Investigation of vegetation structure and carbon storage in lower u minh wetland in vietnam and muthurajawela wetland in sri lanka

LIST OF TABLES Table 2.1 The 15 most mangrove-rich countries and their cumulative percentages --- 37 Table 2.2 List of allometric equations applied to examine the stand biomass of the

INVESTIGATION OF VEGETATION STRUCTURE AND CARBON STORAGE IN LOWER U MINH WETLAND IN VIETNAM AND MUTHURAJAWELA WETLAND IN SRI LANKA

Ph.D thesis

by PHAN TRUONG KHANH

UNIVERSITY OF SRI YAYEWARDENEPURA, SRI LANKA

FACULTY OF GRADUATE STUDIES

INVESTIGATION OF VEGETATION

STRUCTURE AND CARBON STORAGE IN LOWER U MINH WETLAND IN VIETNAM AND MUTHURAJAWELA WETLAND IN SRI LANKA

Ph.D thesis

by PHAN TRUONG KHANH

Advisor:

Professor S.M.C.U.P Subasinghe

Professor Vo Quang Minh

Thesis submitted to the University of Sri Jayewardenepura for the award of the Degree of Doctor of Philosophy in Environmental

Science on 31st March 2018

I certify that the above statement made by the candidate is true and that this thesis is suitable for submission to the Faculty of Graduate Studies, University of Sri

Jayewardenepura, Sri Lanka for the purpose of evaluation

Publications during candidature

1 Khanh, P.T., Subasinghe, S.M.C.U.P (2017) Identification of Vegetation

Change of Lower U Minh National Park of Vietnam from 1975 to 2015 Journal

of Tropical Forestry and Environment, 7(2): 14-26

2 Phan Truong Khanh, Subasinghe S.M.C.U.P (2018) An Assessment of the Carbon Stocks of Meleleuca Forests in the Lower U Minh National Park in Ca

Mau Province of Southern Vietnam American Journal of Engineering Research

(AJER), 7(5): 305-315

3 Phan Truong Khanh, Subasinghe S.M.C.U.P (2018) Estimating Above-Ground Biomass of the Mangrove Communities in the Muthurajawela Wetland, Sri

Lanka International Journal of Science and Research (IJSR), 7(5): 86-93

4 Phan Truong Khanh, Subasinghe S.M.C.U.P (2018) Identification of Vegetation Change of Muthurajawela Wetland in Sri Lanka from 1992 to 2015

