Mohammadreza Gharibreza Muhammad Aqeel Ashraf

Applied Limnology Comprehensive View from Watershed to Lake Applied Limnology

Applied Limnology

Comprehensive View from Watershed to Lake Mohammadreza Gharibreza Muhammad Aqeel Ashraf Soil Conservation and Watershed Department of Geology Management Research Institute University of Malaya Tehran, Iran Kuala Lumpur, Malaysia

ISBN 978-4-431-54979-6 ISBN 978-4-431-54980-2 (eBook) DOI 10.1007/978-4-431-54980-2 Springer Tokyo Heidelberg New York Dordrecht London

Library of Congress Control Number: 2014939876

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Springer is part of Springer Science+Business Media (www.springer.com) This Book is sincerely dedicated to my family. Their support, encouragement, and constant assistance have sustained me throughout my life

Preface

As an author, I am proud to introduce Applied Limnology, which addresses a new, comprehensive method of studying lake systems from watershed to open waters. This book opens up a new view of limnology for researchers and decision makers to consider overall land use across the catchment to ﬁnd the real issues in which lakes are involved. Recently, several issues concerning lakes have been encountered such as pollution of natural resources, shoaling, eutrophication, coastal changes, and reduction of water sources around the world. Human activities have contributed most in recent issues which are exacerbated by natural factors such as climate change. There are conservation and land development approaches in terms of integrated lake management and mitigation of the environmental impact of recent land development projects in catchment areas. This book is remarkable for highlighting a method in which issues are completely investigated and a natural resource management plan is presented with a conservation approach. Applied Limnology has a simple outline of six chapters. Chapter 1 gives a brief introduction to an overall view of Bera Lake and issues that involve it. Chapter 2 is divided into two sections, catchment areas and lake characteristics. Physiographic particulates, geological settings, stratigraphy, structural geology, climatology, and land use are introduced in the catchment section. Lake speciﬁcation comprises hydrology, bathymetry, water quality, and physical properties of sediments in Bera Lake. In Chap. 3 the emphasis is on shoaling as one of the main issues of Bera Lake, which was investigated by using 210Pb and 137Cs radioisotopes. The book highlights the capability of this method in a tropical lake to estimate sedimentation rate. Severe soil erosion and nutrient loss is another issue that plays an important role in devastating natural resources of wetlands and open waters. Chapter 4 presents the application of radiocesium in estimation of soil loss in a tropical area that is far from a source of 137Cs emission. In addition, the contribution of land development projects in the soil redistribution rate is highlighted in Chap. 4. Chapter 5 deals with contamination of sediments and several models that evaluate ecological risk assessment. Application of models of risk assessment and of dating of sediment age is a novel feature of this book that reveals the contribution of land development phases in pollution of Bera Lake. Another contribution to knowledge is provided in

vii viii Preface this book, namely, that the natural background level of several heavy minerals has been calculated for further investigation. Emphasis on the watershed and lake management plan is presented in Chap. 6. I believe that applied limnology must involve management practices to conserve natural resources. Therefore, this book has included a management plan that shows how limnology comprehensively applied will perform and how legislation and a decision support system will be established. I am highly appreciative of Dr. Muhammad Aqeel Ashraf for his partnership in most phases of the research project and for his great guidance and help in editing and providing an opportunity to release this book, Applied Limnology. I attribute the publication of this book to his encouragement and effort; without him the book would not have been completed. I express my sincerest gratitude to Dr. John Kuna Raj, Dr. Ismail Yusoff, Dr. Zainudin Othman, and Dr. Wan Zakaria Wan Muhamad Tahir, whose encouragement and support enabled me to carry out this multidisciplinary research project and to write this book. Great acknowledgment goes to Dr. Dess Walling, professor at Exeter University, UK, for his valuable advice on choosing a suitable model to estimate soil erosion at the study area. I offer sincere gratitude to Dr. Peter Appleby, professor at Liverpool University, UK, for his great advice and geochronology calculation model to determine the sedimentation rate in Bera Lake. Gratitude is also expressed to Dr. Lee Kheng Heng and Dr. Lionel Mabit and the IAEA staff for their valuable help in providing soil erosion conversion models. I gratefully acknowledge the Soil Conservation and Watershed Management Research Institute, Iran, and the Institute of Research Management and Monitoring (IPPP), University of Malaya, for their valuable executive and financial support to accomplish this mission. I am indebted to my many colleagues in the Soil Conser- vation and Watershed Management Research Institute for their contributions in official and departmental support. I owe my deepest gratitude to my parents and my brothers, who gave me financial and moral support. I also offer sincerest heartfelt acknowledgment to my family members, especially to my wife, Mahboubeh Hadadfard, and to my daughters, Zahra, Roghayeh, and Sara, whose encouragement, assistance, and support from the beginning to the conclusion enabled me to accomplish this project.

Tehran, Iran Mohammadreza Gharibreza Contents

1 Introduction ...... 1 1.1 What This Book Is About ...... 1 1.2 An Introduction of Bera Lake ...... 2 1.3 What Problems That Bera Lake Is Involved? ...... 3 1.4 Overview of Applied Limnology in Bera Lake ...... 5 References ...... 6 2 Bera Lake ...... 7 2.1 Catchment Area ...... 8 2.1.1 Physiographic Particulars ...... 8 2.1.2 Geology ...... 12 2.1.3 Climatology ...... 25 2.1.4 Land Use ...... 27 2.2 Lake Characteristic ...... 28 2.2.1 Hydrology ...... 28 2.2.2 Bathymetry ...... 34 2.2.3 Water Quality ...... 38 2.2.4 Physical Properties of Bera Lake Sediment ...... 50 References ...... 60 3 Sedimentation Rate in Bera Lake ...... 63 3.1 Introduction ...... 64 3.2 Modeling ...... 67 3.2.1 The Constant Rate of Supply CRS Model ...... 67 3.2.2 The Constant Initial Concentration CIC Model ...... 68 3.2.3 The Limitation of Models ...... 71 3.2.4 Sampling ...... 72 3.2.5 Sample Preparation ...... 77 3.2.6 Radioisotopes Analysis ...... 79 3.3 210Pb and 137Cs Inventories and 210Pb Flux ...... 80 3.4 Sedimentation Rate at the South of Bera Lake ...... 81

ix x Contents

3.5 Sedimentation Rate at the Middle of Bera Lake ...... 87 3.6 Sedimentation Rate at the North of Bera Lake ...... 91 3.7 Sedimentation Map ...... 95 3.8 Discussion ...... 95 3.9 Conclusion ...... 100 References ...... 102 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment ...... 107 4.1 Introduction ...... 108 4.2 Soil Sampling and Sample Analyses ...... 108 4.3 Soil Type of Catchment Area ...... 110 4.4 Soil Redistribution Models ...... 112 4.5 137Cs and 210Pb Inventories in Soil Samples ...... 114 4.6 Soil Loss Estimation ...... 117 4.7 Nutrient Content in Bera Lake Catchment Soil Proﬁle ...... 121 4.8 Soil Accumulation Rate in Wetlands and Open Waters ...... 124 4.9 Soil Redistribution Map ...... 125 4.10 Discussion ...... 126 4.11 Conclusion ...... 130 References ...... 132 5 Sediment Quality and Ecological Risk Assessment of Bera Lake ...... 135 5.1 Introduction ...... 135 5.2 Chemical and Pollution Analysis ...... 137 5.3 Nutrient Content Analysis ...... 139 5.4 Ecological Risk Assessment Models ...... 139 5.5 Standard Levels of Heavy Metal ...... 141 5.5.1 Background Concentration of Heavy Metals in Bera Lake Sediments ...... 142 5.6 Heavy Metal Concentration in Bera Lake Sediments ...... 143 5.6.1 Pearson Correlation Coefﬁcient ...... 144 5.6.2 Cluster Analysis ...... 144 5.7 Bera Lake Sediment Quality ...... 154 5.7.1 Ecological Risk Assessment of Bera Lake Sediment . . . . 157 5.8 Nutrient Fate in Bera Lake Sediments ...... 165 5.9 Discussion ...... 171 5.10 Conclusion ...... 177 References ...... 178 6 Watershed Management Practices ...... 183 6.1 Introduction ...... 183 6.2 Soil and Sediment Management Plan ...... 186 Contents xi

6.2.1 Mechanical Methods ...... 187 6.2.2 Agronomic Methods ...... 191 6.2.3 Research and Monitoring ...... 195 6.2.4 Socio-Economic Controlling ...... 196 References ...... 197

Appendix ...... 201

Abbreviations

AWB Asian Wetland Bureau BLC Bera Lake Catchment BP Before Present Bq mÀ2 Becquerel per square Meter Bq mÀ2 yearÀ1 Becquerel per square Meter per Year CBSQG Consensus-Based Sediment Quality Guidelines of Wisconsin Cf Contamination Factor CF:CS Constant Flux: Constant Supply CIC Constant initial concentration model ClÀ Chloride cm yearÀ1 Centimeter per Year CRS Constant rate of supply model CV Coefﬁcient of Variation 137Cs Fallout Caesium-137 Radionuclide DEM Digital Elevation Model Df Degree of Contamination DO Dissolved Oxygen DWNP Department of Wildlife and National Parks EC Electric conductivity EF Enrichment Factor EFB Empty Fruit Bunches EIA Environmental Impact Assessment Er Potential Ecological Risk Factor for Individual Metal FELDA Federal Land Development Authority FWHM Full Width at Half Maximum gcmÀ3 Gram per cubic Centimeter GC Gas Chromatographic GIS Geographical Information System H3BO4 Boric Acid HCA Hieratical cluster analysis

xiii xiv Abbreviations

HCl Chloride Acid HF Fluoride Acid 1À HNO3 Nitrate Acid IAEA International Atomic Energy Agency ICP-MS Inductively Coupled Plasma Mass Spectrometry ICP-OES Inductively Coupled Plasma Optic Emission Spectrometry Igeo Index of Geoaccumulation IRBM Integrated River Basin Management ISQG Interim Fresh Water Sediment Quality IWRM Integrated Water Resource Management LDO Lowest Dissolved Oxygen LEL Lowest Effect Level LGM Last Glacial Maximum MACRES Malaysian Centre for Remote Sensing mg kgÀ1 Milligram per Kilogram mg LÀ1 Milligram per Liter MnCO3 Manganese Carbonate MPOB Malaysian Oil Palm Board NE-SW North East—South West +1 NH4 Ammonia À1 NO2 Nitrate 2À NO3 Nitrate NW-NE North West—North East NWQS National Water Quality Standards for Malaysia 210Pb Fallout Lead-210 Radionuclide PEL Probable Effect Level PFE Permanent Forest Estate pH Acidity PO4 Phosphate POC Particular Organic Carbon PPM Per Part Million QAQC Quality Assurance and Quality Control RI Potential Ecological Risk Factor for Basin SEL Severe Effect Level SQG Sediment Quality Guidelines SRM Standard Reference Material SW South West thÀ1 yearÀ1 ton per hectare per year TCD Thermal conductivity detection TDS Total Dissolved Solid TN Total Nitrogen TOC Total Organic Carbon USLE Universal Soil Loss Equation WGS World Geographic Coordinate System Chapter 1 Introduction

Abstract Applied limnology is addressing comprehensive biological, physical, and chemical aspects of the lake and its catchment area. This concept of limnology comprises an integrated study that shows issues that catchment and lake are involved. Management plan of natural resources with conservation approach is the main objective of applied limnology. This hypothesis was tested in the Bera Lake, Peninsular Malaysia. Bera Lake is excellent example of lakes that is located in tropical climate and affected severely by land use changes at catchment area. Consequently, several issues have created such as extensive soil profile degradation, soil and nutrients loss, severe sedimentation in open waters, sediment pollution, and dramatic diminution of animal’s population particularly fishes, birds and relevant animals in Bera Lake and surrounded wetlands. Suggestion will be presented in order to minimize adverse environmental impacts of land use changes and conserve soil and water resources. This book is considerably contributing in knowledge and to achieve several new findings that will help the decision makers. The real reasons for severe reduction of area and depth at Bera Lake, reduction of fish population in the open waters, scarcity of emigrant birds and water quality degradation are the uncertainties for governmental agencies and decision makers.

Keywords Applied limnology • Bera Lake • Conservation approach • Environ- mental issues • Management plan

1.1 What This Book Is About

The book topic has concisely introduced and what the study will be addressed. The book introduces an original research and comprehensive limnological project which was fulﬁlled in the most important natural habitat in Malaysia. This book entitled “Applied Limnology” comprehensive view from watershed to the Bera Lake. The topic has signiﬁcantly represents the multipurpose and has highlighted the relevant methodology. Further, the topic has introduced an especial lake in the

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 1 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2_1, © Springer Japan 2014 2 1 Introduction tropical area with exclusive limnological, ecological, and sedimentary environment in Malaysia. It has appropriately demonstrated that book subject is an applied limnology ﬁeld which has been supported by a high-tech method. This book is not included details about ﬂora and fauna of Bera Lake and is focused mainly on physical features of the lake.

1.2 An Introduction of Bera Lake

Bera Lake is a lacustrine mire system located in the central part of Peninsular Malaysia, in the east-central State of Pahang. Bera Lake has occupied 0.11 km2 area at the most northern part of catchment, is the largest natural lake in Malaysia. The natural rainforest has been covered (593.1 km2) Bera Lake catchment (BLC) entirely prior the Malaysian land development scenarios. Their distribution in study area was decreased dramatically to 300.24 km2 by the end of 1994. Permanent Forest Estate (PFE) in BLC was cited as the first RAMSAR site in Malaysia in November 1994, because of its biodiversity and ecological importance. The oil palm and rubber planted states was established as “Buffer Zone”. According to EIA, despite government regulations stipulating that any project beyond 500 ha should have an EIA (ECD 2002b). Local settlements is disregarding this regulation by deforestation of smaller areas in RAMSAR site since 1994 and leaving destructive effects on BLC ecosystems. Bera Lake wetlands and open waters distribution is 56.3 km2 with a dendritic pattern and an elongate form. Their elevation is lower than 20 m and 2 slope, have remarkably occupied the low land areas which have geologically created 5,500–6,500 (Wu¨st and Bustin 2004) (BP). The history of study area could be divided to two prior and post 1950 or industrialization period. According to Surut (1998, unpublished) this area has been habitat of original Peninsular Malaysia (Orang Asli) people which historically living in the rainforest areas. Malaysian national plans were commenced since 1960 and Bera Lake and its catchment were recognized as one of the main states of land development projects. The catchment area was significantly deforested since 1960 by FELDA, the main executive government agency. The several kinds of timbers extensively harvested between 1960 and 1970. Then, five FELDA land development projects were fulfilled between 1970 and 1995. Official land development has prohibited, 1994, after RAMSAR site citation. Bera Lake has been studied by the commencement of the Second Malaya Plan (1961–1965) due to its multidisciplinary importance. Reviewed literature showed that most of the previous works have been related to biological and ecological aspects of Bera Lake especially its flora and fauna. The biology of Bera Lake was initially studied by University of Malaya and Botanic Garden of Singapore, published by Merton (1962). Between 1968 and 1972, Japanese–Malaysian joint research group undertake an ecological study of Bera Lake (Furtado and Mori 1982) that includes information about plant decomposition (Sato et al. 1982), flora 1.3 What Problems That Bera Lake Is Involved? 3

(Ikusima and Furtado 1982), fauna and fish ecology. The evolution of Bera Lake has been studied by Morley, stated that palynological evidence of Bera Lake Basin evaluation since 5,300 BP. A semi-detailed soil characteristics and geology and mineral resources of east Bera Lake have studied by Tharamarajan (1980), and MacDonald (1970), respectively. In November 1994, Malaysia became a contracting party to the Convention on Wetlands of International Importance (RAMSAR) Convention. The AWB initiated an integrated management project at Bera Lake. The project ended in June 1999 with publications of several reports, including anthropology (Surut 1988), faunal and floral studies (Giesen 1998) and an ecological and geological report (Wu¨st and Bustin 2001). Phillips and Bustin (1998) have implemented a preliminary investigation onto the peat deposits. Geological evolution of Bera Lake and the complementary studies about coalification in wetlands and open waters has been studied by Wu¨st et al. (2003, 2008), and Wu¨st and Bustin (2004). Besides, Wu¨st presented the new classification for organic-rich and peat deposits, and also explained development of the interior peat-accumulating basin of tropical Bera Lake since Late Pleistocene and Holocene. Evolutional trend of Bera Lake documented using three 14C dating samples. Wu¨st and Bustin (2004) have stated that accumulation of organic matter occurred in local lakes during the LGM, but widespread peat deposition did not start until 5,300 BP when climatic changes led to the evolution of a wetland system. As a result, peat accumulation rates, ranging from 0.7 to 2.5 mm yearÀ1, are highest in Pandanaceae environments and lowest in high-ash swamp forests and environments dominated by Cyperaceae. The research hypothesizes assume that soil and nutrient loss rates, sedimentation rat in wetlands and open waters, Bera Lake water and sediment quality have been significantly affected by anthropogenic changes over the last decades. Hypothesizes have been tested by a comprehensive field surveys and experimental analyzes to reveal and approve assumptions. As a result, Bera Lake and its catchment were selected to investigate sedimentary processes in order to cover existing gaps and effective contributions in the knowledge.

1.3 What Problems That Bera Lake Is Involved?

Water and soil resources have been experienced several stresses in Malaysia in the form of national agricultural scenarios. The first and second Malay plan (1956–1966) and the first Malaysian agricultural plan (1966–1970) have been supported by the government to promote the agriculture in the nation’s economy. Efforts were made by the government to settle and cultivate huge tracts of undeveloped land through the FELDA schemes. A widespread operations and extensive adverse consequences have been established in study area during and post five documented deforestation and land development phases. The FELDA has been main executive government agency for 4 1 Introduction land clearing and development in study area. Deforestation phases have been occurred between 1970 and 1975, 1976 and 1980, 1981 and 1985, 1986 and 1990, and then 1991 and 1995. Additionally, undocumented rubber plantations and timber harvesting has been performed in study area during the first and second Malay plans (1956–1966). Consequently, extensive soil profile degradation caused considerable soil and nutrients loss, reduction of soil fertility, and creation of erosional features. In addition, a great sediment transport and severe sedimentation have taken place and depth of the most important of natural lake and wetlands in Malaysia has significantly decreased. Heavy metals as product of deep chemical leaching has been released frequently in aquatic media, therefore, has been resulted in water and sediment pollution, dramatic diminution of animals population particularly fishes, birds and relevant animals in Bera Wetlands and Lakes. Adverse environmental impacts of a huge deforestation program and ecological importance of the largest natural lake in Malaysia has been led to an integrated ecosystem research on Bera Lake during 1970–1974 at Pos (Fort) Iskander, within the framework of the International Biological scheme by the Joint Malaysian– Japanese. Further, the ecological of wet lands and open waters have been studied (1994–1998) by the joint Malaysian–Danish team (DANCED 1998). Their researches have been focused mainly on the biological, coalification, and anthro- pological aspects. Assessment of literature review has remarkably highlighted a significant deficiency in the issues that the present research is concerned have never been properly studied and resolved. Additionally, previous studies in study area have not applied radioisotopes techniques and sediment quality guidelines to qualify adverse effects of land use changes. Therefore, lack of scientific knowledge about current issues, agricultural and ecological importance of study area especially its wetlands and lakes, and considerable people who are effectively have been depended on the water and soil resources of study area, brought a great incentive to investigate issues using advanced methods. This book is introduced issues to find out scientific answers to the following questions: • How much and where soil and nutrient resources of BLC have been degraded? • What has been destiny of redistributed soils and nutrients at catchment area? • What are current and historical variations in sedimentation rates in Bera Lake? • What is ecological risk of Bera Lake sediments for human health and aquatic life? • How sediment management practices could conserve soil and water resources of study area? Evidently, answering to those questions will reveal and resolve problems that the study area has been involved. Hypothesis will be tested by a comprehensive methodology in which the complete field surveying, detailed experimental analyzes, and an advanced modeling will be accomplished to achieve to the objectives. Suggestion will be presented in order to minimize adverse environmental impacts of land use changes and conserve soil and water resources. 1.4 Overview of Applied Limnology in Bera Lake 5

1.4 Overview of Applied Limnology in Bera Lake

The book of applied limnology, comprehensive view from catchment to the Bera Lake is corresponding to determine the soil erosion rate at catchment area, to estimate loss of nutrients from different land uses, to determine the sedimentation rate in Bera Lake, to assess Bera Lake water and sediment quality, to highlight ecological risks for aquatics and human health. Furthermore, this book reveals nutrients fate in the Bera Lake, the latest land use map, the Bera Lake bathymetric map, the Bera Lake hydrology and sediment discharge into the Bera Lake and its trap efficiency. This book is considerably contributing in knowledge and to achieve several new findings that will help the decision makers. The real reasons for severe reduction of area and depth at Bera Lake, reduction of fish population in the open waters, scarcity of emigrant birds and water quality degradation are the uncertainties for governmental agencies and decision makers. In addition, BLC is at the threshold of replantation of new generation of the oil palm and rubber estates. Therefore, this book will present real and quantitative guidelines for further land development projects to mitigate the adverse environmental impacts and to conserve soil and water resources in study area. General outline of this an applied limnology would be followed chart (Fig. 1.1).

