conservation activities equals –4 and the degree of complementarily between households’ awareness of the two sources of external support equals 4. which were less dependent on mangrove forest. Households that were more dependent on mangrove forest tended to have less participation in the conservation activities. It should be noted again that, in these two villages, poorer households were more dependent on mangrove forest. Thirdly, the statistical significance of intercept terms in the case of Ban Sam Chong Tai and Ban Bang Pat indicates that the role of some other factors was not well captured by the model. These factors could be the type of land title and past experience. In the case of the number of the elderly, excepting the case of Ban Sam Chong Tai, results suggest that having old people in households was not a crucial factor in households’ decision to join conservation activities. The above results are based on assumptions that various conservation activities were highly substitutable and awareness of the two sources of support were highly complementary. When the assumptions are relaxed by reducing the degree of substitution and complementarity, findings do not differ significantly. Exploring the factors influencing the participation in mangrove conservation, especially the impacts of households’ mangrove dependency on conservation, can be quite complex. We have to realize that a decision to participate in the conservation of mangroves is quite different, for example, from a decision to adopt soil conservation in order to improve farm productivity. In the Mangrove dependency, income distribution and conservation 113 latter case, the decision is entirely based on an individual, whereas in the former case the decision is also based on a group’s decisions. The adoption of soil conservation directly benefits the decision maker through improving soil quality and nutrients. One may argue that soil conservation also prevents soil erosion, which creates externalities. However, the success of soil conservation in one’s farmland is almost entirely up to the owner who will make his or her own decision whether to invest in the practice. The conservation of mangroves is quite different; it is actually a collective choice since the success of the activity depends on the cooperation of a group. It is also likely that one will participate in the activity only if others do. At the same time the problems of free-riding can obstruct successful conservation. When we conducted a regression analysis to understand factors which have influences on the decision to participate in the conservation of mangroves, we focused on a household level. However, as mentioned earlier, this type of decision is based on collective choice. An individual will make a decision interde- pendently with others; he will cooperate on condition that his colleagues do likewise. The individual decision-making model without such interdepen- dency is likely to omit a crucial element and might not reflect very accurate results. Moreover, for achieving better understanding, an additional analysis at the village level should also be carried out so as to identify factors influencing the cooperation capability of the communities. For example, villages with a closely-knit and homogeneous culture, such as Muslim society, tend to be more effective in enforcing community rules, thus promoting successful conservation of mangroves. Unfortunately, with data limitation, we would not be able to incorporate all these important points. This might explain why the results from the regression do not seem to be consistent. At the beginning of the study, through interviews with villagers and general observation, we suspected that dependency on mangroves will play a crucial role in the decision whether or not to participate in conservation. However, the results of the regression analysis produced low explanatory power to support a hypothesis that mangrove dependency has a significant influence on conservation. This my be either the result of an inaccuracy of the regression analysis or an accurate reflection of reality. On the one hand, it may be that those who rely on the mangrove realize its significance and would like to conserve the resource, as in the case of Ban Sam Chong Tai and Ban Gong Khong households. On the other hand, those who depend on the mangrove too much may actually be exploiting it without considering the long-term impact, like those in Ban Bang Pat and Ban Khlong Khut. However, it is also interesting to note that the poorer households in Ban Bang Pat tend to participate in mangrove conservation more than their richer household neighbors. The decision to participate in the mangrove conservation may require a synergism of various influences such as awareness, support and effective collective rules. 114 Case studies: Phang-nga and Nakhon Si Thammarat

NOTES

1. 40 Thai baht = US$1. 2. Due to data and information constraint, we will focus only on income estimated from the direct use of mangrove such as from the collection of wood and fishery products in the forest. Income from the indirect use of the mangrove in terms of offshore fisheries is not included. 3. Shazam version 8.0. 4. This was lower than the official poverty incidence of around 22 per cent. The official figure was based on a higher poverty line. 7. Household use of mangrove and mangrove conservation decisions Edward B. Barbier, Mark Cox and Isra Sarntisart

INTRODUCTION

The following analysis focuses on the mangrove conservation decisions of households in the four case study coastal villages of southern Thailand. As the previous chapters have indicated, in recent decades the traditional livelihoods of these villagers have been affected by the widespread mangrove deforestation that has occurred in Thailand, especially in southern coastal areas. The major cause of this forest loss has been the conversion of mangroves to commercial shrimp farms, as well as other coastal developments. Given this rapid loss of mangroves, many local communities in southern Thailand have increased their efforts to preserve the remaining forests from which they have traditionally benefited. These conservation efforts have included forest protection and replanting of degraded areas. However, the urban, industrial and tourist developments in the coastal areas not only have contributed to mangrove deforestation but also have led to economic development, demographic change and new employment opportunities in these areas. Therefore, with the rapid demographic, economic and social changes occurring in coastal areas, the willingness of households traditionally dependent on mangroves to participate in local conservation initiatives may vary considerably. This chapter will test the hypothesis that the degree of mangrove dependency is a major causative factor in the active participation of households from the four case study villages in conservation efforts. The hypothesis is that, once households realize that, as mangrove area declines they will experience a reduction in their economic livelihoods, the households will participate in the replanting of mangroves. Whether households choose to be involved in mangrove conservation is also likely to vary with the characteristics of the household and its location, land ownership and tenure considerations, awareness of and attitudes to community conservation efforts, including the replanting programs sponsored by non-governmental organizations and some

115 116 Case studies: Phang-nga and Nakhon Si Thammarat international organizations, and concerns over the threat of the environmental impacts of shrimp farms. In addition, the decision to participate in mangrove conservation may vary between the male and female members of the household. The purpose of the following analysis is to examine how these various factors influence the willingness of mangrove-dependent households in the four case study villages to participate in local conservation efforts. To undertake this analysis, we first develop a model of the key aspects of the household’s behavior that may influence its decision to undertake conservation.

AN AGRICULTURAL HOUSEHOLD MODEL OF LABOR ALLOCATION AND CONSERVATION

Consider a representative rural household that may participate in three main types of economic activity. First, it is assumed that the household always undertakes some form of resource-based production activity. In the case of mangrove systems, such activity could consist of either direct or indirect use of mangrove resources (Barbier 1994). For example, direct use of resources from a mangrove forest may include wood collection, for fuelwood, charcoal production and other wood products, and harvesting of fish and shellfish in mangrove swamps. The household may also harvest fish from a coastal fishery, which is indirectly dependent on the mangroves as a breeding and nursery habitat. In addition, the household may engage in another productive activity, such as agriculture, which is not directly or indirectly dependent on the mangrove forest. Finally, the household may also undertake paid work, for which it receives a market wage. To focus the analysis, and with little loss of generality, we assume that this representative rural household is a price taker in all markets for the commodities that it both consumes and produces. Although some mangrove-dependent households are likely to produce and consume non-marketed goods, we will make the standard assumption that such activities can be subsumed under the broad category of leisure (Barnum and Squire 1979). Thus the profit and utility-maximizing decisions of the household are determined recursively, that is, optimal household production is determined first and independently of consumption and leisure choices. The purpose of such assumptions is that it allows us to examine a key household decision, which is the household’s choice to participate in community mangrove conservation activities, such as replanting and forest protection. Finally, to sharpen the analysis and to simplify notation, the following theoretical model will treat aggregate household labor as homogeneous. However, in empirically applying the model, this assumption will need to be Mangrove conservation decisions 117 relaxed, as the decision of male and female members of the household as to whether or not to participate in mangrove conservation may need to be differ- entiated. In any period, the mangrove-dependent household is assumed to maximize a utility function with the standard properties

U = U(x, lu, C; y), (7.1) where x is a market-purchased consumption good, lu is leisure, C is the household’s total consumption from its own resource-based production activities, and Y are exogenous characteristics of the household and its location that may also affect utility. If y1 is the household’s production of the resource-based good (for example, fuelwood/charcoal, fish, shellfish) obtained from direct or indirect use of the mangroves, then the following production technology is assumed:

1 y1 = f (11, v1; S, Z) ≥ c1, (7.2) where l1 and v1 are respectively the labor and purchased inputs employed to produce y1. In addition, production of the resource-based activity will be affected by the ‘state’, or condition, of the area of mangrove forest, S, that the household requires to support this activity and by various exogenous factors, Z. The latter may consist of household characteristics affecting production decisions, fixed production factors and aspects associated with the household’s location. Finally, the household may or may not consume, c1, all of the resource that it extracts from the mangrove forest or harvests from the mangrove-dependent coastal fishery. If the household is also an agricultural producer, then y2 is the household’s agricultural output (for example, crops):

2 y2 = f (12, v2; Z) ≥ c2, (7.3) where l2 and v2 are the labor and purchased inputs employed in agriculture, and Z are the exogenous fixed factors as defined previously. Again, the household may or may not consume, c2, all that it produces. Finally, the household may defer to other households in the community in mangrove conservation. However, to be successful in maintaining the state of the mangrove area, S, such conservation activity requires active participation from a large number, j = 1, . . . , J, households. Thus mangrove conservation is based on

S = g(S E ; S , A, G), E = fs(l , v ), j = 1, . . ., J. (7.4) j j 0 j s s 118 Case studies: Phang-nga and Nakhon Si Thammarat

th where Ej is the conservation effort provided by the j household, and lS and vS are the labor and purchased inputs, respectively, necessary for this effort. S0 is the initial ecological state, or degree of degradation, of the mangrove forest, A is the mangrove area available to the community and G is exogenous government or NGO expenditures on mangrove conservation. Given market prices, px, pvS, pyi and pvi, i = 1, 2 for the corresponding commodities and the market wage rate, w, the household also faces the following cash income constraint:

pxx + S pviv + pvsv = S pvi(y – c ) + w(L – lu – l – S 1 ) i i S i i i S i i + M, i = 1, 2. (7.5)

The left-hand side of (7.5) represents the cash purchases by the household, and the right-hand side is its income. If (7.2) and (7.3) are strict inequalities, yi > ci, then the first term on the right-hand side is the marketed surplus of the resource-based product (for example fuelwood, fish and crop sales). Denoting u L as the total labor time available to the household implies that L – l – lS – Sli = lw is net labor supply. Thus, if the latter term is positive (lw > 0), then the household engages in other labor employment and receives the wage, w. If the term is negative (lw < 0), then the household is hiring labor for use in its production activities. The final term on the right-hand side, M, represents exogenous non-labor income (that is, remittances, social transfers, rents). Re-arranging (7.5) leads to a single ‘full income’ constraint for the household:

pxx + S pyiv + pvsv + w(lu + l ) = S (pyiy – pviv – wl ) + wL i i S S i i i i + M = I, i = 1, 2. (7.6)

The left-hand side of (7.6) represents the ‘full expenditure’ of the household, including its ‘purchases’ of its own consumption and of its own time in the form of leisure or inputs into conservation effort. Equally, the right-hand side is the household’s ‘full income’, I, which includes any profits earned from its various production activities. Finally, not all mangrove-dependent households may engage in agriculture or participate in mangrove conservation, and so the following additional constraints hold:

y1 > 0, y2 ≥, ci ≥ 0, vi ≥ 0, l1 > 0, l2 ≥ 0, vS ≥ 0, lS ≥ 0, M ≥ 0, x > 0 and C = S c , i = 1, 2. (7.7) i i Maximizing household utility (7.1) with respect to full income (7.6), the conditions (7.2) to (7.4) and the constraints (7.8) will yield the optimal levels Mangrove conservation decisions 119

u of consumption of x, C and l , and of the purchased and labor inputs, vi, li, vS and lS, respectively. However, as the model is recursive, these optimal values can be derived in two stages. The first-order conditions indicate that optimal choice of each input is determined solely by equating its marginal revenue product with the respective market price. As a consequence, the profit-maxi- yi vi vS mizing input demands for vi, li, vS and lS are functions of the prices, p , p , p and w, and thus are independent of the household’s consumption and leisure decisions. Substituting these optimal input levels into (7.7) yields a corresponding profit-maximizing level of full income, I*. The model can then be solved for the utility-maximizing levels of the commodities and leisure, x, C and lu, as functions of prices, px, pyi and w, and I*, as well as the exogenous determinants, y, Z, S0, A and G. From the above model, it is possible to use the components of the profit- maximizing level of full income, I*, to test the hypothesis that a household more dependent on the mangrove system for its welfare will invest more in its conservation. Basically, this hypothesis can be restated as follows:

vS * * y1 * vi * * p v S + wl S p y 1– p v 1 – wl1 —————— increases as ———————— , i = 1, 2 increases. (7.8) I* I*

Solution of the full profit and utility-maximizing conditions of the model can also be employed to examine the determinants of the household’s decision of whether or not to participate in community mangrove conservation. To illustrate this, we will focus on the first-order conditions concerned with the household’s optimal allocation of labor inputs, assuming that the household is also engaged in agricultural production (y2 > 0), undertakes outside employment w (l > 0) and produces marketed surpluses (yi > ci). Thus, for the mangrove- dependent household, the optimal choices of li and ls are governed by

∂fi  ∂f1 ∂S   ∂f1 ∂S  pyi —— = w,  py1 ——— — – w  ≤ 0, l ≥0, py1 ———— – w  l = 0 ∂  ∂ ∂  S  ∂ ∂  S li S lS S lS or (7.9)

∂ i ∂ i ∂ ∂ ∂ ∂ ∂ S f f S S g Ej f pyi —— = w ≥ py1 ————, —— = —————— i = 1, 2. ∂ ∂ ∂ ∂ ∂ ∂ S ∂ li S lS lS Ej f lS

Condition (7.9) states that the household will equate the marginal returns to resource-based and agricultural activities, and these returns must in turn equal the market wage, w. Any labor allocated to mangrove conservation by the household will also benefit it by increasing the marginal returns to any production that 120 Case studies: Phang-nga and Nakhon Si Thammarat depends on the state of the mangrove forest, S. However, whether it is worthwhile for the household to allocate any of its time to conservation will depend on whether the additional returns to mangrove-based production through its conservation effort is worth the opportunity cost of this labor allocation. Clearly, if the opportunity cost of household labor allocated to conservation is insufficiently compensated by the returns it receives from this effort

∂f1 ∂S (that is, w > pyi ————), ∂ ∂ S lS the household will not participate in the labor market (lS = 0). Solution of the above first-order conditions plus those governing profit- maximizing use of purchased inputs, vi, will yield the following optimal labor input demands

* yi vi vS l i = li(w, p , p , p ; Z, S0, A, G), * yi vi vS lS = lS(w, p , p , p ; Z, S0, A, G) ≥ 0. (7.10)

As noted, the corresponding profit-maximizing level of full income, I*, can be employed in the above model to solve for the utility-maximizing levels of consumption decisions of the household with respect to goods and leisure. The result is the following optimal indirect utility function, V, for the mangrove- dependent household:

* yi vi vs * * V = V(w, p , p , p , I ; y, Z, S0, A, G), lS ≥0. (7.11)

If we assume that the above indirect utility function can be linearized, and denoting the vector of explanatory variables as X, the decision of the mangrove-dependent household to participate in community conservation efforts can be formulated as

* * V | * = V (1) = bX + e lS > 0 1 1 * * (7.12) V | * = V (0) = bX + e . lS = 0 0 0 Equation (7.12) indicates that the household’s choice whether or not to allocate any labor to mangrove conservation can be depicted as a binary decision to participate, and can therefore be empirically specified as a probability model,

* * Pr(V (1) > V (0)) = Pr(e0 – e1 ≤ bX1 – bX0) * = Pr(e < bX), z = bX + e, e = e0 – e1, bX = bX1 – bX0, (7.13) Mangrove conservation decisions 121 where z * is the latent dependent variable of the regression. Over the sample of k = 1, . . . , K mangrove-dependent households in the community, the observed * * counterpart to z is zk = 1 if zk > 0 and zk = 0 if zk* < 0. The above binary choice model can be estimated through standard univariate probit or logit procedures. Correction for heteroskedasticity across the sample may also be necessary. So far, the above model has assumed that all labor in the mangrove-dependent household is equivalent, and the household makes a uniform decision with regard to allocating this labor to conservation efforts. However, if household labor is not homogeneous and the decisions of male and female members of the household to participate in mangrove conservation need to be distinguished, the joint probabilities of participation by males and females need to be estimated through a bivariate probit model. The relevant estimation now becomes

* zk(m) = b(m)Xk(m) + ek(m) * * zk(m) = 1 if z k(m) > 0, and 0 otherwise m = 1, . . . , M, (7.14) where M represents the separate members of each of the K households whose decisions to participate in conservation need to be distinguished; for example, if adult male and adult female members make separate decisions whether or not to be involved in mangrove conservation, then M = 2. Although each individual equation in (7.14) is a standard probit model, the individual error terms, ek(m), have a bivariate normal distribution and are jointly correlated. Thus for M > 1, bivariate probit estimation of (7.14) is required to yield the coefficients b(m) relevant to the participation decision for male and female labor, respectively, in the household as well as correct for any correlation between error terms. Alternatively, if household labor is homogeneous and there is no need to distinguish the conservation decision of different members, then M = 1 and (7.14) reduces to the binary choice model of (7.13) that can be estimated by univariate probit or logit methods. From (7.11) it is clear that the exogenous variables, Y, Z, S0, A and G, included in X in the above regressions, will be critical to the empirical analysis of the conservation decisions of mangrove-dependent households. Some of the household and production/income characteristics that comprise y and Z will be the standard variables used in many analyses of household’s dichoto- mous choices, such as age, education, household composition, number of children, debt and size of land holding. However, some of these characteristics will be unique to mangrove-dependent households in southern Thailand: for instance, distance of the household from mangrove forests used, whether land ownership is documented, the number of years the household has been in the village and the location from which the household may have migrated. As noted above, particularly important determinants of the household’s decision 122 Case studies: Phang-nga and Nakhon Si Thammarat to participate in conservation efforts may be influenced by awareness of and attitudes to community conservation efforts, and concerns over the threat of the environmental impacts of shrimp farms. Finally, the additional determinants in (7.11), S0, A and G, are specific to the model of mangrove-dependent household behavior developed here. Unfortunately, it is not possible to include empirically a set of indicators that represent the general state of the mangroves, S, in each village location. Therefore the state of the mangroves and A, the area of mangroves, will be encompassed by the variable area of mangrove utilized by the household. In addition, estimates of G are not included, owing to lack of quantitative information, but this issue will be discussed further below.

BACKGROUND

The four case study coastal villages used throughout all the chapters in Part II were also the focus of the analysis of the conservation decisions of mangrove- dependent households. A randomly stratified survey at two study sites, Nakhon Si Thammarat (east coast) and Phang-nga (west coast) was conducted during April–July 2000. Personal interviews of the head of the household were conducted by trained enumerators speaking the local language, using a pre- tested survey designed under the supervision of the authors and a team of Thailand-based researchers. Pre-testing of the questionnaires was conducted in February 2000. The first stage of the survey was conducted in Phang-nga from 17 to 23 April 2000. The second stage of the survey in Nakhon Si Thammarat was carried out from 2 to 8 July 2000. The survey gathered information on household involvement in conservation activities, the type of activity as well as labor time allocation to conservation and income earned, if any. In addition to the detailed labor allocation to conservation information the survey also gathered the important household characteristics such as age, education, household composition, number of children, debt and size of land holding, and various production/income characteristics. Other factors included distance of the household from mangrove forests used, whether land ownership is documented, the number of years the household has been in the village, and the location from which the household may have migrated. Questions were also posed to evaluate the awareness of and attitudes towards community conservation efforts, and concerns over the threat of the environmental impacts of shrimp farms. The survey gathered detailed information on the mangrove-based activities of households and in particular the area of mangrove utilized by the household. Detailed information on alternative employment was also gathered to establish if the household was undertaking employment that was not dependent on mangroves. Mangrove conservation decisions 123

At each site two villages were surveyed: Ban Khong Khut and Ban Gong Khong in Nakhon Si Thammarat and Ban Sam Chong Tai and Ban Bang Pat in Phang-nga. Ban Sam Chong Tai and Ban Bang Pat are located in Phang-nga Bay, the former having only poor road access and consisting mainly of conservative fishing households that are opposed to modernization. Ban Bang Pat is quite different. The village is located on the main highway and is highly commercialized and relatively modern. Villagers here engage in various commercial enterprises and it is not uncommon for members of the same household to own both rubber plantations and commercial shrimp farms. Ban Khong Khut and Ban Gong Khong both have relatively high levels of urbanization and commercialization. Even though the villages are located on the coast, few people engage in fishing and a larger percentage of household members turn to outside employment. There are many factories in which villagers are employed and many villagers are also hired as labor in commercial shrimp farms, most of which are owned by outsiders. The mangrove areas in Ban Sam Chong Tai have been degraded mainly by forest concessions. According to the law, forest concessionaires are required to replant but, in reality, reforestation has never taken place. Although the forests have not been completely cleared, several areas have been destroyed in this manner. In Ban Bang Pat the mangrove forests were first cleared by tin mining concessions. These activities not only destroyed the forests but also created enormous water pollution in the area. After the prices of the mineral fell drastically, and with the severe decline of mangroves, the Cabinet Resolution on 23 July 1991 abolished tin mining in mangrove forests all over the country. However, the areas became open-access areas upon which anyone can encroach and became a suitable location for conversion into shrimp farming. There are few remaining mangrove areas in Nakhon Si Thammarat. The major cause of the conversion of the mangrove areas along the east coast has been shrimp farming. Historically, commercial shrimp cultures have long been established on the Gulf of Thailand because road access was better than on the Andaman Coast, and it has been suggested the mangrove areas were more easily converted to shrimp ponds. Mangrove areas in Nakhon Si Thammarat have in fact decreased by as much as 336 317 rai (53 811 ha) or 87.93 per cent during the period of 1961–1996. These statistics are much higher than the deforestation rate of 123 388 rai (19 742 ha) or 33.56 per cent in Phang-nga over the same period. At present in Phang-nga there are still 238 362 rai (38 138 ha) of remaining mangrove area, compared to only 46 183 rai (7389 ha) in Nakhon Si Thammarat. In Ban Sam Chong Tai village in Phang-nga Bay, the local community is quite active in the conservation of mangroves. They involve an area of 300–400 rai (48–64 ha), which actually belongs to the state, as their own community forest. These villagers are small-scale fishermen who recognize 124 Case studies: Phang-nga and Nakhon Si Thammarat the important linkages between mangrove areas and capture fisheries. They have set up rules for wood collection and now replant some degraded areas, with some support from a government project. However, it is important to note that the village leader has initiated the idea of reforestation himself and asked for support from outsiders. In Ban Bang Pat, the local community also participates actively in the replanting of mangroves. However, replanting projects in Ban Bang Pat were originally initiated by non-governmental organizations that encouraged the villagers to replant the degraded areas. The situation is similar in the villages of Nakhon Si Thammarat where many re-planting schemes have been initiated under non-governmental or Royal Forestry Department supervision.

EMPIRICAL RESULTS

Table 7.1 provides a brief set of summary statistics for the entire sample split by the type of mangrove activities the household was predominately involved in. The table reports the percentage of households that are aware of the negative environmental impact of shrimp farming, the percentage of households that desire shrimp farming in their village and the percentage of households

Table 7.1 Summary statistics for conservation activities, by household type

Fish only1 Collect only2 Fish and collect3 n = 32 n = 63 n = 104

HH aware of impact of shrimp farms (%) 59 59 88 HH wanting shrimp farms in village (%) 38 43 20 HH aware and want shrimp farms (%) 9 10 12 HH with males replanting (%) 41 44 64 HH with females replanting (%) 9 25 48 Male hrs/year replanting 6 36 28 Female hrs/year replanting 1 15 11

Notes: 1. Fish only households are households that are only indirectly dependent on mangroves through fishing activities but are not involved in collection of mangrove products. 2. Collect only households are households that are directly involved in collection of mangrove products but have no indirect dependence in the form of fishing or aquaculture. 3. Fish and collect households encompass the remainder of the sample who are involved in both direct and indirect use of mangroves. Mangrove conservation decisions 125 who are aware of the environmental impact but still want shrimp farms in their village. The table also reports the percentage of household males and females involved in replanting and the hours spent by both sexes in replanting. The results show that those households that are involved in both fishing and collection activities have a higher percentage of males and females involved in replanting of mangroves. The hours devoted to replanting per year are, however, very low and essentially this is the main reason why we did not attempt to estimate labor supply to conservation but focused instead on the willingness to participate. The awareness of the negative environmental impact of shrimp farming was highest also amongst those that were involved in both fishing and collection activities. However, those households that were involved in only collection activities had the highest percentage wanting shrimp farms in their village. The percentage of households that were aware of the environmental impact and still wanted shrimp farms was low across all household types. Table 7.2 reports the same analysis, but this time by village. The results show that awareness of the impact of shrimp farms is much lower in the villages of Nakhon Si Thammarat and the desire to have shrimp farms is much higher than in the villages of Phang-nga. This result is surprising given the fact that the effects of shrimp farming in Thailand are nowhere else as evident as they are in the east coast regions such as Nakhon Si Thammarat. In Phang-nga

Table 7.2 Summary statistics for conservation activities by village

Phang-nga Nakhon Si Thammarat

Ban Sam Ban Bang Ban Gong Ban Khong Chong Tai Pat Khong Khut n = 55 n = 41 n = 52 n = 51

HH aware of impact of shrimp farms (%) 98 100 48 55 HH wanting shrimp farms in village (%) 0 2 71 43 HH aware and want shrimp farms (%) 0 2 27 12 HH with males replanting (%) 87 85 21 27 HH with females replanting (%) 62 68 8 6 Male hrs/year replanting 23 19 62 2 Female hrs/year replanting 14 9 19 0.3 126 Case studies: Phang-nga and Nakhon Si Thammarat replanting activity also appears to be higher amongst males and females of Ban Sam Chong Tai and Ban Bang Pat. The data from the survey were compiled in LIMDEP7 (Econometric Software, 1995) and used to estimate the joint probability of household male and female participation in replanting activities utilizing the bivariate probit regression. Table 7.3 provides a list of variable definitions and summary statistics. Table 7.4 presents the results of the maximum likelihood bivariate probit estimates of the equations explaining the probability of males and females participating in replanting (equation 7.14). The marginal effects of the regressors on the probability of participation in replanting, which are calculated by multiplying the coefficient by f(b′x)b at the mean values are also reported (Maddala 1983). The estimate of r (rho), which represents the correlation between error structures, that maximized the bivariate probit likelihood function, was 0.6817 and was significantly greater than zero at the 1 per cent level. This suggests that the random disturbances in the replanting participation decisions of males and females are affected in the same direction by random shocks and that their participation decisions are not statistically independent. Thus inefficient parameter estimates may be obtained if the equations are estimated using separate probit models for males and females. The log-likelihood ratio statistic was significant at the 1 per cent level, suggesting that the independent variables taken together influence participation decisions. The McFadden (pseudo) R2, and indication of goodness of fit, is 0.4 (ibid.). Finally, a likelihood ratio test for homoskedasticity could not be rejected, therefore no correction for heteroskedasticity in the variables was made. The results show that, in the male equation, the decision to participate is most greatly influenced by household awareness of community conservation efforts and utilization rules, as shown by the positive coefficient and highest marginal probability. The degree of mangrove-dependent income is second. The coefficient on the MDI variable is positive and significant, with a marginal probability of 0.28. The household’s awareness of the environmental impact of shrimp farming is the other significant variable in the male equation. The positive coefficient and marginal probability of 0.13 suggest that males from households that are aware of the negative environmental impact of shrimp farms are more likely to participate in replanting. In the female equation the results show that the degree of mangrove-dependent income is the most important variable and is significant at the 10 per cent level. This is interestingly followed by the distance to the mangroves from the household. The negative coefficient suggests that females from households that live increasing distances from the mangroves are less likely to participate in replanting. The area of mangrove utilized by the household is also important in the female decision. The result suggests that females from households Table 7.3 Variable definitions and summary statistics

Variable Definition Mean Std dev. Min Max N

ADULTF Number of adult females in household 1.46 0.7897 0 6 199 ADULTM Number of adult males in household 1.64 0.9533 0 5 199 AGEH Average age of household 26.18 10.0935 12 73 199 ATSFARM If household believes shrimp farming has a negative environmental impact ATSFARM = 1, otherwise = 0 0.74 0.4384 0 1 198 AWARE If household is aware of community conservation efforts and utilization rules AWARE = 1, otherwise = 0 0.63 0.4832 0 1 199 CHILD12 Number of children 6–12 0.83 0.8806 0 4 199 CHILD6 Number of children < 6 0.55 0.6404 0 2 199 DF If any household females participate in outside employment DF = 1, otherwise = 0 0.17 0.3729 0 1 199

127 DISM Distance of household to mangroves 7.33 8.4901 0.05 40 155 DM If any household males participate in outside employment DM = 1, otherwise = 0 0.31 0.4622 0 1 199 DUM1 If household’s only mangrove-related activity is fishing DUM1 = 1, otherwise = 0 0.16 0.3683 0 1 199 DUM2 If household’s only mangrove-related activity is collection DUM2 = 1, otherwise = 0 0.32 0.4663 0 1 199 DUM3 If household has lived elsewhere outside village DUM3 = 1, otherwise = 0 0.66 0.4738 0 1 199 EDUCF Average years of female education 5.16 2.7884 0 14 199 EDUCM Average years of male education 5.73 2.5536 0 14 199 MANGROVE Area of mangrove utilized by the household (ha) 54.28 152.9400 0.01 1000 184 MDI Mangrove dependent income as a proportion of total income 0.83 0.2827 0 1 199 NU1 If the household is involved in agriculture NU1 = 1, otherwise = 0 0.08 0.2647 0 1 199 PLANTF If any household females participate in replanting PLANTF = 1, otherwise = 0 0.35 0.4771 0 1 199 PLANTM If any household males participate in replanting PLANTM = 1, otherwise = 0 0.54 0.4994 0 1 199 YRSVH Number of years the household has spent in the village 25.07 7.8749 0 53 199 Table 7.4 Bivariate probit model results for the male and female decision to participate in mangrove replanting efforts

Variable Males Females Coeff. t-ratio P-value Marginal prob. Coeff. t-ratio P-value Marginal prob.

ONE –2.4374 –2.4800 0.0131 –0.6146 –1.9948 –1.6098 0.1075 0.2741 MDI 1.1070 1.9772 0.0480 0.2792 1.5465 1.7843 0.0744 –0.2125 MANGROVE –0.0002 –0.1428 0.8864 0.0000 –0.0057 –2.2296 0.0258 0.0008 AWARE 1.1357 4.3000 0.0000 0.2864 0.8765 2.6493 0.0081 –0.1204 ATSFARM1 0.5012 1.6316 0.1028 0.1264 0.8173 1.4319 0.1522 –0.1123 AGEH 0.0131 0.7055 0.4805 0.0033 –0.0093 –0.6093 0.5423 0.0013 CHILD6 –0.0308 –0.1129 0.9101 –0.0078 –0.6560 –2.5976 0.0094 0.0901 CHILD12 0.1048 0.5644 0.5725 0.0264 –0.1447 –0.7812 0.4347 0.0199 DISM –0.0307 –1.4999 0.1336 –0.0077 –0.0484 –2.1469 0.0318 –0.0066 128 EDUCM 0.0043 0.0982 0.9218 0.0011 ADULTM 0.2142 1.3659 0.1720 0.0540 DM 0.1334 0.4194 0.6749 0.0336 EDUCF 0.0412 0.5620 0.5741 –0.0057 ADULTF 0.0369 0.2810 0.7787 –0.0051 DF 0.2451 0.4069 0.6841 –0.0337 RHO(1,2) 0.6817 4.2975 0.0000 McFadden R2 = 0.40 Log-likelihood ratio statistic = 194.54 Log-likelihood ratio test for homoskedasticity = –21.46

2 2 Note: The McFadden R is calculated as R = 1 – LUR/LR, where LUR is the unrestricted maximum likelihood and LR is the restricted maximum likelihood 2 with all slope coefficients set equal to zero (Maddala 1983). The log-likelihood ratio statistic is given by 2(LUR – LR) and is asymptotically distributed as a c 2 random variable. The log-likelihood ratio test for homoskedasticity was computed by c = –2(LRHOMO – LRHETO), where LRHOMO is the maximum likelihood in the homoskedastic regression and LRHETO is the maximum likelihood in a regression corrected for heteroskedasticity. Mangrove conservation decisions 129 that collect and fish in larger mangrove areas are less likely to participate in conservation. The number of children under six years of age, as might be expected, also affects the females’ decision to participate. Finally, the household awareness of community conservation and utilization rules positively affects female participation in replanting.