by Using GIS-Remote Sensing International Journal of Computational

Engineering Research (IJCER), 8(5): 42-52

TABLE OF CONTENTS

Page

List of tables - - vi

List of figures - x

List of abbreviations - xv

Acknowledgments - xvii

Abstract - xviii

CHAPTER 1: INTRODUCTION - 1

1.1 Background - 1

1.2 The objectives of the proposed resarch -13

CHAPTER 2: LITERATURE REVIEW - 14

2.1 Common wetland types - 14

2.1.1 Freshwater wetlands - 16

2.1.1.1 Freshwater wetlands in the Mekong delta, Vietnam - 16

2.1.1.2 Freshwater wetlands in Sri Lanka - 18

2.1.2 Saltmarsh wetlands - 20

2.1.2.1 Saltmarsh wetlands in Vietnam - 21

2.1.2.2 Saltmarsh wetlands in Sri Lanka - 23

2.2 Functions and importance of wetlands - 24

2.2.1 Carbon storage - 24

2.2.2 Biodiversity and habitat protection - 27

2.2.3 Wood supply -28

2.2.4 Non-wood forest products supply - 28

2.2.5 Flood control, shoreline and storm protection - 29

2.2.6 Social benefits - 29

2.2.7 Tourism -30

2.3 Characteristics of Melaleuca cajuputi - 31

2.3.1 Distribution of Melaleuca forests - 32

2.3.2 The value of Melaleuca forests - 33

2.4 Mangrove ecosystems - 34

2.4.1 Definition and the role of mangrove ecosystems - 34

2.4.1.1 Definition of mangrove - 34

2.4.1.2 The role of mangrove ecosystems - 34

2.4.1.3 Economic value of Muthurajawela wetland - 36

2.4.2 Distribution of mangrove ecosystems - 37

2.4.2.1 Mangrove forest in Sri Lanka - 41

2.5 Biomass and carbon storage in forests - 44

2.5.1 Biomass and carbon storage in Melaleuca ecosystems - 49

2.5.2 Biomass and carbon storage in mangrove ecosystems - 54

2.5.2.1 Biomass and carbon storage in mangrove of Sri Lanka 57

2.5.2.2 Biomass and carbon storage in forests of Sri Lanka - 61

2.6 Remote sensing and GIS approaches used in wetland survey - 63

2.6.1 Low spatial resolution optical systems - 66

2.6.2 Medium spatial resolution optical systems - 67

2.6.3 High spatial resolution optical systems - 68

2.6.4 GIS procedures using imagery - 73

2.7 Application of remote sensing and GIS techniques in wetland mapping - 74

2.7.1 Application of remote sensing and GIS techniques on wetland studies in Vietnam - 77

2.7.2 Application of remote sensing and GIS techniques on wetland

studies in Sri Lanka - 79

2.8 Image classification approach - 82

2.8.1 Unsupervised classification - 82

2.8.2 Supervised classification - 83

CHAPTER 3: METHODOLOGY - 96

3.1 Materials and methods - - 85

3.1.1 Materialss - - 85

3.1.2 Methods - - 87

3.1.2.1 Literature study - 89

3.1.2.2 Field investigations - 89

3.1.2.3 Laboratory analysis - 96

3.1.2.4 Data analysis - 96

CHAPTER 4: RESULTS AND DISCUSSION - 109

4.1 Building the map of vegetation cover - 109

A Lower U Minh National Park - -109

4.1.1 Normalized difference vegetation index (NDVI) - 109

4.1.2 Unsupervised classification - 111

4.1.3 Supervised classification - 115

4.1.4 The changes of vegetation cover from 1975 to 2015 - 119

B Muthurajawela wetland - - 122

4.1.5 Normalized difference vegetation index (NDVI) - 122

4.1.6 Unsupervised classification - 125

4.1.7 Supervised classification - 129

4.1.8 The changes of vegetation cover from 1975 to 2015 - 132

4.1.9 General discussion and comparison of survey approaches between lower U Minh national park and Muthurajawela wetland 135

4.2 Vegetation structure - - 140

A Lower U Minh national park - -140

4.2.1 Natural Melaleuca cajuputi forest zone (grown on the peatland) - 149

4.2.2 Plantation Melaleuca cajuputi forest zone (grown on the clay soil) - 151 B Muthurajawela wetland - -158

4.3 Biomass and CO2 storage - 172

A Melaleuca cajuputi forests-lower U Minh national park - 172

4.3.1 The growth parameters of Melaleuca cajuputi forests - 172

4.3.1.1 Natural Melaleuca cajuputi forest - 173

4.3.1.2 Plantation Melaleuca cajuputi forest - 173

4.3.2 The above-ground biomass of Melaleuca cajuputi - 176

4.3.3 Estimation of below-ground biomass of Melaleuca cajuputi - 181

4.3.4 Mathematical models built for the relationship of biomass and DBH - 183

4.3.5 Above-below ground biomass of Melaleuca cajuputi populations 188

4.3.6 Carbon content and CO2 storage in the Melaleuca cajuputi populations - 190

4.3.7 Estimate the cost of CO2 - 192

B Muthurajawela wetland - 196

4.3.8 The growth parameters of mangroves forests - 196 4.3.9 Mathematical models built to conduct the biomass of woody

species - - 197

4.3.10 The above-ground biomass of mangrove populations - 207

4.3.11 Estimate the cost of CO2 - 214

CHAPTER 5: CONCLUSIONS - 216

5.1 Identification of vegetation structure and cover area change -216

5.2 An assessment of the carbon stocks - 216

5.2.1 The lower U Minh national park - 216

5.5.2 The Muthurajawela wetland - 217

CHAPTER 6: RECOMMENDATIONS - 219

6.1 Identification of vegetation change by GIS technology - 219

6.2 Vegetation structure - - 220

6.3 An assessment of the carbon stocks - 220

REFERENCES -222

APPENDICES - 269

LIST OF TABLES

Table 2.1 The 15 most mangrove-rich countries and their cumulative

percentages - 37 Table 2.2 List of allometric equations applied to examine the stand biomass

of the Melaleuca forests in the study sites of Vietnam - 52

Table 2.3 Allometric equations for estimating biomass in mangrove forests 59

Table 3.1 Landsat time series used in the study - 85 Table 3.2 The characteristics of the landsat images - 87 Table 4.1 Patterns illustration of the 4,3,2 spectrum channel and the 5,4,3

spectrum channel for the vegetation classes of the

lower U Minh national park - 109 Table 4.2 NDVI for the vegetation classes of the lower U Minh

national park - 111 Table 4.3 Error matrix of vegetation cover classification of the

lower U Minh national park in 2015 - 117 Table 4.4 Assess the accuracy of the Landsat image interpretation of

vegetation cover classification in the lower U Minh national park in 2015 - 118 Table 4.5 Patterns illustrate the 4,3,2 spectrum channel and the 5,4,3

spectrum channel for the vegetation classes of the Muthurajawela wetland - 122 Table 4.6 Normalized difference vegetation index value (NDVI) - 124

Table 4.7 Error matrix of vegetation cover classification of the

Muthurajawela wetland in 2015 - 131 Table 4.8 Assess the accuracy of the Landsat image interpretation of

vegetation cover classification in the Muthurajawela wetland

in 2015 - 131 Table 4.9 Percentage of presence of woody species in the lower U Minh

national park in 2015 - 142 Table 4.10 List of plant families and species recorded in the lower U Minh

national park of Vietnam - 143 Table 4.11 Percentage presence of woody species in the Muthurajawela

wetland in 2015 - 159 Table 4.12 List of plant families and species recorded in the Muthurajawela

wetland - 161 Table 4.13 Presence of plant species in the lower U Minh

national park in 2015 - 173 Table 4.14 The growth parameters of Melaleuca cajuputi trees - 174 Table 4.15a The above-ground biomass of individual M cajuputi tree in