Outline of Research

Filed Experimental Result Library Studies Studies Studies GIS Studies Interpretation Publications

Pre filed works Determination of Literature Sample Maps Sampler Soil Erosion Review Preparation Development Innovation Rates

Determination of Data Core Radioisotopes Geological Map Sedimentation Collection Sampling Analyzes Rate

Chemical and Sediment Methodology Hydrography Physiographic Pollution Quality improvement Operation Map Analyzes Assessment

Water and Physical Bathymetric Capability of Sediment Prosperities Map selected discharge Analyzes methodologies

Soil Nutrient Soil Erosion and Sampling Analyzes Rosion Risk Suggestions Maps

Water Sedimentation Quality Map

Land Use Map

Nutrients Map

Soil texture Map

Fig. 1.1 Applied limnology outline chart and procedures 6 1 Introduction

References

DANCED (1998) Wetland international Malaysia programme. Ministry of Science, Technology and the Environment. http://www.mst.dk/danced-uk/ ECD (2002b) Environmental Impact Assessment (EIA) guidelines oil palm plantation development. The Minister of Tourism, Environment, Sabah, http://www.sabah.gov.my/jpas/Assess ment/eia/handbook/Handbook%20Oil_Palm.pdf Furtado JI, Mori S (1982) Tasik Bera: the ecology of a freshwater swamp. Monogrov Biol 47:413 Giesen W (1998) The habitats and flora of Tasik Bera, Malaysia: an evaluation of their conservation value and management requirements. Wetlands International Asia-Pacific, Kuala Lumpur Ikusima I, Furtado JI (1982) Tasik Bera: the ecology of a freshwater swamp. Primary production. Monogrov Biol 43:191–278 MacDonald S (1970) Geology and mineral resources of the lake Chini, Sungia Bera, Sungai Jeram area of South Central Pahang. Ministry of Lands and Mines Malaysia, Kuala Lumpur Merton F (1962) A visit to Tasek Bera. Malays Nat J 16:103–110 Phillips S, Bustin RM (1998) Accumulation of organic rich sediments in a dendritic fluvial/ lacustrine mire system at Tasik Bera, Malaysia: implications for coal formation. Int J Coal Geol 36(1–2):31–61 Sato O, Mizuno T (1982) Tasek Bera: the ecology of a freshwater swamp. Dr. W. Junk, The Hague, 413 pp Surut Z (1988) Sites of cultural and historical interest at Tasek Bera. Wetlands International-Asia Pacific, Kuala Lumpur Tharamarajan M (1980) Semi-detailed soil survey of East of Taesk (Lake) Bera. Ministery of Agriculture Malaysia, Kuala Lumpur Wu¨st RAJ, Bustin RM (2001) Low-ash peat deposits from a dendritic, intermontane basin in the tropics: a new model for good quality coals. Int J Coal Geol 46(2–4):179–206 Wu¨st RAJ, Bustin RM (2004) Late Pleistocene and Holocene development of the interior peat- accumulating basin of tropical Tasek Bera, Peninsular Malaysia. Palaeogeogr Palaeoclimatol Palaeoecol 211(3–4):241–270 Wu¨st RAJ, Bustin RM, Lavkulich LM (2003) New classification systems for tropical organic-rich deposits based on studies of the Tasek Bera Basin, Malaysia. CATENA 53(2):133–163 Wu¨st RAJ, Bustin RM, Ross J (2008) Neo-mineral formation during artificial coalification of low-ash mineral free-peat material from tropical Malaysia-potential explanation for low ash coals. Int J Coal Geol 74(2):114–122 Chapter 2 Bera Lake

Abstract The comprehensive view of applied limnology comprises catchment area and lake. Therefore, this book represents characteristics of Bera Lake in scale of watershed and lake area. The total catchment area is 593 km2 with the area of cleared land, rubber and oil palm plantations covering some 340 km2. The remaining area is covered by wetlands and reed swamps. This catchment has been separated into the 12 sub-catchments in which main open water with 1.11 km2 area is located at most northern part. Overall water flow is directed northward and stream patterns of the fourth to twelfth sub-catchments have been joined and ultimately connect and drain into the south of Bera Lake. Gravelius coefficient of this catchment is 1.57 which illustrates its semi-elongate shape. Bera Lake catchment (BLC) is located in the geological central belt of Malaysia. Catchment area is covered by Semantan formation, Bera formation as well as granitic rock unit. Evidences support the effects of strike-slip faults (N110) in shaping BLC valleys and controlled elongate shape of wetlands and open waters. Probably, accumulation of detritus sediments at the depths of 8–9 m of Bera Lake has been taken place 5,500–6,500 year BP due to a tilting and rapid steepness of the main valley. In addition, forest and reed swamps have developed mainly along depressions which already created by the strike-slip faults especially in the first, third, fourth, sixth, and the twelfth sub-catchments. The first one meter thickness of Bera Lake sediment profile is composed of five distinct layers. These layers with different thickness differentiated along all cores or at whole lake area. The annual mean water level fluctuation in Bera Lake has been 2.7 m since 2007. Bera Lake volume or storage capacity is 2,995,998 m3. Annual water and sediment discharge into the Bera Lake are 24.2 (km3) and 2,042.58 (ton), respectively. Overall classification of Bera Lake water quality before and after land development project is classified IV and V which is suitable for irrigation only and requires extensive treatment for drinking. Consequently, morphology, ecology, water and sediment quality of Bera Lake has been changed since 1972 due to extensive land use changes at catchment area.

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 7 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2_2, © Springer Japan 2014 8 2 Bera Lake

Keywords Bera Lake • Land use changes • Trap efﬁciency • Water level • Water quality

2.1 Catchment Area

2.1.1 Physiographic Particulars

The study area, BLC is located in the central part of Peninsular Malaysia, in southwestern Pahang State and northeastern Negeri Sembilan State (Fig. 2.1), between 2,530,0000–3,100,0000 longitudes and 102,300,3000–102,470,0000 longitudes. This lake can be inversely trough as an island of water surrounded by a sea of rain forest. Two very low but parallel mountain ranges [around 500 m high] ﬂank Bera Lake into existence within a corridor. The mountain range the Bertangga/Cermingat at east, and the Batu Beras/Palong range at west guides water within the lowland. The southern edge is a ﬂat lowland gradually dominated the undulating “waves lands” of Johor.

Fig. 2.1 Geographical position of BLC in Peninsular Malaysia 2.1 Catchment Area 9

Fig. 2.2 The topographic map of BLC and surrounding area

As previously mentioned, the latest physiographic characteristics of study area have been created using the digital topographic maps of 1:25,000 scale (Series L8028) and a satellite image (Spot 5, 2009) of spatial resolution 10 m and GIS media. The total catchment area was determined to be 593.1 km2 with the area of cleared land, rubber and oil palm plantations covering some 340 km2, and open water involving some 1.11 km2 (Fig. 2.1). The remaining area is covered by wetlands and pristine (forest and reed swamps) lowland rain forests. The highest hills in BLC are up to 140 m above sea level and the lowest elevation is 7 m at outlet point of Bera Lake (Fig. 2.2). River valleys mostly have developed from elevation of 40 m and mean water level elevation is obtained 7 m. Digital elevation model was developed in order to draw BLC slope map. Resultant slope map (Fig. 2.3)in degree shows that up to half of study area is composed of low land area with slope of 0–2. Geomorphology of drainage pattern in Bera Lake is controlled by geological formation and topographic criteria. The common drainage pattern is dendritic (Fig. 2.3). A dendritic drainage pattern is the most common form in regions underlain by homogeneous material. That is, the subsurface geology has a similar resistance to weathering so there is no apparent control over the direction the tributaries take. Dendritic pattern is continued in wetlands and open waters as 10 2 Bera Lake

Fig. 2.3 Digital elevation model of BLC well. Several distributaries and elongate open waters have shaped the Bera Lake at northern part of catchment. Indeed, Bera Lake is topographically trapped body of water which has developed into the dendritic distributaries. The total length of stream pattern in BLC area and drainage density were obtained 1,316.844 km and 2.248 km, using geographical information system. The BLC has been separated into the 12 sub-catchments (Fig. 2.4) in which main open water is located at most northern part, at the third sub-catchment. Overall water ﬂow is directed northward and stream patterns of the fourth to twelfth sub-catchments have been joined and ultimately connect and drain into the south of Bera Lake (Fig. 2.5). Two other streams from the ﬁrst sub-catchment (Kelangton stream), and second, drain into the middle, and northern parts, of Bera Lake, respectively. This leaves only one outlet—excess water over spilling into channels in the north where all join Bera River which ultimately ends into Pahang River. In addition, BLC and its sub-catchments were studied in order to calculate physiographic and drainage characteristics (Table 2.1). Catchment form is an essential factor which controls hydrological parameter like time of concentration and water discharge . As a result, the round shape catchments drain faster than elongate 2.1 Catchment Area 11

Fig. 2.4 Stream pattern and sub-catchment of Bera Lake watershed shape ones. Therefore, catchment form has been studied using shape factor, Gravelius coefﬁcient (Gravelius 1914), and Horton form factor (Horton 1932). The highest and lowest Gravelius values were obtained 1.99 and 0.14 for the tenth and seventh sub-catchment, respectively. Gravelius coefﬁcient of BLC was obtained 1.57 which illustrates its semi-elongate shape. Horton form factor is also an indicator of watershed circulatory representing form factor of 1 for circular shape and values less than 1 show diversion from roundness. Horton form factor was calculated for BLC is 1.12, points out a basin with a semi-elongate shape. Time of concentration is a fundamental watershed parameter, which is the longest time required for a particle to travel from the watershed divide to the watershed outlet. It is used to compute the peak discharge for a watershed. The peak discharge is a function of the rainfall intensity, which is based on the time of concentration. Time of concentration of Bera Lake basin was calculated based on the Kirpich equations (Kirpich 1940). Time of concentration in BLC is obtained 8.53 h. In addition, this value is decreasing in order of 7.79 > 6.42 > 3.61 > 3.38 > 3.11 > 2.94 > 2.84 > 2.45 > 2.09 > 1.45 > 1.05 > 0.89 h in the sub-catchments 4, 12, 8, 3, 1, 5, 9, 2, 10, 6, 11, and 7, respectively. Resultant time of concentrations is in accordance to shape of sub-catchment where the most circulate has been the seventh one, indicating the lowest time of concentration 0.89 h. 12 2 Bera Lake

Fig. 2.5 Slope categories at BLC

2.1.2 Geology

Geological setting is one of the most important characteristics of BLC in terms of its contribution in sedimentary processes and evolution of basin. BLC is located in the geological central belt of Malaysia. The central belt signiﬁcantly is different with western and eastern belts in terms of historical evolution, tectonic and structural, and stratigraphy settings (Hutchison and Tan 2009). Figure 2.6 illustrates the Lebir fault and Bentong Suture as a boundary between eastern and western margin of the Central Belt, which covers the entire state of Kelantan, the western and central parts of Pahang, the eastern part of Negeri Sembilan, and the western part of Johor (Ismail et al. 2007). Central Belt involves the Kepis, Lop, Bera, Kaling, Paloh, Ma’Okil, Gemas, Semantan, Tembeling and Koh Formations, and the Gua Musang Group and the Bertangga Sandstone, which range in age from Permian to Cretaceous (Ismail et al. 2007) (Fig. 2.7). . acmn ra13 Area Catchment 2.1

Table 2.1 Physiographic and drainage characteristics of Bera Lake watershed Bera Lake sub-catchment Parameter 1234 56789101112Whole catchment Area (km2) 50.4 18.18 29.9 125.93 28.13 12.93 12.42 60.11 25.56 38.97 49.49 141.1 592.84 Perimeter (km) 39.9 23.53 33.4 69.95 28.65 20.2 17.61 37.31 27.83 44.45 38.2 65.8 138.195 Length (km) 9.58 7 10.33 21.28 8.97 4.96 3.25 10.9 8.85 6.8 3.74 17.86 23 Gravelius coefﬁcient 1.57 1.55 1.71 1.75 1.51 1.61 0.14 1.35 1.54 1.99 1.52 1.55 1.59 Horton form factor 0.55 0.37 0.28 0.28 0.35 0.5 1.18 0.51 0.33 0.84 3.54 0.44 1.12 Concentration time (h)a 3.11 2.45 3.38 7.79 2.9 1.45 0.89 3.61 2.84 2.09 1.05 6.42 8.53 Gravelius Equation [(Kc¼28P/A0.5 ) A: area (km2), P: perimeter (km)] Form Factor in Horton Equation [(F¼A/L2) A: area (km2), L: Length (km)] aKripich Equation [(Tc(hr)¼0.0003L0.77 *S 0.385 ) L: Length of main stream (km)] Fig. 2.6 Geological map of Peninsular Malaysia after (Hutchison and Tan 2009)

Fig. 2.7 Mesozoic stratigraphic column of Central Belt. In (Ismail et al. 2007) 2.1 Catchment Area 15

Fig. 2.8 Geological map of BLC

2.1.2.1 Stratigraphy

2.1.2.1.1 Bera Formation

The Bera Formation was introduced by Sone and Shafeea Leman (2000) for recently exposed Permian layers on the eastern side of Bera Lake (Fig. 2.8). Bedding strata of the Bera Formation was recorded N130 (NE-SE), 60SW at the 12th sub-catchment, east of Bera Lake (Figs. 2.9 and 2.10). Lithology of the Bera Formation is composed of massive mudstone (Fig. 2.10), thick to massive tuffaceous sandstone, siltstone, and thin-bedded siliceous mudstone in its lower part, and thin-bedded shale, siltstone sandstone and subordinate conglomerate in its upper part. Several fossiliferous horizons give general middle Permian (Roadian to Capitanain) age. This formation has showed highly weathered and undifferentiated intrusions, probably the Triassic igneous rocks. Iron oxide nodules appear as Gusan Zone is common product of highly chemical weathering of igneous rocks in study area which represents position of previous original rocks. Another source of iron-rich strata in the Bera Formation probably came from the ﬁnal and dilute intrusion phases of igneous rocks which have been penetrated between sedimentary layers. Hutchison and Tan (2009) stated that the 16 2 Bera Lake

Fig. 2.9 Bera Formation bedding and lithology in east of study area

Fig. 2.10 Thick outcrop of mudstone, Bera Formation at the twelfth sub-catchment

Bera Formation sediments initially were deposited in a shallow marine environment within a closed basin, with rapid sedimentation rate and volcanic input from the surrounding area. Overall sequence of the Bera Formation has been accumulated at a shallow upward to a littoral basin. 2.1 Catchment Area 17

Fig. 2.11 Accumulation of the Semantan Formation in a forearc basin (after Hutchison and Tan 2009)

2.1.2.1.2 Semantan Formation

The Semantan Formation is one of the Paleo-Tethyan deposits which have been reported as Middle to Upper Triassic in age. Convergence between of the Eastmal/ Indosinia and Sibumasu blocks resulted in closure of the Paleo-Tethys ocean in Late Triassic times (Hutchison and Tan 2009) (Fig. 2.11). The upper and lower contacts of the Semantan Formation are not exposed at the type locality. Lower boundary in BLC is not exposed and overlaid with an uncon- formity by Redbeds formation and quaternary deposits. Lithology of the Semantan Formation comprises a rapidly alternating sequence of carbonaceous shale, siltstone and rhyolite tuff with a few lenses of chert, conglomerate and recrystallized limestone. The best outcrops of Semantan Formation at BLC was found at the third sub-catchment where a sequence of fine sandstone with medium bedding layers interbedded with gray calcareous shale thin bedded layers (Fig. 2.12). Another outcrop of the Semantan Formation has sharp contacts with lower and upper formations were found close to open water. It appeared different feature where deeply weathered brown-yellowish argillaceous layer was dominated lithology, overlaid the basal conglomerate at lower contact and beneath the quaternary conglomerate by disconformity (Fig. 2.13). Hutchison and Tan (2009) introduced basal as red beds from Karak to Cheroh along the foothills of the Main Range with an age of pre-Triassic, specifically pre-Anisian or pre-Semantan. Disconformity at the top surface has pointed out the unknown time period of erosion or situation without any deposition. It seems thickness of the Semantan Formation in study area remarkably has been reduced because of severe erosion. Figure 2.13 indicates 10 cm thickness and dark color paleosols at disconformity surface. Figure 2.14 represents another outcrop of Semantan Formation at most northern part of catchment area which points out decrease in its thickness. Several acidic to intermediate igneous intrusion is reported in this formation (Hutchison and Tan 2009). Mohamed (1996) stated that Semantan formation has been appeared by a inter-fingering outcrops and it is comparable with other formations; Raub Series; Calcareous 18 2 Bera Lake

Fig. 2.12 Lithological sequence of Semantan Formation in BLC

Fig. 2.13 Stratigraphic sequences of geological formations in study area 2.1 Catchment Area 19

Fig. 2.14 Common stratigraphic sequences of formations in BLC

Formation; Calcareous Series; Younger arenaceous Series; Raub Group; Jengka Pass Formation; Kerdau Formation; part of Jelai Formation; Gemas Formation; Jurong Formation; Pahang Volcanic Series in the different areas.