SUMMARY AND CONCLUSIONS

This analysis has investigated the factors that are important in male and female household members’ decisions to participate in conservation activities. In this instance the majority of conservation activities involved replanting schemes, some of which were instigated by local communities, while others were funded by non-governmental and governmental organizations. As we hypothesized, the degree of mangrove dependence, measured in terms of the degree of mangrove-dependent income as a proportion of total income (MDI), was particularly important in both the male and female decision to participate in conservation. The results in Table 7.1 showed that those households that rely on mangroves for both direct and indirect income production, in the form of collection and fishing activities, have a higher percentage of males and females involved in conservation. In Phang-nga the involvement in replanting schemes was greater in percentage terms but Table 7.2 shows that in Nakhon Si Thammarat males and females contribute more time in hours per year to replanting. This was perhaps because the replanting schemes in Nakhon Si Thammarat were governmental and on a much larger scale. The attitudinal variables were also of key importance to the conservation decision. In particular, the household awareness of community utilization rules and conservation efforts significantly affected male and female participation decisions. This is an important result and shows that conservation efforts are very much a community activity and rely on larger-scale efforts than just household involvement. Attitudes towards the environmental impacts of shrimp farms were also important for males, but not in the female regression. The importance of mangrove area and distance to mangroves in the female equation, and the higher marginal probability of the MDI variable, may suggest that the female decision to participate in conservation is more sensitive to changes in the environment and household dependence on mangrove variables. The mangrove area and distance to mangrove serve as a proxy for the state of the mangroves. The results suggest that increasing mangrove area means households are less likely to participate in conservation. This could be due to a reduced awareness or need for conservation but also to less time 130 Case studies: Phang-nga and Nakhon Si Thammarat available, because of the opportunity lost to the household of spending less time to obtain its livelihood. With the exception of the number of children aged under six, all of the other basic household characteristic variables included and tested were not significant. We also tested the importance of migration, participation in agriculture, years in the village and whether land ownership was documented. None of these variables was individually significant or improved the overall fit of the model. However, it is perhaps not surprising that the number of children aged under six is negatively related to female participation, owing to the time commitment of childcare. Although no results are shown, the survey also demonstrated that child participation in conservation was negligible. 8. The effects of mangrove loss on the labor allocation of households Edward B. Barbier and Mark Cox

INTRODUCTION

Since the early 1960s the agricultural economics literature has been investi- gating the contribution of off-farm employment to farming households’ total income (see Huffman 1991; Lass et al. 1991 for reviews). In more recent years, similar frameworks have been applied to developing countries, where the need to supplement income from farming in low agricultural productivity areas is of paramount importance (Abdulai and Delgado 1999). The focus of this chapter is on the labor allocation decisions of rural households in coastal areas of Thailand whose economic livelihoods have traditionally depended on the surrounding mangrove ecosystems. In this application few households are involved in agriculture per se and therefore the term ‘off-farm employment’ is replaced by ‘outside employment’. Furthermore, the term ‘on-farm employment’ is used more loosely to represent any household production or income- earning activity that is dependent on mangroves. In this case, mangrove- dependent activities could consist of either direct or indirect use of mangrove resources (Barbier 1994). For example, direct use of resources from a mangrove forest may include wood collection, for fuelwood, charcoal production and other wood products, and harvesting of fish and shellfish in mangrove swamps. The household may also harvest fish from a coastal fishery, which is indirectly dependent on the mangroves as a breeding nursery habitat (Barbier and Strand 1998). The trend in farming households worldwide towards outside employment exposes them not only to fluctuations in the agricultural sector but also to changes in the wider economic climate. In developing countries this has particularly important implications for policies aimed at improving rural livelihoods. Traditional studies in the off-farm literature have therefore focused on examining how individual, family, farm production, financial and locational characteristics of households affect off-farm labor supply. In addition to examining these influences, this chapter aims to examine the role that the natural capital stock plays in off-farm labor supply. This is particularly

131 132 Case studies: Phang-nga and Nakhon Si Thammarat important in developing countries as livelihoods often depend largely on the natural resource base. Therefore this chapter will investigate the role that mangrove area has in determining hours of labor supplied to outside employment in Thailand’s coastal provinces. As previous chapters have indicated, in recent decades, the traditional livelihoods of coastal communities have been affected by the widespread mangrove deforestation that has occurred in Thailand, especially in southern coastal areas. This chapter will investigate the effect of these trends and other important factors on the supply of outside employment by households in the four case study coastal villages, thus providing a detailed understanding of the composition of mangrove-dependent households’ income and affording some insights into rural development and mangrove conservation policies.

AN AGRICULTURAL HOUSEHOLD MODEL OF NATURAL CAPITAL AND LABOR ALLOCATION

Consider a representative rural household that may participate in three main types of economic activity. First, it is assumed that the household always undertakes some form of resource-based production activity which, as mentioned above, could consist of either direct or indirect use of mangrove resources. In addition, the household may engage in another productive activity, such as agriculture, which is not directly or indirectly dependent on the mangrove forest. Finally, the household may also undertake paid work, for which it receives a market wage. Several other aspects of the household’s labor allocation decision need to be considered. First, to sharpen the analysis and to simplify notation, aggregate household labor will be treated as homogeneous in the theoretical model. However, in empirically applying the model, this assumption will need to be relaxed. The male and female labor of the household may not be equivalent, and thus the allocation decisions of each type of labor may need to be differ- entiated. Second, the household may also produce and consume non- marketed goods. Without any loss of generality, we will make the standard assumption that such activities can be subsumed under the broad category of leisure (Barnum and Squire 1979). Finally, the household may also choose to participate in community mangrove conservation activities, such as replanting and forest protection. However, the amount of labor devoted to such conservation activities is usually relatively small compared to the household’s overall labor allocation decision over the period of analysis (that is, one year), and is in fact generally fixed over time (that is, from year to year). Thus the decision to participate in and allocate any household labor to mangrove conservation will be treated as exogenously determined. The effects of mangrove loss 133

Nevertheless, such a decision may prove to be an important household characteristic that influences the allocation of household labor between mangrove-dependent activities, agricultural production and outside employment. In any period, the household is assumed to maximize a utility function with the standard properties,

U = U(x, lu, C; y), (8.1) where x is a market-purchased consumption good, lu is leisure, C is the household’s total consumption from its own resource-based production activities, and y is exogenous characteristics of the household and its location that may also affect utility. If y1 is the household’s production of the resource-based good (for example, fuelwood/charcoal, fish, shellfish) obtained from direct or indirect use of the mangroves, then the following production technology is assumed:

1 y1 = f (l1, h1, v1; S, Z) ≥ c1, (8.2) where l1, h1 and v1 are respectively the household labor, hired labor and purchased inputs employed to produce y1. In addition, production of the resource-based activity will be affected by the area of mangrove forest, S, that the household requires to support this activity and by various exogenous factors, Z. The latter may consist of household characteristics affecting production decisions, fixed production factors and aspects associated with the household’s location. Finally, the household may or may not consume, c1, all of the resource that it extracts from the mangrove forest or harvests from the mangrove-dependent coastal fishery. If the household is also an agricultural producer, then y2 is the household’s agricultural output (for example, crops):

2 y2 = f (l2, h2, n2; Z) ≥ c2, (8.3) where l2, h2 and v2 are respectively the household labor, hired labor and purchased inputs employed in agriculture, and Z is the exogenous fixed factors as defined previously. Again, the household may or may not consume, c3, all that it produces. Finally, the household may decide also to participate in outside employment, lw. Denoting L as the total labor time available to the mangrove-dependent household implies that

w u w u L = l1 + l2 + l + l , l1 > 0, l2 ≥ 0, l ≥ 0, l > 0. (8.4) 134 Case studies: Phang-nga and Nakhon Si Thammarat

Note that, although the household always allocates some labor to mangrove- based activities, the optimal hours of paid work may be zero in any year. In addition, the household may not be an agricultural producer, in which case l2 will be zero. Given market prices, px , pyi, wi and pvi, i = 1, 2, for the corresponding commodities and the market wage rate, w, for outside employment, the household faces the following cash income constraint:

pxx + S[pviv + wih ] = Spyi(y – c ) + wlw + M, i = 1, 2. (8.5) i i i i i i

The left-hand side of (8.5) represents the cash purchases made by the household, and the right-hand side is its income. If (8.2) and (8.3) are strict inequalities, yi > ci, then the first term on the right-hand side is the marketed surplus of the resource-based product and agricultural production (for example, fuelwood/charcoal, fish and crop sales, respectively). The final term on the right- hand side, M, represents exogenous non-labor income (remittances, social transfers, rents). Finally, the following additional constraints are also assumed to hold:

y1 > 0, y2 ≥ 0, ci ≥ 0, vi ≥ 0, hi ≥ 0, M ≥ 0, x > 0 and C = S ci, i = 1, 2. i (8.6)

Maximization of household utility (8.1) with respect to the constraints (8.2) to (8.6) will yield the optimal levels of consumption of x, C and lu, and of the w purchased and labor inputs, vi, li,hi and l , respectively. As we are interested in the household’s labor allocation decision, we will focus on the first-order conditions concerned with this allocation, assuming that the household is also engaged in agricultural production (y2>0) and produces marketed surpluses (yi u w > ci). Thus the optimal choices for li, l and l are governed by

∂U ∂f i l —— = l, pvi —— = —, mw – l ≤ 0, lw ≥ 0, [mw – l]lw = 0 or ∂lu ∂l m i (8.7) ∂U/∂lu ∂f i l ——— = pyi —— = — ≥ w, i = 1, 2, ∂ m li m where l is the shadow value of the household’s total labor and leisure time and m is the shadow value, or marginal utility, of additional cash income for the household. Condition (8.7) states that the household will equate the marginal value of leisure with that of resource-based and agricultural activities, and the value of this labor time may be equal to or exceed the given market wage for any paid The effects of mangrove loss 135 work. Clearly, if the value of household time is insufficiently compensated by outside employment (that is, l/m > w), then the household will not participate in the labor market (lw = 0). Note that, if the household also hires labor for both resource-based and agricultural production, and hired and family labor are perfect substitutes in i this production (that is, yi = f (li + hi)), then the household’s labor allocation decision is fully recursive (Jacoby 1993). That is, optimal production and thus input decisions of the household are determined first and independently of consumption and leisure choices, regardless of whether the household decides to participate in paid work. It is easy to demonstrate that, in this model, the household will value its labor and leisure time in terms of the market wage for hired labor, and that condition (8.7) determining participation in the labor market will now simplify to w1 = w2 ≥ w.1 Whether or not the household’s production and consumption decisions are separated, condition (8.7) will govern the household’s participation in outside employment. This decision to allocate labor to paid work can be easily char- acterized by following the standard procedures from the literature on off-farm labor supply by agricultural households (Abdulai and Delgado 1999; Huffman 1980, 1991; Lass et al. 1991). Let d be an indicator of the binary decision (0,1) of the household of whether or not to undertake outside employment. Using (8.7), the household’s choice is determined by

d = 1 if w * > 0  λ  d = 0 if w * ≤ 0, w* = w – —  w , (8.8)  m  l = 0 where w * is the unobserved difference between the market wage and the shadow value of the household’s labor time. However, the latter is also equivalent to the household’s reservation wage, since condition (8.8) is defined for the marginal value of the household’s time when all of it is allocated to mangrove-based activities, agriculture and leisure. The binary decision to participate in outside employment can therefore be empirically specified as a probability model,

* Pr(d = 1) = Pr(w = ac + ew* > 0), (8.9) where c represents the set of household characteristics (Y, Z) influencing its production and consumption decisions that may also influence a household’s participation in outside employment. If a household does decide to enter the labor market, its optimal supply of labor will be determined by solving the above utility-maximizing problem to obtain 136 Case studies: Phang-nga and Nakhon Si Thammarat

w u w 1 2 y1 y2 x 1 2 l = L – l1 – l2 – l = l (w, w , w , p , p , p , v , v ; S, Y, Z). (8.10)

From equation (8.10) it is possible to derive the reduced-form equations for the supply of labor, lw, and the market wage, w, as a function of the other independent variables on the right-hand side of the equation. Specifying the latter as X, the reduced-form equations are

w l = blX + el (8.11) and

w = bwX + e w. (8.12)

Note that key determinants of these reduced-form equations will include the area of mangroves utilized by the household, S, and other characteristics and attributes unique to a mangrove-dependent household, such as the distance of the household from the mangrove forest, the ecological state of the forest, the household’s attitudes to and degree of participation in mangrove conservation, and the security of land tenure. In particular, the area of mangroves, S, utilized by a household not only determines mangrove-based income, m′, but also affects its supply of labor in outside employment both directly and through the reduced- form wage equation (8.12). A standard assumption in the labor supply literature is that the amount of off-farm labor supplied by an agricultural household will be affected by its on-farm production (Huffman 1980; Lass et al. 1991; Sahn and Alderman 1988). If this is also the case for the resource-based activities of a mangrove-dependent household, it is possible to rewrite equation (8.10) in a simpler form to account for the three possible influences of the mangrove ‘natural capital’ on the amount of outside labor supplied by the household:

w w ′ ′ l = l (w(S, m ), m (l1, S, v1), S). (8.13)

Totally differentiating (8.13) and making use of the envelope theorem that all other inputs are held constant at their optimal levels,

∂lw ∂w ∂lw ∂w ∂m′ dlw = —— · ——  + —— · —— · ——  ∂w ∂S  ∂w ∂m′∂S  (8.14) ∂lw ∂m′ ∂lw  +  —— · ——  + ——dS. ∂m′∂S  ∂S 

Thus the total effect of a change in the natural capital available to a household can be determined from the estimated parameters of the wage equation, the The effects of mangrove loss 137 equation for the supply of outside labor and the income function for mangrove-based activity.

DATA DESCRIPTION

The analysis of this chapter makes use of the same randomly stratified survey at two survey sites, Nakhon Si Thammarat (east coast) and Phang-nga (west coast), that is employed in the analysis of Chapter 7. As noted in Chapter 7, at each site two villages were surveyed: Ban Khlong Khut and Ban Gong Khong in Nakhon Si Thammarat and Ban Sam Chong Tai and Ban Bang Pat in Phang- nga. Further details of these villages and the surveys can be found in Chapter 7 and the other chapters of Part II. The survey of the four villages covered detailed time allocation studies of all income-producing, leisure and conservation activities that depend on mangroves either directly or indirectly, as well as demographic and locational factors for each household. Information on outside (that is, non-mangrove- dependent) employment also included wage rates and detailed time alloca- tions. In total, 201 households were surveyed, although two households reported no direct or indirect income-producing activities that depend on mangroves and were excluded from the sample, leaving a total of 199 households. Table 8.1 provides a brief set of summary statistics for the entire sample split by the type of mangrove activities the household was predominately involved in. The results show that 32 households were only fishers, that is, were involved in either offshore fishing or aquaculture but did not collect mangrove products; 63 households were only involved in direct use collection activities and 104 households did a combination of both. From those three groups the ‘collect only’ group had the greatest percentage of households devoting time to outside employment (49 per cent of males and 32 per cent of females). The households involved in both activities had the lowest percent- ages of households participating in outside employment (males 17 per cent and females 7 per cent). As might be expected, the need to supplement income

Table 8.1 Summary statistics for outside employment, by household type

Fish only Collect only Fish and collect n = 32 n = 63 n = 104

Male Female Male Female Male Female

Outside employment (%) 38 19 49 32 17 7 Mangrove income (%) 82 67 94 138 Case studies: Phang-nga and Nakhon Si Thammarat

Table 8.2 Summary statistics for outside employment, by village

Phang-nga Nakhon Si Thammarat

Ban Sam Ban Bang Ban Gong Ban Khlong Chong Tai Pat Khong Khut n = 55 n = 41 n = 52 n = 51 M F M F M F M F

Outside employment (%) 15 7 17 17 59 23 29 20 Mangrove income (%) 95 89 66 83 Fish only 1 5 3 23 Collect only 19 3 34 7 Fish and collect 35 33 15 21 in the households only involved in collection activities is paramount. This result is reinforced by the figures for percentage of income that is mangrove- based. The households that are solely involved in collection activities have the lowest proportion of mangrove-based income. At the other end of the scale, the households involved in both direct and indirect activities, mangrove-based activities make up almost all of their income. Table 8.2 reports the same analysis, but this time by village. An interesting pattern also emerges here, in that the villages in Nakhon Si Thammarat have the lower proportion of income coming from mangrove-based activities and a higher percentage of households working in outside employment. Households in Phang-nga, on the other hand, obtain a much higher percentage of their income from mangrove-related activities and fewer of them work in outside employment, the majority of households choosing to devote their time to both direct collection and indirect mangrove production activities. Table 8.3 presents the definitions and sample statistics of all the variables used in the empirical estimation. The analysis concentrates on household males or females and not individual household members, therefore many of the factors are measured at the household level. Factors that are specific to household males and females include education. The level of education is thought to indicate productivity potential and earning capacity. At the household level, age and age squared represent general experience that increases the marginal value of time in each activity but at a decreasing rate after a certain age. The experience of the household was also thought to be important and is calculated as the average household age minus the average male and female years of education, minus six. Other household composition factors include the number of children aged under six and children aged between six and twelve, and overall household size. Demographic factors were also thought to Table 8.3 Variable definitions and descriptive statistics

Variable Definition Mean Std.Dev. Min Max N

Dependent variables DF If any HH females work in outside employment DF = 1, otherwise = 0 0.17 0.37 0 1 199 DM If any HH males work in outside employment DM = 1, otherwise = 0 0.31 0.46 0 1 199 HOURF Hours worked in outside employment by females 319.81 884.71 0 4 380 199 HOURM Hours worked in outside employment by males 381.21 939.21 0 6 208 199 LWAGEF1 Log of female wage for outside employment 1.22 0.36 0 2 32 LWAGEM1 Log of male wage for outside employment 1.44 0.38 1 3 60 1 139 MANINC Mangrove-dependent income (Baht) 136 335 147 986 0 1 322 200 199 Explanatory variables AGEH Average age of household 26.18 10.09 12 73 199 AGEH2 Average age of household squared 786.56 716.38 144 5 329 199 CHILD12 Number of children 6–12 0.83 0.88 0 4 199 CHILD6 Number of children < 6 0.55 0.64 0 2 199 DUM1 If household’s only mangrove-related activity is fishing, DUM1 = 1, otherwise = 0 0.16 0.37 0 1 199 DUM2 If households only mangrove-related activity is collection, DUM2 = 1, otherwise = 0 0.32 0.47 0 1 199 DUM3 If household has lived elsewhere outside village, DUM3 = 1, otherwise = 0 0.66 0.47 0 1 199 DUMVIL2 Dummy for village 22 0.21 0.41 0 1 199 DUMVIL3 Dummy for village 3 0.26 0.44 0 1 199 DUMVIL4 Dummy for village 4 0.26 0.44 0 1 199 Table 8.3 (continued)

Variable Definition Mean Std.Dev. Min Max N

EDUCF Average years of female education 5.16 2.79 0 14 199 EDUCM Average years of male education 5.73 2.55 0 14 199 EXPERH Experience of the household3 14.73 10.75 0 67 199 EXPHSQ Experience squared 331.95 561.88 0 4 489 199 FITWF1 Fitted wage for females4 0.90 1.06 –6 7 199 FITWM1 Fitted wage for males 2.27 0.58 1 3 199 HHSIZE Number of household males and females 3.10 1.37 0 8 199 LABORF Total female time devoted to mangrove-dependent activities (hrs per year) 550.85 925.78 0 4 752 199 140 LABORM Total male time devoted to mangrove-dependent activities (hrs per year) 1 893.16 1 672.68 0 10 560 199 MANGROVE Mangrove area used by the HH for all activities (ha) 54.28 152.94 0 1 000 184 MANMINC Mangrove area times full annual income 14.92 71.13 0 783 184 MDI Mangrove-dependent income as a proportion of total income 0.83 0.28 0 1 199 NU1 If HH is involved in agriculture, NU1 = 1, otherwise = 0 0.08 0.26 0 1 199

Notes: 1. An exchange rate of 40 baht/US$. 2. Village 1 = Ban Sam Chong Tai, village 2 = Ban Bang Pat (Phang-nga); village 3 = Ban Gong Khong, village 4 = Ban Khlong Khut (Nakhon Si Thammarat). 3. Household experience = (AGEH–(EDUCM+EDUCF/2) – 6); see Abdulai and Delgaldo (1999), Huffman and Lange (1989). 4. The two fitted wage variables, FITWM1 and FITWF1, are calculated from the estimated wage equations by evaluating the wage equation at the means for each household. The effects of mangrove loss 141 be important and a dummy variable representing whether the household had moved from outside the province was included. Wage rates for outside employment activities were collected as primary data from the survey. The analysis, as discussed in the next section, adopts the predicted wage approach using an estimated wage equation in order to avoid bias in the estimation of the supply of outside employment and maximize the observations utilized. The primary income variable is mangrove-dependent income, but total income was also calculated from all the income-earning activities and used to form the mangrove-dependent income as a proportion of total income variable, MDI. Location was also thought to be important and is represented by a village dummy variable. A crucial variable for each household and in the analysis of this chapter was the state of the natural capital, which is proxied by the area of mangrove that is used by the household in its production activities. As discussed above, the natural capital stock is thought to affect the supply of outside employment both directly and indirectly through income and wage effects. Type of household activities was also thought to be important and therefore two dummy variables representing whether the household was involved directly or indirectly in mangrove production activity were created (DUM1 and DUM2).

EMPIRICAL ESTIMATION

Applying stand ordinary least squares (OLS) regression analysis to wage and labor supply equations would yield biased parameter estimates, since they do not take into account the process generating the observed time allocation of farmers. The main problem in estimating these models is that, although a mangrove-dependent household always engages in some form of mangrove- based activity, it may not participate in outside employment. Given the decision to participate, the market wage rate and the number of hours in paid work will be observed. To avoid sample selection bias, a standard approach adopted in the off-farm labor supply literature is to utilize a two-step Heckman procedure for conditioning the estimations of wages and hours supplied. Therefore the econometric estimation of the theoretical model consists of participation in outside employment equations, wage rate equations and labor supply equations estimated separately for males and females, and an income equation for the household. The first step involves estimating equation (8.9), which is the probability of participation in outside employment. If the household labor is not homogeneous then the empirical estimation of the labor allocation decision must distinguish the sexes. Furthermore, the decisions of males and females may be 142 Case studies: Phang-nga and Nakhon Si Thammarat made independently or jointly within the household. If the latter is the case, estimating equation (8.9) with an ordinary logit or probit regression would misrep- resent the processes going on at the household level. Therefore we test the dependence of male and female labor decisions using a bivariate probit model. This model estimates the correlation between the error terms in the male and female participation equations. Statistical significance of the correlation term would imply that males’ and females’ participation decisions are made jointly and therefore the bivariate probit is the preferred model. If the correlation is not significant, individual probit models can be estimated for the males and females separately. The results from this step are then used to calculate the Inverse Mills Ratio, which is effectively treated as a missing variable in the reduced form for the wage equation and can be subsequently used in the labor supply equations. The second step is to estimate the wage equation (8.12), which can be used to form a predicted wage for those who do not participate in outside employment. The estimation of the wage equation is necessary as market wage rates are unobserved for households that do not participate in outside employment. Hence, the censored nature of the sample has to be corrected by predicting the wage rate for those that do not participate in outside employment. The third step involves estimating the supply of male and female labor to outside employment (equation 8.11). Two common approaches are often found in the literature for proceeding with the outside employment supply. The standard Heckman procedure only utilizes the non-zero sample observations and can be restrictive in smaller samples. Another approach, and the one adopted here, is to use the predicted wages from the above and estimate a tobit model for the structural labor supply function for the entire sample. Finally, in order to estimate the effect of natural capital on outside employment, one must calculate all the component effects of equation 8.14, thus requiring an income equation to be estimated. This was done using straight- forward ordinary least squares, correcting for heteroskedasticity using White’s method.

EMPIRICAL RESULTS

Participation in Outside Employment

Table 8.4 presents the results of the maximum likelihood bivariate probit estimates of the equations explaining the probability of males and females participating in outside employment (equation 8.9). The marginal effects of the regressors on the probability of participation in outside employment, which following Maddala (1983) are calculated by multiplying the coefficient by f(b′x)b at the mean values, are also reported in Table 8.4. Table 8.4 Bivariate probit model for participation in outside employment

Variable Males Females

Coeff. t-ratio P-value Marginal Coeff. t-ratio P-value Marginal prob.1 prob.

CONSTANT 2.6257 1.6226 0.1047 0.8408 0.1927 0.0847 0.9325 0.0006 AGEH –0.0271 –0.3315 0.7403 –0.0087 0.0261 0.1948 0.8455 0.0001 AGEH2 0.0003 0.2243 0.8225 0.0001 0.0000 –0.0136 0.9892 0.0000 EDUCM 0.0485 0.7176 0.4730 0.0155 EDUCF –0.0342 –0.5643 0.5725 –0.0001 CHILD6 0.2269 0.8653 0.3869 0.0726 0.7204 1.9377 0.0527 0.0023 CHILD12 –0.0602 –0.3006 0.7637 –0.0193 0.2807 0.8915 0.3726 0.0009 DUMVIL2 –0.2744 –0.5512 0.5815 –0.0879 0.7211 1.2474 0.2122 0.0023 DUMVIL3 0.7372 1.8198 0.0688 0.2361 0.2044 0.3502 0.7262 0.0007 DUMVIL4 0.1135 0.2698 0.7873 0.0364 0.5022 0.9665 0.3338 0.0016 143 MDI –3.8307 –5.0235 0.0000 –1.2267 –3.9370 –3.6934 0.0002 –0.0125 NU1 –2.0021 –3.7170 –0.0002 –0.6411 –2.3178 –2.5442 0.0110 –0.0074 MANGROVE 0.0011 1.2966 0.1948 0.0004 –0.0037 –0.4921 0.6226 0.0000 HHSIZE 0.2032 1.6744 0.0941 0.0006 RHO(1,2)2 –0.0118 –0.0352 0.9719 n = 184 Log-L = –123.92 Restricted Log-L (b = 0) = –205.78 Likelihood ratio test = 163.72 McFadden’s R2 = 0.39

Notes: 1. Marginal effects of the regressors on the probability of participation in outside employment are calculated by multiplying the coefficient by f(b'x)b at the mean values of x (Maddala 1983). 2. Defined as the estimate of the correlation between errors of the male and female regressions. 2 2 The McFadden R is calculated as R = 1 – LUR/LR, where LUR is the unrestricted maximum likelihood and LR is the restricted maximum likelihood with all 2 slope coefficients set equal to zero (Maddala 1983). The log-likelihood ratio statistic is given by 2(LUR – LR) and is asymptotically distributed as a c random variable. 144 Case studies: Phang-nga and Nakhon Si Thammarat

The estimated correlation of r (that is, RHO1,2) represents the between- error structure that maximizes the bivariate probit likelihood function. The estimated coefficient is around –0.012 but is not statistically significant. This suggests that the random disturbances in the outside employment decisions of males and females are not affected in the same direction by random shocks, suggesting that their labor participation decisions are statistically independent. Thus efficient parameter estimates could be obtained via separate probit models for males and females. In several prior applications in the off-farm literature these two equations were estimated for husbands and wives, therefore a stronger degree of interdependence in the decision-making process may be expected than between household males and females that may not be husband and wife. The log-likelihood ratio statistic was significant at the 1 per cent level, suggesting that the independent variables taken together significantly influence participation decisions. The McFadden (pseudo) R2, an indication of goodness of fit, is 0.39. The most important variable in the equation, on the basis of size of marginal effect and significance level, was MDI. The negative coefficient suggests that, as the degree of mangrove-dependent income relative to total income goes up, household males and females are less likely to participate in outside employment. The marginal effect is much greater for men than for women: –1.23 versus –0.01. The households’ participation in agriculture also appears to be another important factor in the decision to participate in outside employment by males and females. The marginal effect is again much greater for the men than for women: –0.64 compared to –0.01, suggesting that the households’ involvement in agriculture decreases the probability of working in outside employment more for males than for females. Location only appeared to be important for males: the dummy for Ban Khlong Khut in Nakhon Si Thammarat was positive and significant in the equation for males. This suggests that the males in a household from this village are more likely to participate in outside employment. The natural capital variable, mangrove area, was not significant in either regression, implying that mangrove area used by the household does not directly effect the decision to participate in outside employment by males and females. However, the significance of the relationship with mangrove- dependent income suggests that the degree of dependence on mangroves does significantly affect the decision to participate. The results also (and perhaps surprisingly) suggest that few household-level attributes affect the decision of males and females to participate in outside employment, with the exception of the number of children aged under six and household size. The former, surprisingly, had a positive effect on female participation suggesting that households with a greater number of children aged under six increased the probability of females in that household participating in The effects of mangrove loss 145 outside employment. Household size also significantly affected female participation, which suggests that, the larger the household, the greater the probability of female participation. This could also imply that larger households can rotate childcare, therefore providing some justification for the sign of the coefficient on the CHILD6 variable.

Wage Equations

Table 8.5 presents the results of the outside employment wage equations. The Inverse Mills Ratio (Lambda) was significant in the male equation at the 1 per cent level but was not significant in the female equation. This result suggests that sample selection bias would have resulted if the male wage equation had been estimated without taking into account the decision to participate in outside employment. For females, the result implies that sample selection bias would not have occurred. The log-likelihood ratio test statistic for both the male and female regressions (34.40 and 30.38, respectively) were significant at the 1 per cent level, as were the Wald Statistics testing linear restrictions on all independent variables. For both males and females the experience and education variables are not statistically significant. Many previous applications had found human capital in the form of education and experience to be significant determinants of individuals’ earning capacity. However, the MDI variable was positive and significant at the 5 per cent level in the male wage equation. This result implies that, as the degree of mangrove-dependent income increases, so does the male wage rate. This could mean that those individuals with higher proportions of mangrove income can command higher wages than those households that have a lower income dependency on mangroves and ultimately have a less urgent need to supplement income. The household’s involvement in agriculture also significantly and positively affected the male wage rate. This perhaps suggests the same thing as the MDI variable, which is that those households with more income-earning opportunities allow males to command a higher wage because they have a higher opportunity cost of time devoted to other activities. This result is perhaps further reinforced in the male equation by the significance at the 5 per cent level of the DUM2 variable. This dummy variable represents the household’s involvement in collection activities but indicates that they do not depend on mangroves indirectly and therefore are not fishermen or coastal aquaculturists. The negative sign suggests that these individuals command a lower wage, perhaps because of their more pressing need to supplement income than fishermen or households that do both collection and fishing. The regression for females again suggests this owing to the positive and Table 8.5 Two-step selection model results for male and female wages

Variable LWAGEM1 LWAGEF1 Coeff. t-ratio P-value Coeff. t-ratio P-value

ONE 1.6833 5.0230 0.0000 1.5463 4.7296 0.0000 EXPERH –0.0001 –0.0083 0.9934 –0.0157 –0.8910 0.3729 EXPHSQ –0.0001 –0.3227 0.7469 0.0001 0.2578 0.7966 EDUCM –0.0434 –1.5561 0.1197 EDUCF –0.0259 –0.9361 0.3492 NU1 0.5737 1.6842 0.0921 DUM1 –0.1184 –0.6782 0.4977 0.9085 3.8466 0.0001 DUM2 –0.2784 –2.0278 0.0426 0.1018 0.7029 0.4821 146 MANMINC 0.0009 1.0020 0.3163 0.0210 1.2865 0.1983 MDI 1.1164 2.2297 0.0258 –0.3360 –1.2819 0.1999 MANGROVE –0.0009 –1.3015 0.1931 –0.0099 –1.1947 0.2322 LAMBDA1 –0.7220 –2.7839 0.0054 0.0685 0.5162 0.6057 n = 54 n = 29 F[10, 43] = 2.18, Prob. value = 0.038 F[9, 19] = 1.83, Prob. value = 0.128 Log-L = –4.7982 Log-L = 3.702 Restricted log-L = –22.00 Restricted log-L = –11.49 Likelihood ratio test = 34.40 Likelihood ratio test = 30.38 Wald test = 212.63 (p = 0.0000) Wald test = 217.46 (p = 0.0000)

Notes: 1. The inverse Mills ratio. 2 The likelihood ratio statistic is given by 2(LUR – LR) and is asymptotically distributed as a c random variable, where LUR is the unrestricted maximum likelihood and LR is the restricted maximum likelihood with all slope coefficients set equal to zero (Maddala 1983). The Wald test is calculated for the set of restrictions where all slope coefficients are set equal to zero. The effects of mangrove loss 147 significant sign on the DUM1 variable. This variable represents the households’ participation in fishing or coastal aquaculture as their only form of dependence on mangroves and they do not collect other mangrove products. Owing to the more lucrative nature of fishing and aquaculture compared with collection activities it is perhaps not surprising that households that are fishing-based can allow females to command a higher wage. However, statistically speaking, the wage equation for females did not perform as well as the wage equation for males, but this can perhaps be put down to the low sample of females that actually participate in outside employment.

Outside Employment Hours

Table 8.6 presents the results for the labor supply to outside employment equations. The results were estimated using a Tobit model and included the predicted wages for males and females calculated using the model results from Table 8.5. The likelihood ratio test was significant at the 1 per cent level for both male and female equations. In addition, the Wald Test of linear restrictions on all the independent variables was significant at the 1 per cent level. Only the fitted wage for males in the male equation is significant from the direct effects of wages on hours worked (that is, the male wage on male hours worked and the female wage on female hours worked). The negative coefficient on FITWM1 suggests the presence of a backward-bending labor supply curve where increases in wage leads to fewer hours worked. Hernández- Licona (1997) points out that such a backward bending labor market supply curve occurs under sufficiently low market wages when the minimum subjec- tive requirement of income for subsistence cannot be achieved without outside employment. Abdulai and Delgado (1999) and Skoufias (1994) both suggest including the cross-wage effects of male wage on female hours and female wage on male hours worked, to avoid any bias in the coefficients. However, these effects are not statistically significant in this application. The number of children under 12 years of age negatively and significantly affected the number of hours worked by males, but the number of children aged under six positively and significantly affected the hours worked by females. Similar to the participation equation for females, we also observe the positive and significant relationship with household size. Mangrove area was significant at the 10 per cent level for males but was not significant for females in determining hours worked in outside employment. However the proportion of mangrove income (MDI) was again a significant and important influence on both male and female hours worked. The negative coefficient suggests that, as households are more dependent on mangrove-based income-producing activities, they commit less labor in hours to outside employment. Although the households’ involvement in agriculture Table 8.6 Censored Tobit regression results for the hours worked in outside employment

Variable HOURM HOURF

Coeff. t-ratio P-value Coeff. t-ratio P-value

ONE 7647.22 6.1412 0.0000 –2406.65 –0.91522 0.360075 FITWM1 –3360.08 –5.7630 0.0000 –78.4532 –0.13152 0.895365 FITWF1 114.92 1.2246 0.2207 931.141 1.33469 0.181979 AGEH –37.84 –2.0323 0.0421 63.71 1.53219 0.125475 EDUCM 28.07 0.5942 0.5524 EDUCF 24.3639 0.225466 0.821617 CHILD6 –334.09 –1.3566 0.1749 1360.33 2.43188 0.015021 CHILD12 –426.18 –1.8683 0.0617 514.945 1.24201 0.214232 DUMVIL2 329.18 0.6192 0.5358 723.435 0.811553 0.417048 DUMVIL3 388.20 0.9313 0.3517 –340.634 –0.39132 0.695558 DUMVIL4 1291.47 2.5856 0.0097 185.913 0.210724 0.833103 148 HHSIZE 569.028 2.72794 0.006373 MANGROVE 1.19 1.6824 0.0925 –12.9826 –1.13739 0.255374 MDI –1609.75 –3.1522 0.0016 –6373.87 –4.31802 1.57E-05 NU1 –624.83 –1.3322 0.1828 –4055.95 –3.27132 0.00107 Sigma1 907.46 10.5809 0.0000 2185.67 6.74813 1.50E-11 n = 184 n = 184 Log-L = –453.85 Log-L = –304.10 Log-L c2 (= 0) = –622.23 Log-L (c2 = 0) = –370.06 Likelihood ratio test = 336.76 Likelihood ratio test = 131.92 Wald test = 180.64 (p = 0.0000) Wald test = 36.29 (p = 0.0009)

Notes: 1. The inverse Mills ratio. 2 The likelihood ratio statistic is given by 2(LUR – LR) and is asymptotically distributed as a c random variable, where LUR is the unrestricted maximum likelihood and LR is the restricted maximum likelihood with all slope coefficients set equal to zero (Maddala 1983). The Wald test is calculated for the set of restrictions where all slope coefficients are set equal to zero. The effects of mangrove loss 149 was not a significant determinant of male hours worked, it was significant for females, implying that females from households involved in agriculture work fewer hours in outside employment. The age of the household also appears negatively and significantly to affect the amount of male labor supplied. Location was also important for males; in particular, the dummy variable for Ban Khlong Khut in Nakhon Si Thammarat was positive and significant.