Table 4.17 List of allometric equations applied to estimate biomass of the

Melaleuca cạuputi forests in the lower U Minh national park - 184

Table 4.18 The percentage of green biomass difference in plantation forest between the survey value and the simulation value - 186

Table 4.19 The percentage of green biomass difference in natural forest between the survey value and the simulation value - 187

Table 4.20 Estimated the total biomass of Melaleuca cajuputi forests - 190

Table 4.21 The carbon content and CO2 storage in the lower U Minh national park - 191

Table 4.22 The growth parameters of mangrove trees - 197

Table 4.23a The green above-ground biomass of individual mangrove trees - 212

Table 4.23b The dry above-ground biomass of individual mangrove tree - 200

Table 4.24 List of allometric equations applied to estimate biomass of the mangrove trees in Muthurajawela wetland - 201

Table 4.25 The percentage of green above-ground biomass difference for

R mucronata between the survey value and the simulation value - 204

Table 4.26 The percentage of green above-ground biomass difference for A glabra between the survey value and the simulation value - 205

Table 4.27 The percentage of green above-ground biomass difference for B cylindrical between the survey value and the simulation value 206

Table 4.28 The percentage of green biomass difference for other mangrove

species (Sonneratia caseolaris, Hibiscus tiliaceus, Excoecaria

agallocha, Cerbera manghas, Syzygium caryophyllatum,

Dolichandron spathacea and Pandanus tectorius)

between the survey value and the simulation value - 207 Table 4.29a Estimated the total green above-ground biomass of mangrove

populations - 208 Table 4.29b Estimated the total dry above-ground biomass of mangrove

populations - 208 Table 4.30a Estimated the total green above-ground biomass of mangrove

forests in the Muthurajawela wetland - 213 Table 4.30b Estimated the total dry above-ground biomass of mangrove

forests in the Muthurajawela wetland - 213

LIST OF FIGURES

Figure 1.1 Location of the lower U Minh national park in Mekong delta,

Vietnam - 9

Figure 1.2 View of the lower U Minh national park of Vietnam - 10

Figure 1.3 Location of the Muthurajawela wetland of Sri Lanka - 11

Figure 1.4 View of the Muthurajawela wetland of Sri Lanka - 12

Figure 2.1 Map showing areas of special use forests and 10 priority sites for biodiversity conservation in the Mekong delta - 18

Figure 2.2 Kumana villu-natural swamp lake - 19

Figure 2.3 Livelihood model for coastal communities in the Mekong delta, Vietnam - 21

Figure 2.4 Carbon cycle in wetlands - 25

Figure 2.5 Melaleuca cajuputi forest in the lower U Minh national park - 32

Figure 2.6 Worldwide distribution of mangroves - 40

Figure 2.7 Global mangrove forests distribution-2000 - 40

Figure 2.8 Proportion of threatened (Critically Endangered, Endangered, and Vulnerable) mangrove species - 41

Figure 2.9 Distribution of mangrove vegetation in Sri Lanka - 42

Figure 3.1 Summary of methodology used in the study - 88

Figure 3.2 Layout of sample plots in the lower U Minh national park of Vietnam scale 1:25,000 - 90

Figure 3.3 Layout of sample plots in Muthurajawela wetland of Sri Lanka scale 1:50,000 - 91

Figure 3.4 Location of the training field samples in Muthurajawela wetland

scale 1:50,000 - 93

Figure 3.5 Location of the training field samples in the lower U Minh national park scale 1:25,000 - 94

Figure 4.1a The vegetation cover map of the lower U Minh national park in 1975 built by unsupervised classification - 112

Figure 4.1b The vegetation cover map of the lower U Minh national park in 1995 built by unsupervised classification - 113

Figure 4.1c The vegetation cover map of the lower U Minh national park in 2015 built by unsupervised classification - 114

Figure 4.1d The vegetation cover map of the lower U Minh national park in 2015 built by supervised classification - 116

Figure 4.2 The vegetation cover area of the lower U Minh national park 1975, 1995 and 2015 - 120

Figure 4.3 The changes percentage of vegetation area in the lower U Minh national park 1975-2015 - 121

Figure 4.4 The normalized difference vegetation index map - 124

Figure 4.5 The vegetation cover map of the Muthurajawela wetland in 1992 built by unsupervised classification - 126

Figure 4.6 The vegetation cover map of the Muthurajawela wetland in 2001

built by unsupervised classification - 127

Figure 4.7 The vegetation cover map of the Muthurajawela wetland in 2015

built by unsupervised classification - 128

Figure 4.8 The vegetation cover map of the Muthurajawela wetland in 2015

built by supervised classification - 130

Figure 4.9 Vegetation cover change of Muthurajawela wetland in 1992, 2001 and 2015 - 133

Figure 4.10 The changes percentage of vegetation area in Muthurajawela wetland 1992-2015 - 134

Figure 4.11 Presence of plant species in the lower U Minh national park in 2015 - 141

Figure 4.12 Woody species zonation at the lower U Minh national park in 2015 - 143

Figure 4.13 Melaleuca cajuputi forests on clay soil in the lower U Minh national park - 146

Figure 4.14 Melaleuca cajuputi forests on peat soil in the lower U Minh national park - 147