2.1.2.1.3 Post-Semantan Formation Redbeds

One of stratigraphic units with a wide distribution in Central Belt is Redbeds Formation which forms large km-sized folds. It is composed of conglomerate, pebbly sandstone and sandstone whereas the upper part is dominantly comprised by mudstone with subordinate sandstone (Hutchison and Tan 2009). In general view conglomerate layer has been partly covered the Semantan Formation at BLC with the variable thickness. Redbeds Formation outcrop seems to be lenticular and it is not in the form of thick continues beds. The texture is composed of rounded quartz, schist, chert, volcanic fragments and iron oxide phenoclasts, size is varying between 2 and 20 mm. Grain supported texture with different portion of sandy to muddy sand matrix was obtained in the grain size analysis. Redbeds Formation strata have cemented with silica and yellow to red iron oxide cements. Field observations revealed that Redbeds Formation directly deposited on the BeraFormationwithanerosionalcontact especially in fourth and twelfth sub-catchments, east and west of study area, respectively (Fig. 2.15). 20 2 Bera Lake

Fig. 2.15 Redbeds conglomerates overlays the Bera Formation in sub-catchment 4

Granitic rocks in BLC have been exposed in the twelfth sub-catchment at the eastern part. This rock unit has been well studied by MacDonald (1970) especially at Bukit Pandan which is close to BLC with a cliffy morphology and a steep valley. Their topography seemingly shaped by faulting and uplifting mechanisms. The main granite body of BLC has appeared at few outcrops. Field observations especially in the twelfth sub-catchment and soil analysis has been conﬁrmed the granitic character of the plutonic rock from which it is derived. It appears that at the twelfth sub-catchment the granite body is located at a shallow depth beneath the capping of sedimentary strata. The common feature of few exposed granites bodies has been deeply altered and sericitized surface. MacDonald (1970) also has reported hornblende in a minor constituent, and epidote, garnet, pyrite, and clinozoisite as accessories.

2.1.2.1.4 Quaternary Deposits

There is a long history into investigation of quaternary deposits in BLC. The geological setting and evolution of the Bera Lake basin as well as deposition of peat and more recent palynological aspects have been studied (Morley 1981; Phillips and Bustin 1998;Wu¨st and Bustin 2001, 2003, 2004;Wu¨st et al. 2002, 2003, 2008). Several boreholes which have been analyzed by Morley (1981) and Wu¨st and Bustin (2004) revealed sequence of inorganic and organic deposits in 2.1 Catchment Area 21

Fig. 2.16 Historical sedimentation proﬁles in Bera Lake, after Wu¨st and Bustin (2004)

wetlands and open waters. According to the longest borehole log description; basal deposits is composed of detritus sands and coarse debris which may have been deposited at a time when river current ﬂowed in a steep valley. Contribution of forest taxa in the basal deposits has been maximum between other organic taxa which approved by pollen records. Morley (1981) believed that inorganic alluvial sediments have been deposited only during the mid-Holocene; ca. 4,500 radiocar- bon years BP. Wu¨st and Bustin (2004) represented a core in which stated that deposition of detritus sediments have been occurred before 5,500–6,500 year BP has been created by a wet world season and heavily precipitation and runoff (Fig. 2.16). They have introduced organic-rich lake sediments with an age of 20,480 190 year BP. In the other word, they believed that accumulation of organic matter occurred in local lakes during the LGM, but widespread peat deposition did not start until 5,300 BP when climatic changes led to the evolution of a wetland system. According to Morley (1981) contribution of non-forest and swampy pollens and spores have remarkably increased and preserved in sediments since 660 75 year BP. Transition to swampy condition has been rapid and is thought to have been caused by a reduction in gradient of the stream resulting from minor tilting of the area by tectonic movements. 22 2 Bera Lake

2.1.2.2 Structural Geology

Peninsular Malaysia has been structurally divided into three major belts with a less clearly defined fourth domain in the NW direction. Tectonic developments in the Mesozoic have been responsible for configuration of structural belts. BLC is located in the central belt and close to eastern belt. The boundary between the Central and Eastern Belts is marked by the Lebir Fault Zone (Hutchison and Tan 2009) (Fig. 2.17). Structural geology of study area has been partially studied by MacDonald (1970) which divided the tectonic activities into three consecutive phases: (1) Folding due to earth movements along NW-SE lines, and minor faulting along axial planes. (2) East-West trend folding and emplacement of the granites bodies (3) Major north-south faulting MacDonald (1970) has stated a dominate fold structures which are open anti- clines and synclines with a northwest-southeast trend, and pitching gently to the southeast. Bera and Semantan Formations outcrops in BLC has revealed significant effects of granites mass emplacement in the folding of Permian and Triassic rock units. Overall orientation of recorded bedding showed that rock units at BLC are located at right flank of a wide syncline, trending NW-SE and layers inclined 45–60 SE. Although Hutchison and Tan (2009) introduced Bera Fault as a Jurassic-Cretaceous faulting system (Figs. 2.4, 2.5, 2.6, 2.7, and 2.8) which developed between Mersing and Lepar fault zones, that has been active mid-Holocene as quaternary fault in terms of reshaping of Bera Lake basin. Faulting has played remarkable role in the final configuration of BLC. As shown in Figs. 2.4, 2.5, 2.6, 2.7, and 2.8 there are five faults trending NW-NE and two faults are in NE-SW direction. Faults were recognized from aerial photos, stream pattern and confirmed using digital topographic maps. Evidences support the effects of strike-slip faults in shaping BLC valleys and controlled elongate shape of wetlands and open waters. Probably, accumulation of detritus sediments at the depths of 8–9 m of Bera Lake has been taken place 5,500–6,500 year BP due to a tilting and rapid steepness of the main valley. In addition, forest and reed swamps have developed mainly along depressions which already created by the strike-slip faults especially in the first, third, fourth, sixth, and the twelfth sub-catchments. Intensive chemical weathering of rock units resulted in coverage of fractures and joints in study area except at Semantan Formation where exposed with semi-fresh layers at northwest of catchment (Figs. 2.18 and 2.19). Join and fractures were studied in order to find contribution of major fault system in the development of failure surfaces, and faults. Joint studies (Fig. 2.20) showed that the main faults and joints trends can be classified in four groups of N350, N60, N90, and N110, with 5, 25, 30, and 35 % of frequency respectively. Geological map and field observation demonstrated that N350 fault system has played a vital role in the development of fractures even though the maximum 2.1 Catchment Area 23

Fig. 2.17 Major and minor faults and structural zones of Peninsular Malaysia (after Hutchison and Tan 2009) frequency of joint trend was appeared at N110. This maximum joint trend (N110) can be part of the Mersing Faulting Zone while main faults are representing effects of major faults which separated Central and Eastern Belts. 24 2 Bera Lake

Fig. 2.18 Major fault trends in catchment with 5 % frequency

Fig. 2.19 Joint system appeared in the Semantan Formation 2.1 Catchment Area 25

270 90

180

Fig. 2.20 Rose diagram showing direction of joints and fractures in study area

2.1.3 Climatology

The climate of Peninsular Malaysia, can be distinguished four seasons namely, the southwest monsoon, northeast monsoon and two shorter periods of inter-monsoon seasons. The southwest monsoon season is usually established in the latter half of May or early June and ends in September. The prevailing wind ﬂow is generally southwesterly and light, below 15 knots (MMD 2011). The northeast monsoon season usually commences in early November and ends in March. During this season, steady easterly or northeasterly winds of 10–20 knots prevail. The winds over the Penang state may reach 30 knots or more during periods of strong surges of cold air (cold surges) from the north (MMD 2011). During the two inter-monsoon seasons, the winds are generally light and variable. During these seasons, the equatorial trough lies over Malaysia. As Malaysia is mainly a maritime country, the effect of land and sea breezes on the general wind ﬂow pattern is very marked especially during days with clear skies. On bright sunny afternoons, sea breezes of 10–15 knots very often develop and reach up to several tens of kilometers inland. On clear nights, the reverse process takes place and land breezes of weaker strength can also develop over the coastal areas (MMD 2011). 26 2 Bera Lake

3000

2500

2000

1500

1000

Precepitation (mm) 500

0 1980 1967 1969 1970 1971 1974 1975 1989 1972 1973 1985 1986 1987 1995 1996 1978 1981 1982 1984 1966 1968 1976 1977 1979 1983 1990 1991 1992 1993 1988 1994 Year

Fig. 2.21 Annual precipitation of Triang station 1966–1996

The mean monthly relative humidity is between 70 and 90 %, varying from place to place of study area and from month to month. The minimum range of mean relative humidity is varying from a low 80 % in February to a high of only 88 % in November. It is observed that in Peninsular Malaysia, the minimum relative humidity is normally found in the months of January and February. The maximum is however generally found in the month of November (MMD 2011). Mean annual temperature is approximately 30 C, varying from 25 Cto38C (Chee and Abdulla 1998). A number of occasions have been recorded on which the temperature did not rise above 24 C which is quite frequently the lowest temperature reached during the night in most areas. Night temperatures do not vary to the same extent, the average usually being between 21 and 24 C. Individual values can fall much below this at nearly all stations, the coolest nights commonly followed some of the hottest days (MMD 2011). Rainfall records from 1970 to 2009 at the Pos (Fort) Iskandar station, which is located at the mid-point of the BLC, show that minimum, and maximum, annual rainfall is in the range of 1,000, and 2,602 mm. Available rainfall data of the eight nearest rainfall stations (Fort Iskandar, Triang, Gambir, Kemayan152, Buto CGA Mak, Kuala Bera86, Chenor 88, Bukit Imbam) were evaluated in order to ﬁnd the most reliable and complete one. The nearest rainfall station to the Bera Lake is Triang station which has the most complete rainfall data particularly during the land development projects 1966– 1996 (Figs. 2.21, and 2.22). The regulative effect of the forest canopy results in a lower evapotranspiration net water loss (Wu¨st and Bustin 2004). Potential evapotranspiration of the Pahang state as estimated by Penman Method was 1,515 mm year1, ranging from 1,449 to 1,509 mm (Nik 1988). In addition, evapotranspiration rate in the study area is reported 4–4.5 mm/day (Nik 1988). 2.1 Catchment Area 27

Min Mean Max

500 400 300 200 100 Precepitation (mm) Precepitation 0 July May June April March August October January February December November September Month

Fig. 2.22 Long-term mean monthly rainfall between 1966 and 1996 in Triang station

2.1.4 Land Use

Land use is an essential characteristic of each catchment which determines physical and chemical properties and rate of sediment delivery in empirical models and assigns rate of soil loss in radioisotopes conversion models. Investigate and updating of land use data was one of current research objectives. The BLC is located in Pahang State, Malaysia which has experienced the most extensive land use change in the last four decades. FELDA has been the main executive for land use change in Malaysia and has implemented 164 schemes in Pahang State which has 40 % of all the land development in the country until 1990 (Henson 1994). During five FELDA (MPOC 2007) land development programmes from 1970 until 1995, some 292.86 km2 of original forest was converted to oil palm and rubber plantations in the BLC area. FELDA land development districts maps were derived from the digital topographic maps of series L8028 (1:25,000 scale) which could be find in the Appendix. Bera Lake was designated under the Con- vention of Wetlands as the first RAMSAR site in Malaysia in November 1994 with the FELDA districts being known as Buffer Zone. A new land use map of the BLC area has been developed using GIS, a satellite image (Spot5, 2009) of spatial resolution 10 m and an on-screen digitizing method. New land use map has remarkably revealed continues land use change and encroachment into the Bera Lake RAMSAR site. Between 1994 and 2009 the oil palm and rubber plantations and newly opened lands has been increased 47.14 km2 and some 340 km2 area has been established for forested lands (Fig. 2.23). Lake or open waters and original forests are eco-heritage of study area have been restricted to 3.44 and 196 km2, respectively (Table 2.2). 28 2 Bera Lake

Fig. 2.23 Land use map of BLC

Table 2.2 Land use and Land use Area (ha) natural land cover of BLC based on developed land Dried forest 17.93 use map Dried Pandanus 73.58 Dried reed swamp 132.12 Forest swamp 4,269.97 Reed swamp 613.60 Pandanus 197.24 Lake 344.15 Developed oil palm/rubber 23,954.03 Developing oil palm/rubber 8,667.32 Cleared lands 1,406.35 Original forest 19,576.04 Residential 52.30

2.2 Lake Characteristic

2.2.1 Hydrology

Lake Hydrology is known as essential knowledge about each lake that can lead sedimentary regime study in a proper way. Hydrology of a lake can serve as wide range of data from current discharge into and from the lake, water level and 2.2 Lake Characteristic 29 balance, efficiency trap, flood retention, and determine agricultural water balance in catchment area. Drainage pattern in study area drains into Bera Lake at most northern part of catchment at the third sub-catchment. It is evident, that Bera Lake hydrology can reveals remarkable data about historical sedimentary events of catchment area and provides reasonable data for interpreting of sedimentation rate in Bera Lake. Long and short term water and sediment monitoring provides valuable information about basin sedimentary regime. However, hydrology data is the shortage and significant gap of available data in BLC. Although Bera Lake is the largest natural lake in Malaysia, but its hydrological data has been main informational gap between other studies. There is not any hydrological gauge or station in BLC and lack of data encouraged this research to plan field works to a seasonal survey of water and sediment discharge into and from Bera Lake basin.

2.2.1.1 Water and Sediment Discharge

Three hydrological sections were selected based on two main water and sediment entry points and one main departure streams from Bera Lake. The ﬁrst and the most important section was at south of Bera Lake and another section was on the Kelantong stream which terminated to the lake at north-west of basin. Outlet section was marked on the main channel which drains the lake before the junction with Bera River (Sungai Bera). Water and sediment discharge into and from Bera Lake were measured in the two wet seasons (February and August, 2010) and one dry season (October, 2010), respectively. As already mentioned above, water and sediment discharge to and from the Bera Lake were measured in the two wet seasons (February and April, 2010) and one dry season (October, 2009), and result are presented in the Figs. 2.24, 2.25, and 2.26, respectively. A moderate correlation between wet and dry seasons and water balance has been revealed at Bera Lake. The mean contribution of the south and north inlets in terms of water supply obtained were 75.87, and 6.44 %, respectively. Water discharge survey was pointed out as minor contribution of streams and channels in water and sediment supply in the October. Results also showed that hydraulic slope in Bera Lake still tend to drains water into the Bera River even in dry season. Besides, a contribution of 95.7 % for Bera Lake sediment supply has been revealed for the south inlet in February. The mean contribution of the south and north inlets in terms of sediment supply were obtained 87.38, and 7.73 %, respectively. Whenever the water contribution of north inlet decreased to 1 %, its contribution to sediment supply has been increased to 10 %, Table 2.3. A signiﬁcant correlation between water volume from the south inlet of Bera Lake and residual sediment was observed. Furthermore, 30–40 % of sediment during wet seasons has been drained from Bera Lake to the Bera River. Capability of Bera Lake for sediment trapping can be increase up to 70 % when water supply increases especially from the south inlet. Elongate shape and abundance of distributaries are among the other reasons for increase of sediment residual in Bera Lake. 30 2 Bera Lake

Area: 2.72 m2, Ave V: 0.73 m s-1, Q: 1.99 m3s-1 Area: 3.38 m2, Ave V: 2.65 m s-1, Q: 9.97 m3 s-1 Area: 2.05 m2, Ave V: 3.96 m s-1, Q: 0.81 m3 s-1 Total Q: 11.78 m3s-1 Total TSS: 5.55 mg l-1 Qs: 11.78 m3 s-1 × 5.55 mg l-1= 65.41 g s-1

Area: 12.2 m2, Ave V: 0.13m s-1,Q: 1.6 m3 s-1 Total TSS: 3.33mg l-1, Qs: 1.6m3 s-1 × 3.33 mg l-1= 5.38g s-1

Area: 4.10 m2, Ave V: 1.00 m s-1, Q: 4.10 m3 s-1 Area: 4.42m2, Ave V: 2.57 m s-1, Q: 11.40 m3 s-1 Area: 3.84 m2, Ave V: 0.67 m s-1, Q: 2.66 m3 s-1 Area: 2.77 m2, Ave V: 0.46 m s-1, Q: 1.27 m3 s-1 Total Q: 19.06 m3 s-1 Total TSS: 4.58 mg l-1 Qs: 19.06m3 s-1 × 4.58 mg l-1= 87.28 g s-1

Fig. 2.24 Water and sediment discharge into and from Bera Lake 2.2 Lake Characteristic 31

Area: 1.73 m2, Ave V: 0.53 m s-1, Q: 0.92 m3s-1 Area: 3.33 m2, Ave V: 0.58 m s-1, Q: 1.93 m3 s-1 Area: 2.15 m2, Ave V: 0.46 m s-1, Q: 0.98 m3 s-1 Total Q: 3.83 m3s-1 Total TSS: 20.37 mg l-1 Qs: 3.83 m3 s-1 × 20.37 mg l-1= 77.82 g s-1

Area: 1.37 m2, Ave V: 0.08 m s-1, Q: 0.11 m3s-1 Area: 1.61 m2, Ave V: 0.17 m s-1, Q: 0.28 m3 s-1 Area: 1.72 m2, Ave V: 0.16 m s-1, Q: 0.28 m3 s-1 Total Q: 0.67 m3s-1 Total TSS: 5.22 mg l-1 Qs: 0.67 m3 s-1 × 5.22 mg l-1= 3.50 g s-1

Area: 3.97 m2, Ave V: 0.40 m s-1, Q: 1.61 m3s-1 Area: 5.18 m2, Ave V: 0.40 m s-1, Q: 2.05 m3 s-1 Area: 4.13 m2, Ave V: 0.40 m s-1, Q: 1.68 m3 s-1 Total Q: 5.34 m3s-1 Total TSS: 4.17 mg l-1 Qs: 5.34 m3 s-1 × 4.17 mg l-1= 22.26 g s-1

Fig. 2.25 Water and sediment discharge into and from Bera Lake 32 2 Bera Lake

Fig. 2.26 Water and sediment discharge into and from Bera Lake

Area: 1.46 m2, Ave V: 1.02 m s-1, Q: 1.49 m3s-1 Area: 2.94 m2, Ave V: 1.02 m s-1, Q: 3.01 m3 s-1 Area: 1.61 m2, Ave V: 1.08 m s-1, Q: 1.74 m3 s-1 Total Q: 6.24 m3s-1 Total TSS: 4.97 mg l-1 Qs: 6.24 m3 s-1 × 4.97 mg l-1= 31.01 g s-1

Area: 1.62 m2, Ave V: 0.06 m s-1, Q: 0.1 m3s-1 Area: 1.73 m2, Ave V: 0.10 m s-1, Q: 0.18 m3 s-1 Area: 1.10 m2, Ave V: 0.10 m s-1, Q: 0.11 m3 s-1 Total Q: 0.38 m3s-1 Total TSS: 7.53. mg l-1 Qs: 0.38 m3 s-1 × 7.53 mg l-1= 2.90 g s-1

Area: 3.67 m2, Ave V: 0.60 m s-1, Q: 2.20 m3s-1 Area: 4.81 m2, Ave V: 0.32 m s-1, Q: 1.56 m3 s-1 Area: 3.75 m2, Ave V: 0.54 m s-1, Q: 2.02 m3 s-1 Total Q: 5.80 m3s-1 Total TSS: 2.35. mg l-1 Qs: 5.80 m3 s-1 × 2.35 mg l-1= 13.67 g s-1 . aeCaatrsi 33 Characteristic Lake 2.2

Table 2.3 Contribution of water and sediment entry points in Bera Lake based on implemented measurement Water contribution (%) Sediment contribution (%) Water discharge (m3 s 1 ) Sediment discharge (g s 1 ) Water gates Feb Apr Oct Feb Apr Oct Feb Apr Oct Feb Apr Oct South inlet 71.6 94.2 61.8 95.7 91.4 74.94 3.83 6.24 11.78 77.82 31 65.41 North inlet 12.5 5.82 1 4.3 8.56 10.35 0.669 0.386 0.115 3.45 7.53 9.04 Others (wetlands) 15.9 – 37.33 – – 14.7a 0.841 – 7.11 – – – Residual 0 12.6 0 72.61 59.7 0 – – – – – – Outlet – – – – – – 5.34 5.8 19.05 22.26 13.67 87.28 aMinus balance of sediment in Bera Lake 34 2 Bera Lake

Conversely, sediment discharge from Bera Lake could be remarkably increased during dry season, when about 15 % of residual sediments drain in the compensate lack of sediment supply from the south inlet. Water level fluctuation is another hydrology character of Bera Lake that has recently recorded by RAMSAR site directory staff (Fig. 2.27). Results show that the maximum water level recorded during December 2007, October 2008, January 2009, and January 2010 were 8.21, 8.29, 9.2, 8.25 m respectively. On the other hand, the lowest water levels recorded were 6.3, 6.0, 5.0, 5.8 m in March 2007, 2008 July, 2009 August, and March 2010 respectively. The mean Bera Lake water levels obtained were 7.19, 7.6, 7.33, 6.87 m in 2007, 2008, 2009, and 2010, respectively. The annual mean water level fluctuation in Bera Lake has been 2.7 m since 2007. Available data are reliable except for a short period of time which a huge flood event that has happened in the December, 2007, when water level has dramatically rose 11 m and whole wetlands and open waters of catchment has been drowned. This significant event is not recorded in that available data and reports due to its intense destructive effects.