Income Equation

The final set of regression results in Table 8.7 shows an estimated income function for total household income, including all mangrove-based income and non-mangrove-dependent income. This equation was estimated for the entire household in order to complete the component parts of equation 8.14 to determine the total effect of mangrove area on outside employment. The results were estimated using ordinary least squares and corrected for heteroskedasticity using White’s correction (Greene 1997). The results show

Table 8.7 Ordinary least squares regression results for income

Variable Coefficient Standard error t-ratio P-value

ONE –31461.20 56860.20 –0.5533 0.5808 MANGROVE 191.55 103.60 1.8489 0.0662 LABOURF 42.99 13.58 3.1669 0.0018 LABOURM 20.16 4.91 4.1010 0.0001 EDUCM 1261.26 6601.74 0.1911 0.8487 EDUCF 4917.67 2510.34 1.9590 0.0518 DUM1 33963.90 41492.00 0.8186 0.4142 DUM2 –44424.50 11354.60 –3.9125 0.0001 NU1 –38191.30 16432.50 –2.3241 0.0213 DUMVIL2 68630.30 31515.10 2.1777 0.0308 DUMVIL3 24476.10 13632.10 1.7955 0.0744 DUMVIL4 60129.30 18154.20 3.3121 0.0011 DUM3 44152.50 17387.20 2.5394 0.0120 CHILD6 –3360.57 14914.90 –0.2253 0.8220 CHILD12 16607.50 10408.00 1.5957 0.1124 n = 184 R-squared = 0.384 F [14, 169] = 7.52, Prob. value = 0.00 Breusch–Pagan chi-squared = 368.65 150 Case studies: Phang-nga and Nakhon Si Thammarat that mangrove area significantly and positively affects income, suggesting that, as mangrove area goes up, so does household income. Another important determinant was the total time devoted by males and females to income- producing activities that depend on mangroves. The education level of males was not significant, but female education appears to be significant and positive. Those households that were involved solely in collection activities or in agriculture earned significantly less income than all other households. Location also appears to be important, given that each of the village dummies are significant. Finally migration also appears to play an important part; DUM3, the variable representing whether the household had moved from outside the province, was positive and significant, suggesting that those households who had moved from outside the province earned greater incomes.

DISCUSSION

This chapter has investigated the impacts of household characteristics, location and, in particular, natural capital on earnings and labor allocation decisions of households living in coastal areas of Thailand. In particular, the focus of the study was to determine the total effect of the loss of mangrove area on outside employment of males and females. Table 8.8 combines all the regression results to determine the total effect (dlw) derived in equation 8.14. In the case of the males we can see that, overall, a loss in mangrove area of 1 hectare would increase outside employment hours by 4.3 hours per year. In the case of females, the effect is slightly larger, 6.5 hours. Although this may seem like a small effect, in fact 1 hectare is a very small area to lose when compared to the average shrimp farm, which can vary in size from 2 hectares for intensive farms up to 27 hectares for the extensively managed farms. Therefore it is quite conceivable that larger reductions in area will cause more dramatic increases in hours spent working in outside employment. Moreover, the average number of hours worked in outside employment by males and females is low relative to the other activities they undertake. The mean time spent working in outside employment for males is 381 hours per year and for females is 319 hours per year. In comparison, the total labor time of males working on mangrove-dependent activities is 1893 hours per year and for females 551 hours per year. Changes in mangrove area have small but not insignificant effects on the hours supplied to outside employment. In the case of males, a 1-hectare reduction in mangrove area would see the average hours of outside employment hours for males increase by 1 per cent, and for females by 2 per cent. The importance of natural capital was not significant in the decision to The effects of mangrove loss 151

Table 8.8 The effect of natural capital on the supply of outside labor, by mangrove-dependent households

 ∂lw ∂w ∂lw ∂w ∂m′ ∂lw ∂m′ ∂lw  dlw = —— · ——  + —— · —— · ——  +  —— · ——  + —— dS ∂w ∂S  ∂w ∂m′∂S  ∂m′∂S ∂S 

Males Females

∂lw ∂w  0.00 0.00  —— · ——  ∂w ∂S  ∂lw ∂w ∂m′ –3.84 0.00  —— · —— · ——  ∂w ∂m′∂S  ∂lw ∂m′ –1.65 –6.52  —— · ——  ∂m´ ∂S  ∂lw  1.19 0.00  ——  ∂S 

dlw –4.30 –6.52 participate, but out of those males that did participate it was a significant factor in the determination of hours supplied. This result is perhaps similar to the effect of farm size in traditional off-farm studies where it has been observed that, the larger the size of holding, the lower the number of hours supplied by those that work off-farm. The crucial effect of natural capital did not appear directly in terms of area but did so indirectly through the dependence on mangroves for income-producing activities. The positive coefficient in the income production function of mangrove area suggests that a loss in the area of mangrove utilized by the household, whether that be through mangrove loss or just through households operating a smaller production area, is a significant constraint on income production. Therefore this variable may not have fully captured the effect of mangrove loss and, more so, a farm size effect. In addition, because mangrove area utilized was estimated by the household it may have been subject to varying degrees of measurement error. However, the results show the importance of mangrove-dependent income in determining outside employment and suggest that for certain households the need to supplement this income is paramount – in particular, for those households that are solely involved in collection activities and do not get the extra income of fishing or agriculture. In the off-farm literature the off-farm hours equation often contains a variable representing farm output, which is there because it is intuitively expected that 152 Case studies: Phang-nga and Nakhon Si Thammarat farmers with larger farms tend to participate less in the outside employment market. The MDI variable in our model to a certain extent also represents this effect. This variable clearly shows that, as income earned from mangroves increases, males and females are less likely to participate in outside employment and those that do contribute fewer hours. This picture can be further decomposed by the type of mangrove-based activity, the results suggesting that those households that are involved in many types of mangrove-based activity are likely to earn more and less likely to work in outside employment, whereas those households that are not totally dependent on mangroves and in particular those that are only collectors are willing to accept lower wages and work more hours in outside employment. Another factor is the involvement of the household in other income-producing activities such as agriculture. Males and females from households involved in agriculture were less likely to participate in outside employment and, in particular, females those that did contributed fewer hours per year. Wages represent the market value of an individual’s stock of human capital and can be considered fixed in the short run. However, wage equations were estimated to provide predicted wages for individuals who do not work in outside employment. Assuming leisure is a normal good, the response of males and females in outside employment to an increase in wage is ambiguous. As market wages increase, substitutions of market labor for consumption (leisure) and mangrove-based activities occur. There are also income effects for consumption and an income effect due to reduction of mangrove-earned income from mangrove-based activities. Thus the signs and magnitudes for elasticities are uncertain (Lass et al. 1991). One possible interpretation of the negative sign in our estimation for wages could be the need for very poor mangrove-based households to attain subsistence levels of income. Human capital in the form of education and experience appeared to play no role in the participation and outside employment supply decisions of households living in mangroves. Other personal characteristics such as age and age squared played no significant role in the decision of households to participate in outside employment, with the exception of the average age of the household negatively effecting male hours worked in outside employment. This perhaps suggests that older households are more likely to pursue the traditional way of life. Another interesting set of results were those regarding the effects of the number of children and total household size, in particular on female participation and supply. Many past applications have expected and found that the presence of children will be inversely related to hours worked by women (ibid.). However, this application suggests that female participation is more likely and those that do work are likely to work longer in outside employment the more children there are in the household. The positive relationship with household size perhaps supports the hypothesis that other members of the household The effects of mangrove loss 153 rotate childcare owing to the pressure for additional income. The negative effect of children aged between six and 12 on male hours worked could perhaps suggest that they are playing an important role in household activities. The survey suggested that a negligible number of children in that age group actually worked in outside employment for a wage. The effects of location, except in the income equation, generally performed poorly. Location variables have generally performed poorly in many applications (ibid.). In many applications they are included to capture local labor market conditions and effects. In this case the two dummy variables representing the villages in Nakhon Si Thammarat were significant in the bivariate participation and tobit models of hours worked. These results have been obtained because the villages concerned in Nakhon Si Thammarat have relatively higher participation rates in outside employment and greater numbers of hours supplied amongst those that do participate. It is perhaps then no coinci- dence that these villages also have the lowest levels of mangrove-dependent income amongst households and also mangrove area remaining.

CONCLUSION

The natural capital stock influenced the decision by males to supply outside employment directly and also through the income production function. The effect on hours supplied by females was solely present through the household income production function. However, the effect was greater for females, suggesting that female participation is more sensitive than males. Previous research has also shown female labor to be more sensitive to external shocks than male labor (Abdulai and Delgado 1999). However, perhaps the most striking result was the importance of mangrove-based income compared to household and personal characteristics, which implies that the economic livelihood of coastal villagers in southern Thailand is affected significantly by mangrove loss.

NOTE

1. If hired and household labor are perfect substitutes in both y1 and y2, then it follows from the first-order conditions that ∂fi ∂f i pyi —— = pyi —— = wi = l for i = 1, 2. ∂ ∂ li hi It therefore follows that, if hired labor for one of the activities is more expensive (that is, w1 2 > w ), then the household will not employ this labor to produce y1. Thus the household will only hire labor for use in both activities if all hired labor receives the same wage (that is, w1 = w2). 9. Analysis of shrimp farms’ use of land Ruangrai Tokrisna

SELECTED STUDY SITES

The development of shrimp farming in Thailand is considered to be the main factor in decreasing mangrove areas along the shoreline in Thailand. In this study the emphasis has been placed on the analysis of shrimp farms’ land use in the selected study sites; a comparison between shrimp farms on the east coast (Gulf of Thailand), in Nakhon Si Thammarat Province, and the west coast (Andaman Sea), in Phang-nga Province. Development on the east coast took place before that on the west coast. Shrimp farms in Nakhon Si Thammarat Province were developed because of the failure of shrimp farms in the eastern region (mainly in Chanthaburi Province). After the disease outbreak and crop failure in the eastern region, shrimp farmers moved down to the south, starting new farms in areas of Songkhla Province and Nakhon Si Thammarat Province along the coastline of the Gulf of Thailand. Shrimp farms along the west coast were established just recently after the failure of the farms on the east coast, probably due to less appropriate topography, land slope and the cost of water intake. In Nakhon Si Thammarat, two areas were selected for the study of shrimp farms’ land use: one in Muang District and another in Pak Panang District. Muang District was an area where shrimp farms were developed first in Nakhon Si Thammarat during the early 1990s. The area was soon over- exploited. The over-crowded shrimp farms, beyond the natural carrying capacity, soon led to shrimp disease outbreak and the loss of the farms. Recently an attempt has been made to rehabilitate the area. The government promoted the Sea Irrigation Program in order to alleviate the problem of water quality and maintaining sustainable shrimp farms. The Royal Department of Forestry focused on rehabilitation of the mangroves. Shrimp farms in Muang District, Nakhon Si Thammarat were mainly old farms that could be maintained using an intensive system. Some are semi-intensive and extensive farms waiting for better environmental conditions. Farmers maintained the farms at a lower cost, and thus received lower returns. Pak Panang District used to be a district abundant in mangroves and paddy fields. It was well known as the rice bowl of the south. With development of

154 Analysis of shrimp farms’ use of land 155 shrimp farming in the early 1990s, the areas were converted into shrimp farms, which soon became over-exploited. The shrimp farmers soon found themselves in a downturn of development. Capable farm managers that were able to cope with the degraded environment mainly ran shrimp farms in this area. Shrimp farm development in Phang-nga has been more recent. Two districts were selected for study sites: Takua Thung District and Muang District. Takua Thung District used to be well known as a tin-producing area. Shrimp farm development in this district was a relatively larger operation run by local as well as non-local investors. Shrimp farms in Muang District were smaller and more often found in mangrove areas.

THE BACKGROUND OF SHRIMP FARMING IN THE SELECTED STUDY SITES

Survey of Shrimp Farmers

The total number of samples in the shrimp farm survey in this study was 101: 50 from Nakhon Si Thammarat and 51 from Phang-nga. Stratified random sampling was employed in four districts. In Nakhon Si Thammarat there were 14 samples from Muang District and 36 from Pak Panang District. In Phang-nga there were 19 samples from Takua Thung District and 32 samples from Muang District. Table 9.1 gives information on shrimp farmers in the selected area.

Experience and age of the farmers The average age of shrimp farmers in the survey was 46 years. The oldest were farmers in Muang District, Nakhon Si Thammarat (at an average of 50). The youngest were the farmers in Pak Panang District (43). These farmers had nine years of experience in shrimp farming, while the experience in existing farms was only seven years, indicating that the farmers may have been engaged in shrimp farming before working in the present farms. Farmers in Muang District, Nakhon Si Thammarat had the longest experience (14 years) while the farmers in the other areas had an average of eight years’ experience in shrimp farming. In terms of aquaculture experience, farmers in Muang District, Nakhon Si Thammarat had an average nine years of experience in shrimp farming while the others had been practicing for only six years on average. Most of the farmers had some experience before starting their operation in the existing farms. They were not newcomers to this business.

Education of the farmers Almost half of the farmers (43 per cent) had only elementary education (four years at primary school), while 15 per cent had a higher than high school Table 9.1 Information on shrimp farmers in the selected areas in year 2000

Nakhon Si Thammarat Phang-nga TOTAL

Muang Pak Panang Total Takua Thung Muang Total Two District District District District provinces

Total (number of samples) 14 36 50 19 32 51 101 Experience and age (yr) Average experience in shrimp 14 8 11 8 8 8 9 culture (yr)

156 Average experience in this 9 6 8 6 6 6 7 farm (yr) Average age of the farmer (yr) 50 43 47 48 44 46 46 Education of the farmer (% of total samples in the area) Elementary 57 53 55 21 38 30 43 Secondary 22 11 17 26 22 24 21 High school 21 22 22 16 25 20 21 Higher 0 14 6 37 15 26 15 Previous occupation (% of total samples in the area) Fisheries 7 24 16 5 16 10 13 Aquaculture 7 11 9 0 3 2 6 Agriculture 36 14 25 27 13 20 18 Others 50 51 50 68 68 68 63 5 2 3 8 84 87 77 14 20 28 22 21 52 28 27 87 8 3 8 2 82 63 80 19 17 27 34 56 12 27 28 87 0 0 6 3 3 3 84 63 97 16 20 53 29 37 51 91 5 0 0 79 63 63 16 21 13 10 24 21 32 63 53 82 2 2 3 5 8 87 93 91 10 22 48 18 29 49 25 88 3 3 8 3 6 11 11 81 86 81 19 39 15 16 77 39 92 0 0 0 0 0 0 11 11 93 36 57 32 43 21 100 100 Shrimp farm survey, 2000. Shrimp farm survey, itle deed Local Immigrant Non-local Totally T Other paper W/o paper Partially Rent Fisheries Aquaculture Agriculture Others None Residential (% of total samples in each area) Land ownership (% of total samples in each area) Shrimp farming as main occupation (% of total samples in each area) % of total samples in the area % of income from shrimp farming 84 Secondary occupation (% of total samples in each area) : Source

157 158 Case studies: Phang-nga and Nakhon Si Thammarat education. The proportion of farmers who had received higher education was the highest among farmers in Takua Thung District (37 per cent). None of the farmers in Muang District, Nakhon Si Thammarat had experienced higher education while more than half (57 per cent) of them had only received elementary education. The farmers on the west coast seemed to have a higher education than those on the east coast.

Previous occupation Some 18 per cent of shrimp farmers had previously been engaged in agriculture, mainly as paddy farmers. More than one-third of the farmers in Muang District of Nakhon Si Thammarat (36 per cent) had been in the agricultural sector before moving into shrimp farming and 13 per cent had been fishermen before becoming shrimp farmers. Almost one-quarter of shrimp farmers in Pak Panang District had engaged in fisheries. Only 6 per cent had been aquaculturists before turning to shrimp farming, mostly in Pak Panang District. None of the farmers in Takua Thung District had been engaged in aquaculture before. More than half of shrimp farmers in the survey had occupations other than fisheries, aquaculture and agriculture before becoming shrimp farmers. They came from a variety of professions: businessmen, employees, merchants and government officials. More than half of the farmers on the west coast (68 per cent) were in this group, the proportion being about half for those on the east coast.

Residential status Most shrimp farmers (87 per cent) were locals; 8 per cent were non-locals who came to use the land for shrimp farming; 5 per cent were immigrants from other locations. All of the farmers in Muang District, Nakhon Si Thammarat were locals and almost all (97 per cent) of farmers in Muang District, Phang- nga were locals. The ratio was less for Pak Panang District (86 per cent) as there were some non-local farmers (11 per cent) and a few immigrants (3 per cent). Most of them were experienced shrimp farmers in the other areas who felt that they were capable of coping with the degraded environmental condition in Pak Panang District. In Takua Thung District only 63 per cent of the farmers were local people; 21 per cent were non-locals, mainly investors from nearby provinces (for example, Phuket Province); 16 per cent were immigrants who were looking for a new area for shrimp farming. There were no immigrants in Muang District, Phang-nga but 3 per cent were non-local investors.

Land ownership While 77 per cent of shrimp farmers owned their land, only 28 per cent had title deeds and 27 per cent had other documentation to prove their right to the Analysis of shrimp farms’ use of land 159 land. The remaining 22 per cent claimed their land ownership in spite of not having any paper to verify their land right. This latter group comprised mostly local people who had long been in the area, and perhaps had been converting mangroves for their shrimp farming. All of the farmers in Muang District, Nakhon Si Thammarat claimed that they had land ownership, but 325 of them did not have any documents to prove their right. In Pak Panang District, 39 per cent of shrimp farmers had title deeds and 39 per cent had other documents to prove their land right; only 3 per cent did not have any paper to support their claim. The ratio of land ownership was lower for the west coast. Only 63 per cent of the farmers in Takua Thung District and Muang District, Phang-nga claimed that they owned the land; 53 per cent of the farmers in Takua Thung District had other documents, while 10 per cent had the land title deed. In Muang District, Phang-nga, 53 per cent did not have any documents for their land right while 6 per cent had land title deeds and 3 per cent had the other documents. The explanation could be the conversion of mangroves for shrimp farms. The farmers may not have any documents confirming rights over the mangrove areas. About one-third of shrimp farmers in Phang-nga rent the land for shrimp farming.

Shrimp farming as main occupation Some 84 per cent of shrimp farmers had shrimp farming as their main occupation and earned 87 per cent of their income from shrimp farming. The dependence on shrimp farming was the highest for shrimp farmers in Muang District, Nakhon Si Thammarat (93 per cent of the farmers and 84 per cent of income). Income from shrimp farming was 92 per cent for those in Pak Panang District and 91 per cent for those in Muang District, Phang-nga. Shrimp farming was still a high income earner for these farmers. The ratio of farmers who had shrimp farming as their main occupation was lower in Pak Panang District (81 per cent) and Takua Thung District (79 per cent). The farmers in these areas still had alternatives besides shrimp farming.

Secondary occupation Some shrimp farmers may have a secondary occupation. From the survey, 52 per cent of the farmers did not have any secondary occupation, practicing only shrimp farming. The ratio was higher for the west coast (56 per cent). In Nakhon Si Thammarat, 77 per cent of the farmers in Pak Panang District had only one occupation while the figure was only 21 per cent in Muang District. Income earned from shrimp farms was relatively low in Muang District, mean- ing that the farmers needed a secondary occupation for their income. In Phang- nga, 61 per cent of the farmers in Takua Thung District did not have any secondary occupation, while it was 51 per cent in Muang District. Secondary occupations included agriculture (20 per cent), aquaculture other than shrimp 160 Case studies: Phang-nga and Nakhon Si Thammarat

(14 per cent) and fisheries (3 per cent), and occupations other than these three (28 per cent) included trading, business, employees and government officials. This high ratio of secondary occupations may indicate that shrimp farming was an attractive source of income for people from other sectors.

Information on Shrimp Farms in the Study Sites

Table 9.2 gives information by location on shrimp farms in the study sites, including type of culture, land use prior to shrimp farming, soil type, water intake and water effluence.

Type of culture From the total samples of 101 farms, most (91) were intensive farms with a high stocking density, relying on mainly ready-mixed feed. Semi-intensive and extensive farms were found only in Muang District of Nakhon Si Thammarat (10 farms). Semi-intensive farms were shrimp farms with a low stocking density, relying on natural larvae while stocking as an addition to natural feed abundance. Semi-intensive farms used some ready-mixed feed at a lower rate than the intensive farms. They were usually those farms that had been lost to disease. After a while, when the environmental conditions were better, owing to the decrease in numbers of shrimp farms in the area, shrimp farmers turned into lower-cost semi-intensive farms. In this survey, there were only two farms which were semi-intensive. Extensive shrimp farms were those that relied only on natural larvae and natural feed abundance. They were farms covering vast areas. Eight farms in Muang District of Nakhon Si Thammarat were found to be extensive.

Land use prior to shrimp farming Most of the farms in the selected study sites were paddy fields (28 per cent), plantations (27 per cent) and mangrove (26 per cent) before being converted into shrimp farms. A further 14 per cent of the samples started their operation on land that had already been shrimp farms, but where the former owners had left the farms for either new occupations or better-yielding areas. Only 4 per cent used idle land for shrimp farming, and 1 per cent used deserted mining areas (found only in Takua Thung District of Phang-nga). The pattern of land use varied between the east coast and the west coast. On the east coast, almost half (45 per cent) of the farms used to be mangroves and 30 per cent had been paddy fields. Among the two study sites on the east coast, the ratio of mangroves was higher in Muang District, Nakhon Si Thammarat (64 per cent as compared to 25 per cent in Pak Panang District). In Muang District, where shrimp farming had been developed earliest, most of the farm Table 9.2 Information on shrimp farms in the selected areas in year 2000

Nakhon Si Thammarat Phang-nga TOTAL

Muang Pak Panang Total Takua Thung Muang Total Two District District District District provinces

Total (number of farms) 14 36 50 19 32 51 101 Culture type (number of farms in each area) Intensive 4 36 40 19 32 51 91 Semi-intensive 2 0 2 0 0 0 2 Extensive 8 0 8 0 0 0 8 Land use prior to shrimp farming (% of total samples in each area) Mangrove 64 25 45 5 9 7 26 Paddy 29 30 30 11 41 26 28 Plantation 0 17 8 68 22 45 27

161 Shrimp farm 7 14 10 11 25 18 14 Mining 0 0 0 5 0 3 1 Idle 0 14 7 0 3 2 4 Soil type (% of total samples in each area) Clay 100 67 83 5 22 13 48 Sand 0 11 6 11 28 20 13 Mixed 0 22 11 84 50 67 39 Water intake (% of total samples in each area) Canal 93 33 63 84 81 82 73 Directly from sea 7 58 33 5 9 7 20 Mangrove 0 0 0 11 9 10 5 Treatment pond 0 9 4 0 1 1 2 Water effluence (% of total samples in each area) Water source 100 33 67 84 81 82 74 Directly to sea 0 14 7 5 9 7 7 Mangrove 0 6 3 11 9 10 7 Outlet canal 0 47 23 0 1 1 12

Source: Shrimp survey, 2000. 162 Case studies: Phang-nga and Nakhon Si Thammarat areas had been mangroves, followed by paddy fields (29 per cent). In Pak Panang District of Nakhon Si Thammarat, most of the farms used to be paddy fields (30 per cent), followed by mangroves (25 per cent). Of the farms in Pak Panang District, 17 per cent used to be plantations (mainly orchards), 14 per cent were already shrimp farms when occupied by the present farmers, and the other 14 per cent used idle land for shrimp farming. On the west coast, 45 per cent were converted plantations (including Pará rubber, coconut and oil palm). Converted mangroves were only 7 per cent of the samples on the west coast. Following mangrove conversion were paddy fields (26 per cent) and former shrimp farms (18 per cent), which 3 per cent of the samples used deserted mining areas and 2 per cent used idle land. By location, most of the farms in Takua Thung District used to be plantations (68 per cent), followed by paddy fields and old shrimp farms (11 per cent each). Mangroves and deserted mining areas were only 5 per cent each of the farms in Takua Thung District. In Muang District, Phang-nga, most of the farms were converted paddy fields (41 per cent), followed by old shrimp farms (25 per cent), plantations (22 per cent), mangroves (9 per cent) and idle land (3 per cent). The pattern of land use varied by location. On the east coast, where shrimp farming had been developed earlier, the ratio of mangrove conversion was higher. Converted paddy fields were the highest proportion in Pak Panang District, the rice-producing area, and was the highest for Muang District in Phang-nga, where most of the farms were small farms. Plantation conversion was found most in Takua Thung District, where shrimp farmers were usually large operators.

Soil type On average, soil type in shrimp farms was clay (48 per cent); 13 per cent was sandy soil, which was inferior in terms of pond capacity, while 39 per cent reported a mixed soil type. In Muang District of Nakhon Si Thammarat, all farms reported a clay type, while in Pak Panang District 67 per cent reported clay, followed by mixed (22 per cent) and sand (11 per cent). The sandy soil farms were those located near the shoreline. In Takua Thung District, 80 per cent reported mixed soil type, followed by sandy type (11 per cent) and a little clay (5 per cent). In Muang District, Phang-nga, 50 per cent of the farms reported mixed soil, followed by 28 per cent sandy type and 22 per cent clay type. In terms of water-carrying capacity, shrimp farms on the east coast could be considered better than those on the west coast.

Water intake Most shrimp farms pumped water from canals near their farms (73 per cent), while 20 per cent directly pumped water from the sea. These were farms Analysis of shrimp farms’ use of land 163 located along the shoreline. Mangrove water, which could be taken from the sub-canals in the mangroves, was used by 5 per cent. It is likely that there were shrimp farms located in mangrove areas. It was noticed that only 2 per cent used a water treatment pond before introducing the water into a rearing pond. By location, 93 per cent of the farms in Muang District, Nakhon Si Thammarat used canal water and 7 per cent used seawater. These farms relied mainly on communal water quality. In Pak Panang District, a little over half (58 per cent) used seawater, being located nearer to shore, and 33 per cent used canal water. It was in Pak Panang District that the ratio of farms with water treatment ponds was the highest (9 per cent), indicating an awareness of water quality from communal sources. In Phang-nga, most of the farms used canal water (84 per cent for Takua Thung District and 81 per cent for Muang District), followed by mangrove water (11 per cent for Takua Thung District and 9 per cent for Muang District). The ratio of seawater was higher for Muang District (8 per cent compared to 5 per cent for Takua Thung District). It was noticed that only 15 farms in Muang District had a water treatment pond.

Water effluence Most of the farms discharged water into the same source as their water effluence (74 per cent on average), which could be a problem for water quality once the number of farms went beyond its natural carrying capacity. Only 12 per cent had an outlet canal discharging the water into the other sources. Discharging water to the sea and mangroves accounted for 7 per cent each. By location, all shrimp farms in Nakhon discharged water into the source of water effluence. The condition was better in Pak Panang District, where 47 per cent of the farms used outlet canals for water discharging; 33 per cent discharged into the source of water effluence, 14 per cent to the sea, and 6 per cent to mangroves. More than 80 per cent of the farms in the two locations in Phang- nga discharged water into their water effluence sources. Only 1 per cent had a different outlet canal.

Farm Acquisition

Information on farm acquisition would be useful for an understanding of a shrimp farm’s land utilization. Information on farm acquisition, the reasons for leaving their farms given by previous shrimp farmers, and farm registration are given in Table 9.3

Farm acquisition and the reason for previous shrimp farmers leaving the farm Overall, 79 per cent of shrimp farmer started new farms, with 12 per cent rent- ing the farms and 10 per cent buying their farms from other shrimp farmers. Table 9.3 Farm acquisition

Nakhon Si Thammarat Phang-nga TOTAL average Muang Pak Panang Total Takua Thung Muang Total Two District District (average) District District (average) provinces

Farm acquisition (% of total samples in each area) Buying from the shrimp farmer 7 6 7 10 16 13 10 Average operating years 10 14 12 2 7 5 8 Starting new farm 93 86 90 64 72 68 79 Average operating years 11 4 8 6 8 7 7 Rent 0 8 4 26 12 19 12

164 Number of operating years 0 3 2 5 5 5 3 Reason for previous shrimp farmer leaving the farm (% of total samples in each area) Shrimp disease 0 1 1 0 3 2 1 Moving to a better area 0 1 1 0 6 4 2 Changing occupation 7 1 4 10 0 3 4 Loss 0 3 1 0 7 4 3 Farm registration (% of total samples in each area) Registered 50 39 45 74 56 65 55 Being enforced 42 28 35 32 40 36 36 Useful 8 11 10 42 16 29 19 Not registered 50 61 55 26 44 35 45 Afraid of being taxed 0 6 3 5 6 5 3 Lack of information 15 39 27 21 24 23 25 Not interested 35 16 25 0 14 7 17

Source: Shrimp farm survey, 2000. Analysis of shrimp farms’ use of land 165

In Muang District of Nakhon Si Thammarat, 93 per cent of shrimp farmers started their new farms in that area and had been in operation longer than the other farmers, that is, 11 years. The other 7 per cent bought their farms from other shrimp farmers. Years of operation were a little lower, at 10 years. The latter group bought their farms from the former owners who had quit shrimp farming for other occupations. In Pak Panang District, 86 per cent of shrimp farmers operated their new farms for four years on average; 8 per cent rented the farms, 6 per cent bought their farms from other shrimp farmers and the farms had been longest in operation (14 years). They were perhaps capable shrimp farmers who took over the farming from less successful ones. In Phang-nga, the ratio of new farms was lower: 64 per cent in Takua Thung District and 72 per cent in Muang District. Years of operation were six and eight years, respectively. In Takua Thung District, 26 per cent rented the farms and had been in operation for five years, while 10 bought their farms from other shrimp farmers. The latter group had the least number of years in operation (two years). Shrimp farming had been developed recently in Takua Thung District, but there were farmers who left for a new occupation. In Muang District, Phang-nga, the ratio of farmers who bought their farms from other shrimp farmers was higher than in Takua Thung District, being 16 per cent. Of this 16 per cent, 7 per cent of the farmers sold their farms because of the loss in shrimp farming, 6 per cent moved to a better area, and 3 per cent sold their farms because of problems with shrimp diseases. There was a higher rate of transition in farm ownership on the west coast, the more recent shrimp farming development area.

Farm registration Overall, 55 per cent of the farmers registered their farms, mostly by enforcement (36 per cent). Only 19 per cent thought registration was useful. Of the 45 per cent non-registered, the main reason for not being registered was a lack of information (25 per cent), 17 per cent were not interested in registration and 3 per cent reported that they were afraid of being taxed. The ratio of registered farms was highest in the new area, Takua Thung District (74 per cent), and lowest in Pak Panang District (39 per cent). Problems in getting the farmers registered might be the lack of information and the perceived lack of benefits from being registered.

Assistance and Source of Funds for Shrimp Farming

Shrimp farming, especially in unfriendly natural conditions, can be complicated. It was interesting to look at the assistance and the source of assistance the farmers obtained in running their farms. Table 9.4 gives the information on Table 9.4 Assistance and source of funding for shrimp farming

Nakhon Si Thammarat Phang-nga TOTAL (average) Muang Pak Panang Total Takua Thung Muang Total Two District District (average) District District (average) provinces

Source of assistance in shrimp farming (% of total samples in each area) Hatcheries 0 6 3 0 0 0 2 Farm input suppliers 14 56 35 79 56 68 51 Shrimp farmer group 14 11 13 11 22 17 15 166 Shrimp buyers 0 3 2 3 2 3 2 Friends and relatives 7 8 8 11 9 10 9 Government officials 7 5 6 11 16 14 10 Type of assistance in shrimp farming (% of total samples in each area) Larvae 14 3 9 0 0 0 4 Feed 14 8 11 16 9 13 12 Treatment 0 19 10 21 22 22 16 Disease control 7 11 9 16 13 15 12 Farming technique 29 25 27 11 19 15 21 Water control 14 19 17 11 22 17 17 Price 0 3 2 3 2 3 2 Market 0 6 3 3 2 3 3 2 4 5 1 3 3 15 52 15 10 39 2 9 4 3 0 4 6 9 56 17 35 3 3 7 6 0 3 6 59 13 13 28 0 0 0 0 5 5 5 16 53 21 42 3 5 6 3 3 0 11 11 21 47 12 43 6 6 2 6 6 6 0 58 10 14 28 0 7 7 0 0 7 0 36 36 14 57 Shrimp farm survey, 2000. Shrimp farm survey, tally borrowed from: shrimp buyer friends and relatives commercial banks Agriculture and Cooperative Bank friends and relatives commercial banks Agriculture and Cooperative Bank cooperative Own investment fund To Partly borrowed from: Source of funding (% total samples in each area) : Source

167 168 Case studies: Phang-nga and Nakhon Si Thammarat source of assistance in shrimp farming, types of assistance and sources of funds.

Sources of assistance The main source of assistance was farm-input suppliers, mainly feed suppliers. In Takua Thung District, 79 per cent of the samples received assistance from farm input suppliers. More than half (56 per cent) of the samples in Pak Panang District and Muang District of Phang-nga received assistance from farm input suppliers. However, only 14 per cent of the samples in Muang District of Nakhon Si Thammarat got assistance from this source. In fact, assistance was lowest in this location, which could be explained by those extensive and semi-intensive farms which used less input. The second important source of assistance was shrimp farmer groups, followed by government officials, friends and relatives, shrimp hatcheries and shrimp buyers.

Types of assistance Most of the assistance was to do with farming techniques, water control and pond treatment in prevention of disease. Assistance on feed and disease control was also found. There was little assistance on larvae and markets, and least of all on price. Shrimp farmers had been encouraged by the farm input suppliers to raise shrimps, an approach calculated to keep the customers.