Figure 4.15 Phragmites karka on the dike in the lower U Minh national park - 147

Figure 4.16 Nepenthes mirabilis in the lower U Minh national park - 148

Figure 4.17 Dischidia rafflesoawa in the lower U Minh national park - 148

Figure 4.18 Ficus pisocarpain the lower U Minh national park - 149

Figure 4.19 Presence of plant species in natural M cajuputi forest in 2015 - 150

Figure 4.20 Presence of plant species in plantation M cajuputi forest in 2015 152

Figure 4.21 Pistia stratiotesin the lower U Minh national park - 154

Figure 4.22 Ceratopteris thalictroides in the lower U Minh national park - 154

Figure 4.23 Eichhornia crassipesin the lower U Minh national park - 155

Figure 4.24 Eleocharis dulcisin the lower U Minh national park - 155

Figure 4.25 Ludwigia adscendensin the lower U Minh national park - 156

Figure 4.26 Woody species distribution in high, medium and low density

awear of Muthurajawela wetland - -160

Figure 4.27 Rhizophora mucronata in Muthurajawela wetland - 168

Figure 4.28 Annona glabra in Muthurajawela wetland - 169

Figure 4.29 Avicennia marina in Muthurajawela wetland - 169

Figure 4.30 Bruguiera cylindrical in Muthurajawela wetland - 170

Figure 4.31 The green biomass of stems, branches and leaves of M cajuputi 178

Figure 4.32 The dry biomass of stems, branches and leaves of M cajuputi - 180

Figure 4.33 The ratio of dry to green biomass of stems, branches and leaves of M cajuputi in national forest and plantation forest - 181

Figure 4.34 Below-ground biomass of Melaleuca cajuputi tree - 183

Figure 4.35 Relationship between observed values results of biomass predicting equation, natural forest, above ground biomass - 184

Figure 4.36 Relationship between observed values results of biomass predicting equation, natural forest, below ground biomass - 185

Figure 4.37 Relationship between observed values results of biomass predicting equation, plantation forest,above ground biomass - 185

Figure 4.38 Relationship between observed values results of biomass predicting equation, plantation forest, below ground biomass - 186

Figure 4.39 Difference of green biomass between natural and plantation forest - 189

Figure 4.40 The ratio of dry to green biomass of woody species in the Muthurajawela wetland - 199

Figure 4.41 Relationship between observed values results of biomass

predicting equation, R mucronata, above-ground biomass - 202

Figure 4.42 Relationship between observed values results of biomass

predicting equation B cylindrica, above-ground biomass - 202

Figure 4.43 Relationship between observed values results of biomass

predicting equation Annona glabra, above-ground biomass - 203

Figure 4.44 Relationship between observed values results of biomass

predicting equation, others woody species,

above-ground biomass - 203

Figure 4.45 Compare the biomass differences between four plant species - 209

Figure 4.46 Compare the densities differences of woody species between

three densities groups: Low, medium, high - 210 Figure 4.47 The vegetation cover map of the Muthurajawela wetland - 211 Figure 4.48 The area of vegetation classes of the Muthurajawela wetland - 212

Figure 4.49 Compare the biomass differences of woody species between

three densities groups: Low, medium, high - 212

LIST OF ABBREVIATIONS

BGB Below Ground Biomass

CBD Convention on Biological Diversity

CDM Clean Development Mechanism

DBH Diameter at Breast Height

DGPS Differential Global Positioning System

EPA Environmental Protection Agency

FAO Food and Agricultural Organization

GLOVIS Global Visualization Viewer

GPS Global Positioning System

IPCC Intergovernmental Panel on Climate Change

ISODATA Iterative Self-Organizing Data Analysis Technique Algorithmv Landsat TM Landsat Thematic Mapper

LANDSAT Land Observation Satellite

LULUCF Land Use, Land-Use Change and Forestry

MSS Multi Spectral Scanner

NDVI Normalized Difference Vegetation Index

NIR Near Infrared Reflectance

ppm Parts per million

REDD+ Reducing Emissions from Deforestation and Forest Degradation plus

SPOT Satellite Pour I’Observation de la Terre

STRP Scientific and Technical Review Panel

tC/ha Ton carbon per hectare

TIFF Tagged Image File Format

UNCED United Nations Conference on Environment and Development UNEP United Nations Environment Program

UNESCO United Nations Education Scientific and Cultural Organizatio

UNFCCC United Nations Framework Convention on Climate Change

UN-REDD UN- Reducing Emissions from Deforestation and Forest Degradation UTM Universal Transverse Mercator

USA United States of America

USGS United States Geological Survey

ACKNOWLEDGMENTS

First, I would like to express my sincerest thanks and appreciation to my supervisor Professor S.M.C.U.P Subasinghe, Senior Lecturer of the Department of Forestry and Environmental Sciences, University of Sri Jayewardenepura for his supervision and valuable guidance throughout this project His sincere technical advice and moral support allowed me to complete this project in successful manner

I am thankful to Associate Professor Vo Quang Minh, Head, Department of Land Resources, College of Environment and Natural Resources, University of Can Tho, Vietnam and Dr Vo Quoc Tuan for their advices and suggestions on the field research layout and for providing me the expertise knowledge on remote sensing and GIS techniques during the early stages of this study