2.2.2 Bathymetry

Bathymetric map is an essential geo-spatial character of lakes and reservoirs which illustrates bed morphology and provides signiﬁcant information about study area especially sampling site selection and sedimentary sub-basins. Bed morphology is vital information for core sampling and evaluation of sedimentary processes of basin. Trap efﬁciency of reservoirs and lakes is another important parameter that could be achievable using bathymetric map. Bathymetric map is another geo-spatial data gap in Bera Lake although the AWB implemented multidisciplinary projects (DANCED 1998) in order to complete geo-spatial data in study area.

2.2.2.1 Hydrographic Operation

Although Bera Lake nominated as the ﬁrst RAMSAR site in Malaysia 1994, but hydrographic surveying has been not performed before this research. As a result, a comprehensive hydrographic operation was designated to survey bed morphology in order to provide require information for further studies. The most efﬁcient horizontal positioning method is meter-level, code phase DGPS or private provider networks. Alternately, electronic total stations may be used for small lake or impoundment basins; however, this may require locating or establishing additional horizontal control points around the basin, adding considerable time and cost to the survey. Kertau RSO Malay Meter Projection System has been used as horizontal positioning projection system in horizontal positioning system. The best bathymetric scale of 1:500 or 20 20 m network has been applied to make best density of coverage in the hydrographic operation. The package of horizontal positioning 2.2 Lake Characteristic 35

Fig. 2.27 Bera Lake water level ﬂuctuations since 2007 36 2 Bera Lake

Fig. 2.28 Bera Lake cross section and bed morphology records in this research involved 1,000 points as well as 300 point of shoreline records. Vertical surveying in hydrographic operation was designed based on capability of available Echosounder Garmin 400C (Fig. 2.28). Depth accuracy of such Echosounder is 10 cm. Depth correlation refers to the BM (benchmarks) datum, is necessity procedure for preparing a topographical and bathymetric seam- less map. This procedure was implemented by correlation of depth records with the nearest reported datum in the digital topographic maps of 1:25,000 scale (Series L8028). Figure 2.28 depicts Bera Lake bed morphology, non-uniform bed surface and several troughs and obstacles especially at northern part of open water. Maximum depth was recorded 7 m at center middle of open water and along the main channel. Bera Lake bathymetric map (Fig. 2.29) showed appropriately sedimentary sub-basins in different parts of Bera Lake. Several distributaries represents shallow zone with depths of 0–1 m. Probably these branches are water storages with high capacity for wet seasons and have directly connected to wetlands, forest swamps, and reed swamps. Bera Lake volume or storage capacity was calculated 2,995,998 m3 (~3 km3) according to Eq. (2.1) in which sum of two sequential depth interval areas divided on 2 and multiply to depth difference between two surfaces (ΔE ¼ 1m).

1= ðÞþ V ¼ 2HA1 A2 ð2:1Þ

Bera Lake trap efﬁciency was calculated based on Eqs. ((2.2), and (2.3)).

V Δτ ¼ ð2:2Þ Q 2.2 Lake Characteristic 37

Fig. 2.29 Bathymetric map of Bera Lake (accuracy1:500)

0:05 TE ¼ 1 pffiffiffiffiffi ð2:3Þ Δτ

Where V is storage capacity (km3) and Q is discharge at the mouth of basin (km3 a1) and Δτ is residence time of basin, and TE is trap efﬁciency. According to seasonal hydrological surveys, annual water and sediment discharge into the Bera Lake were calculated to be 24.2 (km3 a1) and 2,042.58 (t a1), respectively. Application of Eqs. (2.2), and (2.3) residence time and trap efﬁciency of Bera Lake 38 2 Bera Lake

Table 2.4 Water quality characters of Pos Iskandar open water (IBP 1972) Depth (m) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ph 4.8 4.9 4.7 5.0 4.8 5.0 5.1 5.0 4.8 4.9 4.8 4.8 Transparency (m) 1.2 1.5 1.6 1.7 2.0 1.9 2.1 1.8 2.7 2.5 2.2 2.1 Do (mg/L) 1.1 1.3 1.5 1.3 1.7 2.0 2.4 2.7 2.3 2.3 2.3 1.7 obtained were 0.124 (year) and 86 %, respectively. Results show that Bera Lake is still capable to capture a large amount of sediments that are distributed into the basin. As a result, the annual sediment accumulation rate in Bera Lake could be 1,756.6 t. According to submerged density of the uppermost layer of Bera Lake sediment proﬁle, annual accumulation rate could be 12,547.14 m3. In conclusion, the relative sedimentation rate based on the 1,126,315 m2 of Bera Lake area can be estimated 1.11 cm/year.

2.2.3 Water Quality

Inland fresh water bodies play an important role in human, animals, and aquatic lives and has recognized as source of water for drinking and several activities like ﬁshery, recreation, agriculture, industry, and navigation. Bera Lake is the largest natural fresh water reservoir in Malaysia and has vital environmental and ecological importance for human and wild lives. However, long-term water quality has not recorded in BLC. In addition, few records of water quality by RAMSAR site directory staff in the some cross sections along the Bera Lake are reported but not published. The most reliable water quality report has published by Malaysian-Japanese committee prior to land development projects (IBP 1972). This water quality analysis revealed that the area of open water adjacent to Pos Iskandar at the center of catchment is degraded. The brief available results presented in Table 2.4. 2 1 +1 According to IBP (1972) the mean TN, NO3 ,NO2 ,NH4 and organic nitrogen 1 have been 1.12, 0.11, 0.008, 0.33, and 0.58 mg L , respectively. The mean PO4 concentration was reported 0.021 (0.00–0.065). The ratio of reactive to un-reactive phosphorus has been 1/21 on the average.

2.2.3.1 In-Situ Water Quality Recording

Evaluate of available data about Bera Lake water quality showed that most of published reports about water quality were back dated to 1972, by Malaysian- Japanese committee (IBP 1972) prior to FELDA land development projects. Pres- ently, the directory of RAMSAR site has been taken water samples from 5 stations. Many attempts to access to the resultant data were not successful. 2.2 Lake Characteristic 39

Fig. 2.30 Surveying of Bera Lake water qualities by Hydrolab DS5 apparatus

As a result, lack of reliable water quality information especially previous land development projects have encouraged to conduct Bera Lake water quality assessment comprehensively. In quality surveying was implemented using calibrated fully automated Hydrolab DS 5 USA (Fig. 2.30). Eleven parameters include temperature (C), depth of sampling (m), salinity (ppt), Turbidity (NTU), TDS 1 +1 1 2 1 1 1 (mg L ), pH, NH4 (mg L ), NO3 (mg L ), Cl (mg L ), LDO (mg L ), DO (mg L1) and EC (mS cm1) were recorded at three levels of 0.2, 0.5, and 0.8 water depth. In-situ water quality was recorded in the 100 100 m network and is also based on the morphology of open waters. The mean value of water quality characters are presented in Tables 2.4, 2.5 and graphical distribution of some important parameters are illustrated in Figs. 2.31, 2.32, 2.33, 2.34, 2.35, 2.36,and2.37. National Water Quality Standards for Malaysia (NWQS) (DOE 2006) and Water Quality Index (Brian 2010) were used to evaluate Bera Lake quality (Table 2.6). Overall classification of Bera Lake water quality before and after land development project is classified IV and V which is suitable for irrigation only and requires extensive treatment for drinking. Water temperature is one of climate effects parameters which significantly affects kinds of aquatic life, regulate the maximum DO value of water, and influences the rate of chemical and biological reactions. Seasonal water temperature dictate organism age and life stage and higher biological and chemical reactions expect in the higher water temperature (Brian 2010). In-situ water analyzes showed that Bera Lake mean water temperature is same as Malaysia mean temperature and expects that the mean annual Bera Lake water temperature variation is less than 5 C. In other word, annual Bera Lake chemical and biological reactions happening in limited variation and seasonal water quality represents minor differences. Vertical water quality analysis has revealed a clear stratification in Bera Lake 1 2 water profile in terms of temperature, DO, Cl ,NO3 , pH, and EC parameters. Clear downward reduction of DO in Bera Lake water profile indicates effects of temperature. Maximum coefficient of variation of 0.5 was obtained for vertical variation of DO. Dissolved oxygen was appeared with different concentration in 40 Table 2.5 Bera Lake in-situ water quality sampling results + Station Temp Sal TDS Turb pH NH4 NO3 Cl LDO% LDO SpCond no. (C) (ppt) (mg L 1 ) NTUs units (mg/L–N) (mg/L–N) (mg L 1 ) Sat (mg L 1 ) (mS cm 1 ) 1 28.9 0.000 23.20 1,000 5.13 0.40 0.38 2.90 29.2 2.25 36.23 2 29.1 0.000 23.18 1,000 5.18 0.35 0.58 3.39 31.9 2.45 36.25 3 29.5 0.000 23.20 1,000 5.29 0.28 0.68 3.55 33.8 2.58 36.23 4 28.7 0.000 22.97 1,000 5.88 0.33 0.38 4.16 28.0 2.17 35.90 5 28.8 0.000 23.13 1,000 5.41 0.28 0.55 4.00 30.4 2.34 36.03 6 28.8 0.000 23.10 1,000 5.37 0.27 0.69 3.77 29.7 2.29 36.03 7 28.8 0.000 23.07 1,000 5.32 0.28 0.74 3.32 28.2 2.17 36.03 8 29.3 0.003 23.73 1,000 5.39 0.31 0.78 3.12 36.1 2.77 37.17 9 29.0 0.000 23.57 1,000 5.34 0.30 0.81 3.08 22.2 1.71 36.83 10 29.1 0.000 23.27 1,000 5.39 0.29 0.78 3.13 28.9 2.22 36.33 11 28.9 0.003 23.63 1,000 5.48 0.27 1.12 3.46 28.4 2.18 36.93 12 29.1 0.007 29.67 667 5.54 0.41 1.58 3.92 24.4 1.87 36.70 13 29.0 0.000 23.03 1,000 5.44 0.26 1.29 3.43 34.5 2.65 35.93 14 28.9 0.000 23.30 1,000 5.44 0.23 1.63 3.74 28.8 2.21 36.48 15 28.9 0.000 23.10 1,000 5.48 0.23 1.39 3.90 34.6 2.65 36.03 16 28.9 0.000 23.03 1,000 5.42 0.23 1.42 3.73 32.6 2.51 35.97 17 28.9 0.000 23.03 1,000 5.36 0.23 1.59 3.49 31.0 2.38 36.10 18 28.8 0.000 23.03 1,000 5.37 0.24 1.48 3.58 31.9 2.46 36.00 19 29.0 0.000 23.00 1,000 5.31 0.24 1.49 3.32 33.8 2.60 35.97 20 29.0 0.000 23.23 1,000 5.34 0.25 1.63 3.26 34.3 2.64 36.47 21 28.6 0.000 23.17 1,000 5.38 0.25 1.71 3.15 27.0 2.08 36.17 22 28.9 0.000 23.10 1,000 5.38 0.22 1.57 3.79 28.3 2.18 36.10 23 28.9 0.000 23.07 1,000 5.32 0.23 1.58 3.29 31.5 2.43 36.00 Lake Bera 2 24 28.9 0.000 22.97 1,000 5.42 0.21 2.01 4.43 32.5 2.50 35.93 25 28.9 0.000 23.08 1,000 5.43 0.22 1.78 3.76 32.8 2.53 36.08 26 28.9 0.000 23.07 1,000 5.37 0.23 1.63 3.60 32.6 2.51 36.03 27 28.8 0.000 22.93 1,000 5.35 0.24 1.40 3.11 28.3 2.18 35.80 . aeCaatrsi 41 Characteristic Lake 2.2 28 28.8 0.000 23.33 1,000 5.39 0.25 1.68 3.28 23.7 1.83 35.87 29 29.0 0.003 24.73 1,000 5.40 0.29 1.82 3.58 29.1 2.23 38.70 30 29.0 0.000 23.07 1,000 5.34 0.23 1.72 3.52 29.3 2.25 35.97 31 28.9 0.000 23.03 1,000 5.45 0.22 1.64 3.56 32.0 2.47 36.03 32 26.6 0.007 26.17 1,000 5.66 0.31 1.45 2.88 25.9 2.07 52.30 33 27.1 0.000 23.80 1,000 5.47 0.34 1.19 2.47 31.6 2.50 37.15 34 28.9 0.000 23.03 1,000 5.58 0.23 1.46 3.46 36.8 2.84 35.97 35 29.0 0.000 23.10 1,000 5.42 0.19 1.99 3.88 31.4 2.42 36.10 36 29.0 0.000 22.93 1,000 5.32 0.26 1.65 3.00 32.4 2.49 35.87 37 28.8 0.003 24.73 1,000 5.42 0.24 2.27 4.07 27.8 2.14 38.33 38 29.0 0.000 22.90 1,000 5.37 0.26 1.79 3.30 34.0 2.61 35.87 39 28.8 0.003 25.63 1,000 5.43 0.24 2.61 3.43 26.5 2.04 39.43 40 29.1 0.000 22.87 1,000 5.38 0.25 2.00 3.00 36.4 2.80 35.93 41 29.0 0.000 23.10 1,000 5.37 0.25 1.91 3.04 27.7 2.13 36.13 42 29.1 0.000 23.10 1,000 5.34 0.26 1.57 2.74 34.5 2.64 36.10 43 28.9 0.000 23.13 1,000 5.36 0.25 1.63 3.11 29.0 2.23 36.17 44 29.0 0.000 23.07 1,000 5.39 0.24 1.89 3.29 34.0 2.61 36.00 45 29.1 0.000 23.10 1,000 5.33 0.26 1.65 2.60 32.9 2.53 36.10 46 29.0 0.000 23.17 1,000 5.33 0.26 1.53 2.75 27.9 2.15 36.17 47 28.9 0.000 23.17 1,000 5.27 0.25 1.67 2.85 28.9 2.22 36.23 48 29.4 0.000 23.02 1,000 5.33 0.23 1.93 3.07 37.7 2.88 35.92 49 29.4 0.003 24.47 1,000 5.47 0.26 2.13 3.32 29.5 2.24 38.23 50 29.3 0.000 23.20 1,000 5.40 0.32 2.07 2.74 35.2 2.69 36.23 51 29.2 0.000 23.10 1,000 5.31 0.25 1.88 2.93 35.1 2.69 36.10 28.9 0.001 23.47 993 5.39 0.26 1.49 3.36 30.9 2.38 36.68 1.75 42 2 Bera Lake

Fig. 2.31 Situation of DO (mg L1) in Bera Lake

Bera Lake (Fig. 2.31) as well as its variation with depth. The lowest DO values were recorded at the south and northeast open waters which probably have a weak water circulation and partially restricted by some plant species such as Pandanus. These areas were recognized as the worst locations for biological activities. The mean Do 2.2 Lake Characteristic 43

Fig. 2.32 EC (mS cm 1) of water in Bera Lake value obtained was 2.38 mg L1 may adversely affect the functioning and survival of biological communities. The microbial activity (respiration) has enhanced during the degradation of the organic and nutrients rich waste water, resulted in DO values reduction (Chapman and Kimstach 1996). 44 2 Bera Lake

Fig. 2.33 TDS (mg L 1) levels in Bera Lake

Figure 2.34 depicts that Bera Lake water is moderately homogenous in terms of electrical conductivity and total dissolved solid except at northwest part or Kelantong water entry point. A signiﬁcant correlation between distribution of TDS and EC values was revealed in Bera Lake. Minimum variations in EC and TDS values were recorded in vertical water proﬁle. Dramatic increment of EC and TDS 2.2 Lake Characteristic 45

Fig. 2.34 Distribution of water acidity (pH) in Bera Lake should implication of polluted water (Chapman and Kimstach 1996). In addition, semi-closed open waters and reed swamp at northwest of Bera Lake represents high evaporation and increase of total dissolved solid as well as electrical conductivity. The acidity of water depends on the strong mineral acids, weak acids such as carbonic, humic and fulvic, and hydrolyzing salts of metals (e.g. iron, aluminum), 46 2 Bera Lake

2 1 Fig. 2.35 NO3 (mg L ) levels in Bera Lake as well as strong acids. Bera Lake represents acidic condition with the mean average of 5.39. In such condition bottom-dwelling decomposing bacteria begin to die off and leaf litter and dead plant and animal materials begin to deposition. With regards to heavy metals, the degrees to which they are soluble usually 2.2 Lake Characteristic 47

Fig. 2.36 Ammonium (mg L1) levels in Bera Lake determine their toxicity. The lower the pH, the more toxic the metal as they are more soluble then. Solubility refers to the amount that can be dissolved in water (Chapman and Kimstach 1996). Slightly downward increase having CV of 0.02 in water acidity is observed at Bera Lake. Distribution of acidity in Bera Lake is uniform except at the southern and northern part and at sediment entry points while slightly increased at eastern of the south of basin. A clear correlation between pH and EC was obtained at the south 48 2 Bera Lake

Fig. 2.37 Chloride (mg L1) levels in Bera Lake of Bera Lake, which indicate an efﬂuent plum or discharge into the open water. Similar to DO, increase of acidity at surface water has controlled by higher temperature and photosynbook. 2 Another parameter which represents Bera Lake water quality was NO3 which is the common form of combined nitrogen found in natural waters. Natural sources 2 of NO3 to surface waters include igneous rocks, land drainage and plant and 2.2 Lake Characteristic 49

Table 2.6 Bera Lake water quality that obtained based on NWQS and WQI guidelines Parameter WQI Sampling Salinity TDS pH No3 Cl DO EC Turbidity Brain 2010 DOE 2006 IBP1972 – – III V – IV – II 39 41 Current study I I IV V I IV III IIA Very bad Polluted