Source of funds About half of the farmers in the selected study sites used their own money for investment in shrimp farms (52 per cent). The proportion was lower in Muang District, Nakhon Si Thammarat (36 per cent) as most of the farmers borrowed funds from commercial banks (36 per cent) and the Agriculture and Cooperative Bank (14 per cent). In addition they could borrow from friends and relatives (7 per cent totally, 7 per cent partly). In Pak Panang District, 58 per cent used their own investment fund. Twenty-eight per cent borrowed mainly from the Agriculture and Cooperatives (6 per cent). In the case of total borrowing (14 per cent), sources of lending were commercial banks (67 per cent), Agriculture and Cooperative Bank (6 per cent), and friends and relatives (2 per cent). In Takua Thung District, an important source of funds was the Agriculture and Cooperative Bank. Nevertheless 53 per cent of the samples in this location used their own investment fund. Only 5 per cent borrowed the entire amount and 42 per cent borrowed a portion. In Muang District, Phang- nga, 59 per cent used their own investment fund, 13 per cent totally borrowed (mainly from friends and relatives, 7 per cent) and 28 per cent partially borrowed. It should be noted that shrimp farmers in more recently exploited areas on the west coast (that is, Phang-nga) could borrow from shrimp buyers. Analysis of shrimp farms’ use of land 169

Problems Associated with Shrimp Farming

Table 9.5 summarizes problems that shrimp farmers had in their farming. An average 80 per cent of the farmers in the selected study sites reported a larvae problem, and 64 per cent had water quality difficulties. These were the main problems in all study sites. Other problems were feed (23 per cent), soil (21 per cent), the investment fund (19 per cent), marketing (14 per cent), lack of experience (5 per cent), poaching (4 per cent), climate (3 per cent) and shrimp predators (2 per cent). These difficulties resulted in lower yields, and sometimes a loss in shrimp farming.

Larvae Some 80 per cent or more of the samples in each selected site reported larvae problems. Eighty-nine per cent of shrimp farmers in Takua Thung District reporting difficulties. Of this number almost half (42 per cent) reported disease infection in the larvae they bought and 37 per cent reported that the larvae had a slow growth. Often difficulties were the high cost and weak shrimp (5 per cent each). The situation was similar for the samples in Muang District, Phang-nga: except that slow growth (47 per cent) had been found more often than disease infection (25 per cent). Nevertheless, the ratio of the samples that reported larvae problems in Muang District (75 per cent) was less than in Takua Thung District. In Nakhon Si Thammarat, 79 per cent of the samples in Muang District reported a larvae problem, while it was 78 per cent for those in Pak Panang District. Types of larvae problems varied. In Muang District the main problem was disease infection (44 per cent) followed by inadequate larvae supply (21 per cent) and some slow growth and weakness (7 per cent each). In Pak Panang District the main difficulty was slow growth (30 per cent) and disease infection (28 per cent), followed by weakness (11 per cent), inadequate supply (6 per cent) and high cost (3 per cent).

Water quality On average 64 per cent of the farmers suffered from a poor water quality problem. The incidence of this problem was highest in Muang District, Nakhon Si Thammarat (71 per cent). The main cause was water pollution. About half of the farmers in each location reported difficulties with water pollution.

Feed Almost one-quarter of the farmers in the study sites reported a feed problem. By location, it was worst in Pak Panang District, where 42 per cent reported a feed problem, of which 22 per cent was due to low-nutrition and 20 per cent to the high cost. On the other hand, none of the samples in Muang District, Nakhon Si Thammarat reported a feed problem. On the west coast, 26 per cent Table 9.5 Problems in shrimp farming (% of total samples in the area)

Nakhon Si Thammarat Phang-nga TOTAL (average) Muang Pak Panang Total Takua Thung Muang Total Two District District (average) District District (average) provinces

Larvae 79 78 79 89 75 82 80 Inadequate 21 6 13 0 0 0 7 High cost 0 3 2 5 0 3 2 Slow growth 7 30 19 37 47 42 30 Weak 7 11 9 5 3 4 7

170 Disease infection 44 28 36 42 25 33 34 Water 71 61 66 57 66 62 64 Inadequate 14 5 10 0 9 5 7 Plankton boom 0 3 1 6 0 3 2 Low dissolved oxygen 0 5 3 0 0 0 1 Pollution 57 48 53 51 57 54 54 Feed 0 42 21 26 22 24 23 High cost 0 20 10 0 16 8 9 Low nutrition 0 22 11 26 6 16 14 Soil 29 19 24 21 16 19 21 Acidity 22 5 14 6 16 11 13 Leakage 0 8 4 5 0 3 3 Salinity 0 3 1 0 0 0 1 Low quality 7 3 5 0 0 0 2 Nitrate 0 0 0 5 0 3 1 Sulfur 0 0 0 5 0 3 1 Investment fund 21 19 20 16 19 18 19 Inadequate 21 13 17 16 19 18 17 High interest rate 0 6 3 0 0 0 2 Marketing 14 14 14 16 9 13 14 171 Limited outlet 7 6 7 11 3 7 7 Unfair price 7 8 8 5 6 6 7 Lack of experience 7 8 8 0 3 2 5 Poaching 14 3 9 0 0 0 4 Climate 7 3 5 0 3 2 3 Shrimp predator 6 0 3 0 0 0 2

Source: Shrimp farm survey, 2000. 172 Case studies: Phang-nga and Nakhon Si Thammarat of the samples in Takua Thung District reported a problem of low nutrition feed, while the figure was 22 per cent for farmers in Muang District (16 per cent high cost and 6 per cent low nutrition).

Soil About one-fifth of the farmers reported difficulties with soil quality. In Muang District of Nakhon Si Thammarat, 29 per cent reported a soil problem: mainly soil acidity (22 per cent) and low quality (7 per cent). In Pak Panang District, 19 per cent reported a soil problem but the causes were different. The main problem of soil in Pak Panang District was leakage (8 per cent) followed by acidity (5 per cent), salinity and low quality (3 per cent each). On the west coast, a soil problem was more often found in Takua Thung District (21 per cent). Types of problems were soil acidity (6 per cent), leakage, nitrate and sulfur (5 per cent each) indicating inferior soil quality for shrimp farming. In Muang District of Phang-nga, 16 per cent reported difficulties with soil acidity.

Investment fund About one-fifth of the farmers reported a difficulty with investment, mainly the lack of funds. This problem was greatest in Muang District, Nakhon Si Thammarat (21 per cent), followed by Pak Panang District and Muang District in Phang-nga (19 per cent), and was less acute in Takua Thung District (16 per cent). Shrimp farmers in Takua Thung District were relatively larger-scale farmers, capable of a high investment in shrimp farming.

Marketing About 14 per cent of the farmers reported marketing difficulties. On the east coast, types of marketing problems were more or less equal between limited market outlet and unfair prices. In Takua Thung District 16 per cent reported a marketing problem, mainly a limited market outlet (11 per cent). Marketing difficulties were less severe in Muang District of Phang-nga (9 per cent), mainly unfair prices (6 per cent) followed by a limited market outlet (3 per cent). There could have been some market constraints for shrimp farmers in the selected sites.

Lack of experience In Muang District and Pak Panang District, 7 per cent and 8 per cent of samples, respectively, reported a lack of experience, compared to none of the samples in Takua Thung District and only 3 per cent of samples in Muang District, Phang-nga. This could be explained by there being long-developed areas on the east coast, which meant that the areas had been degraded, requiring relatively skillful farmers to cope with the problems in these areas. The Analysis of shrimp farms’ use of land 173 west coast has been recently developed, so that environmental conditions may not have been much degraded, and some farmers have invested in aquaculture even though they lacked experience in shrimp farming.

Poaching Poaching was found only on the east coast. The problem was more often found in Muang District (14 per cent) than in Pak Panang District (3 per cent). On the west coast, shrimp farms were recently developed and mostly located near the dwelling areas, thus there was not a poaching problem.

Climate Only a few farms reported problems with climate. None of the farmers in Takua Thung District claimed to have difficulties caused by climate.

Shrimp predators Predator problems were found only in Muang District, Nakhon Si Thammarat, which could be explained by there being extensive and semi-intensive farms in a large farm area and at a lower cost of operation.

Shrimp Disease in Shrimp Farming

Disease outbreak was the principal cause of failure in shrimp farming. Overcrowded farms and a lack of a well-maintained water system were the main problems. Weak larvae and sudden climate changes could also cause difficulties. Overall, on average on the east and west coast, 79 per cent of the farmers had to deal with shrimp disease. Some were capable of disease control. Those who could not cope with the problem usually did not show a profit. The incidence of disease problems was highest in Pak Panang District (92 per cent) followed by Muang District in Nakhon Si Thammarat (79 per cent). On the west coast the problem was less grave, being 74 per cent in Takua Thung District and 69 per cent in Muang District of Phang-nga. Details are indicated in Table 9.6.

Years of disease infection From the farm survey, shrimp farmers were asked to report the years they had disease problems in their farms. It was likely that disease occurrence had been found more often in recent years. On the east coast, in Muang District of Nakhon Si Thammarat, 37 per cent of the farmers had a disease problem in 1999. (Muang District was the place where shrimp farming had long been developed); 14 per cent of the farmers reported that they had an occurrence of disease as early as 1992. Another 14 per cent had the problem in 1994. Some had the problem in 1997 and 1998 (7 per cent each). In Pak Panang District, the ratio of Table 9.6 Shrimp disease in shrimp farming (% of total samples in the area)

Nakhon Sri Thammarat Phang-nga TOTAL (average) Muang Pak Panang Total Takua Thung Muang Total Two District District (average) District District (average) provinces

Problem of shrimp disease 79 92 86 74 69 72 79 Year of disease infection 1992 14 3 8 5 0 3 6 1993 0 3 1 0 3 2 1 1994 14 3 8 0 0 0 4 1995 0 8 4 0 9 5 4 1996 0 8 4 5 12 9 6 174 1997 7 14 10 21 19 20 15 1998 7 14 10 10 6 8 9 1999 37 39 41 33 20 25 34 Cause of disease as reported by the farmers Infected water 67 71 69 79 67 73 71 Weather change 8 26 17 0 0 0 9 Rain 8 0 4 7 0 4 4 Infected larvae 8 3 6 7 5 6 6 Do not know 9 0 4 7 28 17 10 Solution as reported by the farmers Immediately harvest 20 27 24 18 32 25 24 Treatment 10 30 20 36 21 29 24 Change water 0 0 0 18 16 17 9 None 70 43 57 28 31 30 43

Source: Shrimp farm survey, 2000. Analysis of shrimp farms’ use of land 175 disease problems was higher. As with Muang District, more than one-third of the farmers reported a disease problem in 1999. Indeed, diseases had been reported every year from 1992 to 1999, with an increasing incidence of outbeaks. On the west coast, a lower ratio of farmers reported disease problems in the earlier years, although the occurrences have been more frequent since 1997.

Causes of disease as reported by the farmers Most of the shrimp farmers reported that infected water was the main cause of disease problems. On average on the east and the west coast, 10 per cent reported that they were unaware of the cause. It is to be noted that a higher ratio of the farmers on the west coast did not know the cause of the disease, especially those farmers in Muang District of Phang-nga where 28 per cent reported that they did not know the cause of disease, which may reflect less experience of shrimp farming. The other causes reported were changes in the weather, infected larvae and rain.

Solutions as reported by shrimp farmers Most of the farmers did not take any measures to cure the disease: 70 per cent of the farmers in Muang District, Nakhon Si Thammarat reported that they did nothing when there was a disease outbreak. This could lead to a high loss in shrimp farming. Usually, farmers would have three alternatives in coping with the disease problem. They could harvest immediately, apply chemical treatment in curing the disease or change the water. In Muang District of Nakhon Si Thammarat, farmers tended to harvest immediately with fewer farmers using treatment. None changed the water, since the new water could be infected water. It was similar for farmers in Pak Panang District, except that the ratio of treatment was higher compared to harvesting immediately. On the west coast, owing to better water conditions, farmers still tried changing the water. The ratio of doing nothing was lower on this side of the country.

Shrimp Farm Operation

Most shrimp farms in the selected study sites were intensive. Semi-intensive and extensive farms were found only in Muang District, Nakhon Si Thammarat, which was the area where there were attempts at rehabilitating mangroves after the number of shrimp farms had decreased following problems of degraded environment. Details of farm operation for intensive, semi- intensive and extensive farms are given in Table 9.7.

Intensive farms Overall average farm size of intensive shrimp farms was around two hectares. By location, the farms in Takua Thung District were the largest (4.24 ha/farm). Table 9.7 Shrimp farm operation

Nakhon Si Thammarat Phang-nga TOTAL (average) Muang Pak Panang Total Takua Thung Muang Total Two District District (average) District District (average) provinces

Intensive shrimp farm Average farm area (ha/farm) 1.82 1.76 1.79 4.24 1.42 2.83 2.31 Average number of ponds 2 1 1 4 2 3 2 per farm Average pond area (% of 44 43 43 59 56 57 50

176 total farm area) Average yield (kg/ha/crop) 3 833 4 304 4 069 5 785 5 941 5 863 4 966 Water system (% of total samples in each area) Open 50 50 50 89 59 74 62 Partially closed 50 50 50 11 41 26 38 Average larvae density 69 69 69 76 71 74 71 (larvae/sq.m) Average feed conversion ratio 1.25 1.50 1.38 1.48 1.87 1.67 1.52 Semi-intensive shrimp farm Average farm area (ha/farm) 1.54 n.a. n.a. n.a. n.a. n.a. n.a. Average number of ponds 1 n.a. n.a. n.a. n.a. n.a. n.a. per farm Average pond area 97 n.a. n.a. n.a. n.a. n.a. n.a. (% of total farm area) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 2 55 48 28.62 98 325 Shrimp farm survey, 2000. Shrimp farm survey, verage yield (kg/ha/crop) verage larvae density verage farm area verage number of ponds verage pond area verage yield (kg/ha/crop) A A (larvae/sq.m) A (ha/farm) A per farm A (% of total farm area) A Extensive shrimp farm : Source

177 178 Case studies: Phang-nga and Nakhon Si Thammarat

They were usually large farms in converted plantations whose owners were better off businessmen in the area or came from nearby provinces. Farms on the east coast were smaller (1.82 ha for Muang District and 1.76 ha for Pak Panang District). Muang District of Phang-nga on the west coast had the smallest average farm size (1.42 ha), with shrimp farms developed by local people in the coastal villages. The number of ponds varied, from one in Pak Panang District to two in Muang District of Nakhon Si Thammarat and of Phang-nga, and four in Takua Thung District. Pond area was less than half of the total farm area on the east coast (44 per cent and 43 per cent) while it was more than half on the west coast (59 per cent and 56 per cent). Average yield was nearly five tons per hectare per crop. The yield was lower on the east coast, being lowest in Muang District (3833 kg/ha/crop). In Pak Panang District, yield was higher, with 4304 kg/ha/crop. On the west coast, the relatively new area for shrimp farming, yield was 5785 kg/ha/crop in Takua Thung District and 5941 kg/ha/crop in Muang District. More than half of the farms used an open water system, pumping water from the common water sources directly into their rearing ponds without any water treatment before discharging the water. Half of the farms in both locations on the east coast were open water systems and the other half used partially closed systems. In the closed system, the farmers usually treat the water before introducing it into their rearing pond, to reduce the risk of infected water. Once the pond had been filled, farmers would change water only as necessary to lessen the risk of low quality water effluence. On the west coast, farmers preferred an open water system: 89 per cent of farmers in Takua Thung District used an open water system, while the figure was 59 per cent for Muang District. This could be explained by the land being fresh shrimp farming areas with a relatively better water condition. Stocking density was a little higher on the west coast. On the east coast, it was 69 larvae/sq.m, while it was 76 in Takua Thung District and 71 in Muang District of Phang-nga. The feed conversion ratio was highest in Muang District of Phang-nga (1.87) and lowest in Muang District of Nakhon Si Thammarat (1.25). In Pak Panang District, it was 1.50, being close to Takua Thung District (1.48). These intensive shrimp farms had a similar pattern of operation. The differences were the farm sizes and environmental conditions.

Semi-intensive farms The average farm size of semi-intensive shrimp farms was 1.54 ha/farm, usually with only one pond. This farm type had a lower cost due to less intensive stocking and feeding. The pond area was almost all of the farm area (97 per cent). The stocking rate was only 48 larvae/sq.m. The average yield was thus as low as 325 kg/ha/crop. Farmers usually harvested every two months. Analysis of shrimp farms’ use of land 179

Extensive farms On average, extensive farms had a large farm area (28.62 ha/farm), generally comprising two large ponds per farm which take up 98 per cent of the farm area. Extensive farms did not have larvae stocking. They relied solely on natural larvae and feed abundance. Thus the yield was as low as 55 kg/ha/crop. Farmers usually practiced partial harvesting monthly, two to three months after taking the water into the pond.

COST–RETURN ANALYSIS OF SHRIMP FARMING IN THE SELECTED SITES BY TYPE OF LAND USE

As mentioned earlier, land use prior to the present shrimp farming for the selected study sites involved mangroves, previous shrimp farming, paddy fields, plantations, mining and idle land. It was the aim of this study to investigate the pattern of land use and the cost–return from shrimp farming in different areas. In Figures 9.1 to 9.4, costs and returns of shrimp farming in different locations, previous land use and type of shrimp farming are given. Details on costs and returns are shown in Table 9.8.

Costs and Returns of Shrimp Farming on the East Coast

On the east coast, intensive shrimp farming was found at both sites, Muang District and Pak Panang District. In Muang District, land use prior to shrimp farming involved mangroves (I:Mangrove NK M) and paddy fields (I:Paddy NK M) while in Pak Panang District there were mangroves (I:Mangrove NK PP), shrimp farming (I:Shrimp NK PP), plantation (I:Plantation NK PP), paddy field (I:Paddy NK PP), and idle land (I:Idle NK PP).1 Costs and returns of these shrimp farms are given in Figure 9.1 and Table 9.8. On the east coast, intensive farming methods allowed most of the farms to earn a profit, the exceptions being farms in previous plantation areas and in idle areas in Pak Panang District. Nevertheless, for the latter the losses were less than the fixed and non-cash costs indicating that, excluding non- cash cost, the farmers were still able to earn a net return (that is, total revenue less total cash cost). Farmers tended not to be worried about such losses and simply continued their operations. The loss for the farm in idle areas was not very good being 11 314 baht/ha, while the total cost was 1 109 719 baht/ha (909 275 baht cash cost and 200 444 baht non-cash cost). The loss for shrimp farms in plantation areas was higher (69 370 baht/ha), while the total cost was 947 526 baht/ha (807 507 baht cash cost and 167 079 baht non-cash cost). The total cost varied around a million baht/ha.2 180 Case studies: Phang-nga and Nakhon Si Thammarat

2 000 000 Profit/loss 1 500 000 Variable costs Fixed costs 1 000 000 500 000 Baht/ha 0 –500 000 I:Idle NK M NK M NK PP NK PP NK PP NK PP NK PP I:Paddy I:Paddy I:Shrimp I:Plantation I:Mangrove I:Mangrove

160 000 Land 140 000 Equipment 120 000 100 000 Pond 80 000

Baht/ha 60 000 40 000 20 000 0 I:Idle NK M NK M NK PP NK PP NK PP NK PP NK PP I:Paddy I:Paddy I:Shrimp I:Plantation I:Mangrove I:Mangrove

1 200 000 Others 1 000 000 Maintenance 800 000 Electricity 600 000 Gasoline

Baht/ha 400 000 Treatment 200 000 Labor 0 Feed Seed I:Idle NK M NK M NK PP NK PP NK PP NK PP NK PP I:Paddy I:Paddy I:Shrimp I:Plantation I:Mangrove I:Mangrove

2 000 000 Profit/loss 1 500 000 Non-cash cost Cash cost 1 000 000 500 000 Baht/ha 0 –500 000 I:Idle NK M NK M NK PP NK PP NK PP NK PP NK PP I:Paddy I:Paddy I:Shrimp I:Plantation I:Mangrove I:Mangrove

Notes: 40 Thai baht = US$1. I = Intensive; NK = Nakhon Si Thammarat; M = Muang District; PP = Pak Panang.

Figure 9.1 Costs and returns of intensive shrimp farms in Nakhon Si Thammarat, 2000 Analysis of shrimp farms’ use of land 181

2 500 000 Profit/loss 2 000 000 Variable costs 1 500 000 1 000 000 Fixed costs 500 000

Baht/ha 0 –500 000 –1 000 000 –1 500 000 PG T PG T PG T PG T PG T I:Paddy I:Shrimp I:Mining I:Plantation I:Mangrove

200 000 Land Equipment 150 000 Pond 100 000 Baht/ha 50 000 0 PG T PG T PG T PG T PG T I:Paddy I:Shrimp I:Mining I:Plantation I:Mangrove

2 500 000 Others 2 000 000 Maintenance Electricity 1 500 000 Gasoline

Baht/ha 1 000 000 Treatment 500 000 Labor 0 Feed Seed PG T PG T PG T PG T PG T I:Paddy I:Shrimp I:Mining I:Plantation I:Mangrove

2 500 000 Profit/loss 2 000 000 Non-cash cost 1 500 000 1 000 000 Cash cost 500 000

Baht/ha 0 –500 000 –1 000 000 –1 500 000 PG T PG T PG T PG T PG T I:Paddy I:Shrimp I:Mining I:Plantation I:Mangrove

Notes: 40 Thai baht = US$1. I = Intensive; PG = Phang-nga; T = Takua Thung District.

Figure 9.2 Costs and returns of intensive shrimp farms in Phang-nga, Takua Thung, 2000 182 Case studies: Phang-nga and Nakhon Si Thammarat

2 000 000 Profit/loss 1 500 000 Variable costs Fixed costs 1 000 000

Baht/ha 500 000 0 –500 000 I:Idle PG M PG M PG M PG M PG M I:Paddy I:Shrimp I:Plantation I:Mangrove

140 000 Land 120 000 Equipment 100 000 Pond 80 000 60 000 Baht/ha 40 000 20 000 0 I:Idle PG M PG M PG M PG M PG M I:Paddy I:Shrimp I:Plantation I:Mangrove

1 200 000 Others 1 000 000 Maintenance 800 000 Electricity 600 000 Gasoline Baht/ha 400 000 Treatment 200 000 Labor 0 Feed Seed I:Idle PG M PG M PG M PG M PG M I:Paddy I:Shrimp I:Plantation I:Mangrove

1 600 000 Profit/loss 1 400 000 1 200 000 Non-cash cost 1 000 000 Cash cost 800 000 600 000 Baht/ha 400 000 200 000 0 –200 000 I:Idle PG M PG M PG M PG M PG M I:Paddy I:Shrimp I:Plantation I:Mangrove

Notes: 40 Thai bhat = US$1. I = Intensive; PG = Phang-nga; M = Muang District.

Figure 9.3 Costs and returns of intensive shrimp farms in Phang-nga, Muang, 2000 Analysis of shrimp farms’ use of land 183

100 000 Profit/loss 80 000 Variable costs 60 000 Fixed costs 40 000

Baht/ha 20 000 0 –20 000 NK M NK M NK M NK M NK M S:Paddy E:Paddy E:Shrimp S:Mangrove E:Mangrove

20 000 Land Equipment 15 000 Pond 10 000 Baht/ha 5 000 0 NK M NK M NK M NK M NK M S:Paddy E:Paddy E:Shrimp S:Mangrove E:Mangrove

50 000 Others 40 000 Maintenance Electricity 30 000 Gasoline

Baht/ha 20 000 Treatment 10 000 Labor 0 Feed Seed NK M NK M NK M NK M NK M S:Paddy E:Paddy E:Shrimp S:Mangrove E:Mangrove

100 000 Profit/loss 80 000 Non-cash cost 60 000 Cash cost 40 000

Baht/ha 20 000 0 –20 000 NK M NK M NK M NK M NK M S:Paddy E:Paddy E:Shrimp S:Mangrove E:Mangrove

Notes: 40 Thai baht = US$1. S = Semi-intensive; E = Extensive; NK = Nakhon Si Thammarat; M = Muang District.

Figure 9.4 Costs and returns of semi-intensive and extensive shrimp farms in Nakhon Si Thammarat, 2000 Table 9.8 Cost and returns of intensive shrimp farm, by location, land use and operation

Area(ha) TR TC TR-CC TC TR-VC TR-TC

Cash Non-cash FC VC

Intensive: Nakhon Si Thammarat, Muang District (I: NK M) Mangrove 1.28 1 575 000 838 510 70 130 736 490 42 786 865 854 709 146 666 360 Paddy 0.67 1 653 750 894 878 90 849 758 872 67 412 918 315 735 435 668 023 Intensive: Nakhon Si Thammarat, Pak Panang District (I: NK P) Mangrove 0.93 1 071 368 747 275 162 895 324 093 115 706 794 464 276 904 161 198 Shrimp 1.53 1 188 931 683 809 105 144 505 122 112 957 675 996 512 935 399 978 Paddy 1.11 1 478 936 994 926 280 578 484 010 150 079 1 125 425 353 511 203 432 Plantation 2.86 905 156 807 507 167 019 97 649 149 076 825 450 79 706 –69 370 Idle 0.93 1 098 405 909 275 200 444 189 130 112 269 997 450 100 955 –11 314 Intensive: Phang-nga, Takua Thung District (I: PG T) Mangrove 4.1 340 909 836 637 83 410 –495 728 66 365 853 682 –512 773 –579 138 Shrimp 7.72 1 106 646 1 456 049 120 340 –349 403 172 303 1 404 086 –297 440 –469 743 184 Paddy 1.48 772 578 1 965 627 51 240 –1 193 049 108 563 1 908 304 –1 135 726 –1 244 289 Plantation 3.34 1 226 157 873 301 110 062 352 856 176 142 807 221 418 936 242 794 Mining 2.5 1 953 646 672 338 135 274 1 281 308 135 274 672 338 1 281 308 1 146 034 Intensive: Phang-nga, Muang District (I: PG M) Mangrove 1.92 1 071 389 980 056 108 517 91 333 119 109 969 464 101 925 –17 184 Shrimp 0.71 1 524 379 1 037 306 86 932 487 073 99 877 1 024 361 500 018 400 141 Paddy 1.73 1 172 927 892 602 125 763 280 325 108 922 909 443 263 484 154 562 Plantation 0.91 1 287 997 951 574 124 002 336 423 121 812 953 764 334 233 212 421 Idle 0.56 857 500 540 150 80 530 317 350 80 530 540 150 317 350 236 820 Semi-intensive: Nakhon Si Thammarat, Muang District (S: NK M) Mangrove 2.56 12 976 16 251 3 020 –3 275 3 020 16 251 –3 275 –6 295 Paddy 0.51 87 891 18 359 42 037 69 532 18 600 41 797 46 094 27 494 Extensive: Nakhon Si Thammarat, Muang District (E: NK M) Mangrove 32.72 10 303 4 427 8 568 5 875 3 011 9 985 317 –2 693 Shrimp 8.12 5 750 2 949 1 688 2 801 663 3 974 1 776 1 113 Paddy 19.2 2 604 1 113 5 711 1 491 4 764 2 060 544 –4 219

Notes: TR = Total revenue; TC = Total cost; CC = Cash cost; FC = Fixed cost; and VC = Variable cost; I = Intensive; S = Semi-intensive; E = Extensive; NK = Nakhon Si Thammarat; PG = Phang-nga; M = Muang District; P = Pak Panang District; T = Takua Thung District. Source: Calculated from shrimp farm survey, 2000. Analysis of shrimp farms’ use of land 185

In Muang District, farms in mangrove areas had a slightly lower cost (908 640 baht/ha; 838 510 baht cash cost and 70 130 baht non-cash cost) than farms in paddy areas (985 727 baht/ha; 894 878 baht cash cost and 90 849 non-cash cost), mainly due to lower fixed cost. The fixed cost included costs of land, equipment and pond construction. In mangrove areas, though the farmers had to pay more for pond construction, they paid less for equipment and land rent; thus they had a lower fixed cost. Farms in mangroves in Muang District also had a lower variable cost. Finally, the profits for farms in Muang District were about the same (Table 9.8). In Pak Panang District, the total cost was lowest for farms in previous shrimp farming areas (788 953 baht/ha; 683 809 baht cash cost and 105 144 baht non-cash cost) and highest for farms in paddy fields (1 275 504 baht/ha; 994 926 baht cash cost and 280 578 baht non-cash cost). Farms in previous shrimp farm areas could earn the highest profit. Farms in mangroves had a similar cost structure to those farms in mangroves in Muang District, but they had to pay more for land rent. Land rent in Pak Panang District was higher for every farm group, but still lowest for farms in mangroves. Relative lower fixed cost, especially land and pond construction in certain areas, could be an incentive in converting mangroves to shrimp farming. For variable cost, the main cost item for all farm groups was feed cost. In Muang District, the performance on profitability did not vary much between farms in mangroves and in paddy fields. In Pak Panang District, farms in previous shrimp farms may have been managed by skillful farmers who were capable of using lower costs (especially feed cost) and earned more profit than other farm groups in the same site. Nevertheless, the profits of farms in Pak Panang District were still lower than those in Muang District. The high profit of farms in Muang District could be explained by their lower fixed cost, especially land and pond construction.

Costs and Returns of Intensive Shrimp Farms on the West Coast

Costs and returns of intensive shrimp farms in Takua Thung District There were five types of previous land use for intensive shrimp farms in Takua Thung District: mangroves (I:Mangrove PG T), shrimp farms (I:Shrimp PG T), paddy field (I:Paddy PG T), plantation (I:Plantation PG T) and mining areas (I:Mining PG T).3 (See Figure 9.2 and Table 9.8.) Intensive farms on land converted from mangroves, shrimp farms and paddy fields in Takua Thung District showed losses. Only those farms on lands used previously for plantations and mining areas could earn a profit. The losses were greater than the fixed cost and the non-cash cost. Shrimp farmers in previous mangrove swamps, shrimp farms and paddy fields in Takua Thung District had negative net returns from shrimp farming. In spite of relatively 186 Case studies: Phang-nga and Nakhon Si Thammarat low cost, both fixed and variable cost, shrimp farming in mangrove swamps could not make any profit because of low yield (2841 kg/ha) and a lower shrimp price (120 baht/kg). The farm size was considered large (4.10ha). Shrimp farming in mangroves in this selected site might not be productive. Environmental conditions, such as topography and soil quality, are less favor- able for shrimp farming, unlike those on the east coast. This could be a reason for the slow development of shrimp farming and less mangrove conversion in this area. Farms in previously shrimp farm areas incurred a loss. They may have been those farms deserted by the previous owners who turned to other occupations after realizing that shrimp farming was not suitable in this area. The cost of land was high for this farm type, highest among all in the same location, while the variable cost was the second highest. The farms in previous paddy fields had the highest variable cost, especially feed cost. Even if the yield was quite high (3552 kg/ha) and received a good price (218 baht/kg), the high return could not cover the high cost. This farm type in Takua Thung District incurred the highest loss. Most shrimp farms in Takua Thung District were previously plantations, mainly rubber plantations. They could earn a profit. Nevertheless, land cost was high, almost as high as the land cost of shrimp farming in previous shrimp farm areas. In spite of a high fixed cost, the farmers spent less on variable costs and were able to gain a profit, more or less comparable to those profitable farms in Pak Panang District.

Costs and returns of intensive shrimp farms in Muang District of Phang-nga In this location shrimp farms were originally from five different types of previous land use: mangroves (I:Mangrove PG M), shrimp farms (I:shrimp PG M), paddy fields (I:Paddy PG M), plantation (I:Plantation PG M) and idle land (I:Idle PG M). All of the farms except those in previous mangrove areas earned a profit. Nevertheless, the loss of the latter farms was not very high (17 184 baht/ha), less than fixed cost and non-cash cost. The farmers were able to gain a net return (101 925 baht/ha), which explained their continuation in shrimp farming. (See details in Figure 9.3 and Table 9.8.) The cost of shrimp farming did vary considerably among different types of previous land use. Shrimp farms in previously idle land had the lowest cost. The farmer was able to get a high profit, second only to the farm in previous shrimp farm areas, owing to their lower cost – both fixed and variable. As it was reported that former shrimp farm owners had left the farms because of shrimp disease and moving to more productive areas, the farms may have been bought by capable farmers who were able to carry on the operation and gained quite a high profit (400 141 baht/ha). Analysis of shrimp farms’ use of land 187

Costs and returns of semi-intensive and extensive shrimp farms on the East Coast For the semi-intensive farms, the previous land use was for mangroves (S:Mangrove NK M) and paddy fields (S:Paddy NK M). The previous land use for extensive farms were mangroves (E:Mangrove NK M), shrimp farms (S:Shrimp NK M) and paddy fields (E:Paddy NK M). (See Figure 9.4 and Table 9.8.) Semi-intensive farms and extensive farms in mangrove swamps incurred a loss. The loss was higher for semi-intensive farms, owing to a higher cost. Extensive farms in previous paddy fields also lost. Nevertheless, only semi- intensive farms in previous mangrove swamps had a negative net return, being unable to cover all the cash cost. These were the farms that continued their operation while waiting for a better opportunity, such as a higher shrimp price and improvement in environmental conditions that would lead to a better yield.