I am thankful to the administrators of Lower U Minh National Park in Vietnam and Department of Wildlife Conservation of Sri Lanka for their unlimited logistic support during the field work

I would like to express my sincere gratitude to all of the friends and colleagues in Department of Forestry and Environmental Science, University of Sri Jayewardenepura for their assistance and support during the field work

I am thankful to the Ministry of Higher Education, Sri Lanka and Ministry of Education and Training, Vietnam for their financial support for the study

Last but not least I like to thank my wife Hong Ngoc and two children Tan Dat and Tan Loc for their encouragement, patience and unlimited support to complete this study

Investigation of Vegetation Structure and Carbon Storage in Lower U Minh Wetland in Vietnam and Muthurajawela Wetland in Sri Lanka

2016 in Muthurajawela wetland using 36 plots Both unsupervised and supervised classifications were used to map the vegetation cover for two study areas

However, maximum likelihood method of supervised classification showed better results when compared with unsupervised classification for distinguishing vegetation classes in both study areas It identified six vegetation classes for both sites Change of the classes of vegetation cover classes in the lower U Minh national park is high mean In contrast, Muthurajawela wetland indicated a low change in the mangrove vegetation during the study period The analysis of this study proved that RS and GIS system approaches provide useful baseline dataset on the changes of wetland vegetation over a time period It therefore, provides valuable information to aid the management and conservation of wetland habitats

The results also showed that the average of density, height and DBH respectively were

528.65 trees/ha, 14.73±3.01 m and 17.17±7.05 cm for the natural M cajuputi forest and

6,312.12 trees/ha, 11.45±2.25 m and 9.01±2.14 cm for the plantation forest of the lower U

Minh national park The average green biomass of the natural M cajuputi populations was

113.65 tons/ha (68.52 tons/ha dry) and that of for the plantation forest was 274.36 tons/ha

(179.16 tons/ha dry) The average carbon content of natural M cajuputi forests was 56.18

tons/ha, which is equivalent to 206.18 tonsCO2/ha The amount of carbon accumulated in

M cajuputi population of the lower U Minh national park was 518,535.76 tons, which is

equivalent to 1,902,665.08 tons of CO2

Bruguiera cylindrical, Rhizophora mucronata and Annona glabra were the dominated and

well-developed mangrove species in Muthurajawela wetland R mucronata had an average

density of 261 tree/ha, with the average height of 8.19±3.69 m, canopy cover of 5-7 m and

DBH of 9.54±2.87 cm B cylindrical population had the average density of 1,208.33 tree/ha, DBH of 9.05±3.95 cm and average height of 8.81±4.14 m A glabra which was

grown along the water canal had the average density of 1,375 tree/ha with an average height

of 6.50±2.29 m and DBH of 7.66±2.82 cm

The average green biomass of B cylindrical, A glabra, R Mcronata respectively were

31.56 kg/tree (equivalent to dry biomass of 17.36 kg/tree), 25.40 kg/tree (dry biomass of 13.44 kg/tree) and 36.76 kg/tree (dry biomass of 20.59 kg/tree) Other woody species had the average green biomass of 34.24 kg/tree (dry biomass 18.45 kg/tree) The total above-ground biomass of the mangrove population in the Muthurajawela wetland was 447,357.48 tons (245,174.07 tons dry biomass), with their wealth of stored carbon of 115,231.81 tonsC (22.05 tonsC/ha) which is equivalent 422,516.64 tonsCO2 (80.86 tonsCO2/ha)

CHAPTER 1: INTRODUCTION

1.1 Background

Wetlands are one of the most important ecosystems on Earth Due to the characteristic ecological functions, wetlands can be considered as the "kidneys" of a regional landscape, in which, geography, geomorphology, soil, water and living organisms have

an interact connected relationships to create typical wetland ecosystem

Due to unsustainable management, hamesting land for forest products, conversion for socio-economic development, forest area and forest types have qualitatively been decreased continuously over the past years Based on the documents of Forest Science Institute of Vietnam, Vietnam had 14.3 million ha of forests in 1943, with 43% forest cover (FSIV, 2009) However, by the year 1990 only 9.18 million ha remained, with a forest cover of 27.2% from the total land area During the period 1980-1990, the average forest lost was more than 100,000 ha each year However, from 1990 to the present, the forest area has been increased gradually due to afforestation and rehabilitation of natural forest According to the National Forest Inventory Report of VNFOREST (2017) Viet Nam has around 14.4 million hectares of forested land, which constitutes 41.2% of the total land area Around 10.2 million hectares are primary or otherwise naturally regenerated forest, and around 4.2 million hectares are planted forest (VNFOREST, 2017) According to the recent studies, Vietnam's forests contain

992 million metric tons of carbon in living forest biomass (UN, FAO, 2011)