2 1 2 animal debris. In lakes, concentrations of NO3 in excess of 0.2 mg L NO3 tend to stimulate algal growth and indicate possible eutrophic conditions (Chapman and Kimstach 1996). 2 1 The mean average of NO3 was obtained to be 1.49 mg L which is indicator of a moderate eutrophication in Bera Lake. Chapman and Kimstach (1996) stated that land clearing and plough for cultivation has increased soil aeration, resulted in 2 enhancement of nitrifying bacteria action and production of soil NO3 . Further- more, burning of felled tress has been released a large amount of nitrogen especially after the first heavy raining to the sink areas. Both mechanisms have happened in BLC since 1972 in which half of study area cleared, disturbed and felled tress 2 burned. The most concentration of NO3 was recorded at one of semi-closed open waters at northwest of Bera Lake. The rest of lake represents an acceptable range between 0.4 and 1.9 mg L1. Bera Lake water column was appeared stratified 2 and upward increasing in NO3 concentration is dominated. According to Chap- man and Kimstach (1996) natural occurrence of ammonia in water bodies promoting from the breakdown of nitrogenous organic and inorganic matter in soil and water, excretion by biota, reduction of the nitrogen gas in water by micro-organisms and from gas exchange with the atmosphere. The mean average of ammonia was obtained to be 0.26 mg L1. Bera Lake water profile represents clear reduction downward in ammonia with a coefficient of variation 0.51 in which ammonia value deplete two times with depth. Chapman and Kimstach (1996) stated that ammonia plays an important role in creation of toxic condition for aquatic life and being detrimental for the ecological balance of open waters at certain pH levels. Higher concentration of ammonia and pH is observed at surface water in the Bera Lake. The mean average value of ammonia content is an indication of organic pollution by agriculture or industrial sewages, and fertilizer run-off at BLC area. Chlorine enters surface waters with the atmospheric deposition of oceanic aero- sols, by the weathering of some sedimentary rocks (mostly rock salt deposits) and from industrial and sewage effluents, and agricultural and road run-off (Chapman and Kimstach 1996). Minimum Cl value was recorded at the south water entry point and at the departure point of Bera Lake. Conversely, the highest value of Cl was obtained at the north open water especially at the end of connection channel. There is vivid increment downward in Cl concentration with coefficient of 2 variation of 0.25. Probably downward increasing of Cl and NO3 are two active ions in Bera Lake water column, which points out a significant correlation with anoxic condition and lowest DO. 50 2 Bera Lake

2.2.4 Physical Properties of Bera Lake Sediment

Physical properties of a lake can talk properly about current and long-term physical condition of depositional system. Sediments in all sedimentary media involves signature of natural events and anthropogenic changes in source and sink areas. Bera Lake as other fresh water lakes around the world has experienced several changes in sediments physical properties over the last decades (Malmer 1990). Grain size distribution, bulk density, moisture, soil, and porosity contents, soil and sediment classification are physical properties which have been determined in this research. Detailed physical properties of Bera Lake sediment column represented by 300 subsamples which were analyzed in depth intervals of 2 0.2 cm. These samples were Grain size distribution diagrams and calculation of statistical parameters were achieved by GRADISTAT, Version 6.0 (Blott and Pye 2001). The program is best suited to analyze data obtained from sieve or laser granulometer analysis. For this purpose, the mass or percentage of sediment retained on sieves spaced at intervals, or the percentage of sediment detected in each bin of a Laser Granulometer was transferred to GRADISTAT. The following sample statistics are then calculated using the Method of Moments: mean, mode(s), sorting (standard deviation), skewness, kurtosis, D10,D50,D90,D90/D10,D90-D10,D75/D25 and D75-D25. Grain size parameters are calculated arithmetically and geometrically (in microns) and loga- rithmically (using the phi scale) (Krumbein and Pettijohn 1983). Linear interpolation was also used to calculate statistical parameters by the graphical method (Folk and Ward 1957) and derive physical descriptions (such as “very coarse sand” and “moderately sorted”). The program also provides a physical description of the textural group which the sample belongs to and the sediment name (such as “fine gravelly coarse sand”) after Folk (1954). Table that gives the percentage of grains falling into each size fraction, modified from Udden (1914) is also included. In terms of graphical output, the program provides graphs of the grain size distribution and cumulative distribution of the data in both metric and phi units, and was displayed the sample grain size on triangular diagrams. Consequently, five distinct layers were identified in the first 1 m thickness of Bera Lake sediment profile (Fig. 2.38). These layers with different thickness differentiated along all cores or at whole lake area. The identified layers have been confirmed after analysis of subsamples for grain size, bulk density, porosity, and organic matters. Description of Bera Lake physical properties have continued by introducing of stratigraphic layers of sediment column. Core 7 recognized as master core to analyze grain size distribution in Bera Lake sediment column. Additionally, some samples from individual layers of Cores 5 and 6 were analyzed as control samples in order to verify the results of master core. Core 7 is the longest among the all collected cores which have taken from Bera Lake. Detailed grain size distribution and relevant statistical parameters for each sample presented in Fig. 2.39 and Table 2.6. Bulk density and porosity are inevitable physical 2.2 Lake Characteristic 51

Fig. 2.38 Stratigraphic layers of Bera Lake sediment proﬁle

Fig. 2.39 Grain size distributions along the master core 7 properties of sediments in a sedimentological study of each basin. Bulk density is necessary for estimation of sedimentation rate using radioisotopes techniques (Appleby and Oldﬁeld 1978). 52 2 Bera Lake

Minerals and coarse grain particles contribute in increase of bulk density. However, ﬁne grain size sediments, organic matters and porosity cause to decrease bulk density values. Therefore, bulk density and porosity used as indicators of environmental changes which have occurred over the past decades in BLC. Vari- ations of bulk density and porosity values with depth have presented in Figs. 2.40 and 2.41, respectively (Table 2.8).

2.2.4.1 Sediment Layers Stratigraphy

The first layer from base in Bera Lake sediment profile is gray mud with 20 cm. Consequently, five distinct layers were identified in the first one meter thickness of Bera Lake sediment profile (Fig. 2.38). These layers with different thickness differentiated along all cores or at whole lake area. The identified layers have been confirmed after analysis of subsamples for grain size, bulk density, porosity, and organic matters. Description of Bera Lake physical properties have continued by introducing of stratigraphic layers of sediment column. Core 7 recognized as master core to analyze grain size distribution in Bera Lake sediment column. Additionally, some samples from individual layers of Cores 5 and 6 were analyzed as control samples in order to verify the results of master core. Core 7 is the longest among the all collected cores which have taken from Bera Lake. Detailed grain size distribution and relevant statistical parameters for each sample presented in Table 2.7. Bulk density and porosity are inevitable physical properties of sediments in a sedimentological study of each basin. Bulk density is necessary for estimation of sedimentation rate using radioisotopes techniques (Appleby and Oldfield 1978).

2.2.4.1.1 Gray Mud to Sandy Mud (Layer 1)

The first layer from base in Bera Lake sediment profile is gray mud with 20-cm average thickness. Maximum thickness was recorded in Cores 1 and 8. Layer 1 overlaying white sandy mud is considered as substrate in the present study. It was recognized that muddy texture with clay, silt and sand size grains has contributed at an average of 18 2.5, 35 1.7, and 48 2.5 %, respectively. Contribution of clay mineral in layer 1 at the middle and the north of Bera Lake sediment column decreased to 10 % while silt size grains portion has been increased to 62 %. Mean grain size represents coarse to very coarse silt with a very poorly sorted texture. Layer 1 at the south of Bera Lake is composed of polymodal sediments while it comprises unimodal sediments at the middle and the north of study area. Its cumulative curve skewed to fine grains and which illustrate its platykurtic to mesokurtic shape. Grain size description of cores indicates existence of roots, barks, and charcoals in some sub-layers. The highest lithogenic content in layer 1 caused an increase of bulk density to 2.57 g cm3 in Core 10. This value calculated to be 1.58, 1.47, 1.4 g cm3 in layer 1 at cores 2, 7, and 5, respectively. Porosity 2.2 Lake Characteristic 53

Fig. 2.40 Northward bulk density variations in Bera Lake sediment proﬁle 54 2 Bera Lake

Fig. 2.41 Northward porosity variations in Bera Lake sediment proﬁle 2.2 Lake Characteristic 55

Table 2.7 (a)–(g) Sediment size distribution in master core 7 and statistical parameters 7-1 7-3 7-5 (a) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Polymodal, very Polymodal, very Polymodal, very parameters poorly sorted poorly sorted poorly sorted Textural group: Sandy mud Sandy mud Sandy mud Sediment name: Coarse sandy mud Coarse sandy Coarse sandy very coarse very coarse silt silt Folk and ward Mean ðÞxa : 5.392 4.946 4.965 method (f) Sorting (σI): 3.956 3.589 3.612 Skewness (SkI): 0.211 0.200 0.199 Kurtosis KG: 0.719 0.728 0.722 Folk and ward Mean: Coarse silt Very coarse silt Very coarse silt method Sorting: Very poorly sorted Very poorly Very poorly (Description) sorted sorted Skewness: Fine skewed Fine skewed Fine skewed Kurtosis: Platykurtic Platykurtic Platykurtic Mode (mm) Mode 1 (mm): 816.5 816.5 816.5 Mode 2 (mm): 0.985 0.985 152.176 Mode 3 (mm): 8.359 1.558 0.985 Grain size % Gravel: 0.0 0.0 0.0 % SAND: 43.4 45.9 45.8 % MUD: 56.6 54.1 54.2 7-7 7-9 7-10 (b) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Polymodal, very Polymodal, Very Trimodal, very parameters poorly sorted Poorly Sorted poorly sorted Textural group: Sandy mud Sandy mud Muddy sand Sediment name: Coarse sandy Coarse sandy very Very coarse silty very coarse coarse silt coarse sand silt Folk and ward Mean ðÞxa : 4.898 4.974 4.647 method (f) Sorting (σI): 3.607 3.601 3.600 Skewness (SkI): 0.217 0.200 0.301 Kurtosis KG: 0.726 0.732 0.771 Folk and ward Mean: Very coarse silt Very coarse silt Very coarse silt method Sorting: Very poorly Very poorly Very poorly (Description) sorted sorted sorted Skewness: Fine skewed Fine skewed Very ﬁne skewed Kurtosis: Platykurtic Platykurtic Platykurtic Mode (mm) Mode 1 (mm): 1.0 177.3 816.5 Mode 2 (mm): 8.359 0.985 0.985 Mode 3 (mm): 11.345 9.738 3.895 Grain size % Gravel: 0.0 0.0 0.0 % SAND: 46.7 45.6 51.0 % MUD: 53.3 54.4 49.0 (continued) 56 2 Bera Lake

Table 2.7 (continued) 7-12 7-15 7-17 (c) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Trimodal, very Unimodal, very Unimodal, very parameters poorly sorted poorly sorted poorly sorted Textural group: Muddy sand Sandy mud Sandy mud Sediment name: Very coarse silty Very fine sandy Very fine sandy coarse sand very coarse very coarse silt silt Folk and ward Mean ðÞxa : 4.110 6.023 6.100 method (f) Sorting (σI): 3.458 2.311 2.211 Skewness (SkI): 0.396 0.276 0.283 Kurtosis KG: 0.860 1.050 1.055 Folk and ward Mean: Very coarse silt Medium silt Medium silt method Sorting: Very poorly Very poorly Very poorly (Description) sorted sorted sorted Skewness: Very fine Fine skewed Fine skewed skewed Kurtosis: Platykurtic Mesokurtic Mesokurtic Mode (mm) Mode 1 (mm): 816.5 44.8 38.5 Mode 2 (mm): 0.985 Mode 3 (mm): 3.344 Grain size % Gravel: 0.0 0.0 0.0 % SAND: 58.7 16.9 13.8 % MUD: 41.3 83.1 86.2 7-19 7-21 7-23 (d) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Unimodal, very Unimodal, very Unimodal, very parameters poorly sorted poorly sorted poorly sorted Textural group: Sandy mud Sandy mud Sandy mud Sediment name: Very fine sandy Very fine sandy Very fine sandy very coarse very coarse very coarse silt silt silt Folk and ward Mean ðÞxa : 5.325 5.218 5.246 method (f) Sorting (σI): 2.335 2.270 2.303 Skewness (SkI): 0.281 0.290 0.288 Kurtosis KG: 1.109 1.108 1.089 Folk and ward Mean: Coarse silt Coarse silt Coarse silt method Sorting: Very poorly Very poorly Very poorly (Description) sorted sorted sorted Skewness: Fine skewed Fine skewed Fine skewed Kurtosis: Mesokurtic Mesokurtic Mesokurtic Mode (mm) Mode 1 (mm): 44.8 52.2 52.2 Mode 2 (mm): Mode 3 (mm): Grain size % Gravel: 0.0 0.0 0.0 % SAND: 29.4 31.0 31.2 % MUD: 70.6 69.0 68.8 (continued) 2.2 Lake Characteristic 57

Table 2.7 (continued) 7-25 7-27 7-29 (e) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Unimodal, very Bimodal, very Unimodal, very parameters poorly sorted poorly sorted poorly sorted Textural group: Sandy mud Sandy mud Sandy mud Sediment name: Very fine sandy Very fine sandy Very fine sandy very coarse very coarse very coarse silt silt silt Folk and ward Mean ðÞxa : 5.198 6.096 5.239 method (f) Sorting (σI): 2.379 2.452 2.505 Skewness (SkI): 0.350 0.325 0.325 Kurtosis KG: 1.120 0.958 1.035 Folk and ward Mean: Coarse silt Medium silt Coarse silt method Sorting: Very poorly Very poorly Very poorly (Description) sorted sorted sorted Skewness: Very fine skewed Very fine skewed Very fine skewed Kurtosis: Leptokurtic Mesokurtic Mesokurtic Mode (mm) Mode 1 (mm): 60.9 52.2 60.9 Mode 2 (mm): 0.459 Mode 3 (mm): Grain size % Gravel: 0.0 0.0 0.0 % SAND: 33.8 18.8 34.7 % MUD: 66.2 81.2 65.3 7-31 7-33 7-35 (f) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Unimodal, very Unimodal, very Unimodal, very parameters poorly sorted poorly sorted poorly sorted Textural group: Sandy mud Sandy mud Sandy mud Sediment name: Very fine sandy Very fine sandy Very fine sandy very coarse very coarse very coarse silt silt silt Folk and ward Mean ðÞxa : 5.309 5.087 5.437 method (f) Sorting (σI): 2.436 2.386 2.422 Skewness (SkI): 0.319 0.346 0.322 Kurtosis KG: 1.064 1.073 1.038 Folk and ward Mean: Coarse silt Coarse silt Coarse silt method Sorting: Very poorly Very poorly Very poorly (Description) sorted sorted sorted Skewness: Very fine skewed Very fine skewed Very fine skewed Kurtosis: Mesokurtic Mesokurtic Mesokurtic Mode (mm) Mode 1 (mm): 52.2 70.9 52.2 Mode 2 (mm): Mode 3 (mm): Grain size % Gravel: 0.0 0.0 0.0 % SAND: 32.1 36.9 29.9 % MUD: 67.9 63.1 70.1 (continued) 58 2 Bera Lake

Table 2.7 (continued) 7-37 7-39 7-40 (g) Sediment size distribution in master core 7 and statistical parameters Sample statistics Sample type: Unimodal, Unimodal, Unimodal, parameters poorly sorted poorly sorted poorly sorted Textural group: Muddy sand Muddy sand Muddy sand Sediment name: Very coarse silty Very coarse silty Very coarse silty fine sand fine sand fine sand Folk and ward Mean ðÞxa : 3.777 3.657 3.739 method (f) Sorting (σI): 1.920 1.730 1.703 Skewness (SkI): 0.321 0.371 0.346 Kurtosis KG: 1.123 1.046 1.051 Folk and ward method Mean: Very fine sand Very fine sand Very fine sand (Description) Sorting: Poorly sorted Poorly sorted Poorly sorted Skewness: Very fine Very fine Very fine skewed skewed skewed Kurtosis: Leptokurtic Mesokurtic Mesokurtic Mode (mm) Mode 1 (mm): 206.5 177.3 177.3 Mode 2 (mm): Mode 3 (mm): Grain size % Gravel: 0.0 0.0 0.0 % SAND: 60.0 63.9 62.0 % MUD: 40.0 36.1 38.0

Table 2.8 Mean bulk density (g cm3) of Bera Lake sediment layers Core number Layer no. 12345678910 4 0.23 0.36 0.27 0.28 0.35 0.45 0.20 0.27 0.40 1.09 3 0.88 1.01 0.71 0.40 0.88 1.16 0.75 0.73 0.32 1.37 2 0.78 1.18 0.58 0.85 1.40 1.06 0.52 0.88 0.41 2.12 1 1.58 0.90 1.20 NR 1.40 0.87 1.47 0.53 NR 2.57 Base NR NR NR NR NR 0.99 1.47 NR NR NR NR Not recorded in collected core values showed a downward decrease with depth especially in cores 1, 3, 4, 7, and Core 10. The lowest porosity value in Bera Lake sediment column calculated to be 42 and 41.5 % respectively in layer 1 of cores 7 and 10. The mean porosity value of layer 1 was obtained 75 0.06 % in studied cores.

2.2.4.1.2 Gray to Dark Sandy Mud (Layer2)

This section of sediment proﬁle with 25 cm average thickness, characterized by medium size matrix, abundance of partly decomposed roots, barks, stems, charcoal and organic debris, and gray to dark color. Lithology in Layer 2 gradually changed from grey to dark sandy mud and then to muddy sand deposits. Muddy matrix and 2.2 Lake Characteristic 59 clay size grain portion has decreased in Layer 2. Clay, silt and sand size grains have been contributed with an average of 11 2, 61 15, and 28 15 %, respectively. The mean size is comparable to coarse silt, very poorly sorted texture and platykurtic shape of cumulative curve. Bulk density in the most of studied cores was reduced because of organic contamination especially in Cores 1, 3, 4, 7, 8, and 9. Minimum, maximum and average of bulk density in Layer 2 was calculated to be 0.41, 2.12, and 0.98 0.5 g cm3, respectively. The minimum, maximum, and mean porosity values for layer 2 calculated to be 69.83, 79.53, and 76 0.06 % respectively. The maximum porosity in Layer 2 observed in Cores 9, 4, 1, and 7 which are in positive correlation with the lowest bulk density values.

2.2.4.1.3 White Sandy Mud (Layer 3)

Erosion-induce deposits accumulated in Bera Lake as white sandy mud sediments in Layer 3 during and after maximum deforestation activities. It overlaid on Layer 2 with a sharp contact. Contribution of silt size grains was increased to 58 5% while clay and sand portions were reduced to 11 2 and 32 7 % on the average. Although, analyzed samples in this layer represent a mesokurtic and unimodal cumulative curve, but they are very poorly sorted sediments. The mean grain size is in the range of coarse silt and the sedimentological name is very ﬁne sandy very coarse silt. Analyzed samples from same layer in Core 5 and 6 represented similar kind of statistic parameters. Contribution of clay, silt and sand size grains at the middle and north of study area were calculated to be 15, 68, and 17 %, respectively. A remarkable charcoal horizon was recognized at lower contact of Layer 3, signals of maximum land preparation by burning of fallen trees. This horizon has significantly reduced bulk density values to 0.5 g cm3 in Cores 1, 4, and 9. Lithogenic contents in Layer 3 have contributed to increase bulk density especially in Cores 1, 3, 6, and 7. Minimum, maximum and mean bulk density values in Layer 3 calculated to be 0.32, 1.37, and 0.82 0.31 g cm3, respectively. Scatter roots, barks, charcoals were found along this layer. The highest porosity of Layer 3 was observed in Cores 4, 9, 5 and 6. These cores seem to be more contaminated by organic matters than others. The maximum, minimum, and mean porosity values for white sandy mud layer calculated to be 91, 72, and 78 0.07 %, respectively.