Factors Affecting Shrimp Farms’ Use of Land

The pattern of shrimp farms’ use of land seemed to vary along the east coast and the west coast. On the east coast, intensive shrimp farming started from the conversion of mangroves and paddy fields. These were profitable farms on the east coast. On the west coast, such farms incurred a loss from shrimp farming. Profitable intensive shrimp farms on the west coast were those in previous plantations. Shrimp farming in the areas where there had been shrimp farms made a profit in Pak Panang District on the east coast and in Muang District of Phang-nga on the west coast, but incurred a loss in Takua Thung District. (See Table 9.8.) Three factors appear to affect the shrimp farms’ use of land: type of ownership, the profitability of aquaculture and the locality. For the 101 farms surveyed, a logit function was employed in order to determine the probability of a decision on various types of land use for shrimp farms. These land uses included the uses of mangroves, paddy fields, shrimp farms, plantations, idle land and mining areas for shrimp farming. Dependent variables were the six dummy variables for such land uses. Explanatory variables included the two dummy variables for ownership (0 if owned and 1 if rented) and residency (1 if owners lived in the area, 0 otherwise); six variables for shrimp price (lagged for one period, in baht/kg), land price (baht/ha), larvae price (baht/100 larvae), feed price (baht/kg), labor wage (baht/month), and fuel price (baht/litre); and one dummy variable for locality (1 if the farm was on the west coast, 0 if otherwise). Owing to a limited number of observations, only three explanatory variables could be included in the final estimations presented in Table 9.9. Shrimp price was the significant factor in every type of land use. Larvae 188 Case studies: Phang-nga and Nakhon Si Thammarat

Table 9.9 Logit function of shrimp farm’s land use, by type of land use

Land use Shrimp pricea Larvae priceb West coastc Log likelihood

Mangrove 0.0075** –0.2646*** –1.1596* –43.4606 (0.0034) (0.0794) (0.6094) Paddy field –0.0071** 0.1069* –1.0487** –57.3830 (0.0030) (0.0648) (0.4730) Shrimp farm –0.0063** –0.0213 –0.1964 –42.1541 (0.0033) (0.0721) (0.5644) Plantation –0.0105*** 0.0392 1.7958*** –48.0765 (0.0038) (0.0807) (0.5024) Idle land –0.0091** –0.0159 –1.6795 –22.8643 (0.0044) (0.0934) (1.1040) Mining –0.0189* –0.0555 0.4409 –7.3086 (0.0100) (0.2192) (1.7319)

Notes: Land use = a (shrimp price) + b (larvae price) + c (west coast); * = significant at 90%; ** = significant at 95%; ***= significant at 99%. Numbers in parenthesis are standard errors of the estimates. price was selected as a representative of farm input price. Other factors, such as other input prices, which may also affect stocking density, could not be significantly included in the estimation. Larvae price was significant for shrimp farms in previous mangroves and paddy fields. The west coast dummy variable was significant in the case of mangroves, paddy fields and plantations. In the case of mangroves, the higher shrimp price could lead to a higher probability of converting mangroves into shrimp farms, while the increase in larvae price would reduce the probability. Farms in the west were less likely to be originally converted from mangroves. For those farms using paddy field areas, the increase in shrimp price would result in less conversion of paddy fields. The limitation of suitable land, the loss of farms in paddy fields in the new areas, and the expansion to the west coast could be the reasons. Increase in larvae price led to more paddy field conversion. Among all land types, paddy fields might have been the most accessible and perhaps at a lower cost of conversion. When input prices increased, farmers would turn to use of paddy fields. Again this was less probable for shrimp farms on the west coast to convert paddy fields for shrimp farming. For shrimp farming in existing shrimp farms, the increase in shrimp price led to less investment in such areas. Existing shrimp farm owners who might want to continue their operation when the shrimp price was better therefore did not sell the farms to others. In the case of plantations, idle land and mining, the increase in shrimp price led to less conversion of these lands. This increase only led to more conversion of mangroves, since the cost of conversion was Analysis of shrimp farms’ use of land 189

Table 9.10 Probability of using different type of land for shrimp farming, by location

Land use East coast West coast Overall

Mangrove 0.3346*** 0.1232*** 0.2278*** Paddy field 0.3531 0.2344*** 0.2932** Shrimp farm 0.1563 0.1510* 0.1537** Plantation 0.1159*** 0.4618 0.2679*** Idle land 0.1000*** 0.0196*** 0.0594*** Mining 0.0102*** 0.0212*** 0.0158***

Notes:*= significant at 90%; ** = significant at 95%; ***= significant at 99%.

Source:Calculated from equations in Table 9.9. the lowest. Nevertheless, on the west coast, there was more conversion of plantations. From the above six logit functions for various land uses, the probabilities of converting the land into shrimp farms were calculated for the east coast, for the west coast and overall. Results are given in Table 9.10. Overall, the probability of converting paddy fields into shrimp farms was the highest (0.2932) followed by plantations (0.2679). Conversion of mangroves was in third place (0.2278). The probability of new investors using previous shrimp farm areas was only 0.1537. The probability of using idle land was only 0.0594. The least probable was the use of mining areas. By location on the east coast, it was most likely the shrimp farming would be in previous paddy fields (0.3531) and mangroves (0.3346). The probability of such uses were lower for the west coast (0.2344 and 0.1232, respectively). Nevertheless, the estimation for the conversion of paddy fields on the east coast was not significant, owing to wide deviation in the probability values as compared to a limited number of samples in this area. Such a problem was also found in cases of the use of existing shrimp farms where the probability was 0.1563 but not significant. In the case of plantations, the probability was 0.1159, followed by idle land (0.1000) and it was minimal for mining areas (0.0102). On the west coast, the probability of converting plantations into shrimp farms was highest (0.4618) but not significant, owing to the marked variation of data in a limited number of observations. The second most probable land use was the conversion of paddy fields (0.2344), which was less significant than that of the east coast. Conversion of existing shrimp farms (buying from the other shrimp farmers) was the third (0.1510), about the same as on the east 190 Case studies: Phang-nga and Nakhon Si Thammarat coast. Mangrove conversion was much less popular on the west coast (0.1232), being in fourth place. Conversion of mining and idle land was minimal (0.0212 and 0.0196). The threats to mangrove conversion on the west coast was almost one-third less than on the east coast owing to the lesser suitability for shrimp farming and, perhaps, the increased interest in mangrove conservation on the west coast.

NOTES

1. I = Intensive; NK= Nakhon Si Thammarat; M = Muang District; PP = Pak Panang. 2. 40 Thai baht = US$1. 3. I = Intensive; PG = Phang-nga; T = Takua Thung District. 10. Coastal communities, mangrove loss and shrimp farming: social and institutional perspectives Wattana Sugunnasil and Suthawan Sathirathai

BACKGROUND

When natural resources such as mangroves are depleted at an alarming rate, it is obviously a question of mismanagement. As in the case of terrestrial forests in Thailand, mangroves are under the jurisdiction of the state through the care of the Royal Forestry Department (RFD). However, in practice, local coastal communities play significant roles in the use and management of the resources. This chapter will examine relationships between coastal communities and mangrove forests, also in the context of shrimp farming expansion under the influence of the current institutional settings. The chapter is divided into three main sections. The first briefly discusses the existing law and policy regarding the use and conservation of mangroves. The second discusses the communities’ interaction with the resources. The last section attempts to analyze the situations in the light of social and institutional perspectives.

EXISTING LAW AND POLICY ON MANGROVE MANAGEMENT AND CONSERVATION: PROBLEMS AND TRENDS

Under the current legal system, the Royal Forestry Department (RFD) is the sole agency with legal authority to protect and manage mangrove forests in Thailand. However, in practice, there are several governmental agencies which affect the utilization and conservation of mangrove; for example, shrimp farming enterprises and mining concessions in the mangrove area have been carried out with the support of the Fishery Department and the Department of Mineral Resources, respectively. The national committee on policy and planning for the management of mangrove was set up along with

191 192 Case studies: Phang-nga and Nakhon Si Thammarat several sub-committees to oversee conflicts of various objectives. Major legislation that has had a direct effect on the management and conservation of mangrove includes the Forest Act of 1941 (amended version), the National Forest Reserve Act of 1964 (amended version), the Protection and Conservation of Wild Animals Act of 1960, the National Park Act of 1961 and the Forest Plantation Act of 1992. Under the current Constitution (1997), people and communities are encouraged to participate in the management and conservation of natural resources, including mangroves. Accordingly, their rights and responsibilities have to be recognized by law. However, legislation intended to bring about such a constitutional objective, which in this case would be the Forest Community Act, has not yet been promulgated. Attempts have failed as a result of conflict over the devolution of RFD’s power. Besides major legislation, several Cabinet resolutions have also played an important role in setting up various measures and the policy direction for the utilization and protection of mangroves under different circumstances over the past 30 years. Under the current mangrove law and policy, mangrove areas are divided into two zones, namely the conservation and the economic zones. The conservation zone includes both the existing mangrove forest and the newly planted areas. In the economic zone, a multiple-use system has been encouraged to ensure the sustainable use of mangrove. The Cabinet Resolution of 17 October 2000 focused on the strict protection of buffer zones of mangrove forest along the coastlines by RFD and a resolution on people’s settlement in the mangrove areas before the designation of the conservation zone. According to the existing policy, a multiple-use system has been encouraged in the economic zone. Nevertheless, clear cutting of the forest to pave the way for intensive shrimp farming is still a normal practice. Moreover, bribery and corruption have consistently weakened the ability of the RFD strictly to protect mangrove forest in the conservation zone, as stated by law. It can be clearly seen that the current policy encourages strict conservation of mangroves carried out exclusively by the RFD. There is no clear policy direction on how to encourage local community participation in the management and conservation of mangroves. As mentioned earlier, there has not yet been legislation that actually executes the constitutional objectives of recog- nizing the rights and responsibilities of the local people and communities in the management and conservation of natural resources. The passing of a Community Forest Law has already been denied. Moreover, there are currently a number of conflicts concerning several policy objectives, being proposed by various governmental agencies, involving the utilization and protection of mangroves. Problems might be even more complicated with additional governmental agencies at the local level. However, if the local government truly represents local people and protects their interests, it is likely that the local authorities will manage the resource Coastal communities, mangrove loss and shrimp farming 193 better than the central governmental agencies, provided that the appropriate incentive and penalty system is in place.

DISCUSSION OF THE INTERACTION OF LOCAL COMMUNITIES AND RESOURCES IN THE STUDY AREAS

This section will focus on the interaction and dynamic relationships between coastal communities and mangrove forests in the context of shrimp farming expansion. The discussion will be based on four case studies covering the range of experiences of coastal communities dependent upon mangrove forests in southern Thailand.

The Cases of Ban Khlong Khut and Ban Gong Khong in Pak Panang Bay

Fisheries and land-based agriculture have traditionally been two major sources of income for local residents of Pak Panang Bay. However, the productivity of fishing and agriculture around the bay has declined steadily owing to a combination of factors, including population pressure, improved fishing technology and changes in coastal environment and resources. In the early 1970s, shrimp aquaculture was introduced along the coast of Thailand, with great success in some areas. This has led to a rapid increase in the number of shrimp farms in Nakhon Si Thammarat Province, especially on the western part of Pak Panang Bay. In the late 1980s, shrimp farming expanded to the eastern part of the bay, particularly on the western part of Ta Lum Puk Cape. Areas used for shrimp farms increased from 6900 rai in 1988 to 10 724 rai in 1990, while the number of farms also increased, from 279 to 1507 (Boonchuwong 1995). In 1975, mangrove forests in Nakhon Si Thammarat covered approximately 96 875 rai. By 1989, the area had been reduced to 53 256 rai. Several deforestation agents have contributed to this loss, including the demands for urban and infrastructure development, and a variety of agricultural and other uses (Boonchuwong 1998; Plathong 1998). However, of the 43 600 rai converted to other uses between 1975 and 1989, more than 80 per cent was converted to aquaculture, making it the single largest contributor. The loss of mangrove forests is attributable, in part, to illegal encroachment into areas designated as forest reserves. The two case studies in Pak Panang Bay are Ban Khlong Khut and Ban Gong Khong coastal communities. A dirt road interspersed with concrete surface leads through Ban Khlong Khut. Houses, coconut groves, shrubs and large shrimp ponds are spread along the road and canal leading to Pak Panang 194 Case studies: Phang-nga and Nakhon Si Thammarat

Bay. Although physically and socially a single unit, it is administratively divided into two sections: one is included within Pak Nakhon Subdistrict municipality and the other is not. In the past, all families in Ban Khlong Khut were dependent on rice farming as the main source of income but at present there are only four or five households which regard rice farming as their main source of livelihood. Their cultivated lands, however, are not located in the village. Today, about 86 per cent of the 51 households under survey depend on fishing as their main source of income. All fishermen own capital-intensive fishing gear called Yor Peek, a large stationary liftnet with wings, and some own mini or large trawlers for fishing purposes. With an urban center nearby, working as wage laborers has become an important source of income for many villagers (43 per cent). Some families (14 per cent) directly or indirectly engaged in shrimp ponds reside and live in their two-story houses, which are conspicuous for their size, material used and luxury. (See Table 10.1.) In the past, the community was surrounded by thick mangrove forests. Houses were built along the canal. Rice growing was the main occupation and rice was cultivated in the area located between the mangrove forests and the canal connected to the main stream leading to Pak Panang Bay. Smaller crabs and shrimps in the mangroves were collected for sale. Fishing (using cast nets, hook and line) was mostly for personal consumption. Villagers depended heavily upon the mangroves for direct uses (for example, timber for house poles, fishing boats, fuel, nypa for thatching) and indirect uses (for example, harvesting smaller crabs and shrimps). In the early 1970s, aquaculture ponds in Muang District, Nakhon Si Thammarat, were constructed in reserved mangrove forests close to the shores. Areas with thick stands of large mangrove trees were cleared and the

Table 10.1 Sources of income of households in Ban Khlong Khut

Sources of income No. of households Percentage

Fishing 44 86 Shrimp farming Traditional 7 14 Intensive 7 14 Off-farm/wage labor 22 43 Total 51 100

Note: The sample respondents report more than one source of income.

Source: Survey of 51 households. Coastal communities, mangrove loss and shrimp farming 195 vegetation was reduced to low scrub, making the areas easy to develop. After the trees were cut, dikes were built around the area and the roots were left to rot for one or two years. In the early years, the use of shrimp ponds was largely traditional and was based on an extensive system of production. This practice rapidly expanded to cover many coastal communities in Muang District, including Ban Khlong Khut, where rice farmers were experiencing low productivity. In 1975, the rice fields in Ban Khlong Khut were flooded with saline water, and since then rice productivity has been drastically reduced. Some rice fields were therefore abandoned. Large tracts of paddy fields in Ban Khlong Khut and nearby communities were intermittently susceptible to the problem of flooding from high tides. In some years, paddy growth was inhibited, yields were low or negligible and salinity posed an additional problem, with low and irregular rainfall and insufficient freshwater outflow. Shrimp aquaculture in Ban Khlong Khut has evolved from simple fish/shrimp traps such as mud walls which trap shrimp and fish coming into the estuary at high tide and hold them while the tide recedes. The traditional shrimp farming practice in Ban Khlong Khut is essentially such a system of trapping and holding. Since the early 1970s, shrimp ponds in Ban Khlong Khut have been constructed in reserved mangrove forests nearby, and, through drainage and the construction of dikes, villagers have gradually reclaimed mangrove land. By the early 1980s, most mangrove forests around the village had been completely degraded. The arrival of shrimp farming further aggravated the situation of rice farmers in Ban Khlong Khut, as the seepage of saline water from adjoining shrimp farms has resulted in yield losses and a reduction in rice productivity. Conflicts between rice farmers and shrimp pond producers occurred. However, this has never become a serious problem as most residents were implicated, directly as owner- operators or indirectly as rentiers. Furthermore, high profits, sustained by the huge demand of the developed nations, encouraged many farmers to switch from the traditional and semi-intensive culture to intensive methods. Some rented out or sold their land to local or outside shrimp investors, while others used their own savings or borrowed capital to turn their rice fields into shrimp ponds. By the late 1990s, intensive shrimp farms had been completely abandoned as the result of disease outbreaks and low productivity. Many residents became heavily indebted. Some switched back to the extensive method. Mud crabs and grapsid crabs, known locally as Pu Preow, had reportedly disappeared from the vicinity of Ban Khlong Khut. Most residents are now increasingly dependent upon and compete for their catch from the dwindling marine stock in Pak Panang Bay. This decreasing marine stock, some believe, could be attributed to the increasing number of fishermen and polluted wastewater discharged into the bay from thousands of rai of shrimp farms located along the bay’s 196 Case studies: Phang-nga and Nakhon Si Thammarat coastline. Nevertheless, more invested their money to upgrade and improve their fishing boats and fishing gear, particularly the popular Yor Peek. This kind of fishing gear requires a constant replacement of wood and poles, most of which are provided by illegal poaching from reserved mangrove forests on the west side of Ta Lum Puk Cape. (Hence 28 households, or 55 per cent, reported their dependence on mangrove forests, even though the mangroves around the community have been completely degraded.) Wage labor in nearby factories and downtown has become another important source of income for many villagers as Ban Khlong Khut has been increasingly incorporated into the Pak Nakhon Subdistrict municipality. Ban Gong Khong is another study site located on the eastern part of Pak Panang Bay, Pak Panang District. The community is located within and surrounded by the reserved mangrove forest on the western coast of Ta Lum Puk Cape, east of Pak Panang Bay. Early settlers, in the 1950s, recalled working as woodcutters for charcoal production on Ta Lum Puk Cape as the main attraction. Fishing in the mangrove canals also provided an important additional income. Later on, when charcoal concessions were no longer operating, working as hired laborers in the mangrove replanting program of the Forestry Department, started in the 1970s, became a major source of income for many Ban Gong Khong residents. A sample survey of 53 households in Ban Gong Khong shows that most villagers are highly dependent upon mangrove forests (Table 10.2). About 74 per cent of sample households derive their income from fishing in the mangrove areas. Mud crabs and small shrimps such as Acetes (known locally as Kung Keoy) have been extensively caught in mangrove canals. Local wage laborers (working for shrimp farms) and shrimp farming are two other sources of income for 68 per cent and 21 per cent of households, respectively.

Table10.2 Sources of income of households in Ban Gong Khong

Sources of income No. of households Percentage

Fishing: in coastal areas 18 34 in mangrove forest 39 74 Intensive shrimp farming 11 21 Off-farm/wage labor 36 68 Total 53 100

Note: The sample respondents report more than one source of income.

Source: Survey of 53 households. Coastal communities, mangrove loss and shrimp farming 197

In the 1950s, the local vegetation of Ban Gong Khong mainly consisted of dense mangrove forests, mostly large trees. Wood cutting for nearby charcoal factories was the major source of income for early settlers. Harvesting small shrimps and crabs in mangrove canals and estuaries provided supplementary income. Pioneer families also depended heavily upon the mangrove for materials used for house construction and firewood. New families were able to clear the mangrove areas as much as they needed, mostly for their own residences. In early 1960, there was an increase in demand for shrimp from local markets in Pak Panang District. Villagers intensified their catch using simple fishing gear such as paddling boats and small push nets. More landless and poor people, many of whom were related to early settlers, moved in as wage laborers engaged in wood cutting and fishing, as this provided a more stable and secure livelihood. Some families started expanding their residential areas and cleared more mangrove forests. Ban Gong Khong villagers claimed to have been living in the area before the mangrove forest on Ta Lum Puk Cape was declared a reserved forest, in 1965. However, as the village head failed to notify the matter to local authorities, they regarded Ban Gong Khong residents’ occupancy as illegal. Villagers recalled a couple of occasions when forestry officials threatened them with eviction. Nevertheless, villagers continued to expand their residential areas by clearing more mangrove forests despite several warnings by authorities not to encroach further, particularly upon those mangrove forests opposite the canal, as they are all declared reserved forests. Replanting programs on reserved forests by the Forestry Department began in the early 1980s . As charcoal factories were closing down, Ban Gong Khong villagers began working for replanting programs instead. More people moved in and made their living from hired labor in the replanting program and fishing. Collecting small crabs in the mangroves still provided a substantial income for villages. Communication with urban centers became easier as a dirt road connecting villagers to the main highway was completed in 1983. The reclaimed land was not of much value until intensive shrimp farming came to Ban Gong Khong in the late 1980s. The high profit encouraged many villagers to invest their savings or borrowed capital in shrimp farming. Mangrove forests were cleared and large trees were burnt down, using mostly human labor to avoid attracting the attention of local authorities. During this early expansion of shrimp farms in Ban Gong Khong, forestry authorities came in to designate the community boundaries, and put up signs around reserved forests. The profit from shrimp farming enabled some villagers to build new and modern houses. In the early 1990s, shrimp farming in Ban Gong Khong expanded rapidly. Bulldozers were brought in to clear mangrove areas and dig up shrimp ponds. 198 Case studies: Phang-nga and Nakhon Si Thammarat

Villagers claimed to have given some money to the village head, who was a pioneer shrimp farmer himself, and to the authorities before they could start digging up the ponds. Many fishermen used saved or borrowed capital to invest in shrimp farming. At present there are 120 shrimp ponds located within the vicinity of the village. Nevertheless, harvesting marine life in the mangroves is still an important source of income for some who do not own much land or lack the necessary capital. As there was no coordination between shrimp farm operators, disease outbreaks and polluted water became a serious problem. In the late 1990s, many local shrimp farmers went bankrupt. Most returned to their fishing and faced the fact that the fish stock had already declined. Small crabs in mangrove canals were harder to find. Many villagers claimed shrimp farm investors on the east coast of Ta Lum Puk Cape had dumped effluents and polluted wastewater into mangrove forests on the west side of the Cape, thereby destroying the habitats of marine life. Water in canals, along which many shrimp farms are located, became polluted. Alarmed by the situation, forestry authorities came to survey and record the number of shrimp ponds and declared that no more new ponds were allowed. Temporary occupation rights for villagers were permitted, but the transfer of the right was prohibited. However, in the last few years, tracts of land have been transferred to outside shrimp farming investors, although this is against the law. At present, approximately 30 per cent of shrimp ponds in Ban Gong Khong are owned and operated by outside investors. In the late 1990s, the replanting mangrove program to honour His Majesty The King extended to areas alongside Ban Gong Khong’s road, covering about 3000 rai. Key informants claim mangrove forests around the village and in reserved areas are much denser, thicker and healthier than they were 20 years ago as a result of replanting programs. At present, villagers are still harvesting timber and wood to be used for making boardwalks and poles, although the availability of electricity and gas has reduced the local need for firewood. There are a number of families in Ban Gong Khong who do not own a large tract of land and do not have enough savings to invest in the shrimp farming business. A few of them are very poor and still live in houses covered by thatched roofs. These are villagers who have been experiencing the direct impacts of shrimp farming on mangrove forests as they are more dependent on fishing and collecting shrimps and crabs in mangrove canals. For some, collecting grapsid crabs, although these are increasingly hard to find, remains an important source of income. Not only is their access to these marine resources in areas close to shrimp farms increasingly limited, but they are also observing a decline in marine species as a result of polluted water discharged into mangrove canals by shrimp farm operators. Many villagers also complain about the quality of water in canals, which has become polluted since the arrival of shrimp farms. Coastal communities, mangrove loss and shrimp farming 199

Table 10.3 Sources of income of households of Ban Sam Chong Tai

Sources of income No. of households Percentage

Capture fishery Coastal areas 33 60 Mangrove forest 39 71 Fish aquaculture 10 18 Off-farm/wage labor 11 20 Total 55 100

Note: The sample respondents report more than one source of income.

Source: Survey of 55 households.

The Cases of Ban Sam Chong Tai and Ban Bang Pat in Phang-nga Bay

The study area is located in the western part of Phang-nga Bay, Phang-nga Province. Ban Sam Chong Tai is surrounded by mangrove forests, with streams and canals to the north and west. The whole area is inundated by seawater during high tides. Most houses are located near the shoreline, some having been built on stilts over water. Mangrove timber is used for boardwalks, floors and verandas, where many household activities take place. All villagers earn their main living from fishing, mostly with boats using small outboard motors (Table 10.3). Surrounded by mangrove forests and a rather isolated community, until a dirt road connected to main highways was built as recently as 1997, Ban Sam Chong Tai has been, and still is, highly dependent upon direct and indirect uses of the mangroves. Small species of shrimps such as Acetes (Kung Keoy) have been extensively caught in mangroves. They are sold fresh, dried or as shrimp paste. The latter is made of ground and fermented shrimps and forms an important ingredient in Thai and Southeast Asian cooking. Usually these small shrimps are sold for local consumption. Mud crabs (Pu Dam) command a high price and form the basis of valuable small-scale fisheries throughout coastal areas. They are caught by means of baited traps or simply dug up and pulled out of their burrows with a long hook. The small grapsid crabs (Pu Preow) are also a major source of income in Ban Sam Chong Tai. They are sold fresh and some are fermented and used in cooking. In the past, the village was surrounded by dense mangrove forests, consisting mostly of large trees. Koey was plentiful in the area, and harvesting Koey in mangrove canals provided the main source of income for local residents. Other important marine species included mantis shrimp, mud crabs and 200 Case studies: Phang-nga and Nakhon Si Thammarat mullet. Simple fishing gear was used such as sails, stake traps, cast nets, hook and line, and small push nets. They also had to travel to inland communities to exchange their fish products for other necessities, mainly rice. Cutting down trees for charcoal production for Chinese merchants to be exported to Penang was practiced by most villagers. In 1965, an area of 2000 rai, including parts of Ban Sam Chong Tai’s residential area, was declared a National Park. Historically, Phang-nga Bay has been an open access resource with relatively free-for-all harvesting of mangrove and fishery products. Local elders recalled that, until the early 1960s, resource use problems were minimal. Resource abundance, together with the use of non-destructive harvesting practices and the predominance of subsistence village economies, enabled resource users to coexist peacefully. The subsequent decades saw a rapid depletion of mangroves with the coming of mining activities, and the entry of commercial mangrove wood cutting for charcoal production. Mining activities started to operate in the area in the early 1970s, followed by charcoal factories in the late 1970s. Some villagers were hired as woodcutters. Thick mangrove forests under charcoal concession areas, covering 3000–4000 rai, were degraded rapidly. During this time, large tracts of the mangrove areas, including the area where Ban Sam Chong Tai is located, were also declared a reserved forest. In the mid-1970s, villagers began using motorized boats and other modern fishing gear such as gill nets, but their fishing activities were still mostly confined to nearshores and mangrove canals. A decrease in numbers of mud crabs began to be noticed. In 1985, charcoal factories began hiring illegal migrants as woodcutters, and using non-selective methods of cutting down mangrove trees. The mangrove forests were therefore heavily over-cut. Aggravating the situation was the absence of official efforts to avert indis- criminate mangrove cutting. In the late 1980s, shrimp farms started to appear in watershed areas to the north and discharged wastewater into canals flowing to coastal waters around Ban Sam Chong Tai. A variety of marine species in mangrove canals and around nearshores decreased noticeably. The conversion of mangroves into shrimp farms was allegedly due more to influence and financial leverage than to the following of sound environmental practices: some villagers say ‘money talks’. According to villagers, prawn investors are suspected of having paid off state officials who are refusing to take legal action against encroachment. Subsequently, shrimp farmers have been discharging contaminated effluents from their shrimp ponds into streams, coastal creeks and estuary zones. This discharge has seriously affected the freshwater quality of adjacent coastal waters, resulting in the death of diverse aquatic life, including fish, crustaceans and mollusks, and also resulting in extensive areas of dead mangroves In 1989, the authorities came to evict villagers on the grounds that they Coastal communities, mangrove loss and shrimp farming 201 were living in a National Park, but they refused to leave. To them, it was not fair that they should be evicted from the land on which they had lived for a long period of time. Some claimed their parents had moved into this area even before it was declared a reserved forest. Since they had been living there for such a long time, they demanded some official recognition of their right to continue living on the land. This line of argument was unacceptable to the authorities. However, the show of defiance by villagers worked to some extent, as the threat to evict them was not carried out. After their encounter with the authorities, villagers became aware of the common threat to their land. In the early 1990s, dwindling coastal marine resources forced local fishermen to venture further off shore and spend more time fishing. Although mangrove forests degraded under charcoal concessions (which were cancelled earlier) began to regenerate and attract more marine life, mangrove streams, creeks and canals became more polluted as a result of an increased number of shrimp farms discharging wastewater into them. It was during this time of difficulties that villagers began their conservation activities. Advised by a Department of Fisheries (DOF) official, who came to conduct research in the areas in 1993, villagers started to use their conservation activities as a pretense to gain sympathy from the authorities and as a transitional step to obtaining the right to occupy the land in reserved forests. Key informants recalled that, when the threat of eviction from the authorities emerged, villagers began to perceive a common interest in fighting against eviction. With the possibility of gaining sympathy and the need to cooperate in confronting the authorities being realized, community-based activities such as replanting mangrove trees and setting up a community forest in degraded areas were chosen as the tactical option. After some success with their replanting project, it was also decided that villagers apply for the right to manage, as their own community forest, 1000 rai of degraded reserved forest around the village. Forestry authorities finally granted a total of 200 rai to Ban Sam Chong Tai villagers to be managed as their own community forest. They also declared the replanted area a local sanctuary, prohibiting any kind of exploitation for five years. The cutting down of mangrove trees near streams, canals and the coast is prohibited. Villagers of Ban Sam Chong Tai recognize the value of these resources as they provide important fishing grounds as well as preventing soil and coastline erosion. They also recognize the value of the mangrove ecosystem to their marine environment. They know that these are fish breeding areas and have to be protected. Hence, as a rule, mangrove trees cannot be cut down unless there is consent from the village committee. Specific products including medical plants, wood and other edible resources may be gathered from the forests. The replanted mangroves are sustainably protected by local rules 202 Case studies: Phang-nga and Nakhon Si Thammarat prohibiting the cutting down of mangrove trees for commercial uses. A rule common to the use of the community mangrove forest is that one must not extract from it in unsustainable quantities. In collecting or cutting wood, for example, it is important that one selects large trees and leaves them in a good condition to sustain their life. The homogeneity of this rather isolated, religiously and socially knit community appears to have been a factor in promoting cooperation. Since the beginning of conservation activities when joint action was called for, there has not been a lack of participation and support from villagers. It is clear now that the decision to proceed with the community forest project was to some extent a tactical success, because no more threats of eviction or intimidation have been made or carried out since then. Villagers are, however, still facing the continuous decline of marine resources as a result of polluted water from shrimp farms, which they now consider as the real threat to their livelihood. Another village in this study area of Phang-nga Bay is Ban Bang Pat. In the early 1960s, a small group of families moved to settle in the area. At that time, the village was part of a larger Ban Klang community, Bang Toey subdistrict. Early settlers of Ban Bang Pat, like residents of other coastal communities, were highly dependent upon the mangroves, which formed dense, diverse and thick forests surrounding the community. Rice growing was the main occupation of local residents, while fishing was mainly for personal consumption. Fish and Acetes (Koey) were plentiful in the area, and harvesting Koey in mangrove areas provided a supplementary source of income. Simple fishing gear such as sails, paddling boats, set bags, cast nets, and hook and line were used. Sources of income are shown in Table 10.4. During the 1960s, the outside demand for shrimp increased. Fishing became more commercialized. Charcoal concessions in mangrove forests,

Table 10.4 Sources of income of households of Ban Bang Pat

Sources of income No. of households Percentage

Capture fishery Coastal areas 31 74 Mangrove forest 20 48 Aquaculture 23 55 Off-farm/wage labor 13 31 Total 42 100

Note: The sample respondents report more than one source of income.

Source: Survey of 42 households. Coastal communities, mangrove loss and shrimp farming 203 covering 2000–3000 rai, east of the community were granted to outside investors. Some local residents were hired to cut wood for charcoal factories. Villagers could still harvest timber from the forests as their needs were limited. Improved transportation and profits from selling their catch, especially shrimp, enabled many residents to build their houses using more durable materials such as plank wood, tiles and cement from the town market. In the mid-1970s, mining cooperations began their operations in areas upstream and in northern portions of the community. The clearing of mangrove forest, together with heavy sedimentation and turbidity, reportedly took their toll on marine life in the coastal waters of Bang Toey subdistrict. Facing declining marine resources near the shoreline, local residents were forced to improve their fishing gear, buying motorized boats and push nets, for example, to venture off shore. Some turned to cutting down timber for sale in markets, thereby accelerating mangrove degradation. Rice growing declined and villagers increasingly bought rice from the market. Many turned their rice fields into small oil palm plantations. In the late 1980s, shrimp farming by outsiders began to operate in neighboring villages north of Ban Bang Pat and Ban Klang. Shrimp farmers had been discharging contaminated effluents from their shrimp ponds into streams, coastal creeks and coastal water/estuary zones. This discharge seriously affected the freshwater quality of adjacent coastal waters, resulting in the death of diverse aquatic life, including fish, crustaceans and mollusks, and also resulting in extensive areas of dead mangroves. As shrimp farming expanded and more wastewater was discharged into canals and creeks upstream, local villagers began to feel the impacts. These included the high salinity of their drinking wells, salt water seepage into nearby rice fields, and high mortality of their aquaculture. They voiced their concerns to the authorities, but no serious efforts were made to solve the problems. In the early 1990s, a representative of the Thai Volunteer Service, a fledg- ling local environmental group, came to start working with Ban Bang Pat residents. At that time the mangrove forests in the area had already been extensively degraded by mining activities and charcoal production, and shrimp farms had also started to make inroads into the neighboring communities. The situation has also taken its toll on local residents, as their catch decreased rapidly. After meetings and discussions on a number of occasions, it was decided that there was an acute need for the conservation of the degraded mangrove areas. With cooperation from outside agencies and local authorities, villagers set a target of replanting 1000 rai from 1993 to 1996. An area of 100 rai was also designated as a community forest, protected and managed by a local committee, which was responsible for the observance of rules and regulations, including imposition of penalties and sanctions for violations committed by villagers and outsiders. 204 Case studies: Phang-nga and Nakhon Si Thammarat

The village committee and all participants agreed to a set of informal rules: only villagers are entitled to collect wood in the declared community forest area; mangrove trees will be cut down only for personal use and replanting must be done quickly; replanted areas are to be protected until the trees are fully matured and outsiders are not allowed to collect wood or other resources within replanting areas. So far, these norms appear to be followed by most villagers. In 1996, Ban Bang Pat was administratively separated from Ban Bang Toey but relationships and communication between these two villages were still close and many communal activities were shared. The conservation activities of local residents are a well-known phenome- non in Phang-nga, attracting media attention and funds from donors. However, it was the establishment of a collective fund, donated by external agencies, to support local replanting mangrove activities that created division among villagers. Early on, the village committee decided to use some of the money to set up a revolving savings fund for the benefit of all villagers. However, complaints about corruption, nepotism and favoritism, allegedly practiced by village leaders and committee members, quickly led to disputes, gossip and conflicts among those villagers who were excluded from borrowing or obtained smaller loans from the revolving fund. Stories began to spread that village leaders were deriving monetary benefits from their leadership activities. The situation was aggravated by the allegedly dishonest conduct of the leaders in the revolving savings fund. Disillusioned with his fellow villagers for accusing him, the local leader began to withdraw from active interest in village affairs. Some villagers, however, link his loss of interest to his investment in shrimp farming. Others are cynical about their leader and about community organization generally, and state that they will no longer attend any village meeting. Some members of the village committee claimed that the misappropriation of funds took place without their consultation. This situation had a great impact on village morale, demoralizing those who used to be supportive of conservation activities.