Mekong Delta has many forest areas which have been restored and preserved, including the lower U Minh national park wetland The lower U Minh national park belongs to U Minh and Tran Van Thoi districts of Ca Mau province in Vietnam The total extent of the Park is estimated to be about 8,476 ha It is located between 9o12’30” to 9o17’41”N and 104o54’11” to 104o59’29”E (Figure 1.1 and Figure 1.2) The average temperature in the area is 26.50C and the average annual precipitation is 2,360 mm Its terrain is relatively flat and the average elevation varies from 1 to 1.5 m above sea level The main soil types are peat and clay with alum sub-soils dominating in water logging areas Due to the presence of dyke systems in the area, the lower U Minh national park is not affected by the diurnal tidal of the West sea However, the area is flooded from 0.1 to 1m during the rainy season for 5-6 months from June to November in each year The amount of water in the forest can be adjusted, lowered or stored in each zone by regulating water through culverts The lower U Minh national park has been dominated

by M cajuputii trees with a grass community and vines The Melaleuca forest is of 88.64% of the total area of the National Park in 2015 and rest was comprised of bare soil, canals and grassland The Meleluca forest area could be divided into two sub-zones

as natural zone and plantation zone The age of M cajuputii trees varied as < 9, 9-13, and >13 years and these are growing in the two soil groups: peat and acid soil Forests is

in the process the care and nurturing

The vegetation of the lower U Minh national park is also an important component of the valuable contribution of the ecosystem (Kokaly et al., 2003; Lin, 2006) It is also an excellent indicator for early signs of any physical or chemical degradation in such ecosystems (Dennison et al, 1993) Therefore, the research of vegetation structure in the lower U Minh national park is very much essential for proper management Apart from

cultural, economic and environment functions mentioned earlier, the lower U Minh national park has a wealth of stored carbon as any other forest ecosystem and therefore

it provides a potential sink for atmospheric carbon

The vegetation of the lower U Minh national park is also an important component of the valuable contribution of the ecosystem (Kokaly et al., 2003; Lin, 2006) It is also an excellent indicator for early signs of any physical or chemical degradation in such ecosystems (Dennison et al, 1993) Therefore, the research of vegetation structure in the lower U Minh national park is very much essential for proper management Apart from cultural, economic and environment functions mentioned earlier, the lower U Minh national park has a wealth of stored carbon as any other forest ecosystem and therefore

it provides a potential sink for atmospheric carbon Over the time, the vegetation cover

in the lower U Minh national park has been constantly changing because of natural disasters or under the impacts of humans Fires and land conversion for agriculture have reduced many plant species as well as the area of intact peatland in the lower U Minh national park (Nguyen, 2003) Only about 800 ha of virgin forest in the lower U Minh national park survived with the fires in 1994 and 1998 (Nguyen, 2003) Another 3,300

ha of Melaleuca forests in the lower U Minh national park was destroyed by fires in the dry season of 2002 (Nguyen, 2003) Further, the loss of peat and the vegetation in this area has led to the exposure of the underlying acid sulfate soils If such ecosystems are not managed properly, they could become sources of greenhouse gases such as carbon dioxide and methane Therefore, management, monitoring of the changes of plant species, quantification of the carbon storage in the lower U Minh national park is a necessential steps to gain a better understanding of this resource

Many studies were conducted on different aspects in the Lower U Minh National Park

in the past Its plant diversity and ecosystem management were studied by Tan (2005) and Hiep (2005) respectively while studies were conducted on fire eruption by Hiep (2005) Vegetation growth and peat layer were studied by Hoa et al., (2009), Quoi (2014) and Hong et al., (2015) However, a study on the temporal change of the vegetation structures had not been done in the past for the Lower U-Minh National Park Availability of such information is vital for the park managers and for the annual reports which are currently prepared by various relevant agencies based on traditional mapping methods which are inaccurate as the scale is not considered Further, the information generated by a proper mapping study using remote sensing and GIS activities would help the Management Board of the Lower U Minh National Park to understand the forest resources change through different stages This will also act as a scientific database to help the management to conserve the National Park Therefore the present study was conducted in the Lower U Minh National Park with the objectives of identifying the present vegetation distribution and mapping the vegetation cover change over the years of 1975, 1995 and 2015using remote sensing and GIS techniques

Similar to Vietnam, Mangroves in Sri Lanka is highly endowed with biological resources, are also the largest reservoir of carbon, which plays a particularly important role in balancing O2 and atmospheric CO2, so it has a great influence on the climate of Srilanka, and greatly affects the temperature of the Earth through the process of regulating greenhouse gases, especially CO2 The natural forests were once a rich source

of timber of the highest quality in Srilanka, but many decades of exploitation have reduced both the area of the forest and the quality of the remaining forests (Caring for

the Environment, 2003) Sri Lanka’s forest cover was estimated by the FAO, 2010 to be 26.6% of the land area or 1.7 million ha in 2010 Bulk of the forest estate is dense natural forests and is mainly situated in the dry zone of the island (UN REDD, 2010) Based on the last forest cover assessments, FAO extrapolated declining forest cover of 0.6 to 0.3% over the past decade (FAO, 2010a) The main driving forces of deforestation are the increasing population and the resulting land hunger and they are leading to increase pressure on forestland for converting to non-forest uses Agricultural production of the country has been increased mainly by converting natural forest to farmlands (Caring for the Environment, 2003) Presently Sri Lanka has lost more than 60% of its forest cover from about 80% in the late 1800s to 25% in early 2000 (FAO, 2010b) Deforestation has seriously created the diminishing the timber supply, less soild productive, erratic water supply and frequent floods and severe (Bandaratillake and Fernando, 2003)