2.2.4.1.4 Organic-Rich Deposits (Layer 4)

General upward decrease in lithogenic mineral and bulk density value has been continued with deposition of organic-rich sediments at top of Bera Lake sediment column. Layer 4 was characterized by very low matrix content, abundance of partially decomposed roots, barks, stems, charcoal and organic debris, and dark color, and 25-cm thickness of average. It overlaid on white sandy mud deposits with a gradual contact. Contribution of clay and silt size grains has reduced dramatically to 2.7 and 35.5 % of the average. Coarse grains mainly composed of organic 60 2 Bera Lake particles in different size. Therefore, this sediment represents very poorly sorted texture. Detailed organic matters include TOC and POC will present at Sect. 5.4. Minimum, maximum, and mean bulk density values in Layer 4 obtained 0.2, 1.09, and 0.39 0.25 with coefﬁcient of variation of 0.66. General upward increasing in porosity value has reach to maximum content in Layer 4. Minimum, maximum and average porosity values were calculated to be 91, 95.5, and 85 0.1 %, respectively. An interruption recorded in general upward decrease in bulk density by deposition of thin layer muddy sand sediments at the depth of 0–4 cm in all parts of Bera Lake. This Layer (5) is an indicator of a hiatus event in which catchment area ﬂooded extensively at December, 2007. This event recorded in study area after 1,200 mm continues and intense precipitation during 11 days.

References

Appleby PG, Oldfield FT (1978) The calculation of 210Pb dates assuming a constant rate of supply of unsupported 210Pb to the sediment. CATENA 5:1–8 Blott SJ, Pye K (2001) GRADISTAT: a grain size distribution and statistics package for the analysis of unconsolidated sediments. Earth Surf Process Landf 26:1237–1248. doi:10.1002/ esp.261 Brian O (2010) The water quality index, from http://www.water-research.net/watrqualindex/ waterqualityindex.htm Chapman D, Kimstach V (1996) Selection of water quality variables. In: Chapman D (ed) Water quality assessments – a guide to use of Biota, sediments and water in environmental monitoring, 2nd edn. ISBN 0 419 21590 5 (HB) 0419 21600 6 (PB) UNESCO/WHO/UNEP, p 60 http://www.who.int/water_sanitation_health/resourcesquality/wqachapter3.pdf Chee WC, Abdulla A (1998) Country pasture/forage resource profiles, Malaysia. Ministry of Agriculture Malaysia, Kuala Lumpur DANCED (1998) Wetland international Malaysia programme. Ministry of Science, Technology and the Environment. http://www.mst.dk/danced-uk/ DOE (2006) Department of Environment Malaysia, “Malaysia Environmental Quality Report 2006”. In: River water quality, Chap 3. Sasyaz Holdings Sdn Bhd, p 24. http://elib.uum.edu. my/kip/Record/u623755 Folk RL (1954) The distinction between grain size and mineral composition in sedimentary-rock nomenclature. J Geol 62:344–359 Folk RL, Ward WC (1957) Brazos River bar: a study in the significance of grain size parameters. J Sediment Petrol 27:3–26 Gravelius I (1914) Grundrifi der gesamten Gewcisserkunde. Band I: Flufikunde (Compendium of Hydrology, vol I. Rivers, in German) Goschen, Berlin Henson IE (1994) Environmental impacts of oil palm plantations in Malaysia, vol 33. Palm Oil Research Institute of Malaysia, Kuala Lumpur Horton HE (1932) Drainage basin characteristics. Trans Am Geophys Union 13:350–361 Hutchison CS, Tan DNK (2009) Geology of Peninsular Malaysia. The University of Malaya and the Geological Society of Malaysia, Kuala Lumpur IBP (1972) Research at Tasek Bera. The Malaysian IBP (PF) Subcommittee Kuala Lumpur. http:// www.ilec.or.jp/database/asi/asi-15.html#top Ismail HH, Madon M, Abu bakar ZA (2007) Sedimentology of the semantan formation (Middle– Upper Triassic) along the Karak-Kuantan Highway central Pahang. Geol Soc Malaysia Bull 55:27–34 References 61

Kirpich ZP (1940) Time of concentration in small agricultural watersheds. Civil Eng 10(6):362 Krumbein WC, Pettijohn FJ (1983) Manual of sedimentary petrography. Appleton-Century- Crofts, New York MacDonald S (1970) Geology and Mineral Resources of the Lake Chini, Sungia Bera, Sungai Jeram area of South Central Pahang. Ministry of Lands and Mines Malaysia, Kuala Lumpur Malmer A (2010) Phosphorus loading to tropical rain forest streams after clear-felling and burning in Sabah, Malaysia. Hydrogeochem Water Chem 32:2213–2220 MMD (2011) Malaysian Climate, http://www.met.gov.my/index.php?option¼com_content& task¼view&id¼75&Itemid¼1089&limit¼1&limitstart¼2 Mohamed AR (1996) Semantan formation distribution in Peninsular Malaysia. Sains Malays 25 (3):91–114 Malmer A (1990) Stream suspended load after clear-felling and different foresty treatment in tropical rainforest, Sabah, Malaysia, vol 192. International Association Hydrology Science, p 62–71 Morley RJ (1981) The palaeoecology of Tasek Bera, a lowland swamp in Pahang, West Malaysia. Singap J Trop Geogr 2(1):49–56. doi:10.1111/j.1467-9493.1981.tb00118.x Malaysian Palm Oil Council (MPOC) (2007) Palm oil, tree of life. http://www.mpoc.org.my/ pubs_view.aspx?id=7311eff0-84d9-4066-87dd-e10fa3748014 Nik AR (1988) Water yield changes after forest conversion to agricultural landuse in Peninsular Malaysia. J Trop Forest Sci 1(1):67–84 Phillips S, Bustin RM (1998) Accumulation of organic rich sediments in a dendritic fluvial/ lacustrine mire system at Tasik Bera, Malaysia: implications for coal formation. Int J Coal Geol 36(1–2):31–61 Sone M, Shafeea Leman M (2000) Some Mid-Permian fossils from Felda Mayam, Central Peninsular Malaysia. Paper presented at the Annual geological conference Kuala Lumpur Udden JA (1914) Mechanical composition of clastic sediments. Bull Geol Soc Am 25:655–744 Wu¨st RAJ, Bustin RM (2001) Low-ash peat deposits from a dendritic, intermontane basin in the tropics: a new model for good quality coals. Int J Coal Geol 46(2–4):179–206 Wu¨st RAJ, Bustin RM (2003) Opaline and Al-Si phytoliths from a tropical mire system of West Malaysia: abundance, habit, elemental composition, preservation and significance. Chem Geol 200(3–4):267–292 Wu¨st RAJ, Bustin RM (2004) Late Pleistocene and Holocene development of the interior peat- accumulating basin of tropical Tasek Bera, Peninsular Malaysia. Palaeogeogr Palaeoclimatol Palaeoecol 211(3–4):241–270 Wu¨st RAJ, Ward CR, Bustin RM, Hawke MI (2002) Characterization and quantification of inorganic constituents of tropical peats and organic-rich deposits from Tasek Bera (Peninsular Malaysia): implications for coals. Int J Coal Geol 49(4):215–249 Wu¨st RAJ, Bustin RM, Lavkulich LM (2003) New classification systems for tropical organic-rich deposits based on studies of the Tasek Bera Basin, Malaysia. CATENA 53(2):133–163 Wu¨st RAJ, Bustin RM, Ross J (2008) Neo-mineral formation during artificial coalification of low-ash mineral free-peat material from tropical Malaysia-potential explanation for low ash coals. Int J Coal Geol 74(2):114–122 Chapter 3 Sedimentation Rate in Bera Lake

Abstract The evolutionary environmental history of Bera Lake was studied using the fallout radioisotopes137Cs and 210Pb. 317Cs horizons in the all ten studied cores showed a constant rate of 210Pb supply along all distinctive layers in each core. The lithology of layers significantly affected the variation of 210Pb value with depth. The chronology of Bera Lake sediment was conducted using the Constant Rate of Supply (CRS) model. The 1963 fallout maximum 137Cs from atmospheric testing of nuclear weapons found in all selected master cores at the depth of 40 cm. The mean pre-1950 sediment accumulation rate was ranged between 0.06 0.02 and 0.16 0.2 g cm2 year1. Environmental impacts of five deforestation projects performed from 1972 to 1995 at the catchment area, contributed significantly toward increasing the sedimentation rate within Bera Lake. Besides the 137Cs horizons, the charcoal horizon at the lower contact of white sandy mud revealed the datum of maximum deforestation in the study area. 210Pb dates using the CRS model correlated historical sediment fluxes to anthropogenic changes in Bera Lake catchment area. Organic-rich sediments deposited mostly at the top of the Bera Lake sediment columns with a mean rate of 0.2 0.1 g cm2 year1 since 1994. High biomass productivity of mature oil palm plantations, which were developed in the catchment area, dictated organic-rich deposit distribution. This study highlighted capability of radioisotopes to reconstruct long-term (100–150 years) history of a natural lake at a tropical area where surrounding catchment has extensively deforested over the recent decades.

Keywords 210Pb and 137Cs radioisotopes sedimentation rate • Bera Lake • CRS model • Deforestation

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 63 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2_3, © Springer Japan 2014 64 3 Sedimentation Rate in Bera Lake

3.1 Introduction

Determination of sedimentation rate at Bera Lake is the most important objectives of present study. The main aims of this research are therefore, to estimate the historical changes of sedimentation rates at Bera Lake and to correlate dated layers to land development projects which were carried out in the catchment area. 317Cs horizons in ten studied cores marked a constant rate of 210Pb supply especially along four distinct layers. The Lithology of layers, however, affected variation 210Pb values with depth. Lithological change in four distinct layers created hiatus or severe dilution on 210Pb content in studied cores. The Bera Lake sediment chronology was determined using the CRS models. Assumptions for application of CIC model were not met in this study. An extreme mixing recognized at top of sediment column in Core 10, it had to be discarded in the interpretation of sedimentation status. Therefore, it discarded from Bera Lake interpretation of sedimentation status. There is the long history into the limnology research around the world. Paleolimnology studies also have been performed especially to reconstruct history of a lake using different methods. The sedimentological studies involve sediment transport and sedimentation rates are the most interests among limnology studies because of their importance for rebuilding history of lakes and sedimentary processes. A lake sediment column could reveal signature of several processes which have involved in sediment transport and distribution, nutrients cycle, and contamination within body of water. Besides, effects of worldwide parameter likes climate changes could be studied in a lake sediment profile. General issue with lakes is their reduction in capacity and trap efficiency due to sedimentation. This process has been repeated many times on the geological time scale, but recently caused many constraints to lake users. Sedimentation rates are measurable by traditional and new methods as hydrographic maps, in-situ surveying and physical measurements, and using isotopes tracer. Nucleons are the protons and neutrons which compose the nucleus of an atom. Normally the number of protons and neutrons in an atom are equal to each other. However, sometimes the number of protons and neutrons differ from each other. Atoms with different numbers of protons and neutrons in the nucleus are referred to as being isotopes (IAEA 2001). All the different combinations of unequal numbers of protons and neutrons are called nuclides. There are about 1,000 known nuclides. Of these, 25 % are stable and 75 % are unstable. An unstable isotope is one which seeks stability by giving off protons, neutrons, or electrons. A stable isotope does not seek stability by giving off protons, neutrons, or electrons. Ionizing radiation is produced by unstable atoms (Fig. 3.1). Unstable atoms differ from stable atoms because they have an excess of energy or mass or both. There are three different types of atomic radiation alpha (α), beta (β), and gamma (γ) (Fig. 3.2). On 16 July 1945 at 1230 Greenwich Civil Time, nuclear weapon testing was started resulting in the release of 137Cs and other radioactive nuclides into the environment (Ritchie and Ritchie 2005). Over the last 50 years after the first atomic 3.1 Introduction 65

Fig. 3.1 Types of radiation from unstable isotopes Radiation (IAEA 2001)

ionizing Non-Ionizing

Directly ionizing (Charged particles) Electrons, protons, etc.

Indirectly ionizing (Neutral particles) Photons, neutrons, etc.

Fig. 3.2 Physical properties of radionuclides (IAEA 2001) weapon test, many studies have been published on the application of radionuclides to the study of soil erosion and the subsequent redeposition of the eroded particles on the landscape. Unstable isotopes or radioisotopes most commonly used in sedimentary processes and environmental research are presented in Fig. 3.2. According to Ritchie and Ritchie (2005) more than 3,000 articles and reports on the application of only 137Cs in investigating of sedimentary processes have been published. The nature and distribution of radioisotopes have been found in Bujdoso´ (1997), Faure (1997), Robbins (1980), Jeter (1999), Smith (2001), and Smith and Amonette (2006). These references have supported this research in terms of understanding radionuclides concepts and their generations. The fundamental analytical methods for calculating radionuclide inventories in environmental samples and sediment date have been identified in several references. The IAEA (1983) has been the foremost reference in this field which is supported by recent research works especially Ebaid and Khater (2006), IAEA (1983, 2005), Benoit and Rozan (2001), Abraham et al. (2000), Holmes (1998), and Hakanson et al. (1996). Ebaid and Khater (2006) has sophistically explained and compared three analytical methods (gamma and alpha spectrometry, and beta-counting) to 66 3 Sedimentation Rate in Bera Lake detect fallout 137Cs and 210Pb radioisotopes inventory. Advantages and disadvan- tages of analytical methods and their capability to this project are to utilized gamma- spectrometry as the chosen analytical method for the research. Application of radionuclides in environmental studies especially estimations of soil erosion, sedimentation rates and historical detection of environmental changes have been studied by many researchers around the world. The literature reviewed has shown that IAEA (1983, 1995, 1998, 2001, 2005) is the former in introducing the radioisotopes capability in sediment studies. The most important identified topic in the reviewed literature is sedimentation rate in lakes and reservoirs. Severe sedimentation at Bera Lake is the main research issue and application of radioisotopes is a perfect method to calculate historical deposition trend in this lake. One third of reviewed literature exemplified application of radioisotopes in investigation of sedimentation rate. Although IAEA has been the former in the application of radioisotopes in order to estimate of sedimentation rates, the most cited reference in this field belongs to Appleby and Oldfield (1978) and his age calculation methods. In addition, Robbins (1980) and Walling (1999), Zapata and Garcia-Agudo (2000), Mabit et al. (2008a) have presented fundamental articles in this field of studies. For example, comparative advantages and limitations of the fallout 137Cs, 210Pb, and 7Be radionuclides for assessing soil erosion and sedimentation have been presented by Mabit et al. (2008b). (CIC) Constant initial concentration model (Robbins 1980) and (CRS) constant rate of supply model (Appleby and Oldfield 1978) are well known models that have been used in the published literature to calculate sediment age and sedimentation rate in lakes and other aquatic environments. Both models are based on activity of total 210Pb (supported), 226Ra, and 210Pb excess (unsupported). Total activity of 210Pb refers to both values of 226Ra, and 210Pb excess in soil or sediments. Disequilibrium between 210Pb and its parent isotope in the series, 226Ra, arises through diffusion of the intermediate gaseous isotope 222Rn (Begy et al. 2009). This gaseous phase decays to 210Pb within 10 days of its creation from radon. The 210Pb daughter removed from atmosphere by precipitation or dry falling will be immediately attracted to soil on the earth’s surface because of its high affinity to fine grained particles. In addition, 210Pb which directly falls on lake or other water bodies’ surface will be recorded in sediment column after deposition. The best sediment column age can be calculated accurately in stable basins with constant sediment supply and sedimentation. On the other hand, sedimentation rate in environments with certain environmental changes especially anthropogenic events and land use changes dominantly can be estimated by mentioned models. In an elaborate and specified article, Smith (2001) believes validation of 210Pb geochronology needed at least one independent tracer that separately provides an unambiguous time-stratigraphic horizon. In this project, 137Cs is artificial radionuclide which widely used as complementary tools to validate 210Pb geochronology. In addition to fundamental topics, numerous articles remarked in reviewed literatures discuses application of radioisotopes in estimation of sedimentation rate in lakes. Some pertinent reviewed articles in this field include Ariztegui et al. (2010), Flower et al. (2009), Hughes et al. (2009), Sidle (2009), Putyrskaya 3.2 Modeling 67 and Klemt (2007), Arnaud et al. (2006), Bonotto and de Lima (2006), Mazˇeika and Taminskas (2005), McKee et al. (2005), Ruiz-Fernandez et al. (2005), Pfitzner et al. (2004), Eriksson et al. (2004), Abril (2003), Lu (2004), Guevara and Arribe´re (2002), and Benoit and Rozan (2001). These references in fact are several case studies which have emphasized the importance of method and thus encouraged its use in the present project to estimate sedimentation rate in Bera Lake.

3.2 Modeling

Application of radioisotopes to date lake sediments of some 100–150 years old is one of the most common methods (IAEA 1983). Goldberg (1963) and Krishnaswami et al. (1971) were formers to introduce this valuable method. Dating of sediment profiles in lakes using 210Pb is the more acceptable method where the accretion rate is relatively constant throughout the given time period. In such lakes, the concentration of 210Pb exponentially decreases with depth at a rate that is inversely proportional to the sedimentation rate. This assumption has been commonly used in the Constant Initial Concentration (CIC) and the CF:CS which theoretically was explained by Robbins et al. (1978), Jeter (1999), Appleby et al. (2001). Lakes that have experienced variations in sediment supply due to natural and anthropogenic impacts show a non-exponential reduction of 210Pb concentration with depth. This assumption has been used commonly in the Constant Rate of Supply Model (CRS) (Appleby and Oldfield 1978; Robbins et al. 1978). In addition, Pennington et al. (1973) and Appleby et al. (1991) have used 137Cs and 241Am as artificial radioisotopes derived from the atmospheric testing of nuclear bombs and from the 1986 Chernobyl reactor accident to validate 210Pb resultant sediment ages. The basic models have been improved (Oldfield and Appleby 1984) in order to evaluate 210Pb data and best interpretation of sediment chronology. The reviewed literatures also showed that IAEA (1983, 1995, 1998) is the first organization to introduce the use of radioisotopes in sediment studies.

3.2.1 The Constant Rate of Supply CRS Model

The CRS model assumes that the inﬂux of excess 210Pb supply to the sediment is constant with time at a particular location. The CRS dating model (3.1) is expressed as follows (Appleby and Oldﬁeld 1978):

λt At ¼ Aoe ð3:1Þ

210 where At is the cumulative Pbex below the level representing time t, λ represents 210 210 1 the Pb decay constant of Pb (0.03114 year ) and Ao is the total cumulative 68 3 Sedimentation Rate in Bera Lake

210 2 210 Pbex inventory (Bq m ) at the point where the Pbtot activity reaches radioactive equilibrium with the supporting 226Ra (3.2). X ¼ ðÞρ ð: Þ A0 ihiAi 3 2

3 where ρi ¼ dry bulk density (kg m ) of the ith depth interval, hi ¼ thickness of the 210 1 210 ith depth interval (m) and Ai ¼ Pbex (Bq kg ). Furthermore, Pb ﬂux (Bq m2 year1) can be calculated with by the following equation (3.3):

210 ¼ λ ð : Þ Pbflux A0 3 3 In addition, the age of the sediments (3.4) at any depth is given by: 1 A t ¼ In 0 ð3:4Þ λ A Sedimentation rate (cm year1) will be obtained by dividing mass flux (g cm2 year1) on saturated bulk density (g cm3) (Table 3.1). A mean sediment flux and sedimentation rate can be calculated by a slope regression model. When 210 the In Pbex is plotted against depth, resulting profile will be linear, if reduction in 210 1 Pbex content decreasing exponential. The mean sedimentation rate (cm year ) for a given sediment column will be determined by dividing of constant decay on λ slope (Fig. 3.3). The resultant slope should be valid to calculate the mean ðÞslope sedimentation rate when a significant r value and p < 0.05 establish.