BOX 10.1 COMMUNITY RESOURCE MANAGEMENT

The experience of Ban Khlong Khut, Ban Gong Khong, Ban Sam Chong Tai and Ban Bang Pat can be regarded as case studies in local organization and mobilization of resource management within a larger socioeconomic context. Coastal villagers in these Coastal communities, mangrove loss and shrimp farming 205 communities have been increasingly driven by the same market incentives and economic imperatives as rural villagers and urban people elsewhere. There is evidence indicating the process of intensified commercialization of coastal resources, increased heterogeneity among coastal residents, and the urgency of their resource constraints. Nevertheless, there are also a number of coastal communities which are now working on community mangrove forest projects to protect their local resources and using them in a more sustainable way, as exemplified by the cases of Ban Sam Chong Tai and Ban Bang Pat. In these two villages, the boundaries of the community forests were informally established, and access to community forests was strictly limited to villagers who were local residents. It should be noted that defining the boundaries of the common resource and specifying those authorized to use it can be regarded as an important step in organizing the local collective activity of resource management. So long as the boundaries of the resource or the specification of individuals who can use the resource remain uncertain, no one knows what is being managed or for whom. Without defining the boundaries of the community forest and closing it to outsiders, local villagers face the risk that any benefits they produce by their efforts will be exploited by others who have not contributed to those efforts. In addition to defining who has access to the mangroves, local villagers also established regulations specifying rules to limit appropriation levels. The local rules and regulations are voted on by all local residents and provide the general traditional authority for village committees to manage the mangrove forests. The local committees are responsible for the observance of rules and regulations, including the imposition of penalties and sanctions for violations committed by villagers and outsiders. However, it should also be emphasized that these local rules and local systems of resource management are fragile because they are not legally recognized by the government. The chal- lenge now is for the government to provide an enabling, appropriate and adequate legal and policy framework that institutionalizes and recognizes the important role of local communities in coastal resource management by providing a framework for the confirmation of existing and functioning local management systems. 206 Case studies: Phang-nga and Nakhon Si Thammarat

Phang-nga Bay, where Ban Sam Chong Tai and Ban Bang Pat are located, supports a variety of intensive activities, including small-scale fishing, mining, charcoal production, oyster and shrimp farming, and commercial fishing, causing intense conflict and competition among these user groups and further endanger- ing the marine environment, its resources and water quality. Despite the number of national and local laws as well as numerous regulations issued by the specialized agencies, the bay’s aquatic environment continues to deteriorate. Critical factors that have contributed to this problem are the lack of coodination among agencies performing related functions and the lack of participation by local fishing communities around the bay in terms of planning and management. Since local communities have the greatest interest in the conservation and sustainable use of coastal resources, they should have incentives, resources and the capacity for marine and coastal ecosystem management. Experiences in Ban Sam Chong Tai and Ban Bang Pat, given the complexity of issues and conflicts, illustrate that no one community-based approach can be a model for all communities. Indeed, as case studies show, the activities and responses of communities change according to government policy, patterns of power relations, the conditions and characteristics of the marine and coastal resources, the profiles of the stakeholders and the nature of the relationships among key actors and the like. Thus national law should provide only for a legal and institutional framework in the management of marine and coastal resources. Such a framework should include the principle of utilization and management (such as sustainable development, integrated coastal management and recognition of community-based systems). The framework should also establish democratic and participatory processes for, among other things, policy making and conflict resolution. The management model of coastal marine resources calls for a more flexible notion of community-based management, where a larger community of different stakeholders, including the government, makes plans for the sustainable management of coastal resources while taking into consideration the various interests of the different stakeholders. In this sense, it is community-based. However, the model also brings in an integrated coastal management system, as the conventional community- based management, where the local fishermen themselves take Coastal communities, mangrove loss and shrimp farming 207

a direct hand in managing the resource, may not be appropriate for a complex system such as Phang-nga Bay because there are many conflicting and competing interests involved. The management of these sectors needs special skills and clear legal mandates, especially as they involve not only various local resource user groups but also national policies and regulations on coastal law enforcement, land development, forestry management, commercial aquaculture and pollution control. It should also be stressed, however, that the problems of community- based resource management are inherently political, entailing issues of resource allocation and distributive equity. As such, community-based resource management cannot be separated from broader problems of Thailand’s political economy and are only solvable within this larger context.

ANALYSIS OF THE PROBLEMS FROM SOCIAL AND INSTITUTIONAL PERSPECTIVES

The experience of Ban Khlong Khut, Ban Gong Khong, Ban Sam Chong Tai and Ban Bang Pat can be regarded as case studies in local organization and the mobilization of resource management within a larger socioeconomic context. The fact that the market-oriented attitude is widespread and pervasive among coastal communities is reflected by the way Ban Khlong Khut and Ban Gong Khong actively took part in clearing mangrove forest and finally ventured into shrimp farming. On the east coast, infrastructures such as road networks are very well established. This paves the way for a process of rapid commercialization in the area. The two communities, Ban Khlong Khut and Ban Gong Khong, were among those which have been strongly influenced by this process of commercialization. On the west coast, however, the situation is somewhat different. Even though infrastructures are now in place, the process has been relatively tardy when compared to the east coast. It is notable that, when faced with a similar threat and economic pressure, villagers of Ban Sam Chong Tai and Ban Bang Pat sought resolution through their own self-organized community forest and conservation efforts. At the village level, the social climate of cooperation and mutual support has been rooted in strong Islamic beliefs and reinforced by daily religious practices. Being rather isolated until recently, Ban Sam Chong Tai and Ban Bang Pat, were highly dependent on mangrove forests for their livelihood and survival. The experience of successfully and locally managed community forests in communities on the Andaman coast in the mid-1980s, together with 208 Case studies: Phang-nga and Nakhon Si Thammarat lessons learned from the devastating ecological impact of shrimp farms on the east coast, helps to foster mangrove conservation activities in Phang-nga Bay. Together these factors, and the availability of advice and support from external agencies, explain why Ban Sam Chong Tai and Ban Bang Pat villagers have been able to set up their own conservation and community forest project. Key informants in both villages also identified the support and participation of some external agencies, which were able to introduce new ideas and provide support for local organizations, as another critical factor. This finding is consistent with the results of the regression analysis in Chapter 5. Even though the analysis shows results with low explanatory power, they indicate that the role of households’ awareness of external support was found to be a significant determining factor in the decision to participate in mangrove conservation activities. In the situation where villagers have little political bargaining power, it appears that the intervention and contribution of external agencies could have made a significant difference. Moreover, evidence has clearly shown that property rights have played a significant role in the local communities’ decisions to participate in the conservation of natural resources. Local communities may have incentives to participate in conservation activities in order to secure rights to land and resources they possess de facto. The recognition of local communities’ rights to these resources, which is conditional upon the adoption of conservation, has proved to be vital (Sathirathai 1995). The current development movement in the country is supportive of local organizations and a self-organized community-based resource management approach. The emergence of local community forest activity in many coastal communities, including Ban Sam Chong Tai and Ban Bang Pat, should be considered within this context. Nevertheless, it should be noted that there are still discrep- ancies between broad policy direction and actual policy practices at the field level. According to institutional perspectives, individuals and society will behave and interact in a certain way according to the incentives and disincentives facing them. ‘Institutions’ are like rules of the game with pay-offs which provide such incentives and disincentives. In order to take part in collective action, such as the conservation of natural resources work, it is important that institutional settings provide appropriate incentives. Using the Institutional Analysis and Development (IAD) framework, it is useful to distinguish between three levels of rules governing the use and management of the resources (Kiser and Ostrom 1982; McGinnis 1999):

1. Operational rules directly affect day-to-day decisions made by the participants on the use and management of the resources. Coastal communities, mangrove loss and shrimp farming 209

2. Collective-choice rules affect actions at the operational level through their impact on determining who is eligible and what rules are to be used in changing operational rules. 3. Constitutional-level rules also affect actions at the operational level and their effects in determining who is eligible, and the rules to be used in designing the set of collective-choice rules that in turn affect operational rules.

In Thailand, Sections 45, 56, 58, 59, and 60 of the current Thai Constitution (1997) has already set the framework at the constitutional level by allowing rights and encouraging the participation of local communities in the sustainable management of natural resources. At the same time, some evidence also supports the fact that there are several cases at the operational level where local communities successfully manage their resources (NGO-Cord 1989; Ramitanondh et al. 1993; Sathirathai and Barbier 2001). However, the problems lie within the institutional settings at the level of the collective-choice rules, which have not yet allowed legal recognition of local community rights in the management of the resources. For example, the Community Forest Bill, which legally endorses local people’s rights to use and manage forest resources in a sustainable way, has not been made law as a result of the RFD’s disapproval of the draft. The RFD argues that there is significant evidence that indicates the destruction of natural resources by local communities. Indeed, the argument of the RFD is not totally invalid. Nevertheless, it is important to be able to identify factors that lead to such a failure. This might point to some mercantilist attitudes and corruption at the level of local administration and governmental agencies. For example, the illegal conversion of mangrove forests into commercial shrimp farms indicates collusion between the governmental officials who take responsibility for the national mangrove areas, local people and the business owners of the commercial shrimp farms. The successful management of mangroves requires the crafting of effective institutional settings at all three levels in order to provide appropriate incentives and disincentives. More importantly, the institutional settings need the effective system of checks and balances. Successful local community management of natural resources should be encouraged and set as a good example. Further in-depth studies should also be conducted to understand the basis of such success. 11. Comparative returns of mangroves for shrimp farming and local direct and indirect uses in Surat Thani Province Suthawan Sathirathai and Edward B. Barbier

INTRODUCTION

In southern Thailand, local communities, who have traditionally utilized mangrove resources for a variety of products, ranging from fuelwood and other wood products to honey, and who have exploited coastal fisheries that benefit from the nursery and breeding ground function of mangrove habitat fisheries, believe that there is insufficient government protection of mangrove forests from conversion to shrimp ponds. There is also widespread concern over the water pollution in coastal areas that is a byproduct of intensive shrimp farming. As shrimp culture is capital-intensive and the technology is too expensive for small-scale farmers, investors in shrimp farm enterprises are generally from outside traditional coastal local communities, and very few of the returns to farming are invested locally. At the same time, local people do not have the legal right to protect mangrove forests from conversion to shrimp farming; that is, unless the Royal Forestry Department (RFD) recognizes their efforts. Some local communities that have been affected severely by the loss of mangroves have sometimes reacted violently to encroachment by shrimp farmers. Many have also begun to guard the forests themselves instead of waiting for the authorities to do something. However, there have been signs of recent shifts in policy towards actively promoting the conservation of mangroves and the participation of local communities (see Chapter 6). The Ministry of Agriculture and Cooperatives, which governs the RFD, has announced that mangrove conservation has to be taken more seriously. As a result, the RFD is considering banning mangrove forest concessions and regulating the use of mangrove areas, particularly those affected by shrimp farming. Furthermore, new legislation on community

210 Comparative returns of mangroves for shrimp farming 211 management of forests is being introduced, which offers the hope that the right of local communities to protect mangove forests may receive legal recognition. The motivation for this potential change in policy arises from the recognition that the economic benefits of mangroves to local communities may be substantial, and could possibly even outweigh the returns to intensive shrimp farming that lead to mangrove conversion. However, little is known about the economic value of local direct use of mangrove resources in southern Thailand, and the intangible ecological benefits of mangroves to the local communities in terms of habitat–fishery linkages and coastline protection have never before been evaluated. Without such an assessment, it is not possible to compare the economic benefits of mangroves to local communities with the returns to shrimp aquaculture, or to determine whether there are sufficient benefits from conserving the mangrove systems to provide the incentives for local communities to participate in their protection. To address these key policy issues, the present chapter assesses the benefits of mangroves compared to the net returns from converting the areas into shrimp farms in a case study area of southern Thailand. The preliminary analysis was conducted initially as part of a research project into land use conflict and policy issues arising from mangrove conversion conducted by one of the authors (Sathirathai 1998). The area selected for the study is Ban Tha Po Moo, in Tha Thong Sub-district, Kanjanadit District of Surat Thani Province, in which 400 ha of mangroves are utilized by the local community, Tha Po Village. The villagers have also organized their own means of protecting some of this mangrove forest area from outside encroachment, including that from conversion by shrimp farmers. Local direct uses derived from mangrove areas are valued by determining the net income generated from harvesting timber, fuelwood and other wood products, as well as non-wood resources, such as birds and crabs. In addition, two important ecological services are also assessed, the role of mangroves in serving as breeding grounds and nursery habitats for offshore fisheries, and in protecting the coastline from erosion. Other possible ecological functions, including carbon sequestration and the control of flooding, are not included in the analysis.

THE ECONOMIC VALUE OF MANGROVES IN SOUTHERN THAILAND

Background Information

Tha Po Village in Surat Thani Province in Southern Thailand was selected for the case study as it is a representative example of a Thai coastal fishing 212 Case studies: Phang-nga and Nakhon Si Thammarat community on the Gulf of Thailand with mangrove areas. The village is more than a hundred years old, and its present population is 652 people (131 households). The villagers are mainly involved in fishing, although they also used to rely considerably on directly exploiting the forest resources for their livelihoods. However, mangrove deforestation has affected the area significantly. Until recently, this part of Surat Thani Province was extensively covered with mangrove swamps of approximately 1120 ha. In the past decade, 640 ha along the coast has been cleared for commercial shrimp farms, which are mostly owned by business people from Bangkok and outside investors from other Thai cities. Since 1993, the villagers have been protesting vociferously to the government against the forest encroachment by shrimp farmers, especially as the local community has noted several problems of resources and environmental degradation, such as a drastic decline in offshore fishery yields and water pollution from the ponds. There was also an incident in which some villagers had to move temporarily from their houses during a storm because the mangrove was no longer there to shield them from strong gales. A further problem is that the shrimp farms in the area have begun to experience viral disease. Several farms have had to be closed down, leaving the area with a large number of abandoned farms. Yet the demand for converting mangroves to establish new shrimp ponds continues. After additional areas of mangroves were deforested recently, without any government intervention, the local villagers decided to take unilateral action to protect the remaining 400 ha of mangrove area available to them. The remaining mangrove forest left to Tha Po Village consists of a variety of tree species, with Avicennia marina (55 per cent), Excoecaria agallocha (35 per cent), Thespesia populnea (5 per cent) and Rhizophora apiculata (5 per cent) being predominant. The average stand density of the mangrove forest is 2256 tree/ha, with an average biomass of about 45.24 ton/ha. It is important to note as well that the forest is mainly composed of small-sized trees, as this appears to have affected the availability of forest resources, especially wood products, for use by the local community.

The Economic Valuation Approach

As discussed in the introduction, the total economic value of the remaining 400 ha of mangroves to the local community may comprise many, diverse benefits. However, owing to limited data, the case study of the Tha Po Village was able to estimate only the value of three key economic benefits: the value to the villagers of their direct use of wood and of non-timber products from the forest, and the ecological values of the mangrove area in terms of offshore fishery linkages and coastline protection. These values of the mangrove forest Comparative returns of mangroves for shrimp farming 213 were estimated in order to obtain the net benefits of protecting the remaining mangrove area, which are in turn compared to the returns of the alternative use of the mangroves, which in this case is conversion to shrimp farming. The rest of this section discusses the economic valuation of the three key benefits to local villagers of protecting the remaining mangrove area. The third section contains the estimation of the returns from converting the mangroves to shrimp farming.

Local Direct Use Value of Forest Resources

The direct use value of mangrove resources was assumed to be equivalent to the net income generated from the forests in terms of various wood and non- wood products. If the extracted products were sold, market prices were used to calculate the net income generated (gross income minus the cost of extrac- tion). If the products were used only for subsistence, the gross income was estimated on the basis of surrogate prices, that is, the market prices of the clos- est substitute. To estimate these local use values, two field surveys were conducted. The first was a detailed household survey that took place in February 1996 to obtain data on the frequency and quantity of the different products collected from the mangroves, as well as the labor input used in collecting these products. The second follow-up survey, in June 1996, used in-depth household interviews to acquire more specific data. The surveys revealed that the major products collected by the households were various fishery products, honey, and wood for fishing gear. The second survey also revealed that the villagers collected fuelwood, although most of the interviewees stated that the quality of the wood found in the remaining forest area was not suitable for fuelwood and so they actually collected only small amounts. Moreover, as the trees are relatively small, the villagers could not use them as timber, except for repairing fishing gear. The net income estimated from the major mangrove products collected by the Tha Po villagers is indicated in Table 11.1. The estimated returns on fishery products are based on actual survey results of respondents who reported regular collection of these products. However, because of monsoon conditions, an extensive survey of the whole village could not be conducted on other collected products. Instead, on the basis of the survey results, it was assumed that 10 per cent of the village households collect fuelwood, 40 per cent collect tree trunks for repairing fishing gear and 80 per cent collect honey. Moreover, the surveys also revealed that the villagers tend to use their leisure (that is, non-working) time to collect the various mangrove products. At the time of the surveys, the local daily wage rate was $3.75 for men and $3 for women. Based on UNEP calculations, the wage rate for leisure time is considered to be one-third of the 214 Case studies: Phang-nga and Nakhon Si Thammarat

Table 11.1 Net income from the major mangrove products collected by Tha Po households

Products Number of Average annual Total annual households returns per net income engaged in household of village collection (US$) (US$)

Fish 11 385 4 235 Shrimp 3 2 079 6 237 Crab 13 1 279 16 627 Molluscs 6 17 102 Honey 88a 55 4 840 Wood for fishing gear 44a 9 396

Note: aEstimated from survey sample. daily wage rate in rural Thailand (UNEP 1994). The opportunity costs of labor used in calculating the net returns from all of the major products were, therefore, based on hourly rates for leisure time in terms of these adjusted daily wage rates. Based on the estimated net income from all mangrove products (including fuelwood and other minor products), the mean annual value per household from direct use of the mangrove forest resources was calculated to be around $924. However, the surveys revealed that only 38 households collected mangrove products on a regular basis. Based on this conservative estimate of village use rates, the aggregate annual value of the 400 ha of remaining mangrove forest was estimated to be $35 135, or approximately $88 per hectare.

Value of Offshore Fishery Linkages

As noted in the introduction to this chapter, one important ecological service of mangroves is their support of offshore fisheries by serving as a nursery ground. Even though the reduction in production of offshore fisheries is normally attributed to over-exploitation, the situation is worsened as mangrove areas decrease. From the interviews in Tha Po Village, Surat Thani, it became apparent that, after the shrimp farms had cleared out a vast area of the mangrove, the villagers could clearly observe a sharp decline in the yields of their fishery products. When asked about the causes of the decline in their offshore fishing harvests, 50 per cent of respondants cited mangrove forest clearing by shrimp farming activity as the main cause of the problem (Sathirithai 1998). Comparative returns of mangroves for shrimp farming 215

The ‘production function approach’ is regarded as a promising valuation method to be used in capturing the indirect use value of wetland resources in terms of their ecological support for an offshore fishery (Barbier 1994). Several empirical studies have been conducted utilizing this approach to measure the value of coastal mangroves and marshlands as inputs in fishery production (Barbier and Strand 1998; Ellis and Fisher 1987; Freeman 1991; Lynne et al. 1981). Here, we have attempted to value the offshore fishery linkages provided by the mangroves in the Tha Po village area by applying a model originally developed by Ellis and Fisher (1987) and updated by Freeman (1991). The Ellis–Fisher–Freeman model is based on a static optimization framework using the Cobb–Douglas form to represent production of an offshore fishery in which the mangrove area is included as one of the input factors (see Appendix). After this production relationship is estimated, the supply function for offshore fishery products can be derived. This is the concept of the ‘production function approach’, as discussed earlier. The value of mangroves in terms of offshore fishery linkages is determined by the net welfare change (consumer and/or producer surplus) associated with the change in the area of mangroves. From the model, both equilibrium quantity and price associated with different levels of mangrove areas can be computed (see Appendix). An increase in mangrove area will lower the cost and hence drive the price of the offshore fishery products down. However, as Freeman (1991) has demonstrated, the welfare effects of the resulting impacts on price and harvest in the fishery will depend on the prevailing management regime. In the case of a typical Thai fishing community such as Tha Po Village, there are two alternative management regimes for its offshore fishery: an open-access situation and a fishery that is ‘managed’ by the local community. In the first case, an open-access situation, the value of the mangroves in terms of its support for the offshore fishery is determined by a change in consumer surplus only. Under open-access, the lower cost resulting from an increase in mangrove area will attract new entrants into the fishery, which will eventually dissipate all producer surplus. However, it is likely that, in the case of Tha Po Village, its offshore fishery is not completely open-access. Even though the community does not regulate fishing per se, there are no outsiders coming into their fishing ground. Such a ‘managed’ offshore fishery regime is more likely to resemble the case of a private property regime in the original Ellis and Fisher Model (see Appendix). In this case, the value of the mangrove in terms of its support of the offshore fishery is measured by changes in both consumer and producer surplus. In order to assess the net welfare change associated with the change in the area of mangroves, the market demand and supply of offshore fishery products had to be obtained. This involved using data from the Tha Po Village survey, 216 Case studies: Phang-nga and Nakhon Si Thammarat our representative fishery village with mangroves, and estimating a production function for the key fisheries based on panel data for the entire Gulf of Thailand region. Following the Ellis–Fisher–Freeman model, the production function was assumed to take the following Cobb–Douglas form:

– – X = f(E, A) = mEaAb ,( 11.1) where X is fish harvest (in kg), E is fishing effort and A is the area of coastal mangroves. The surveys of Tha Po identified the important mangrove-dependent fish species in the study area. These were in turn classified into two main categories, demersal fish and shellfish (crabs and shrimps).1 The major fishing instruments were also identified, and the time spent on fishing per instrument were recorded and used as a proxy for human effort. Detailed data on the costs of fishing effort were also collected. However, as it was not possible to collect time series primary data from the local area for the amount of catches, effort per fishing instrument and the area of mangroves, these survey data could not be employed to estimate the above production function (11.1) for the Tha Po shellfish and demersal fisheries. Therefore empirical data used in this estimation had to be based on secondary data collected by the Department of Fishery (DOF) and the RFD across all fishing zones in the Gulf of Thailand. The following approach was used. First, a panel analysis was employed to estimate a log-linear version of equation (11.1) for all shellfish and all demersal fish in the Gulf of Thailand. The analysis combines harvesting, effort and mangrove data across all five zones of the Gulf of Thailand and over the 1983–93 time period.2 This allows estimation of the parameters m, a and b in equation (11.1), for two separate Cobb–Douglas production functions, one each for demersal fish and shellfish. Combining this information with the data on unit cost of effort, c, from the Surat Thani survey allowed the supply function to be specified for both the shellfish and demersal fisheries. As discussed above and indicated in the Appendix, these conditions will vary under the two alternative management regimes. Under open access, equilibrium harvest in the fishery will occur where price, P, equals average cost, AC:

– C(c, X, A) –1 –(–b (1–a) P = AC = ––––––––– = cm /aA /a) X /a. (11.2) X

Substituting the estimated parameters from the production function (11.1), and the survey estimate of c, the above average cost function was computed for the case of demersal fish and shellfish, respectively, as Comparative returns of mangroves for shrimp farming 217

– AC = 2.0363* 105 X0.723467 A–1.26701 (demersal fish), (11.3)

– AC = 2.6191* 102 X0.090336 A–0.20884 (shellfish). (11.4)

In the case of managed offshore fisheries, as under a private property regime, equilibrium harvest will occur where price equals marginal cost, MC:

∂C c –1 –(–b (1–a) P = MC = –––– = –– m /a A /a) X /a.(1 1.5) ∂X a

After again substituting for all the known parameters, the above marginal cost function was also computed for the case of demersal fish and shellfish, respectively:

– MC = 2.0363* 105 X0.723467 A–1.26701 (demersal fish), (11.6)

– MC = 2.6191* 102 X0.090366 A–0.20884 (shellfish). (11.7)

To solve for the above equilibrium market conditions, five alternative hypothetical demand functions were used. As no data on the demand for fish products in Thailand were available for this study, the hypothetical demand functions were created, based on different choices of demand elasticity (h) of –10, –2, –1, –0.5 and –0.1 to test for sensitivity. To simplify the analysis, this approach was conducted at the national level, under the assumption that the national and local demands for fishery products in Thailand are the same. Finally, using 1993 as the base case year, it was assumed that all the linear demand functions passed through the observed (1993) national price and harvest data, with price equal to $0.95/kg and harvest 1 545 000 kg for demersal fish and price equal to $1.61/kg and harvest 1 917 000 kg for shellfish. Following the methodology indicated in the Appendix, it was then possible to use the resulting equilibrium supply and demand conditions to estimate the likely welfare impacts of a change in mangrove area on a typical Gulf of Thailand fishing community, such as Tha Po Village, assuming alternatively open access and managed fishery conditions. Table 11. 2 shows the results of the welfare calculation for the impact of a per hectare change in mangrove area on the shellfish and demersal fisheries used by the Tha Po villagers. For all mangrove-dependent fisheries, the value of a change in mangrove area ranges from US$21 to US$69/ha, depending on whether the fisheries are open access or managed. Similar to the outcome reported by Freeman (1991) for the Florida Gulf Coast blue crab fishery, when the demand for Gulf of Thailand fish is inelastic, the value of a change in mangrove area is higher under open 218 Case studies: Phang-nga and Nakhon Si Thammarat

Table 11.2 Value of a change in mangrove area in terms of offshore fishery linkages

Economic value of a change in mangrove area (US$ per ha) Management Demand Demersal Shellfish All fish regime elasticity fish

Open access –10 5.24 15.58 20.82 h = –2 17.53 25.01 42.54 h = –1 24.82 27.06 51.88 h = –0.5 31.34 28.22 59.5h = 6 h = –0.1 39.68 29.22 68.90 Managed fisheries h = –10 24.41 27.90 52.31 h = –2 24.34 27.83 52.17 h = –1 24.30 27.81 52.11 h = –0.5 24.26 27.80 52.06 h = –0.1 24.21 27.79 52.00 access than under optimal regulation, whereas the wetlands are more valuable under optimal regulation when demand is elastic. Under managed fishery conditions, different demand elasticity assumptions hardly affect the welfare estimates of a change in mangrove area, which are estimated to be around US$52/ha for all fish.

Value of Coastline Protection and Stabilization

Another important ecological function of mangroves is to serve as a wind- break and shoreline stabilizer. In this case, a replacement cost method has been adopted to assess the net benefits of this mangrove service. According to the Harbor Department of the Ministry of Communications and Transport, several areas along the coastline where there is no mangrove cover experience severe erosion. The unit cost of constructing breakwaters to prevent such erosion is estimated to be around $875 per meter of coastline. Based on ecological studies, the Cabinet Resolution of 15 December 1987 stated that it is necessary to preserve mangrove forests with a width of at least 75 meters along the coastline in order to stabilize the shore to the same degree as breakwaters. Given the above per unit cost of breakwater construction, and assuming that breakwater is approximately one meter wide, the equivalent cost of protecting the shoreline with a 75 meter-width stand of mangroves is approximately $11.67 per square meter, or $116 667 per hectare. Over a 20-year Comparative returns of mangroves for shrimp farming 219 period, the annualized value of this protection and stabilization function provided by mangroves amounts to $12 263 per hectare.3 However, one of the limitations of the replacement cost approach is that it tends to overvalue the benefits of an ecological function (Barbier 1994; Ellis and Fisher 1987). For example, if all the mangrove area was ‘replaced’ by breakwaters, there is no guarantee that there would be sufficient demand for this protection function to make such an investment worthwhile. This in turn implies that not all of the mangrove area is valued for its stabilization function. There is evidence that this may be the case for the mangroves in Surat Thani. According to the Harbor Department, approximately 30 per cent of the coastal areas in the region have experienced severe erosion and require some kind of protection or stabilization, either natural or human-made. If the latter is considered a proxy for the current ‘demand’ for shoreline stabilization, then as a conservative estimate we adjust the average replacement cost value of mangroves in terms of coastline protection to $3679 per hectare.

Summary of the Value of Mangrove Benefits

Table 11.3 summarizes the values of the three main mangrove benefits, the net income derived by the local community from the use of forest resources ($88/ha), the value of mangrove–fishery linkages ($21–69/ha) and the value of coastline protection and stabilization ($3679/ha). The latter value is clearly the most important benefit, although it is interesting to note that the survey of Tha Po villagers indicated that they were most concerned about the threats from shrimp farming to the other two benefits of the remaining mangrove area (Sathirithai 1998). One possible explanation is that mangrove deforestation more directly affects the economic livelihoods of the community through the loss of net income from collecting timber and non-timber products and from declining fishing yields than through coastal erosion. Over a 20-year time period, and depending on the discount rate used, the net present value of all three values of the mangrove system ranges from $27 264 to $35 921 per hectare (see Table 11.3). In contrast, the net present value to the Tha Po villagers of harvesting various mangrove resources ranges from $632 to $823 per hectare.

MANGROVE CONVERSION TO COMMERCIAL SHRIMP FARMS

The above economic benefits of maintaining mangroves need to be compared to the returns to the alternative use of the mangrove area, which is conversion to shrimp farming. Only by comparing the returns to these two alternative uses 220 Case studies: Phang-nga and Nakhon Si Thammarat

Table 11.3 Net present value of mangrove forest benefitsa

Benefit Value (US$) per ha

Direct use value Net income from timber and non-timber products 87.84 Indirect use value Offshore fishery linkages 20.82–68.90 Coastline protection 3 678.96 Total direct and indirect use value 3 787.62–3 835.70 Direct use value only Net present value (10% discount rate) 822.59 Net present value (12% discount rate) 734.83 Net present value (15% discount rate) 632.27 Direct and indirect use values Net present value (10% discount rate) 35 470.72–35 920.98 Net present value (12% discount rate) 31 686.34–32 088.57 Net present value (15% discount rate) 27 264.13–27 610.22

Note: a All net present value calculations are based on a 20-year time horizon. is it possible to determine whether or not full conversion of mangroves into commercial shrimp farms, which is occurring in the study area and throughout southern Thailand, has been worthwhile. To facilitate this comparison, two analyses are discussed in this section. The first is a financial cost–benefit analysis (CBA) of the private returns to a typical commercial shrimp farm in southern Thailand established through mangrove conversion. This analysis indicates the overall commercial profitability of shrimp aquaculture and determines the extent to which there is a private incentive to invest in such operations. However, shrimp farming also imposes certain external costs, such as water pollution and severe land degradation. Thus the second part of the section examines an extended CBA of commercial shrimp ponds that includes these external costs. In this latter analysis all input costs are also adjusted to reflect their full economic costs. This allows the economic returns of commercial shrimp farming to be more readily compared to the economic benefits of conserving mangrove forests.

Financial Returns to Commercial Shrimp Farming

The productive life of a typical commercial shrimp farm in southern Thailand is normally five years. After this period, there tend to be problems of drastic yield decline and disease; shrimp farmers then usually abandon their ponds and find a new location. Even though the initial investment (in terms of fixed Comparative returns of mangroves for shrimp farming 221

Table 11.4 Financial analysis: net present value of commercial shrimp farms

Year Values (US$/ha) 1 2 3 4 5

Benefits Gross returnsa 17 932 17 932 17 932 17 932 17 932 Costs Variable costsb 12 940 12 940 12 940 12 940 12 940 Annualized fixed costsc,d 2 992 2 992 2 992 2 992 2 992 Net present value (10% discount rate) 8 336.47 Net present value (12% discount rate) 8 071.54 Net present value (15% discount rate) 7 706.95

Notes: a Assumes non-declining yields over five-year period of investment, and based on Royal Forestry Department estimates for Surat Thani Province of average shrimp yields of 3856.25 kg/ha and farm price of $4.65/kg. b Includes costs of shrimp larvae, feed, gasoline, oil and electricity, pond cleaning, pond and machine maintenance, labor and miscellaneous variable costs. c Land tax and rent, interest payments, opportunity cost of land and pond-clearing costs, depreciation. d Based on estimates of initial fixed costs by Rawat (1994).

Source: Based on data from MIDAS (1995) and Rawat (1994). costs alone) in the first year can be as high as $9375 per hectare (Rawat 1994), the gross return is so large that it leaves a very high profit for the venture throughout the project life. Table 11.4 provides various estimates of the net present value of the operating returns per hectare during a five-year period for a commercial shrimp farm. These returns range from $7707 to $8336 per hectare, which suggests a considerable profit on the overall operation. The financial CBA demonstrates that, from a private investor’s standpoint, it is worthwhile to convert mangrove forests into a commercial shrimp farm. The de facto open access availability of mangrove swamps means that the investor incurs only the direct (mainly labor and dredging) costs of conversion and usually pays nominal land rent and taxes (if any) to the government after conversion. Moreover, as the initial investment requirement for a commercial shrimp farm is rather high, only the wealthier households in local villages can afford the venture. Thus those investors who benefit from the financial returns from shrimp farm enterprises are generally from outside local communities, 222 Case studies: Phang-nga and Nakhon Si Thammarat and very few of the returns to farming are invested locally. For example, the survey of Tha Po Village indicated that only 11 households were engaged in shrimp farming, with a total area of 112 hectares. The remaining shrimp farm area (528 ha) in the vicinity was owned by outside investors, mainly businessmen from Bangkok and other large cities (Sathirithai, 1998).

Economic Returns to Commercial Shrimp Farms

While converting mangrove forests into commercial shrimp farms in southern Thailand is clearly financially rewarding, one major external cost of shrimp ponds is the considerable amount of water pollution that they generate. This consists of both the high salinity content of water released from the ponds and agrochemical run-off. In addition, there is the problem of the highly degraded state of abandoned shrimp ponds after the five-year period of their productive life. Across southern Thailand those areas with abandoned shrimp ponds degen- erate rapidly into wasteland, since the soil becomes very acidic, compacted and too poor in quality to be used for any other productive use, such as agriculture. In addition, without considerable additional investment in restoration, these areas do not regenerate into mangrove forests. Finally, many of the conventional inputs used in shrimp pond operations are subsidized, below border- equivalent prices, thus further increasing the private returns to shrimp farming. Table 11.5 summarizes the results of the economic cost–benefit analysis of the returns to commercial shrimp farming in southern Thailand, which includes accounting for the external costs of water pollution and rehabilitating the mangrove forest as well as the full economic (that is, border-equivalent) costs of conventional inputs. Two estimates of the net present value of the economic returns are depicted in the table. The first estimate does not include the additional costs of restoring the mangrove forest from years six to 20, after the shrimp farm has been abandoned. The second estimate does include mangrove rehabilitation costs. The results indicate that, even if mangrove restoration does not take place, the economic returns to commercial shrimp farming are considerably less than the financial returns that investors receive (see Tables 11.4 and 11.5). Depending on the discount rates used, the economic returns range from $194 to $209 per hectare. If the costs of regenerating the mangrove forest over the years six to 20 are included, the economic returns to shrimp farming are actually negative.