Muthurajawela wetland is the largest saline coastal peat bog in Sri Lanka, which covers

an area of 6,232 ha in total extent (IUCN Sri Lanka, 2002), located on the west coast (7003’N, 79055’E) between the Negombo lagoon and Kelani river and spreading inland

up to Ragama and Peliyagoda in the Gampaha District (Figure 1.3 and Figure 1.4) The marsh-lagoon complex is estimated to have originated in about 5000 years BC (CEA/Euroconsult, 1994) The area receives an annual average rainfall of 2000-2500mm, while the average annual temperature is 270C (Samarakoon and Renken, 1999) According to historical evidence, Muthurajawela was subjected to extensive cultivation of paddy rice, more than 500 years ago (GCEC/Euroconsult, 1991) The soil

is a uniform, potentially acidic sulphate, and the land is poorly drained with a peaty substrate which is saturated for almost the whole year

Muthurajawela receives and retains high loads of domestic and industrial wastes and sediment from both surrounding and upstream areas Wetland plants facilitate sediment deposition, before water enters Negombo lagoon The plants also act as a filter for through-flowing waters, and assist in the removal of nutrients and toxic substances During the rainy season the wetland acts as a retention area for run-off from surrounding higher grounds and floodwaters from Dadugan Oya, Kalu Oya and Kelani Ganga

The Muthurajawela wetland is mainly dominated by mangrove vegetation The marsh plant community is unstable and represents one of the final stages of succession towards dry land formation High levels of human disturbance have led to significant change in the composition of dominant plant species over the last ten years, which in turn had an effect on the faunal composition One hundred and ninety-four species of flora belonging to 66 families are distributed over seven major vegetation communities (marsh, lentic, reed swamp, short grassland, shrub land, stream bank and mangrove swamp) The shrub land harbors the highest number of species (115), while the mangrove forest and stream bank/ riparian type provide the lowest (23) (Bambaradeniya

et al., 2002) Within the recorded flora, one endemic (Phoenix zeylanica), and three nationally threatened (Aponogeton natans, Nypa fruticans, Caesalpinia crista) species occur in the marsh The mangrove in the northern border of the marsh is dominated by Bruguiera Cylindrica and Rhizophora mucronata The lentic flora in open water bodies

is dominated by Nymphaea stellata and Eleocharis dulcis The riparian vegetation includes Pandanus tectorius, Cerbera manghas and Syzygium caryophyllatum The reedbeds consist of Phragmites karka (Bambaradeniya et al., 2002)

Because, Muthurajawela wetland forms an integrated coastal wetland system of high biodiversity and ecological significance Therefore it is listed as one of 12 priority wetlands in Sri Lanka About 1,777 ha of the northern section of Muthurajawela wetland was declared as a wetland sanctuary (Lucy, 2005) Because of the presence of natural habitats and species, Muthurajwela wetland is a popular destination of recreation, education and domestic tourism (Emerton and Kekulandala, 2002) Although more than 300,000 people live in the Muthurajawela wetland, Negombo area, just under 5,000 people live in and around the marsh itself, half of whom are squatters and about three quarters who live on unauthorised landholdings (Mahanama, 1998) About 80% of industries in the country are concentrated in Colombo and Gampaha districts (UNEP, 2001) Today this number has undoubtedly increased, as much of the southern part of Muthurajawela wetland has been now turned into an industrial area Further, the location of the Muthurajawela wetland in a rapidly developing urban area which makes

it an extremely vulnerable ecosystem (IUCN, 2003) At present, the Muthurajawela wetland is being rapidly degraded by inadequately planned development activities and other detrimental activities related to growing pressure of increasing human population (Nidhi et al., 2006)

The consequence of this attitude is that humans will suffer in the future, if we do not act soon and in unison, to protect and restore mangrove forests (Baba, 2004).Therefore with continuing degradation and destruction of mangroves, there is a critical need to understand them better (Kathiresan, 2002) The importance of management of mangrove resources on a sustainable basis is very significant and needs to be implemented seriously Mismanagement of mangroves will affect negatively not only the mangrove ecosystem proper but also adjoining coastal

ecosystems, particularly sea-grass beds and coral reefs as well as the entire coastal system This is because mangroves are a major component of the tropical coastal belt, with a very important role in the intensive physical, chemical, and biological dynamism

of the coastal area At present activities towards mangrove forest conservations in Sri Lanka have been launched by different organizations in the country such as rural communities, government agencies, international organizations like IUCN and nongovernmental organizations Mangrove forests are very important to rural communities for their livelihood Therefore local communities of fishers in mangrove forest areas are very actively participating in mangrove conservation However existing conservation measures are inadequate comparatively to the decline rate of mangrove forests (Karunathilake, 2003)