3.2.2 The Constant Initial Concentration CIC Model

The CIC model assumes the unsupported 210Pb remains constant with time at a particular location and a constant sedimentation rate. As a result, the unsupported 210Pb concentrations vary exponentially with depth. In most of recent sedimentary basins which has been affected extremely by anthropogenic changes and those are tectonically active, the assumption of the CIC model are extremely rare. However, in systems such as the remote lakes and the deep ocean where the system variations are muted the CIC model may be applicable. The CIC dating model (3.5)is expressed as follows (Appleby and Oldﬁeld 1978)

210 210 λ210t PbexðÞ z ¼ PbexðÞ o e ð3:5Þ

210 210 where Pbex(z) represents the unsupported (excess) activity of Pb at the 210 sediment-water interface. The radioactive decay constant λ210 for Pb is 0.03114 year1 and t is the deposition time (age, in year). The cumulative dry weight per unit area (g cm2), W, is related to the deposition time according to the expression t ¼ W/f, where f is the sediment mass flux (g cm2 year1). The least equation can be simplified and rewritten as follow (3.6) Table 3.1 CRS model running for calculation of sediment date, and flux Dry Total Pb210 SAR Depth Mass Pb210 Ra226 Conc Cum A A Chronology Estimated (g/cm2/ Density Sedimentation (cm) (g/cm2) (Bq/kg) (Bq/kg) (Bq/kg) (Bq/m2) (Bq/m2) age (year) date year) (%) (g/cm3) rate (cm/year) 0 0.00 0.00 1,792.54 208 0.00 0 1 0.32 61.1 8 41.2 6 19.96 10 64.69 33 1,727.85 208 1.18 1 2008 0.27 51 0.21 1.28 3 0.63 51.0 7 34.5 6 16.41 9 119.72 43 1,672.82 206 2.22 2 2007 0.32 56 0.18 1.75 5 0.93 94.5 10 34.1 6 60.45 11 234.40 56 1,558.14 204 4.50 2 2004 0.08 22 0.19 0.43 7 1.18 65.0 8 32.2 6 32.78 10 353.36 62 1,439.18 201 7.05 2 2002 0.14 32 0.08 1.73 9 1.44 65.0 8 32.2 6 32.78 10 437.02 67 1,355.52 199 8.97 3 2000 0.13 33 0.07 1.88 11 1.69 65.0 8 32.2 6 32.78 10 520.69 72 1,271.85 197 11.02 3 1998 0.12 33 0.09 1.30 13 2.09 45.3 7 34.7 6 10.68 9 606.62 80 1,185.92 196 13.27 3 1996 0.35 84 0.12 2.96 15 2.48 45.3 7 34.7 6 10.68 9 648.85 88 1,143.69 192 14.43 3 1995 0.33 84 0.25 1.35 17 2.83 65.6 8 49.3 7 16.29 11 696.05 96 1,096.49 189 15.78 4 1993 0.21 66 0.36 0.59 19 3.20 61.3 8 37.2 6 24.06 10 771.09 103 1,021.45 185 18.06 4 1991 0.13 44 0.37 0.36 21 3.60 38.0 6 35.4 6 2.59 9 824.19 108 968.35 181 19.78 4 1989 1.16 323 0.34 3.38 23 4.01 54.7 7 33.4 6 21.27 9 873.21 115 919.33 178 21.44 5 1988 0.13 46 0.34 0.40 25 4.41 69.2 8 47.8 7 21.36 11 957.73 123 834.82 174 24.54 5 1984 0.12 53 0.42 0.29 27 4.82 55.3 7 49.8 7 5.44 10 1,012.99 130 779.55 168 26.74 5 1982 0.45 183 0.42 1.06 29 5.25 65.5 8 44.7 7 20.78 10 1,069.52 138 723.02 163 29.16 6 1980 0.11 54 0.39 0.28 31 5.66 40.4 6 38.5 6 1.89 9 1,115.07 142 677.47 156 31.25 6 1978 1.12 469 0.43 2.59 33 6.08 47.5 7 45.4 7 2.10 10 1,123.59 148 668.96 152 31.65 6 1977 0.99 433 0.48 2.05 35 6.52 72.8 9 41.6 6 31.23 11 1,197.29 156 595.25 147 35.40 7 1974 0.06 39 0.47 0.13 37 6.95 73.9 9 40.9 6 32.99 11 1,334.95 163 457.59 138 43.85 9 1965 0.04 42 0.49 0.09 39 7.38 59.8 8 42.2 6 17.66 10 1,441.80 168 350.74 130 52.39 11 1957 0.06 63 0.43 0.14 41 7.79 61.2 8 45.7 7 15.55 10 1,510.47 174 282.07 123 59.38 13 1950 0.06 75 0.44 0.13 43 8.21 52.6 7 45.7 7 6.91 10 1,558.08 179 234.46 115 65.32 15 1944 0.11 137 0.45 0.23 45 8.69 57.3 8 43.2 7 14.10 10 1,607.99 185 184.55 107 73.01 18 1936 0.04 84 0.48 0.09 47 9.16 41.1 6 34.3 6 6.85 9 1,657.07 189 135.47 96 82.94 22 1926 0.06 135 0.50 0.12 (continued) Table 3.1 (continued) Dry Total Pb210 SAR Depth Mass Pb210 Ra226 Conc Cum A A Chronology Estimated (g/cm2/ Density Sedimentation (cm) (g/cm2) (Bq/kg) (Bq/kg) (Bq/kg) (Bq/m2) (Bq/m2) age (year) date year) (%) (g/cm3) rate (cm/year) 49 9.54 41.20 6 35.31 6 5.89 9 1,681.76 192 110.79 87 89.40 25 1920 0.06 154 0.41 0.14 51 9.95 40.00 6 35.00 6 5.00 9 1,703.96 196 88.58 80 96.58 29 1912 0.06 173 0.41 0.14 53 10.36 42.05 6 35.24 6 6.81 9 1,728.12 199 64.43 72 106.80 36 1902 0.03 148 0.42 0.07 55 10.81 40.8 6 35.3 6 5.53 9 1,756.03 203 36.51 62 125.04 55 1884 0.02 200 0.36 0.06 57 11.20 40.0 6 35.0 6 5.00 9 1,776.40 206 16.14 48 151.26 96 1858 0.01 297 0.26 0.04 59 11.60 39.3 6 36.1 6 3.17 9 1,792.54 208 0.00 34 NA NA 0.00 NA 0.39 60.45 0.23 1.06 1.89 Total 208 Basal 0.18 SAR 0.02 3.2 Modeling 71

6 0.8 cm/y y = -0.0387x + 3.715 4 R2 = 0.2946 2 LnPb210 Excess 0 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 Depth (cm)

Fig. 3.3 Mean sedimentation rate by plotting In210Pb against depth by CRS

6 y = -0.2108x + 3.4606 5 R2 = 0.2552 4 3 2

Ln Pb210 Excess 1 0 0246810 Mass Depth (g cm-2)

Fig. 3.4 Mean sedimentation rate by plotting In210Pb against mass depth by CIC

λ 210 210 210 In Pb ðÞ Pb ðÞ¼ w ð3:6Þ ex z ex o f

A slope regression estimates a mean sediment flux in CIC model. When 210 In Pbex(z) is plotted against the cumulative dry weight per unit area, W, the λ resulting 210Pb profile will be linear, with slope 210 . The sediment mass f flux f, may then be determined from the mean slope of the profile, using the least- squares fit procedure (Fig. 3.4). The resultant slope should be valid to calculate the mean sedimentation rate when a significant r value and p < 0.05 establish.

3.2.3 The Limitation of Models

In the real world, cores often show a non perfect trend and exhibit deviations from the ideal data set: (1) The data may reveal a vertical 210Pb activity proﬁle in the core surface. In this case mechanical mixing of the surface sediments contributed by benthic organisms or by hydrodynamic activity of the overlying water. 72 3 Sedimentation Rate in Bera Lake

(2) The 210Pb activity shows a peak slightly below the sediment surface. This is commonly seen and may be caused by steep redox gradients across the uppermost few centimeters of sediment. (3) The deepest sections analyzed may still appear to be above background levels of 210Pb, as evidenced by a non vertical profile in the deepest part of the core. (4) Necessity to an independent time marker (5) When the core is not enough long to reach the background levels of 210Pb (6) When the sandy layers exist along the sediment profile In the case of (1) and/or (2), the data may still form a straight line on a log [excess 210Pb activity] vs. cumulative dry sediment plot if the upper part of the core data is disregarded. This will allow the determination of accumulation rate for the mid portion of the core. If one assumes that the accumulation rate has remained constant in the upper, more recent sediments, then the age of the sediments can be calculated for any depth in the core. In case (3), where the deepest core sections appear to be above background level, the excess 210Pb activity cannot be calculated because there is no estimate of the background level of 210Pb. It is necessary to make an assumption that the background level is less than the lowest activity measured in the core but greater than zero. Independent tracer provides an unambiguous time stratigraphic horizon (Pennington et al. 1973; Smith 2001; Robbins et al. 1978). Independent time marker in Case (4) recommended the statement firmly. The well known independent time index is fallout 137Cs which has been introduced firstly by Pennington et al. (1973) as a verification time tool. 210Pb considered is verified by subsurface 137Cs peaks in sediments located at depths where 210Pb dates agree with the date fallout maximum, 1963–1964. Furthermore, non radiological markers and depositional history, such as varves, known contaminant inputs, or known natural episodic events, and certain anthropogenic activities used commonly as time signals. In this study the accuracy of 210Pb dates validated by referencing to well-known 137Cs horizons. The validation is proven by its first appearance in sediment columns (1952–1954), the maximum fallout from atmospheric testing of atomic bombs (1963–1964) and the Chernobyl reactor accident (1986), charcoal horizons, and special influx of heavy metals, nutrients and exchangeable cations.

3.2.4 Sampling

Core sampler is the most important equipment for sedimentation rate study and environmental pollution. Capabilities of known sediment corers, such as the Russian type, KC sediment trap, Slide-hammer, Kajak-Brinkhurst, Phleger, Benthos, Alpine, Boomerang, and Ballchek were considered in order to select best one according to Bera Lake situation. These samplers are usually deployed using a winch that suspends the sampler about 5 m above the sediment to be 3.2 Modeling 73 sampled and allows the sampler to free fall, penetrating the sediment and forcing the material into the sample liner (Burton 1998). In an area like Bera Lake, which has an average depth of 2.5 m, the ability of a boat-launched sampler to reach the subsurface may be limited, and it may be more appropriate to use a modiﬁed device that can adjust to the boat’s maneuvering in a shallow lake. In this study, two new kinds of core samplers, known as UM Core sampler (A and B), were developed based on the sediment properties, depth, and boat availability at Bera Lake (Fig. 3.5a, b). The sampler was designed and developed at Department of Mechanical Engineering, University of Malaya by

Fig. 3.5 (a) Core sampler Type A, design and accessories. (b) Core sampler Type B, design and accessories 74 3 Sedimentation Rate in Bera Lake

Fig. 3.5 (continued)

the author. The novelty of corer has been acknowledged and approved by center of innovation and commercialization of Malaysia vide patent no. PI2011003971. The sampler is classified as hand sampler or manually controlled. The sampler type A has main steel core barrel and interior transparent acrylic tube and the main transparent acrylic tube in type B with maximum 2 m length. Both A and B types have a drop weight to serve as a hammer to drive the core tube into the sediment column easily. The samplers have additional drive rods that extend the core to collect samples of up to 10 m depth. The primary object of the UM core sampler (Type B) is taking a plurality of undisturbed and un-compacted sediment samples simultaneously at one geographic sampling point in shallow lake, swamps, rivers, reservoirs, estuaries or coastal areas. The plurality of samples (Type B) allows implementation of various sediment tests with high accuracy. UM core sampler is 3.2 Modeling 75 portable, simple-to-operate, with high rate of coring success and low compaction. UM core sampler type B discloses that the sampling tube comprises a detachable stopper to prevent sediment from falling out when the apparatus is lifted from the ground. The present preferred embodiment of the invention consists of novel features and a combination of parts hereinafter fully illustrated in the accompanying drawings (Fig. 3.5a, b) Core sampling is the recommended method to be used when sedimentation rate in the aquatic media is targeted, when accurate surficial sediment sampling depths are important, when vertical profiles are needed to assess the quality of sediment at various depths, when geotechnical properties of sediment profile in needed and when it is important to maintain an oxygen-free environment (Radtke 2005). The U.S Geological Survey (USGS) bottom-material sampling manual (Radtke 2005) was used for pre-field works, during sampling, and after field work procedures. Radtke (2005) stated that selected sites for core sampling will affect the quality of the data collected. Experiences show that there is no formula for design of a sediment sampling pattern which would be applicable to all sediment sampling programs (Mudroch and MacKnight 1994). Radtke (2005) has recommended applying statistical or deterministic methods to design the distribution pattern and number of sampling sites. Deterministic methods for selecting sampling sites for bottom material are based on professional judgment alone. Statistical methods for site selection sediment cores include stochastic random, stratified random, systematic regular, and fixed transect methods. Applications and limitations of selected statistical methods for selection of sites for collection of bottom-material samples are presented below (Mudroch and Azcue 1995). 1. Stochastic random method • Commonly used in reconnaissance surveys where little is known about local conditions. • Most unbiased method of site selection. • Efficient in areas with homogeneous bottom material. • Potentially ineffective in areas with heterogeneous bottom material. 2. Stratified random method • Often permits elucidation of subtle but real differences. • Requires knowledge of local conditions. 3. Systematic regular method • Randomness achieved through selection of initial sampling site using a number chosen from a random numbers table or from electronically gener- ated random numbers. • Produces biased results. • Fixed-transect method • Sites not chosen randomly, therefore any inferences are site specific, and areal conclusions may not be valid. 76 3 Sedimentation Rate in Bera Lake

3.2.4.1 Sampling Strategy

General and bottom morphology of basin are playing an important role in sampling strategy. Evaluating of previous works (Dorall and Sinniah 1997;Wu¨st and Bustin 2004) showed that the available base map of study area was belongs to 1997 with 1:25,000 scales. Therefore, the latest Bera Lake morphological map was developed using a satellite image (Spot 5 2009) of spatial resolution 10 m in GIS media. New geomorphological map of study area highlights the dendritic pattern of Bera Lake and surrounding sedimentary units. Four pilot core samples were taken from different parts of Bera Lake to evaluate homogeneity of Bera Lake sediment column or any variation in the strata thickness. Pilot core samples were taken based on stochastic random method. Overall analysis of sediment stratigraphic column showed five distinct layers along the depth profile of 0–100 cm and illustrated conformity of processes which have been contributed for deposition of layers. Dendritic morphology of Bera Lake and stream pattern governs the hydrological circulation and sediment redistribution. Elongated morphology of Bera Lake and separation of water bodies by Pandanus plants, has led to the core sampling pattern to be more deterministic. Pilot core sampling showed that sediment column has not been developed properly along the main water way, and therefore sampling was focused on distinct sub-basins. Deterministic sampling method was applied after recognition of different parts of Bera Lake in terms of sediment entry and departure points and sub-basins. Final location of core sampling was selected to include 10 core samples from different parts of Bera Lake (Figs. 3.6 and 3.7). Sediment Cores 2, 3, 7, and 10 were collected from the south, Cores 4, 6, and 8 were collected from the middle while Cores 1, 5, 9 were collected from the north of Bera Lake. Core samples have mostly collected by UM sampler type B because of its better maneuvering and sediment core recovery. Sediment core sampling procedures are presented as follows: 1. The core tube was decontaminated. 2. Water depth was recorded by Echo sounder Garmin 400C 3. The core tube was attached to the UM sampler head. 4. Location of each coring station was determined by the GPS 5. The coring device was gradually lowered into the water. 6. The core was driven into the sediment, using drive rods, until allowable penetration level. 7. The filled core tube was retrieved slowly and steadily to avoid agitating the sample. 8. As the corer is lifted out of the water, a plug was immediately inserted into the bottom of the core tube to prevent sediment from slipping out. 9. The core will be evaluated against the following acceptability criteria: • At least 5 cm of overlying water is present • The overlying water is not excessively turbid • The sediment surface is relatively undisturbed • The core thickness is representative for research objectives 3.2 Modeling 77

Fig. 3.6 Some of core samples which were taken from Bera Lake

10. If the core met the above acceptability criteria, the core was processed immediately by cutting the core from 10 cm of overlying water. 11. The characteristic of the core was documented (Date, time of collection, layers texture and composition). 12. Core were sealed and kept vertically to prevent of mixing.

3.2.5 Sample Preparation

Three hundred sediment samples were prepared according to standard instructions which published by IAEA (1983). Collected core samples were sealed and stored vertically to prevent mixing while transported to the laboratory. Sample cores were preserved in a freezer at the temperature of 4 C before slicing. The main idea behind the core freezing was to minimize the sediment column compaction during slicing. The freeze sediment cores samples were evacuated from core plastic tubes using an extruder. The extruder has a diameter lower than interior liner diameter of the core tube. The corers were sliced at 2 0.2-cm intervals using a plastic saw (Fig. 3.8). The sliced samples were dried at 60 C and ground for further analytical procedures. The dried samples were packed in special containers (Fig. 3.9) for 78 3 Sedimentation Rate in Bera Lake

Fig. 3.7 Bathymetric condition (m) and core sampling position of Bera Lake

3 weeks before counting to allow the 226Ra to secularly equilibrate with 222Rn and its’ shorter half-life daughters. In case of soil samples, the bulk and dry densities of the well preserved cylindrical core samples were determined after they had been dried at 80–105 C and weighed. The samples were then ﬁnely ground and packed in special containers for 3 weeks to allow secular equilibration of radioisotopes. 3.2 Modeling 79

Fig. 3.8 Sliced samples before and after drying and charcoal content

Fig. 3.9 Packing of soil and sediment samples before radioisotope counting

3.2.6 Radioisotopes Analysis

210Pb and 137Cs speciﬁc activities were measured using well calibrated gamma- spectrometry based on hyper pure germanium (HpGe) detectors at Nuclear Malaysia (Fig. 3.10) and Genie 2000 software Version 3.2. The gamma- spectrometer model GCW2523, (Canberra) detector at Nuclear Malaysia had a relative efﬁciency of 27 % and FWHM of 2.04 keV for 60Co gamma-energy line at 1,332 keV. The gamma transmissions used for activity calculations was 46.5 keV with a branching ratio of 5.6084 %. The gamma-spectrometers were calibrated 80 3 Sedimentation Rate in Bera Lake

Fig. 3.10 Gamma-spectrometer model GCW2523 used in this study using multinuclides standard (NIST) solutions in the same sample–detector geom- etry. The lower limit of detection, with 95 % conﬁdence, is 0.3 Bq for 24 h measuring time. IAEA reference samples QAQC2 and QAQC6 were used for quality control of the gamma-spectrometer and its calibration. Deﬁned energy spectrum in γ-spectrometric analyses was included 7Be, 54Mn, 40K, 57Co, 60Co, 134Cs, 137Cs, 212Pb, 210Pb, 226Ra, 226Ra, and 228Ra radioisotopes in which total activity of 210Pb, supported 210Pb, and 137Cs were utilized in age calculation and determination of historical variation of sedimentation rate at Bera Lake. Disequilibrium between 210Pb and its parent isotope (226Ra) in the 238U series arises through emission of the noble gaseous isotope 222Rn (half-life 3.8 days). Escaped gas 222Rn to the atmosphere naturally decays to 218Po, a metallic radionuclide which in a period of hours or days, precipitates to the earth with dust and rain. A number of daughters radioactive decays occur over a period of minutes and 210Pb or unsupported 210Pb (half-life ¼ 22.3 years) is produced. Supported 210Pb in each sample was assumed to be in equilibrium with the in situ 226Ra, and unsupported 210Pb value was calculated by subtracting 226Ra activity from total 210Pb activity (Appleby 2000).