Comparison with the Economic Benefits of Mangrove Forests

Although the estimates in Table 11.4 confirm that the conversion of mangrove forests in southern Thailand into commercial shrimp farms is financially attractive, it is clear that, once some of the external and foreign exchange costs Table 11.5 Economic analysis: net present value of commercial shrimp farms

Year Values (US$/ha) 1 2 3 4 5 6 Years 7–20

Benefits Gross returns 17 932 17 932 17 932 17 932 17 932 Costs Variable costsa 14 540 14 540 14 540 14 540 14 540 Annualized fixed costsb 3113 3113 3113 3113 3113 Cost of pollutionc 228 228 228 228 228 Costs of forest rehabilitationd 8 240 118

223 Without forest rehabilitation: Net present value (10% discount rate) 209.36 Net present value (12% discount rate) 202.71 Net present value (15% discount rate) 193.55 With forest rehabilitation: Net present value (10% discount rate) –5 447.97 Net present value (12% discount rate) –4 917.66 Net present value (15% discount rate) –4 239.75

Notes: a Adjusted using the standard conversion factor of 0.89 for construction costs in Thailand. bAdjusted using the standard conversion factor of 0.961 for capital costs in Thailand. cBased on costs of treatment of chemical pollutants in water and loss of farm income from rice production from saline water released from shrimp ponds, from Rawat (1994). d Based on costs of rehabilitating abandoned shrimp farms, replanting mangrove forests and maintaining and protecting mangrove seedlings, from Royal Forestry Department. 224 Case studies: Phang-nga and Nakhon Si Thammarat of shrimp farming are accounted for, conversion of mangroves into commercial shrimp farms is not economically worthwhile. This is the case even if the costs of restoring mangrove forests after shrimp pond abandonment are ignored. For example, Table 11.3 indicates that the net present value of local uses of the mangrove forests by a small coastal community such as Tha Po Village are around $632 to $823 per hectare. This is three to four times higher than the economic returns to shrimp farming, excluding the costs of mangrove rehabilitation, that are reported in Table 11.5. Once the values of offshore fishery linkages and coastline protection are also included, it is clear that the economic benefits of conserving mangroves far exceed the economic returns from mangrove conversion to commercial shrimp ponds. Table 11.5 also indicates that, if commercial shrimp farmers are required to restore mangrove forests, shrimp farming in mangrove areas may not be economically viable. This result suggests that the de facto open access availability of mangrove forests for conversion to shrimp farming in southern Thailand may cause economic distortions in commercial shrimp farming in two ways. First, as shrimp farmers do not have to compensate anyone for conversion of mangrove forests, they tend to over-exploit these resources. Shrimp farm operations are essentially subsidized in their use of coastal land resources; hence the operations are financially profitable but lead to economically irrevocable degradation of mangroves. Second, the free availability of mangrove resources for conversion in southern Thailand means that the shrimp farm operations are economically inefficient. They will tend to use too much converted mangrove area relative to other inputs, leading to extensive and lower-yielding rather than intensive and higher-yielding operations. There is evidence that shrimp farms in Surat Thani are not as high-yielding as they could be. As reported in Table 11.4, average shrimp yields in Surat Thani Province are around 3856.25 kg/ha. Ideally, however, intensive shrimp farming yields should be double this amount (Rawat 1994). It is easy to demonstrate that an intensive shrimp farm that attains the latter yields would be able to generate sufficient economic returns to cover the full economic and external costs of its operation, including the costs of replanting and restoring the converted mangrove forest. However, as long as mangrove conversion remains essentially ‘costless’, shrimp farm operators will not have the incentive to invest either in more intensive operations or in the restoration of degraded mangrove areas.

CONCLUSION

In this study, the economic value of mangroves in southern Thailand in terms of local use of forest resources, offshore fishery linkages and coastline protection Comparative returns of mangroves for shrimp farming 225 was estimated to be in the range of $27 264 to $35 921 per hectare (see Table 11.3). However, much of this value is accounted for by the replacement cost estimate of the coastal protection and stabilization function of mangroves. As noted in the literature, the use of the replacement cost method to value an ecological function is prone to over-estimation (Barbier 1994; Ellis and Fisher 1987). Thus the above estimations of the economic benefits of mangroves must be considered an upper bound. As noted in Table 11.3, the net present value to a local community, such as Tha Po Village, of harvesting various mangrove resources ranges from $632 to $823 per hectare. If the value of offshore fishery linkages is also included, the net present value (at a 10 per cent discount rate) of these two benefits is $1018 to $1468 per hectare. The latter figures must therefore be the lower bound on our estimates of the value of mangrove benefits in southern Thailand. However, it is important to note that lack of data has meant that this chapter has ignored other potential economic values of a mangrove system, such as tourism, carbon fixation, option values and non-use values. Thus the overall value of mangroves in southern Thailand may be considerably higher than the results reported here. Conversion of mangrove forest into commercial shrimp farming in southern Thailand appears to be financially attractive to investors, but this does not necessarily make conversion of mangroves into shrimp ponds economically worthwhile. Once inputs are priced at border-equivalent levels and the costs of water pollution from shrimp ponds are taken into account, the economic returns from commercial shrimp farming are considerably lower than the financial profits that investors receive (see Tables 11.4 and 11.5). More importantly, these economic returns, which range from $194 to $209 per hectare, are significantly less than the economic benefits of conserving the mangroves. If the costs of restoring the mangrove forest after shrimp pond abandonment are also included, extensive shrimp farming as practiced throughout Surat Thani and much of southern Thailand is no longer economically viable. The case study of Tha Po Village in Surat Thani also suggests that there is a major distributional concern with respect to shrimp farming. Even though such operations are financially profitable, those who gain are mainly outsiders who can afford the high initial investment requirement. In comparison, the local people tend to experience losses in terms of the net forgone benefits of mangrove deforestation and the damage costs of saline water and agrochemical pollution released from shrimp ponds. Surat Thani is in fact not a unique example of mangrove forests which have been severely encroached upon by shrimp farms. The problem is pervasive throughout southern Thailand, Southeast Asia and many other coastal tropical regions. Our case study indicates that there is a strong incentive for local 226 Case studies: Phang-nga and Nakhon Si Thammarat coastal communities to protect mangrove forests. For example, the Royal Forestry Department estimates that the cost of effective mangrove forest protection in southern Thailand is around US$4.70 per hectare. As the annual net income from local use of mangrove forest resources alone is around $88 per hectare in the case of Tha Po Village (see Table 11.3), there is certainly an incentive for the local community to protect the forest. However, the long-term success of any local initiative will depend on how well-organized and effective are the resulting institutions for common property management. This will, in turn, depend on whether the national legal system recognizes the rights of the local people to protect and manage mangrove forests. There is substantial evidence that, in similar cases throughout the developing world, common or communal property can be an effective management regime for common pool resources (McCay and Acheson 1987; Ostrom 1991; Bromley and Chapagain 1984; Baland and Platteau 1996). In fact, provided that exclusivity is well enforced, a common property regime is similar to private property for the group (Bromley and Cernea 1989). It is only when exclusivity completely breaks down that the resource becomes essentially open access (Ostrom et al. 1994; Sandler 1992; Seabright 1993). Cultural norms and traditions can help to build up ‘trust’ for assurance and form ‘punishment’ to enhance the costs of retaliation (Seabright 1993). A secured communal property regime is vital to ensure the net long-term streams of benefits from cooperation. In the case of Tha Po Village and other similar cases, it is therefore essential that the rights of local communities be well recognized by the law. As discussed in the introduction to this chapter, recent policy developments regarding the conservation of mangroves and the participation of local communities in such activities are encouraging. The Ministry of Agriculture and Cooperatives, to which the RFD belongs, has recently announced that the conservation of mangroves has to be taken seriously; the Ministry is considering banning mangrove forest timber concessions and the use of mangrove areas for shrimp farming nationwide. As yet, however, the ban has not been applied to mangroves. Finally, new legislation on community forests is about to be promulgated in Thailand, which will for the first time support local communities’ rights to protect mangroves and other forests that they have traditionally used. This new law will certainly be welcomed in southern Thailand. At a village gathering led by the head- man to discuss protection of their local mangroves, more than 60 per cent of the villagers in Tha Po attended. All of them unanimously express their desire to have the remaining mangrove forest in the vicinity designated as a protected community forest under the prospective community forest law (Sathirithai 1998). Comparative returns of mangroves for shrimp farming 227

NOTES

1. Mangrove-dependent demersal fish include those belonging to the Clupeidae, Chanidae, Ariidae, Plotosidae, Mugilidae, Lujanidae and Latidae families. The shellfish include those belonging to the families of Panaeidae for shrimp and Grapsidae, Ocypodidae and Portnidae for crab. 2. In this analysis, total fishing effort per year is the number of fishing instruments (for example, gill net boats) recorded per annum times the average number of hours spent on fishing per fishing instrument each year. For further details of the panel analysis, see Sathirithai (1998). 3. This annuity value with a present value of $116 667 was estimated using a 10 per cent discount rate.

APPENDIX

Using data and information from the work of Lynne et al. (1981) which stud- ied the relationship of natural marsh to the economic productivity of blue crab on Florida’s Gulf Coast, Ellis and Fisher (1987) developed a static optimization model using a Cobb–Douglas relationship to represent production of blue crab. The cost-minimization problem faced by a price-taking fishing industry is – min L = cE + l(X–mEaAb), (11A.1) E – where E is human effort as measured by the number of crab traps set; A is coastal wetland area in acres, which is considered exogenous in this problem; c is the unit cost of effort; X is the quantity of crabs caught, which depends on human effort and the area of wetland as represented by the Cobb–Douglas production function

– – X = f(E, A) = mEaAb . (11A.2)

Solution of the above problem for E leads to the following optimal cost function:

– – C(c,X,A) = cm–1/aX1/aA– b/a. (11A.3)

Ellis and Fisher assumed that the fishery is under a private property regime, and therefore in equilibrium price, P, is equal to marginal cost, MC. Thus from (11A.3), this equilibrium condition can be expressed as

∂C c –1 –(–b (1–a) P = MC = ––– = –– m /aA /a)X /a. (1 1A.4) ∂X a 228 Case studies: Phang-nga and Nakhon Si Thammarat

Assuming an iso-elastic demand function, X = DP–d, the equilibrium quantity of crabs harvested can be solved as

da/[d+(1–d)a] a – X = –– D1/dm1/aAb /a .( 11A.5) [ c ]

However, Freeman (1991) has argued that most fishery resources are open- access, which means that rents are dissipated. In this situation, the market equilibrium occurs where price equals average cost, AC:

– C(c,X,A) –1 –(–b (1–a) P = AC = –––––––– = cm /aA /a)X /a. (11A.6) X

Given an iso-elastic demand, the equilibrium quantity harvested under open access is

da/[d+(1–d)a] 1 – X = –– D1/dm1/aAb/a . (11A.7) [ c ]

Both equilibrium quantity and price associated with different levels of wetland area can therefore be calculated, and the resulting welfare impacts will vary according to the fishery management regime. For example, an increase in wetland area will lower the cost of harvesting and hence drive the price of fish down. In the case of an open-access fishery, the lower cost will attract new entrants (and increase effort), which will eventually dissipate all producer surplus. Only consumers will benefit. The value of the increase in wetland area can then be measured in terms of the associated increase in consumer surplus. In contrast, under a private property regime, the value of the increase in wetland area should be measured in terms of the associated increase in both producer and consumer surplus. PART III

Mangrove Loss and Shrimp Farming in Thailand: Conclusions This page intentionally left blank 12. Conclusion of the study and policy recommendations Edward B. Barbier and Suthawan Sathirathai

SUMMARY OF FINDINGS AND CONCLUSIONS

Mangrove forests are a crucial component of coastal resources that are valuable and important in terms of forestry, fisheries and the protection of the quality of the coastal environment. Nowhere is this more evident than in Thailand. Thus studying the impacts of shrimp farm conversion of mangroves in Thailand provides important insights into the ways in which the loss of a valuable and ecologically critical coastal resource can affect the livelihoods of local communities as well as national economic welfare. Against the latter losses must be weighed the considerable commercial and foreign exchange benefits of shrimp aquaculture and production, which is a major industry in Thailand. Such an analysis of both the economic causes and the consequences of mangrove deforestation due to shrimp farm expansion was the main purpose of this study. Chapter 1 highlighted the fact that mangrove deforestation, particularly as the result of shrimp farming, is a worldwide problem. Employing an empirical analysis of a cross-section of 89 countries containing mangroves, the chapter was able to provide evidence that mangrove loss globally is associated with expansion of aquaculture production and primary-sector (that is, agricultural) activities more generally. In particular, low and middle-income economies, such as Thailand and other rapidly developing tropical countries, that are expanding aquaculture production and are dependent on resource-based economic development generally for current growth, tend to have high rates of coastal mangrove conversion. Part I of this study focused on shrimp farm expansion and mangrove conversion across Thailand. As noted in Chapter 2, in Thailand the loss of mangrove forests has meant the subsequent decline of important ecological services, especially to local coastal communities. The ecological functions of mangroves provide direct and indirect benefits to a society as a whole in both the short term and the long term. In particular, local people and communities living along the coasts have been dependent on mangroves for a long period

231 232 Mangrove loss and shrimp farming in Thailand: conclusions of time. One consequence of mangrove decline is that it forces local communities to depend on and exploit smaller and fragment forest areas. The result is further degradation of mangrove systems from over-use. The scale of mangrove loss in Thailand over the past 35 years has been astounding (see Chapter 3). Over 1961 to 1996, nearly 205 000 hectares (ha) of mangroves disappeared, approximately 55 per cent of the original mangrove area that existed in Thailand before 1961 (see Table 3.1). Mangrove deforestation started in the provinces near Bangkok, has spread down the southern coast along the Gulf of Thailand, or Eastern Peninsula, and has now started up on the Andaman Sea coast, or Western Peninsula. The principal cause of mangrove deforestation, especially along the Gulf of Thailand, is clearly conversion to shrimp ponds. A survey in 1996 attributed around one- third of converted mangrove area in Thailand to shrimp ponds (see Table 3.4).1 Although mangrove conversion for aquaculture began as early as 1974 in Thailand, the expansion of shrimp farming through mangrove clearing took off with the 1985 shrimp export boom (see Chapters 3 and 4). Shrimp farm area in 1983 was around 31 906 ha in 1983, but had doubled to 64 606 ha by 1990 (see Table 3.5). In recent years, the rate of growth in shrimp farm area has been less dramatic, owing to a scarcity of suitable coastal sites for establishing new farms, but by 1998 it was estimated that there were 76 019 ha of shrimp ponds in Thailand. To shed light on the role of the profitability of shrimp farming, as well as other economic factors, in determining both mangrove deforestation and shrimp farm expansion in Thailand over the critical 1979–96 period, Chapter 4’s analysis of mangrove conversion in Thailand’s 21 coastal provinces over the latter period provides several important insights. First, it is clear from the analysis that the profitability of shrimp farming over 1979–96 in the coastal provinces of Thailand was an important driving force for shrimp farm conversion of mangrove areas. Second, the accessibility of mangrove areas, in particular their distance from Bangkok, has been an important geographical factor in explaining the historical pattern of mangrove loss in Thailand. Third, land and labor may be substitutes in aquaculture production in Thailand, and rising wages may lead some shrimp farmers to expand pond area and switch to less intensive operation in order to save on labor costs. Finally, consistent with the findings of Chapters 2 and 3, we also find evidence that coastal economic activities other than shrimp farming, such as agriculture, tourism, industrialization and urbanization, are contributing to mangrove conversion in Thailand. Part II of this study focused on detailed analyses of shrimp farm expansion, mangrove conversion and the resulting impacts on local communities in four representative case study sites, two from Nakhon Si Thammarat Province on the Gulf of Thailand and two from Phang-nga Province on the Andaman Sea coast. Conclusion of the study and policy recommendations 233

Chapter 5 provided the ecological, historical and social background to the four case study sites. In Nakhon Si Thammarat Province, Ban Gong Khong in East Pak Panang Subdistrict, Pak Panang District and Ban Khlong Khut in Pak Nakhon Subdistrict, Muang District were selected. As for Phang-nga Province, Ban Sam Chong Tai in Kalai Subdistrict, Takua Pa District and Ban Bang Pat in Bang Toey Subdistrict, Muang District were chosen. The criterion for selecting these research sites was mainly the condition of mangrove forest depletion. Mangroves in Nakhon Si Thammarat have been depleted extensively, whereas in Phang-nga the rate of destruction has been much slower and pristine forest still exists. However, one surprising result of our surveys is the extent to which local communities still depend on utilization of the mangroves, even in the case of severely degraded forests in Nakhon Si Thammarat. Generally, however, the degree of dependence on mangroves is much higher in the two Phang-nga village sites, as is the degree of local involvement in mangrove replanting activities. The consumption behavior of households in the four case study sites, and in particular the dependence of household income and consumption on local mangroves, was analyzed more extensively in Chapter 6. Income earned directly from exploitation of the mangrove forest was more important to households in Ban Sam Chong Tai and Ban Gong Khong than to households in the other two case study sites. However, households in Ban Khlong Khut were more indirectly dependent on mangroves in terms of their ecological support for commercially important coastal fisheries, compared to the other villages. Households in Ban Bang Pat were the least dependent, either directly or indirectly, on mangroves for consumption and income. However, all four villages indicated that at least some households were dependent on the local mangrove forests for their income and consumption needs. More importantly, we found concrete evidence that mangrove forests act as a natural social safety net for the poor in coastal communities. In all four case study sites, if households did not have access to mangrove resources, the incidence of poverty would have been significantly higher in each village. Both Chapters 6 and 7 examined whether the degree of mangrove dependency of households in the case study sites influenced their willingness to participate in mangrove conservation. The majority of conservation activities in the case study sites involved replanting schemes, which were instigated either by the local community, non-governmental organization, or by the Royal Forestry Department. Chapter 6 found evidence that the awareness of external support and the degree of dependency on mangroves as a source of income are important determinants of the participation of households in local mangrove conservation activities. A more detailed intra-household analysis of mangrove conservation decisions was conducted in Chapter 7. This analysis confirmed that the degree of mangrove dependence, measured in terms of the 234 Mangrove loss and shrimp farming in Thailand: conclusions proportion of total household income from direct or indirect mangrove use, is a significant factor in both male and female household members’ decisions to participate in mangrove conservation. In addition, the household’s awareness of community mangrove utilization rules and of local conservation efforts also significantly affected male and female participation in these efforts. Not surprisingly, the number of children under the age of six in the household is an important deterrent to increased participation in conservation activities by female members of a household. In all four case study sites, there are considerable opportunities for employment both outside the village and, consequently, in economic activities that are not related to the local mangrove forests. Chapter 8 investigated the extent to which the degree of the dependence of a household on local mangroves for income, as well as the loss of that forest, may affect the household’s decision to seek outside employment. Once again, the degree of dependency of a household on mangrove-based activities as a source of income affects strongly the decision by its male and female members to spend time in outside employment. This appears particularly important for those households that are solely involved in collection activities and do not obtain income from fishing or agriculture. Although loss of the mangrove area does not appear to affect the decision by villagers to participate in outside employment, mangrove deforestation does affect significantly the number of hours worked. We estimate that, for every hectare of mangrove forest lost, male members of households will increase outside employment on average by 4.3 hours per year (a 1 per cent increase) and female members by 6.5 hours per year (a 2 per cent increase). Chapter 9 examined more broadly the development of shrimp farming in Muang and Pak Panang Districts, Nakhon Si Thammarat Province and Takua Thung and Muang Districts, Phang-nga Province. The surveys of shrimp farmers in these districts confirm that, in addition to mangrove deforestation, the negative impacts of commercial shrimp farming include the discharge of wastewater and sludge from the farms into the coastal areas, which affects the marine life and reduces the fertility of coastal resources. Intensive shrimp farming also creates conflicts between different resource user groups in many areas. We also confirm the national trend, reported in Chapter 3, that, up to now, the conversion of mangrove forests into shrimp farms on the Andaman coast (represented by Phang-nga Province) has been less severe than on the Gulf of Thailand coast (represented by Nakhon Si Thammarat Province). Several reasons may help explain such a situation. One important factor is the less developed road network and infrastructure on the Andaman coast. Geographical conditions, such as steeper coastlines on the west coast, make the conversion of mangroves along the Andaman Sea much harder. Moreover, coastal communities on the west coast tend to learn from experiences of the east coast and are more active in the conservation of mangroves (see also Chapters 5–7). Conclusion of the study and policy recommendations 235

As for the future threat to the remaining mangroves along the west coast, the present study has indicated that, at present, mangrove areas are in general less attractive for use for shrimp farming, compared to rice paddies and rubber or fruit plantations. However, mangrove areas are still under the threat of being converted into shrimp farms, provided that the price of shrimps rises to a certain level (see Chapters 4 and 9). The possible prevention lies within the willingness and capability of stakeholders, consisting of both governmental officials and local communities, in effectively conserving the area. Appropriate laws and policies that provide the right incentives and an effective system of checks and balances are essential. This issue was examined more closely in Chapter 10. On the basis of the current law, the Royal Forestry Department (RFD) is the sole governmental agency that has full authority for the management and control of mangrove forests. However, the rapid destruction of the mangrove areas points to the agency’s inefficiency and lack of responsibility. Moreover, there tend to be conflicts in terms of policy directions regarding the utilization and conservation of mangroves among related governmental agencies. For example, the Department of Fisheries (DOF)’s promotion of intensive shrimp farming along the coastal areas has encouraged the conversion of mangroves. In contrast, the analysis of community management of mangrove resources in the four case study village sites shows that mobilization of villagers, active participation of households in conservation activities and the external support of governmental and non-governmental organizations is very important to the success of conserving local mangrove forests (see Chapter 10). For example, in Ban Sam Chong Tai and Ban Bang Pat, the communal decision to define the boundaries of the common mangrove forest and to specify those authorized to use it is an important first step in organizing local collective resource management. However, such local management rules are fragile, as the Thai government does not yet legally recognize them. Even though the current Thai Constitution has already approved community rights and encouraged the participation of local communities in the sustainable management of natural resources, there has not yet been any law to support such principles in practice. Without official support and legal endorsement, rules and regulations issued by local communities may be limited in terms of managing mangrove forests and overcoming conflicts between different resource user groups. This suggests that, in the absence of formal legal endorsement of community mangrove forest management, local coastal communities will remain power- less to prevent the illegal conversion of mangroves into commercial shrimp farms, which is often the result of collusion between corrupt government officials, local people who gain financially from such conversion and absentee business owners of the shrimp farms. If there is to be a change in governmental policy towards mangrove 236 Mangrove loss and shrimp farming in Thailand: conclusions management, the impetus for this policy change may arise from the recognition that the economic benefits of mangroves to local communities may be substantial, and could possibly even outweigh the returns to intensive shrimp farming that lead to mangrove conversion. To address this issue, Chapter 11 assessed the local economic benefits of mangroves and compared them to the net returns from converting the mangroves to shrimp farms, using the example of Tha Po Village, Kanjanadit District, Surat Thani Province on the Gulf of Thailand. As noted in Chapter 11, the net present value to Tha Po Village of harvesting various mangrove resources ranges from $632 to $823 per hectare. If the value of offshore fishery linkages is also included, the net present value of these two benefits is $1018 to $1468 per hectare. Although conversion of mangrove forest into commercial shrimp farming in southern Thailand is clearly financially attractive to investors, Chapter 11 demonstrates that, once inputs are priced at border-equivalent levels and the costs of water pollution from shrimp ponds are taken into account, the economic returns from commercial shrimp farming are considerably lower than the financial profits that investors receive. More importantly, these economic returns, which range from $194 to $209 per hectare, are significantly less than the economic benefits of conserving the mangroves. If the costs of restoring the mangrove forest after shrimp pond abandonment are also included, then extensive shrimp farming as practiced throughout Surat Thani and much of southern Thailand is no longer economically viable. The case study of Tha Po Village in Surat Thani also suggests that there is a major distributional concern with respect to shrimp farming. Even though such operations are financially profitable, those who gain are mainly outsiders who can afford the high initial investment requirement. In comparison, the local people tend to experience losses in terms of the net forgone benefits of mangrove deforestation and the damage costs of saline water and agrochemical pollution released from shrimp ponds. In essence, the Tha Po Village case study appears to be a good example of the economic problem of shrimp farm expansion experienced throughout the coastal areas of southern Thailand. Shrimp aquaculture is highly profitable to commerical investors, but a major reason is that individual investors are not paying the full economic (that is, border-equivalent) cost of the inputs used in establishing shrimp farms, and they do not compensate for the external costs of water pollution and mangrove deforestation that accompany shrimp pond establishment and production. For Thailand, this implies that the annual export earnings earned from shrimp aquaculture production over-estimate the actual economic benefits to the country of this activity. In addition, because the external costs of shrimp farming are not controlled, expansion of this activity has resulted in excessive loss of mangrove forests and coastal water pollution. It appears that it is local coastal communities that bear disproportionately the Conclusion of the study and policy recommendations 237 burden of the costs caused by mangrove deforestation and water quality decline. Of course, as discussed throughout this study, mangrove deforestation in Thailand is not solely the result of shrimp farm expansion. Past policies have also encouraged other extractive sectors to utilize mangroves. These have included, for example, mining, timber and charcoal concessions. The development of infrastructure, roads and commercial activities, combined with increased population pressure, in coastal areas has contributed to the loss of mangrove forests. In essence, mangroves are a natural resource that are clearly under-valued from an economic perspective. As this study has emphasized with the example of shrimp farm expansion and mangrove conversion, the result is a classic case of policy failure with regard to managing this critically important coastal resource. At the local level, mangrove resources are clearly recognized as being highly valuable. As a result, there is a current trend among villagers in many coastal communities, especially those on the west coast who are dependent on mangroves, to try and conserve the areas and establish community forests to restore and protect the resources for long-term benefits. The successful management and conservation of mangrove forests by these local people has demonstrated to a certain extent the potential of the community in dealing with problems and conflicts. However, the systems are still vulnerable and face certain limitations because they are not legally recognized. In sum, two clear policy recommendations emerge from this study. First, there is an urgent need to address the main institutional failure concerning management of mangrove resources. The present law and formal institutional structures of resource management in Thailand do not allow coastal communities to establish and enforce their local rules effectively. Nor do the current formal institutions and laws provide the incentives to local and other resource user groups to resolve conflicts among themselves. The result is that any effort to resolve such conflicts incurs high risk and management costs, which in turn make it even harder for the successful establishment of collaborative resource management systems by local communities. There is also a need to address the main policy failure at the heart of the economic incentives for excessive conversion of mangrove areas to shrimp aquaculture. As long as government policies continue to subsidize shrimp farm establishment and production, both directly through under-pricing inputs and indirectly through not requiring shrimp pond owners to control the external costs of water pollution and mangrove deforestation, this activity will remain financially profitable to the commercial investor. The result is that the commercial pressure to convert mangroves and other coastal land to shrimp farming will remain, even though the actual economic returns to such investments may not always justify such conversion. 238 Mangrove loss and shrimp farming in Thailand: conclusions

The next section discusses the key policy recommendations that are required to overcome these two main institutional and policy failures. In addition, we discuss the various steps necessary to improve the sustainability of shrimp aquaculture in Thailand. This in turn leads to the possibility of imple- menting a certification or eco-labeling scheme to promote sustainable shrimp farming practices. We end this concluding chapter by proposing some possible lessons learned for other countries from this study of shrimp farm expansion and mangrove loss in Thailand.

POLICY RECOMMENDATIONS

Improving the Institutional Framework

The management of mangroves is a complicated issue that involves several factors, such as the complexity of coastal ecology, the potential and vulnera- bility of local communities, the conflicts of resource uses among different user groups, and the limitation of the governmental policy and capability in handling problems and resolving disputes over the coastal resources. Thus the sustainable management of mangroves requires more than just the responsibility of a single governmental agency, namely the Royal Forestry Department (RFD), which currently holds the legal mandate for managing mangrove forests in Thailand. All stakeholders should have the right to participate in the management of such a key resource, especially local communities whose incentives to protect the remaining mangrove resources were very apparent from this study. The successful management of mangroves also requires the crafting of effective institutional settings so as to provide appropriate incentives and a system of checks and balances. To help foster and initiate national debate on these critical institutional issues, the Thai research team participating in this study organized a seminar on 9 July 2001 in Bangkok, Thailand, in order to discuss the initial findings of this study and the relevant policy issues. The main stakeholders concerned with mangrove management in Thailand, which include governmental agencies such as the Royal Forestry Department and the Department of Fisheries, local community representatives and key non-governmental organizations (NGOs) were invited. Based on the consensus among the participants at the meeting, the following policy recommendations for a new institutional framework for mangrove management in Thailand were agreed. First, a strict prohibition on the use and conversion of preserved mangrove forests, in particular wood concession and commercial shrimp farming, should be issued in any area designated as a conservation zone. However, local communities who depend on the collection Conclusion of the study and policy recommendations 239 of forest and fishery products from mangrove forests should be exempted, as long as such harvesting activities are conducted on a sustainable basis. Although existing policy has already put restrictions on the use and conversion of mangroves in the conservation zone, in practice, enforcement is only imposed on local people, whereas business ventures are allowed de facto access to these areas to convert them to commercial activities, such as shrimp farming. Second, the establishment of community mangrove forests will not be confined to areas in the economic zone but will also apply to those in the conservation zone. However, the decision to allow such local management efforts should be based on the capability of communities to enforce their local rules effectively and manage the forest sustainably. Moreover, such community rights should not involve full ownership of the forest, but be in the form of user rights. Management of the forests should be the joint responsibility of the local communities and the government (see the fifth paragraph, below). Third, the sustainable commercial use of mangroves, especially for timber products, should focus on the plantation areas rather than on the remaining natural mangrove forests. Plantation schemes and mangrove replanting should also be encouraged under the community (mangrove) forest management regime. In Thailand, most of the estimated 11 000 or more hectares (ha) of areas replanted over 1991–5 were previously unvegetated tidal mudflats (Lewis et al. 2000). Such ‘afforestation’ efforts have been strongly criticized as being ecologically unsound (Erftemeijer and Lewis 2000; Stevenson et al. 1999). However, more recent efforts at mangrove replanting in southern Thailand have focused on ecological restoration of mangrove areas destroyed by both legal and illegal shrimp ponds (see Chapter 5 and Lewis et al. 2000). Future mangrove plantation schemes should follow the example of these projects and focus on the ecological restoration of abandoned shrimp pond areas. The Royal Forestry Department should not only expand its efforts in promoting these initiatives but also work closely with local coastal communities to enhance the success of replanting programs. As discussed below, shrimp farm owners should be required to have some financial obligation to fund efforts to rehabilitate mangrove areas that they have converted (see next sub-section). Fourth, a successful community (mangrove) forest management regime requires active participation from all stakeholders with joint responsibility among governmental agencies, local communities and other user groups. Fifth, community (mangrove) forests should be co-managed by the government and local communities. Such effective co-management will require the active participation of existing coastal community organizations, and will allow the representatives of such organizations to have the right to express opinions and make decisions regarding the management plan and regulations related to the utilization of mangrove resources. 240 Mangrove loss and shrimp farming in Thailand: conclusions

Sixth, there is no specific model for the co-management of mangrove forests. Its form will have to vary with the unique conditions and characteristics of each area. It is important for stakeholders and other relevant parties to understand concepts of co-management and management partnership and to be able to adapt them in order to cooperate in successfully establishing and enforcing the rules. Finally, the government must provide technical, educational and financial support for the local community organizations participating in managing the mangrove forests. The co-management system is not just passing all the responsibilities from the government to community organizations. It requires the sharing of work and responsibilities between the governmental agencies and local communities. In terms of power and property rights, the resource co- management system requires a relatively complex property and user rights system. For example, local communities have the right to use and manage the forests under their community forest regime. However, the community rights can be attenuated by the state or governmental agencies, such as the Royal Forestry Department, which should retain the right to monitor and sanction in order to protect the forests. Moreover, conflicts between local communities and outside resource users, or other management problems that are beyond the ability of local communities to resolve, will require a more active intervention by the state. As for which part of the government’s rights and duties need to be transferred to local community organizations and how much the government should intervene in any resource disputes, these are subjects that have to be considered carefully.