Recently, there are many studies (Ranasinghe,1998; Ranasinghe 2001; Amarasinghe, 1996) conducted to describe the ecology and biology of mangroves in SriLanka However, Research on biomass as well as the investigation of vegetation structural change in Sri Lanka is still a very new issue (Gunawardena, 2016), the number of studies is small, and the content and approach are limited For these reasons, estimating the biomass and CO2 content, the investigation of vegetation structural and area change have become a priority requirement for the management of Muthurajawela wetland Applications of Remote sensing and GIS techniques will be very helpful to resolve these problems in a short time period Obtaining information after a thorough study on vegetation cover will partly help the Management Board of Muthurajawela wetland to understand the forest resources change through different stages This will also act as a scientific database to help management conserve wetland better

Figure 1.1: Location of the lower U Minh national park in Mekong delta of Vietnam

National Park

Figure 1.2: View of the lower U Minh national park of Vietnam

Figure 1.3: Location of the Muthurajawela wetland of Sri Lanka

Figure 1.4: View of the Muthurajawela wetland of Sri Lanka

1.2 The objectives of the proposed research

i Building three maps of vegetation cover for the years of 1975, 1995 and 2015 for the lower U Minh national park, Vietnam and for the years of 1992, 2001 and

2015 for Muthurajawela wetland, Sri Lanka by using remote sensing and GIS

To find out the changes of forest cover area over time;

Evaluate the interpretation ability of multi-temporal Landsat images with the average resolution

ii Identify the current vegetation structure of the selected both wetlands:

The number of species and the names of woody trees, other living forms (shrubs, vines, herbaceous, grass…) will be determined in two the study areas;

The abundence determination of woody species in the lower U Minh national park

in 2015 at three zones: Natural forest; Plantation forest and Regenerated forest; Percentage presence of mangrove woody species in the Muthurajawela wetland in

2015 at three the difference dense: Low dense, medium dense and high dense forest

iii Determination of the biomass and assessment of the carbon stocks for two study areas:

Identification of the growth parameters of M cajuputi and mangroves woody trees: density; DBH; the average height of tree;

Identification of the above-below ground biomass of M cajuputi and mangrove woody populations (above-ground biomass) by Mathematical models built for the relationship of biomass and DBH;

Estimating the potential for carbon storage of M cajuputi forests and mangroves woody population based on the total of above-ground dry biomass

CHAPTER 2: LITERATURE REVIEW

2.1 Common wetland types

Wetland is a land area that is saturated with water, either permanently or seasonally, so that it bears the characteristics of a distinct ecosystem (Department of Environmental

Protection State of Florida Glossary, 2011) These are the areas where water covers the

soil, or water is present either at or near the surface of the soil during all year or for

varying periods of time during the year (EPA, 2016a)

There are many different types of wetlands However, Matthews and Fung (1987) divided wetlands into 5 classes: (i) forested bogs, (ii) non-forested bogs (where bogs are formed by infilling of shallow lakes; usually with no inflow or outflow), (iii) forested swamps, (iv) non-forested swamps (swamps found in poorly drained areas near streams

or lakes) and (v) alluvial formations Bogs and fens are the most common wetlands across large areas of the northern hemisphere (Aselmann and Crutzen, 1989) It is estimated that about half of the world’s wetlands are in the boreal region, mostly in the form of bogs (Matthews, 1990) However, according to Aselmann and Crutzen (1989), the most widespread wetland category is bogs, covering 1.9x106 km2, followed by fens and swamps, contributing about 1.5x106 km2 and 1.1x106 km2, respectively Floodplains add another 0.8x106 km2, whereas marshes and lakes contribute only 7% to the total Other major types of wetlands of the world fall into the categories of coastal river deltas, inland river deltas, great riverine forests, saltmarshes, northern peatland, inland freshwater marshes and swamps, and constructed wetlands (Mitsch, 1994)

The RAMSAR classification of wetland types is intended as a means for fast identification of the main types of wetlands for the purposes of the convention According to that the wetlands are classified into three major classes: marine/coastal

wetlands; inland wetlands and human-made wetlands (RAMSAR, 2016)

Classification of wetlands has been however, a problematic task, especially with the commonly accepted definition of which constitutes a wetland being among the major difficulties In the 1970s, the RAMSAR Convention on Wetlands of International Importance introduced the first attempt to establish an internationally acceptable

wetland classification scheme (Scott and Jones, 1995) The degradation risk of wetlands

is becoming a serious problem in many parts of the world due to rapid increase of population and the resulting pressure on natural resources (Turner, 1991; Koch et al.,

2001; Mitsch & Gosselink, 2007) Factors such as loss of wetland area, changes to the

water regime, changes in water quality, over-exploitation of wetland products and introduction of alien species have increased and wetland degradation has been therefore

amplified (Shine and Klemm, 1999) Destruction and degradation of wetlands can lead

to serious consequences such as increase of flooding, extinction of species and declining

water quality (Shine & Klemm, 1999; Kotagama & Bambaradeniya 2006)

The RAMSAR convention was established more than 40 years ago to protect wetlands around the world Today, there are more than 2,000 wetlands, covering 192,712.55 ha, designated as Wetlands of International Importance This means that the country where the wetland is located is committed itself to protect the pacticular site from development, pollution, and drainage About 75% of the sites were added to the list

since 1999 as a result of WWF’s work (World Wildlife Fund, 2016) Several terms are