Improving the Incentives Framework

Establishing an improved institutional framework is a necessary but not sufficient step in controlling excessive shrimp farm expansion and subsequent mangrove loss. As long as shrimp farming in Thailand is directly and indirectly subsidized, there will remain strong economic incentives to convert accessible mangrove areas to shrimp farming. Moreover, as the profitability of shrimp farming encourages outside investors to search for any remaining pristine mangrove areas to convert, there will invariably be increased conflicts between these investors and the local communities in coastal regions that wish to preserve these areas. There are clearly several steps that the Government of Thailand could take to reduce the current economic incentives for excessive mangrove conversion for shrimp farming. First, the preferential subsidies for the inputs used in shrimp farming, such as for the larvae, chemicals and machinery used in production, should be ended. Similarly, any preferential commercial loans for the establishment and clearing of shrimp farms are an unnecessary subsidy. As Conclusion of the study and policy recommendations 241 an export-earning commercial activity, all inputs in shrimp aquaculture should be priced at border-equivalent levels. Otherwise, the net economic gains to the Thai economy in foreign exchange earnings are over-stated, and the subsidies will allow those shrimp farm operations that are less efficient and productive to flourish. Second, although it is possible to adopt shrimp aquaculture systems in the coastal areas of Thailand that involve treating any wastewater from the farm before it is released, such systems are rare compared to the typical small-scale pond operations found in much of Thailand, which are dependent on highly intensive and untreated systems. The main reason is that shrimp farm operations do not bear any of the external costs of the water pollution they generate. The Department of Fisheries should adopt appropriate laws and regulations for the development of wastewater treatment systems for shrimp farming. This will also require strict monitoring and enforcement procedures, including routine testing of water quality and the assessing of punitive fines for violating water quality standards. The development of closed, water- recycling systems and new low-water-exchange, aeration systems for shrimp ponds are showing promising results in Thailand and elsewhere in terms of reducing toxic effluent discharges with only minimal, if any, reductions in the profitability of shrimp farming (Jory 1996a; Martinez and Seijo 2001). Third, several options are available for controlling the loss of mangroves resulting from the establishment of shrimp farms. Each of these options is discussed briefly in turn. The most restrictive is to require each shrimp farm established in mangrove forest zones to fund mandatory replanting and rehabilitation of all mangrove forests damaged or destroyed by the shrimp farm. Although such a regulation will ensure the most complete protection of mangrove areas, it is likely to be prohibitively expensive for most shrimp farm operations. A second option is to restrict shrimp farms to selective coastal land use zones, including areas that include mangrove forests. Moreover, shrimp farm operators should pay a concession fee to the government for the mangrove areas they convert, and this fee should be sufficiently high to reflect the forgone value of mangrove or other coastal resources. The revenues generated by this scheme could compensate local communities and finance the technical, educational and financial support for the local community organizations participating in managing the mangrove forests (see previous sub-section). As a variant on the latter policy, the government could institute competitive bidding between the various commercial interests vying for conversion of these coastal development zones, such as between shrimp farmers, timber concessionaires, mining operations and other extractive resource users. There should be a minimum reservation price for the concession bid, again set in accordance with the forgone value of the mangrove or other coastal resources. 242 Mangrove loss and shrimp farming in Thailand: conclusions

Shrimp farm operators and other coastal developers could also be charged a replanting fee, which could be used to finance local mangrove conservation and forest regeneration schemes. Finally, the most ambitious but perhaps most innovative policy instrument would be the adoption of environmental assurance bonds (EABs) for shrimp aquaculture (Mathis and Baker 2002). An EAB is an ex ante financial commitment by a farm owner to pay for certain unintended environmental damages should they occur. Before constructing a pond and beginning production, the farm owner would be required to purchase the EAB at a prescribed amount. At the end of production, and depending on the environmental impacts of the shrimp farm operation, the owner would either receive a full refund of the EAB (plus any accrued interest) or forfeit all or some of the bond. Essentially, the EAB combines elements of two market-based instruments: (a) a deposit refund incentive to encourage precautionary behavior by shrimp farm owners, and (b) insurance to cover environmental damages or to compensate individuals adversely affected by such damages. In the case of shrimp farming, an EAB could be used to cover the impacts on local communities of mangrove conversion and effluent discharges from shrimp farming, as well as to finance the ecological restoration of degraded mangrove systems and abandoned shrimp ponds.

Improving the Sustainability of Shrimp Farming

Reducing the environmental impacts of shrimp farming in Thailand should be part of the overall issue of improving the sustainability of shrimp aquaculture. Several authors have questioned whether intensive shrimp aquaculture, as currently practiced in Thailand and in other areas of the world, is currently sustainable (Boyd and Schmittou 1999; Jory 1996b; Naylor et al. 1998, 2000; Primavera 1997). In this book, we have documented the problems of habitat (that is, mangrove) destruction and pollution problems associated with shrimp aquaculture in Thailand and worldwide. In addition, there are other aspects of intensive shrimp farming today that may affect the overall sustainability of global shrimp aquaculture: Intensive shrimp farming using the black tiger shrimp (Penaeus monodon) in Thailand and elsewhere is entirely dependent on the capture of wild breeding stock for pond culture. In Southeast Asia, more than one million black tiger shrimp broodstock must be captured every year to supply the industry with needed seed for its farms (Jory 1996b). The process of collection can be highly wasteful and damaging to wild marine fisheries. For example, it is estimated that, in India and Bangladesh, up to 160 fish and shrimp fry are discarded for every fry of the black tiger shrimp that is collected to stock shrimp ponds (Naylor et al. 2000). As 57 per cent of the shrimp farmed worldwide are black Conclusion of the study and policy recommendations 243 tiger prawns, and in Thailand 95 per cent of all production uses this species, these effects are significant (Jory 1996a). The importation and transportation of wild black tiger shrimp broodstock may also be contributing to the spread of disease among shrimp farms. It is well known that wild shrimp stocks carry a variety of pathogens, including common diseases (Jory 1996b). Since the early 1990s, whitespot and yellow- head viruses have caused millions of dollars of losses in shrimp aquaculture across Asia (Naylor et al. 2000). These two viruses alone are thought to be largely responsible for the 25 per cent reduction in shrimp farm production across Thailand over 1994–5 (Jory 1996b). This outbreak was linked to the spread of the diseases through the introduction of infected wild breedstock and water contamination. Hepatopancreatic viruses and bacterial infections are also thought to be a major problem in Thailand. The widespread use of antibiotics in Thailand to control bacterial outbreaks has led to concern about the development of possible resistance to antibiotics (Jory 1996b). Shrimp feed contains about 30 per cent fishmeal and 3 per cent fish oil (Naylor et al. 1998). This in turn implies that around 2.81 kilograms (kg) of wild fish are required to produce 1 kg of shrimp through aquaculture (Naylor et al. 2000). In addition, the impacts on wild fishery stocks due to the mangrove conversion associated with shrimp farming are large. For Thailand, an estimated total of 400 grams (g) of fish and shrimp are lost from offshore capture fisheries per kilogram of shrimp farmed as a result of the loss of mangroves as breeding and nursery grounds. If the loss of other fish and shellfish species caught within the mangrove areas is also considered, the total reduction is 447 g of wild fish biomass per kilogram of shrimp raised (Naylor et al. 2000). Clearly, the rapid development of shrimp farms in Thailand and worldwide that took place over recent decades has been concerned more with increased production to meet growing world demand than with making the industry more sustainable. Since 1989, shrimp aquaculture has increased by over 400 per cent, and its share of world shrimp production increased from 5 per cent in 1982 to over 30 per cent more recently (Anderson and Fong 1997). However, the rapid rise of production from shrimp farming has actually created a ‘boom and bust’ pattern of development. In the early 1990s, the increased supply of farm-raised shrimp to the international market caused a glut in import markets that resulted in falling prices. One result of the development of shrimp aquaculture and increasing world trade has been the trading of frozen shrimp futures contracts and options (ibid.). However, the continuing problems with disease outbreaks in intensive farming operations and the sustainability issues listed above and throughout this report have raised concerns about the long-term viability of the industry. It is now recognized that, given current management practices, ‘it is doubtful that aquaculture production can continue to increase fast enough to meet the 244 Mangrove loss and shrimp farming in Thailand: conclusions rising demand for aquatic products’ (Boyd and Schmittou 1999). As one industry expert has commented, ‘the key to industry sustainability in Thailand, as it is for most shrimp farming countries, is continuing research and breakthrough in three areas: species domestication, minimizing the negative environmental impact of pond effluents on coastal ecosystems, and controlling diseases, particularly those caused by viruses’ (Jory 1996b, p.74). Specifically, the following innovations are urgently called for in Thailand.

1. Domestication and selective breeding programs for black tiger shrimp, so as to eliminate dependence on the capture, importation and transportation of wild breeding stock. 2. Controlling and minimizing the negative environmental impact of pond effluents through the development of closed and semi-closed water- recycling systems. Such systems developed in Thailand have been shown to exclude pathogens and pollutants, establish a healthy phytoplankton bloom early in the growth cycle, maintain adequate water salinity levels during the rainy season and significantly reduce effluent discharge from the ponds (Jory 1996a). 3. Increased use of biofiltration treatment, particularly through the use of species such as seaweeds, oysters, mussels, mullets and milkfish, to remove organic particulate matter and to contribute to nutrient recycling.

Combined with the improved incentives and institutional framework discussed on pages 240–42 and 242–4 for controlling mangrove conversion from shrimp pond expansion, the above ‘best management practices’ should go a long way toward improving the sustainability of shrimp aquaculture in Thailand. However, there may be increasing incentives for the shrimp aquaculture industry and the government in Thailand to do so from the ‘demand side’. It appears that the future demand for shrimp and other aquaculture products in the major markets of North America, Europe and Japan may be increasingly influenced by consumers’ perceptions of the environmental attributes of aquaculture production (Young et al. 1999). Pollution from farms is the most widely perceived negative environmental impact of aquaculture production, but concerns are also being expressed about the impacts of tropical shrimp farming on mangrove conversion, the inadequacy of domestic legislation in controlling aquaculture expansion in developing countries, and the lack of adequate controls over site and water usage, disease transmission, the use of chemicals and antibiotics, and overall food safety issues. As noted throughout this study, and in this chapter especially, the shrimp aquaculture industry in Thailand is vulnerable to these criticisms. However, if Thailand is willing and able to implement a successful institutional and incentive framework for encouraging more sustainable shrimp Conclusion of the study and policy recommendations 245 farming practices, and private farm owners respond by adopting best management practices, there may be an opportunity to benefit from the increasing importance of environmental attributes in determining consumer preference for aquaculture products. Already there is a burgeoning movement in major import markets towards eco-labeling seafood and aquaculture products from production sources that can be certified as ‘sustainable’ (Gudmundsson and Wessells 2000; Mariojouls and Wessells 2002; Wessells 2002; Young et al. 1999). For example, in 1997, the Marine Stewardship Council (MSC) for eco- labeling seafood was formed through collaboration between the World Wildlife Fund and Unilever, a multinational corporation that includes the frozen seafood products marketed by BirdsEye and Gorton. The Global Aquaculture Alliance has also launched the Aquaculture Certification Council (ACC), which is a new non-governmental organization established to certify environmental, social and food safety standards for aquaculture throughout the world (Global Aquaculture Alliance 2002). Although the ACC will initially certify only shrimp farms and processing plants, in the future hatcheries and feed mills will be incorporated into the certification process. Once the process is established for shrimp, other species will also be included. It is expected that the ACC’s first fully certified facilities will be approved in January 2003. If eco-labeling and certification of sustainable shrimp aquaculture production becomes a common practice, it could have important implications for the market worldwide. Processors, wholesalers and retailers who purchase shrimp products from these accredited fisheries will be able to ‘eco-label’ their seafood products, thus informing consumers that the product was obtained from a sustainably managed shrimp farm. Consumers could respond by purchasing predominantly eco-labeled products, thus reducing demand for unlabeled shrimp products but increasing the demand and price for shrimp from ‘sustainable’ production sources. This should in turn provide the incentive for the shrimp aquaculture industry in Thailand and elsewhere to reduce mangrove conversion and other environmental damages associated with shrimp farm expansion, as well as to adopt ‘best management practices’ for pond production, so that the industry may attain the certified status and thus receive the price premium from eco-labeling. As reported by Gudmundsson and Wessells (2000), using organic produce as a guide, the possible price premium for certified seafood prices could be as high as 30–40 per cent.

LESSONS FOR OTHER COUNTRIES

As noted in Chapter 1, mangrove conversion as the result of shrimp farm expansion is prevalent across tropical regions globally. However, we believe that this study is the first attempt to provide a comprehensive economic, 246 Mangrove loss and shrimp farming in Thailand: conclusions ecological and social study of the causes and consequences of shrimp farm expansion and the corresponding impacts on coastal mangroves in any country of the world. We believe that Thailand is an excellent choice for such a case study. First, Thailand has established itself as the world’s leading exporter of cultured shrimp from aquaculture. For example, one in three of farmed shrimp produced worldwide is from Thailand (Jory 1996a). However, as is clear from this study, over the 1980s and 1990s, this phenomenal export boom in Thailand came at a considerable price, in terms of contributing significantly to the virtual destruction of the country’s coastal mangroves on the Gulf of Thailand and a burgeoning threat to the remaining mangrove forests on the Andaman Sea coast. As we have documented in this study, the resulting economic impact on local coastal communities has been extensive, and considerable conflicts over use of the remaining mangroves have arisen. Moreover, when the full economic costs of shrimp farm establishment in mangrove areas are taken into account, including the economic costs of subsidized inputs, the loss of mangrove benefits to local communities and the external costs of deteriorating water quality due to untreated water release, there is not always a net economic gain from this activity. Yet, because shrimp farming remains a highly profitable investment for the individual investor, and appears to boost export earnings, many countries in Southeast Asia and in other tropical regions have sought to emulate Thailand’s example and expand rapidly their domestic shrimp aquaculture industry.2 Also following Thailand, most of this expansion of shrimp farming has come at the expense of coastal mangrove areas. As our study has shown, other countries should be more cautious in allowing rapid conversion of mangrove forests into shrimp farms. Shrimp aquaculture is often a highly profitable short-run investment for the private owner and operator because key inputs are usually subsidized, mangrove forests are freely available for conversion to shrimp farming, and any wastewater is untreated. If these additional costs are taken into account, the economic returns to shrimp farming are often less attractive, and sometimes even negative. Moreover, there is clearly an important distributional issue at stake. Shrimp aquaculture investments rarely generate large benefits for local coastal communities, yet it is these communities that disproportionately bear the burden of the economic losses associated with mangrove deforestation and deteriorating water quality resulting from shrimp farming. However, our study also has some positive recommendations to make. Shrimp aquaculture in Thailand and elsewhere can be made more sustainable, efficient and productive if the right policies and economic incentives for its development and expansion are in place. The correct incentives can also reduce substantially the environmental damages associated with shrimp Conclusion of the study and policy recommendations 247 farming, especially widespread mangrove deforestation and water pollution. Equally, the appropriate institutional framework to support local community management of mangrove and other coastal resources can also ensure that the people most affected by the loss of these resources through shrimp farming have a say in controlling this process. Such a framework is vital for the wise and sustainable management of mangrove forests and for resolving conflicts between local and outside users of the resource. Finally, the establishment of a sustainable aquaculture industry in Thailand will require the adoption of ‘best management practices’ for pond management by farm owners and operators, as well as continuing research and breakthroughs in the domestication of black tiger shrimp breeding, minimizing effluent discharges and controlling disease outbreaks. In sum, a sustainable shrimp aquaculture industry and conservation of mangrove areas can be compatible in Thailand and in other tropical countries, provided the right policies and institutions are developed to ensure this dual objective. We hope that this is the main lesson learned from our study of shrimp farm expansion and mangrove conversion in Thailand. In addition, the increasing awareness of consumers of the negative environmental impacts of current shrimp farm practices is prompting a growing trend towards certifying the sustainability of shrimp aquaculture and other seafood production. Such eco-labeling efforts may provide additional impetus for Thailand and other tropical countries to address the problems of mangrove conversion and other social and environmental impacts associated with shrimp farm expansion.

NOTES

1. In fact this figure is likely to be an underestimate, as it does not necessarily take into account unregistered, or illegally established, shrimp farms that are prevalent throughout Thailand. 2. In fact, many of the same multinational companies involved in large-scale development of shrimp aquaculture in the coastal areas of Thailand have invested in recent years in the aquaculture industries of other Southeast Asian and tropical countries. See Goss et al. (2000). This page intentionally left blank References

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260 Index 261

wood production 88, 97, 99, 105, 108 BirdsEye 245 Ban Khlong Wan, fish species in 28 black tiger shrimps (Peneaus monodon) Ban Klang 92, 94–5, 202, 203 41, 43, 45, 49, 242–3 Ban Sam Chong Tai Breusch–Pagan chi-squared test 9 charcoal production 92, 93, 200–203, Burma, workers from 55 206 community forest 93, 200, 201–2, Cabinet Resolutions 75, 123, 192 205, 207–8 carbon dioxide release 2, 52 community interaction 199–209 Central Region 46, 49, 55, 68 conservation activities 93, 111–13, Center for Ecological Economics 35 129–30, 200, 201–2, 205, 207–8 Chanthaburi Province 54, 154 ecological history 92–3 charcoal production 3, 30, 31, 50, evictions 200–201 116–17, 131, 133–4 household expenditure 104–9 Ban Bang Pat 94, 206 household, number of 77 Ban Gong Khong 90, 196, 197 income 76, 96–100, 101, 109–10, Ban Sam Chong Tai 92, 93, 200–203, 137–41 206 income sources 73–5, 199 see also wood production mining 93, 206 checks and balances, provision of 238 National Park 93, 200, 201 China, and charcoal export 92, 200 pollution 200, 201, 207 Chumphon Province poverty, incidence of 110–11 land use 44 tree density 80–83 mangroves 42 wood production 73–4, 97, 99, 105, climate 171, 173–4 107, 124 closed system shrimp farming 46 banana shrimps (Peneaus merguiensis) coastal communities and mangroves 41, 43 30–33 Bang Toey Subdistrict 73, 75–7, 79–82, see also individual areas 92, 94–5, 203–4 coastal erosion 2, 29 Bangkok Community Forest Bill 192, 209 distance from 60, 61–5, 67, 232 community forests 93, 94, 200, 201–2, seminar 238 205, 207–8, 239 Bangladesh 2, 52, 242 community interaction 33, 95, 193–209 Barbier, Edward B. concession fees 241 ‘Analysis of shrimp farm expansion conservation 100–113, 115–30, 132, and mangrove conversion in 137, 201 Thailand’ 1979–96 52–69 activities 93, 94, 95, 111–13, 122–30, ‘Conclusion of the study and policy 200–205, 207–8 recommendations’ 231–47 policy on 191–3, 238–9 ‘Effects of mangrove loss on the labor see also individual areas allocation of households’ 131–53 construction, residential and industrial ‘Household use of mangrove and 3 mangrove conservation decisions’ cost–return analysis 179–90 115–30 Cox, Mark ‘Introduction: global mangrove loss ‘Analysis of shrimp farm expansion and economic development’ 1–23 and mangrove conversion in biofiltration treatment 244 Thailand 1979–96 52–69 see also water ‘Effects of mangrove loss on the bird species 29–30 labor allocation of households’ see also wildlife habitat 131–53 262 Index

Cox, Mark (cont.): farmers, shrimp ‘Household use of mangrove and education 155–8 mangrove conservation decisions’ experience and age 155–6 115–30 experience, lack of 172–3 ‘Introduction: global mangrove loss land ownership 157, 158–9 and economic development 1–23 occupation, main 159 crabs 34, 88, 89, 90, 91, 197, 198 occupation, previous 156, 158 grapsid 91, 195, 199 occupation, secondary 159–60 mud 31, 89, 90, 92, 93, 195, 196, residential status 157, 158 199 survey 155–79 farms, shrimp debt service, total 9 acquisition of 163–5 deforestation see mangrove loss culture type 160, 161 Department of Fisheries 201, 238, 241 funding 165–8 Department of Mineral Resources 191 funding sources 168 disease, shrimp 45, 54, 55, 89, 166, land use, prior 160–62 173–5, 198, 243–4 number of 47–8, 54, 60, 61–4 operation of 175–9 East Pak Panang Subdistrict 73, 76, 77 problems, specific 169–79 Eastern Peninsula see Gulf of Thailand registration 164 Coast soil type 161, 162, 170–71, 172 eco-labeling of products 245 water effluence 161, 163 ecological importance of mangroves water intake 161, 162–3 7–8, 27–36, 77–83 fish species 28, 32, 34, 92, 95, 199–200 economic causes for mangrove see also crabs; shrimps conversion Fishery Department 191 analysis 53–69 fishing industry 2, 30–32, 49–50, data and estimation approach 5–19 116–18, 131, 133–4, 238–9 development activities 7 decline of 52, 93, 94, 195, 200, 202, estimation results 10–19, 60–63 203 model for 3–5, 55–9 fisheries, nursery ground for 27–8, economic development and mangrove 49, 131 loss 1–23 Yor Peek construction 89, 90 economic incentives see incentives see also individual areas framework food, shrimp 166, 169–72, 243 Economy and Environment Program ammonium phosphate price 60, 61–2, 35 64, 67 education 33, 138, 145, 152, 155–8 Forest Act 192 effluent discharge see pollution Forest Community Act 192 employment, outside 33, 131–2, Forest Plantation Act 192 137–53, 194, 202 Forestry Department 90, 197 see also wage labor freshwater ban on shrimp farming 46, environmental assurance bonds (EABs) 49 242 fruit-growing areas 55, 68, 88 environmental protection 7, 8, 17, 20, funding 165–8 35, 54, 243–4 evictions 200–201 GDP 7, 9, 10–12, 14, 15, 17, 18–19, 20, experience and shrimp farmers 155–6, 21 172–3 Global Aquaculture Alliance 245 export earnings 2, 10, 52, 53 Gong Khong Canal 85 Index 263

Gorton 245 Khlong Ngao government involvement 166, 191, 238, canal 87 240 fish species 2 see also institutional framework; shoreline stability 29 legislation; non-governmental Koey (Acetes) 92, 94, 196, 199 organizations; political stability Kor-yao District 77–9 GPP (gross provincial product per Krabi Province person) 60, 61, 64 borders 92 green mussels 95 land use 44 groupers 28, 31 mangroves 42 Gulf of Thailand Coast 37, 40, 41, 42, Kung Keoy (Acetes) 92, 94, 196, 199 45, 53, 54, 65, 67, 73, 76 Kuraburi District 77, 78 see also Chumphon; Nakhon Si Thammarat; Pattalong; Samut labor allocation of households 131–53 Prakarn; Samut Sakhon; Samut labor costs see wages Songkram; Surat Thani lady fish 28 Laem Pak Biak 28 households land erosion 2, 52 expenditure 104–9 land use 44, 154–90 labor allocation of 131–53 larvae, problems with 169, 170, 173–4, 188 incentives framework 238, 240–42, legislation 191, 205–7 244–5 see also government involvement; income institutional framework; political household 75, 96–100, 101, 109–10, stability 137–41, 149–50 leisure time 105–6, 116, 137 sources 73–5, 92, 94, 196, 199, 202 Linear Expenditure System (LES) 100 income distribution 96–114 living standards 33 income, household 96–100, 101, see also poverty 109–10, 137–41 loans 9, 167, 240 income sources 92, 94, 202 India 1, 242 mangrove loss Indian Ocean see Andaman Coast and accessibility 7, 65, 67 industrialization 3, 31, 66, 67, 76, 77, coastal erosion 2, 29 79, 207, 232 conversion analysis 37–51, 231–2 Institutional Analysis and Development current status 37–41 (IAD) framework 208–9 and ecological disruption 2, 7–8 institutional framework 7, 8–9, 238–40, economic causes see economic causes 244–5 for mangrove conversion see also government involvement; and economic development 1–23 legislation and labor allocation of households interest rate, real 9 131–53 Inverse Mills Ratio 145 and political instability 2, 5, 8, 11, investment fund, shrimp farming 171, 13, 14, 15, 17, 18–19, 20, 21 172 population density 9–12, 14–15, 17–18, 52, 60–62, 64–7, 193 Japan, demand for shrimps 54 replanting programs 90, 91, 93, 94, 103, 201–2, 239, 241 Kalai Subdistrict 73–5, 76–7 and shrimp see shrimp farming Khanom District 78, 84 see also individual areas 264 Index mangroves land use 154–5 and accessibility 7, 65, 67 problems associated with shrimp and coastal communities, significance farming 169–79 to 30–33 mullet 31, 92, 200 community forests 93, 94, 200, 201–2, 205, 207–8, 239 Nakhon Si Thammarat Province and conservation see conservation Ban Gong Khong see Ban Gong dependency on 96–114, 196 Khong distribution of 38, 39–40, 42 Ban Khlong Khut see Ban Khlong ecological importance of 7–8, 27–36 Khut and economic value 33–6 case studies 73–95 environmental protection 7, 8, 17, 20, community interaction 193–9 54, 243–4 conservation studies 122–30 fisheries, nursery ground for 27–8, cost-return analysis 179–85 49, 131 East Pak Panang Subdistrict 73, 76, management of 239 77 ownership 5, 31 farmers’ survey see farmers, shrimp; poverty, incidence of 33, 110–11, 198 farms, shrimp regulation of use 68 household expenditure 104–9 reserved 31, 90, 196, 197 income, household 96–100, 101, sediment displacement 29 109–10, 137–41, 149–50 sedimentation 29, 31, 34, 50, 94 Khanom District 78, 84 sewage treatment sites 29 land use 44, 154–90 shoreline stability 28–9 mangrove dependency 96–114, 196 and shrimp farming see shrimp mangroves in 42, 78, 79, 83–8 farming Muang District see Muang District water quality control see water Pak Nakhon Subdistrict 73, 76, 77, wildlife habitat 29–30, 31, 34, 50 88, 194 World Mangrove Atlas 5–6, 10 Pak Panang District see Pak Panang see also individual areas District mantis shrimps 31, 92, 199 Pak Poon 84 Marine National Park 79 problems associated with shrimp Marine Stewardship Council (MSC) 245 farming 169–79 marketing 171, 172 regeneration, natural 87 medicinal plants 201 resettlement areas 80 migrants, illegal 93 Sichol District 78, 84 mining 2, 7, 37, 41, 52, 179, 184, Talum Puk Cape 88, 90, 193, 196, 188–9, 191, 241 197, 198 Bam San Chong Tai 93, 206 Thasala District 78, 84 Ban Bang Pat 123, 203, 206 trees, sapling and seedling density 85 Bang Toey 75 trees, species of 84, 85, 86 Phang-nga 79, 200 trees, stand density of 84, 85, 86 Takua Thung 155, 160, 162, 185 trees, stem volume of 84, 86 Muang District Narathiwat Province 60 community interaction 194 National Forest Reserve Act 192 cost–return analysis 179–87 National Park 93, 200, 201 ecological background 77–82, 84, National Park Act 192 86–8, 92 non-governmental organizations 124, farmers’ survey see farmers, shrimp; 208, 238 farms, shrimp see also government involvement Index 265 nutrient recycling 244 household expenditure 104–9 nypa see thatching material income, household 96–100, 101, 109–10, 137–41, 149–50 occupations and shrimp farmers Kalai Subdistrict 73–5, 76–7 156–60 Kor-yao District 77–9 off-farm employment see employment, Kuraburi District 77, 78 outside land use 44, 154–90 oil palm plantations 94, 203 mangrove dependency 96–114 ownership mangroves in 42, 77–83 private 31 mining 79, 200 security of 5 Muang District see Muang District oysters 95 National Park 93, 200, 201 poverty, incidence of 33, 110–11 paddy fields see rice farming problems associated with shrimp Pak Nakhon Subdistrict 73, 76, 77, 88, farming 169–79 194 regeneration, natural 82 Pak Panang District resettlement areas 37, 80 community interaction 193 Taimuang District 77, 78 cost–return analysis 179–85 Takua Pa District 77, 78, 79 ecological background 77–8, 84–7, Takua Thung District see Takua 88, 90 Thung District farmers’ survey see farmers, shrimp; tree sapling and seedling density 82, farms, shrimp 83 land use 154–5 tree species 79, 80, 81 problems associated with shrimp trees, stand density of 80, 82, 83 farming 169–79 trees, stem volume of 81, 82, 83 rice growing 88, 154 water 75, 206 Pak Poon 84 Phetchaburi Province, water quality Pattalung Province control 29 land use 44 Phuket Province mangroves 42 borders 92 Pattani Province fish species 28 land use 44 land use 44 mangroves 42 mangroves 42 Phang-nga Province poaching 171, 173 Ban Bang Pat see Ban Bang Pat policy Ban Klang 92, 94–5, 202, 203 existing 191–3 Ban Sam Chong Tai see Ban Sam recommendations 238–47 Chong Tai political stability 2, 5, 7–10, 11, 13–15, Bang Toey Subdistrict 73, 75–6, 77, 17–21 79–82, 92, 94, 95, 204 pollution 2, 10, 45, 49, 242, 244 case study 73–95 Ban Bang Pat 94, 95, 123, 207 community interaction 199–207 Ban Gong Khong 91–3, 198 conservation activities 93, 94, 95, Ban Khlong Khut 89, 195 111–13, 122–30 Ban Sam Chong Tai 200, 201, 207 cost–return analysis 185–7 Pak Nakhon 77 ecological background 77–83 population density 2, 9–12, 14–15, farmers’ survey see farmers, shrimp; 17–18, 31, 52, 60–62, 64–7, 193 farms, shrimp poverty 33, 110–11, 198 fish species 28 Prachub Khiri Khan Province 28 266 Index predators 171, 173 salinization of coastal soils 2, 52 President Feed Industry 43 salt ponds 2, 3, 7, 30, 37, 41, 43, 52 property rights 55 Samut Prakarn 41 protected areas 11, 14, 17, 18, 22 Samut Sakhon 41 see also community forests; Samut Songkram 41 conservation Sarntisart, Isra Protection and Conservation of Wild ‘Household use of mangrove and Animals Act 192 mangrove conservation decisions 115–30 rainfall 7–8, 10, 11–12, 14, 15, 17, 18, ‘Mangrove dependency, income 20, 22 distribution and conservation Ranong Province 96–114 bird species 30 Sathirathai, Suthawan fish species 28 ‘Analytical background of the case Khlong Ngao see Khlong Ngao studies and research sites’ 73–95 land use 44 ‘Coastal communities, mangrove loss mangroves 42 and shrimp farming’ 191–209 shoreline stability 29 ‘Conclusion of the study and policy recommendations, policy 238–47 recommendations’ 231–47 recycling systems, water 241, 244 ‘Importance of mangroves’ 27–36 reforestation 75, 76, 77, 103, 123–4, ‘Mangrove dependency, income 126, 132, 198 distribution and conservation regeneration, natural 82, 87 96–114 registration of shrimp farms 164 Satun Province, fish species 28 replanting programs 90, 91, 93, 94, 103, Saturi Province 201–2, 239, 241 land use 44 see also conservation mangroves 42 reserved mangroves 31, 90, 196, 197 savings fund 204 resettlement areas 37, 80 sea bass 31 residential status 157, 158 Sea Irrigation Program 154 rice growing 160, 162, 188–9 sedimentation 29, 31, 34, 50, 94 Ban Bang Pat 94, 95, 200, 203 sergistid shrimps 34 Ban Khlong Khut 89, 194, 195 sewage treatment sites 29 Pak Nakhon 77 shoreline stability 29, 31, 34, 49, 50 Pak Panang 88, 154 shrimp farming and shrimp farming ban 46, 49, 55, area utilization problems and 68 constraints 46–51 road building 11–12, 15, 17, 18, 21, 22, ban, and rice growing 46, 49, 55, 68 37, 41, 49, 76, 79, 90, 93, 197, climate 171, 173–4 199, 207 closed system 46 Royal Forestry Department 55, 60, 68, competitive bidding for 241 77, 124, 154, 191, 192, 209, 238, and concession fees 241 239, 240 cost–return analysis 179–90 Royal Leam Pakbia Environmental and disease 45, 54, 55, 89, 154, 166, Research and Development Project 173–5, 198, 243–4 29 eco-labeling of products 244 rubber and palm plantations 68, 76, 162, environmental costs 35 179, 184, 185, 188–9 export earnings 2, 10, 52, 53 rule of law see government involvement; farmers see farmers, shrimp legislation; political stability farms see farms, shrimp Index 267

food see food, shrimp welfare losses 2, 52 freshwater ban 46, 49 survey, shrimp farmers’ 155–79 intensive 2, 9, 45, 54, 89, 91, 124–5, 175–9, 195, 197, 206, 232, 238, Ta Lum Puk Cape 88, 90, 91, 193, 196, 242 197, 198 investment fund 171, 172 Taimuang District 77, 78 and land use 154–90 Takua Pa District 73, 77, 78, 79 larvae 169, 170, 173–4, 188 Takua Thung District 73, 77, 78, 80–83, mangrove conversion analysis 37–51, 92, 155 231–2 cost–return analysis 185–7 and mangrove loss 52–69, 80, farmers’ survey see farmers, shrimp; 191–209 farms, shrimp marketing 171, 172 land use 155 poaching 171, 173 mining 155, 160, 162 predators 171, 173 problems associated with shrimp price 60, 61–5, 66, 166, 241 farming 169–79 and private investment 198 tannin production 3 sustainability improvement 242–5 tarpon 28 traditional 194, 195, 196, 198 temperature 8, 10, 22 see also fishing; individual Thai Constitution 209 communities; water Thai Volunteer Service 203 shrimps 2, 34 Thang Province, mangrove use 34–5 banana (Peneaus merguiensis) 41, Thasala District 78, 84 43 thatching material 30, 31, 88 black tiger (Peneaus monodon) 41, tidal conditions 8, 9, 22 43, 45, 49, 242–3 Tobit model 147 disease 45, 54, 55, 89, 154, 166, Tokrisna, Ruangrai 173–5, 198, 243–4 ‘Analysis of shrimp farms’ use of land mantis 31, 92, 199 154–90 predators 171, 173 ‘Importance of mangroves’ 27–36 sergistid 34 ‘Overview of shrimp farming and Sichol District 78, 84 mangrove loss in Thailand’ 37–51 snappers 28 tourism 55, 66, 67, 232 soil type 161, 162, 170–71, 172 Trang Province Songkhla Province land use 44 bird study 30 mangroves 42 land use 44, 154 trees mangroves 42 sapling and seedling density 82, 83, Southern Thailand 40, 41, 45, 53, 55 85, 87 state ownership 55 species of 79–82, 84, 85, 86, 87 subsidies see incentives framework stand density of 80, 82, 83, 84, 85, 86 Sugunnasil, Wattana stem volume of 81, 82, 83, 84, 86 ‘Analytical background of the case see also wildlife habitat; wood studies and research sites’ 73–95 production ‘Coastal communities, mangrove loss and shrimp farming’ 191–209 UNDP/UNESCO Regional Mangrove ‘Importance of mangroves’ 27–36 Project 29 Surat Thani Province Unilever 245 land use 44 urbanization 31, 37, 41, 55, 66, 67, 76, mangroves 35–6, 42 77, 232 268 Index viruses, shrimp 243 Western Peninsula 40, 41 see also diseases wildlife habitat 29–30, 31, 34, 50 see also birds; fish species; trees wage labor 92, 98, 102, 116–22, 145, wood production 3, 30, 31, 34, 35, 49, 152, 197 50, 73–4, 76, 116–18, 131, 133–4, see also employment, outside 238–9, 241 wages, minimum 60, 61, 63–5, 66–7 Ban Bang Pat 94, 97, 99, 105, 107, Wald Test 147 203, 204 water Ban Gong Khong 90, 91, 97, 99, 106, Ban Bang Pat 203, 206 108, 197, 198 Ban Gong Khong 92, 198 Ban Khlong Khut 88, 97, 99, 105, 108 biofiltration treatment 244 Ban Sam Chong Tai 73–4, 97, 99, Phang-nga Bay 75, 206 105, 107, 124 quality 2, 8, 29, 49, 50, 52, 54, 55, see also charcoal production; trees 161–3, 166, 169, 170, 241 World Mangrove Atlas 5–6, 10 recycling systems 241, 244 world trade 243 waste 32, 45, 54, 93, 161–3, 195, World Wildlife Fund 245 203, 241 see also pollution Yor Peek construction 89, 90, 194