3.3 210Pb and 137Cs Inventories and 210Pb Flux

Calculation of inventory and ﬂux of fallout radionuclide 210Pb is based on Eqs. (3.2) and (3.3), respectively. The mean maximum and minimum 210Pb inventories at Bera Lake calculated to be 5,112 70 and 1,440 41 Bq m2, respectively 3.4 Sedimentation Rate at the South of Bera Lake 81

210 Table 3.2 Pb inventory Pb210 inventory Pb210 ﬂux and ﬂux at studied sediments Core no. (Bq m) (Bq m2 year1) cores 1 2,245.87 81 69.64 3 2 2,898.00 162 90.24 5 3 3,054.40 51 95.11 2 4 3,657.35 128 113.90 4 5 3,228.00 113 100.52 3 6 2,920.47 72 90.94 2 7 2,496.00 61 77.41 2 8 1,440.28 41 44.85 1 9 5,129.01 70 159.71 2

(Table 3.2). The estimated value of the 210Pb flux along the mainstream of Bera Lake is 90 5Bqm2 year1. An increase in 210Pb flux of 159 2Bqm2 year1 is observed towards the corners of the lake due to divergent currents which release sediments in a semi closed area (Fig. 3.11). In other words, morphological shape and stream pattern are controlling 210Pb distribution at the Bera Lake. Previous studies (Neergaard et al. 2008; Othman et al. 2003; Moungsrijun et al. 2010) which were carried out in Malaysia, Thailand and Indonesia highlighted the low activity of 137Cs (<400 Bq m2) which is in accordance with 137Cs activity in tropical Australia. They stressed also the ability of 137Cs for soil redistribution studies and as a time confirmation marker in sedimentation studies in tropical areas. The expected low activity of 137Cs in Malaysia thus anticipated in this study. 137Cs activities can be divided into two distinctive categories. The first involves known 137Cs horizons (1954, 1963, and 1986) while the second category implied reworked and erosion-induced 137Cs from catchment area. Although 137Cs showed peaks in studied cores coincide with Chernobyl accident in 1986, scientific reports to verify its fallout in Malaysia are not available.

3.4 Sedimentation Rate at the South of Bera Lake

Unsupported 210Pb inventory and its variation with depth and sedimentation rate at the south of Bera Lake studied in Cores 2, 3, and 7. The 226Ra activity gained a mean value of 38 6.5 in the studied cores. Equilibrium of total 210Pb activity with the supporting 226Ra obtained at depth of 60 cm in master Core 2. The maximum unsupported 210Pb concentration obtained between 60.45 11, 40.50 11, and 38.20 16 Bq kg1 in Core 2, 3, and 7, respectively. On the other hand, the lowest unsupported 210Pb values in Cores 2, 3, and 7 calculated to be 2 9, 2 9, and 0.5 11 Bq kg1. The unsupported 210Pb variation versus depth (Figs. 3.12, 3.13, and 3.14) revealed a clear lithological dependence of 210Pb activity in Bera Lake sediment. The unsupported 210Pb values decreased with a number of minor irregularities in separate layers. A deeper zone (Layers 2 and 1) depicts an exponential 82 3 Sedimentation Rate in Bera Lake

Fig. 3.11 Annual ﬂux and distribution of 210Pb in Bera Lake variation of unsupported 210Pb with depth in Cores 2 and 7. However, an exponential decrease 210Pb value observed in the uppermost layer of Cores 2 and 3 until depth of 30 cm. Sediment mixing appeared from depths of 0–2 cm in Cores 2 and 7, probably because of bioturbation. . eietto aea h ot fBr ae83 Lake Bera of South the at Rate Sedimentation 3.4

Fig. 3.12 Fallout radionuclides concentration versus depth at Core 2 and 210 Pb dates 43SdmnainRt nBr Lake Bera in Rate Sedimentation 3 84

Fig. 3.13 Fallout radionuclides concentration versus depth at Core 7 and 210 Pb dates . eietto aea h ot fBr ae85 Lake Bera of South the at Rate Sedimentation 3.4

Fig. 3.14 Fallout radionuclides concentration versus depth at Core 3 and 210 Pb dates 86 3 Sedimentation Rate in Bera Lake

A northward increase in the mean sedimentation rate recognized at the south of Bera Lake, where accumulation rate calculated to be 0.24 0.32, 0.27 0.25 and 0.47 0.54 g cm2 year1 at Cores 2, 3 and 7, respectively. The mean pre-1950 sedimentation rate furthermore, was determine 0.06 0.02, 0.07 0.07 and 0.21 0.21 g cm2 year1 at core 2, 3 and 7. Layer 2 which composed of grey to dark sandy mud experienced several sediment fluxes since 1950 to 1970. Two sediment flux events recorded at Core 7 in which sedimentation rate increased significantly to 1.88 and 2.39 g cm2 year1 in 1952 and 1963, respectively. Similarly, three peaks in sedimentation rates observed at Core 3 where sediment fluxed by rates of 0.48, 0.64, 0.43 g cm2 year1 in 1950, 1957, and 1962, respectively. Bera Lake experienced a remarkable accumulation of terrestrial sediments during Layer 3 deposition with mean rates of 0.48 0.48, 0.39 0.13, and 0.41 0.29 g cm2 year1 at Cores 2, 3, and 7, respectively. Five FELDA land development projects mark sediment fluxes with rates of 0.43, 0.12, 0.17, 0.34, 0.82 g cm2 year1, respectively at Core 7. General upward growth of sedimentation rate in Layer 3, decreased gradually in 1996 with a rate of 0.51 g cm2 year1 when deforestation prohibition rule has established in 1994. Similar upward increase in sedimentation rate from the first to forth FELDA land projects was recorded at Core 3 in which sediment flux varies between 0.29 and 1.18 g cm2 year1. At the beginning of the south of Bera Lake (Core 2) similar trend of sediment fluxes were detected. From the first to fifth FELDA projects, sedimentation rates vary between 1 and 1.18 g cm2 year1. This process continued with a mean rate of 0.22 0.1 g cm2 year1 at the uppermost layer of Bera Lake sediment column. The mean accumulation rate for layer 4 at Cores 3 and 7 were calculated to be 0.27 0.34 and 0.29 0.24 g cm2 year1. Lithological descriptions revealed that contribution of land clearing projects were slightly extended in Layer 4. Their effects observed in 1996 at Core 2 and 1998 at Core 7 with the rates of 0.35 and 0.62 g cm2 year1. Another vivid organic-rich sediment flux recorded at both Cores 2 and 7 in 2001 with rates of 0.14 and 0.67 g cm2 year1, respectively. A clear sediment flux with rates of 0.32 and 0.17 g cm2 year1 in cores 2 and 7 were recorded at depths of 2 to 4 cm and mark a great flood in December, 2007. 210Pb dates using CRS model and peaks in reworked 137Cs placed, is in good agreement with FELDA land development dates and natural events particularly in layer 3 and 4. 137Cs showed well-resolved peaks at depths of 39 and 37 cm at Core 2 which is in agreement with 210Pb dating using CRS model. An activity of 8.38 Bq m2 marked the first appearance of 137Cs in 1954 at the south of Bera Lake sediment column (Fig. 3.12). Another remarkable 137Cs peak with an activity of 10.66 Bq m2 observed at depths of 39 cm which is agreement with the 1963 maximum 137Cs fallout because of atmospheric atomic bomb testing. Difference in bed morphology caused in deeper depths of 1954 and 1963 137Cs horizons in cores 3 and 7. Once again, northward increasing in sedimentation rate at the south of Bera Lake has revealed in 137Cs activities. For instance, in Core 7, 317Cs peaks of the first appearance and the 1963 maximum fallout calculated to be 23.32 and 3.5 Sedimentation Rate at the Middle of Bera Lake 87

5 y = -0.1405x +3.2273 Core 2 2 4 R = 0.2913 3 2

Ln Unsupported 1 0 0 2 4 6 8 10 12 Mass depth (g cm-2)

4 Core 3 4 3 3 2 2 y = -0.0786x + 2.9509 1 R2 = 0.1398 Ln Unsupported 1 0 02468101214 Mass depth ( g cm-2)

Fig. 3.15 Mean sedimentation rate at Core 2 and 3 using slope regression model

15.06 Bq m2, showing greater inventories than Core 2. Another considerable 137Cs peak appeared at depths of 30 and 36 cm (Figs. 3.13 and 3.14), with 13.34 and 21.52 Bq m2 activities in cores 2 and 3, probably indicating 137Cs fallout in 1986 due to Chernobyl accident. In addition, 137Cs peaks reﬂected natural events in study area. For instance, Layer 5 is an indicator of a huge ﬂood has occurred in 2007, displayed properly by peaks at depths of 3–6 cm and 137Cs activity of 37.25 and 15.37 Bq m2 at cores 2 and 7, respectively. As a result, 137Cs horizons highlighted the ability of CRS model in chronology of Bera Lake sediments. A mean sedimentation rate based on stratigraphic depths of 137Cs horizons at Bera Lake sediment column calculated 0.7, 1 and 1.12 cm year1 at Cores 2, 3 and 7, respectively. Results are in agreement with the mean sedimentation rate that has been calculated by a slope regression model in which unsupported plotted against cumulative mass depth in Cores 2 and 3 (Fig. 3.15).

3.5 Sedimentation Rate at the Middle of Bera Lake

Sedimentation status at the middle of Bera Lake investigated in Core 6, Core 4, and Core 8. Detailed unsupported 210Pb and 137Cs inventories and their variation with depth and sedimentation rate were analyzed in master Core 8. The 226Ra activity gained a mean value of 40.4 7.5 in the studied cores. Equilibrium of total 210Pb 88 3 Sedimentation Rate in Bera Lake activity with the supporting 226Ra calculated at a depth of 70 cm. The unsupported 210Pb concentration at north and east of Bera Lake main open water ranged 18.78 18 and 0.2 8Bqkg1 (Fig. 3.16), while at deepest part varied between 95.35 19 and 1 10 Bq kg1 in Core 6 (Fig. 3.17). The results once again emphasized lithological effects on unsupported 210Pb distribution with depth at middle of Bera Lake. The unsupported 210Pb values decreased steeply with a few irregularities till lower contacts of layers. An exponential variation of unsupported 210Pb with depth appeared at uppermost layer of Core 6. The unsupported 210Pb activity showed a peak slightly below the sediment surface at Core 8. This peak may be caused by steep redox gradients across the uppermost few centimeters of sediment. A margin ward increase in the mean sedimentation rate recognized at the middle of Bera Lake, where deposition rate calculated 0.4 0.59, 0.35 0.75, and 0.13 0.16 g cm2 year1 at cores 6, 8, and 4, respectively. The mean pre-1950 accumulation rate evaluated to be 0.05 0.01 and 0.16 0.16 g cm2 year1 at Core 6 and Core 8. As a result, sediment flux and sedimentation rate at the south and along main axes of Bera Lake show similar values for the pre-industrial period. The grey to dark sandy mud (Layer 2) was deposited from 1950 to 1970 with mean rates of 0.12 0.11, 0.44 0.62 at cores 8 and 6, respectively. Two remarkable fluxes of sediments recorded at the middle of Bera Lake in the year 1954 and 1962 with a mean rate of 0.53 and 0.975 g cm2 year1, respectively. White sandy mud (Layer, 3) deposited at the middle of Bera Lake with a mean rate of 0.78 0.75 g cm2 year1 in Core 6, and 0.54 1.2 g cm2 year1 in Core 8. Results revealed that terrestrial sediment fluxed significantly at the main Bera Lake open water during the deposition of Layer 3. The contribution of land development projects in sediment fluxes into the middle of Bera Lake appeared especially in the Layer 3. For instance, five FELDA land development projects contributed to sediment flux along the main axes of Bera Lake at Core 6 with rates of 0.69, 0.52, 1.01, 1.53, and 2.16 g cm2 year1, respectively. In Core 8, furthermore, the first FELDA project started with the sedimentation rate of 0.17 g cm2 year1. Maximum sediment flux calculated to be 3.95 g cm2 year1 during the second and the third FELDA land development projects from the year 1976 until 1985. Sedimentation in Layer 3 continued with a rate of 0.17 g cm2 year1 during the fourth FELDA land development project. A decline in deposition rate of organic-rich sediments dominated at uppermost Layer 4 of the middle Bera Lake. The highest accumulation rate recognized at Core 8 with a mean rate of 0.35 0.38 g cm2 year1, while organic-rich deposits settled with a mean rate of 0.08 0.02 g cm2 year1 at the deepest part of Bera Lake. Deforestation projects have ceased in 1994 but local deforestation activities are continuing with sediment fluxed into the north margin of the middle of Bera Lake with a rate of 0.47 g cm2 year1. Sedimentation rate continued and increased to 1.35 g cm2 year1 in the year 2004. The CRS 210Pb dating model placed the first appearance of 137Cs, 10.5 Bq m2 value at a depth of 44 cm. A well-resolved peak appeared at depths of 40 cm with 26.41 Bq m2 activities. It represents the 1963 maximum 137Cs fallout which is in . eietto aea h ideo eaLk 89 Lake Bera of Middle the at Rate Sedimentation 3.5

Fig. 3.16 Fallout radionuclides concentration with depth at Core 8 and 210 Pb dates 03SdmnainRt nBr Lake Bera in Rate Sedimentation 3 90

Fig. 3.17 Fallout radionuclides concentration with depth at Core 6 and 210 Pb dates 3.6 Sedimentation Rate at the North of Bera Lake 91

0.27 g cm-2 y-1 4.0 0.8 cm y-1

3.0

2.0

1.0 y = -0.1148x + 2.2704

LnUnsupported 2 0.0 R = 0.1125 0 2 46810 -1.0 Mass depth (g cm-2)

Fig. 3.18 Mean sedimentation rate at Core 8 using slope regression model agreement with 210Pb dates using CRS model. Clear correlation recorded between depths of this peak at both south (Core 2) and middle (Core 8) of Bera Lake. A remarkable peak in 137Cs activity, 19 Bq m2 concentrations appeared at depth of 30 cm, likely showed 137Cs fallout in 1986 due to Chernobyl accident. Similar peak in 137Cs activity placed at depth of 25 cm by CRS 210Pb dating model in Core 6. Other 137Cs peaks between depths of 0–40 cm in Core 8 and from 0 to 45 cm in Core 6 inferred reworked and erosion-induced 137Cs sources because of deforestation projects. For example, five FELDA projects indicate 137Cs fluxes in Core 6 which is in good agreement with 210Pb dates using CRS model. Another peak in 137Cs activity observed at depth of 3–5 cm in Core 8, indicating a huge flood in December, 2007. As a result, ability of CRS model in chronology of Bera Lake sediments verified significantly by 137Cs horizons at the middle of Bera Lake. Stratigraphic dates based on records of fallout 137Cs represent a mean sedimentation rate of 0.8 and 1.01 cm year1 in Core 8 and Core 6, respectively. This value in master Core 8 agrees with the mean sedimentation rate that calculated by a slope regression model in which unsupported plotted versus accumulative mass depth (Fig. 3.18).

3.6 Sedimentation Rate at the North of Bera Lake

Sedimentation rates at the north of Bera Lake evaluated in Core 1, Core 5, and Core 9. Detailed unsupported 210Pb and 137Cs inventories and their variation with depth and sedimentation rate are shown in master Core 5 (Fig. 3.19). The 226Ra activity gained a mean concentration of 36 7.8 at the north of Bera Lake. The total 210Pb activity approached equilibrium with supporting 226Ra at a depth of 65 cm. The unsupported 210Pb values at north of Bera Lake vary between 66 and 5.28 Bq kg1. A clear steep decline in unsupported 210Pb values is observed at layer contacts (Fig. 3.20) which reveals the effects of lithology and sedimentary conditions on the radionuclides concentration. An exponential variation of unsupported 210Pb versus depth with some minor irregularities appeared along layers 3 and 4, separately. 23SdmnainRt nBr Lake Bera in Rate Sedimentation 3 92

Fig. 3.19 Fallout radionuclides concentration with depth at Core 5 and 210 Pb dates . eietto aea h ot fBr ae93 Lake Bera of North the at Rate Sedimentation 3.6

Fig. 3.20 Fallout radionuclides concentration with depth at Core 1 and 210 Pb dates 94 3 Sedimentation Rate in Bera Lake

The mean sedimentation rate at the north of Bera Lake in semi closed open water (Core 9) was calculated to be 2.58 2.1 cm year1. Additionally, the maximum 210Pb flux into the north of Bera Lake calculated to be 159 2Bqm2 although mean sediment fluxes rate 0.17 0.23 and 0.34 0.5gcm2 year1 were observed at Core 1 and Core 5, respectively. Therefore, the mean sedimentation rate along main axes of Bera Lake especially at the middle and the north of basin calculated to be 1.06 cm year1. The mean pre-1950 (Layer 1) deposition rate calculated to be 0.06 0.01, 0.05 0.02, 0.14 0.26 g cm2 year1 at cores 1, 9, and 5, respectively. Sediment has thus been mainly deposited along the main axes of Bera Lake at the north, slightly more than the south and middle of basin. Sediment fluxes into the north of Bera Lake continued by accumulation of high organic content, grey to dark sandy mud deposition in Layer 2. The mean sedimentation rate calculated to be 0.11 0.03, 0.1 0.02, and 0.55 0.9 g cm2 year1 at cores 1, 9, and 5, respectively. Similar to the south and the middle of Bera Lake, two peaks in sediment flux occurred in the year 1955 and 1963 at the north of basin. The most important peaks recorded at depth of 40 cm in which sedimentation rate increased dramatically to 2.74 g cm2 year1 in 1963. The accumulation rate gradually decreased in 0.58 and 0.28 g cm2 year1 in 1967 and 1969, respectively. New sediment fluxes commenced with deposition of the white sandy mud of Layer 3 at north of Bera Lake. Terrestrial sediments indicates an intensive erosion induced deposits at the north of Bera Lake with a mean rate of 0.55 0.43, 0.17 0.12, and 0.2 0.08 g cm2 year1 in cores 1, 5 and Core 9, respectively. Five land development projects manifested clearly in Layer 3 in which sediment fluxed into the north of Bera Lake with rate of 0.43, 0.34, 0.18, 0.12, and 0.17 g cm2 year1, respectively. Similarly, five distinctive peaks in sediment fluxes recorded in semi closed basin at the north of study area where accumulation rates calculated to be 0.17, 0.16, 0.2, 0.26, 0.39 g cm2 year1, respectively. In comparison with Core 5, deforestation phases caused an upward increase in sedimentation rate in the semi closed area at the north of basin. Sedimentation continued at the uppermost layer of the north Bera Lake sediment profile with organic-rich sediments since 1992. The highest accumulation rate of this layer recognized at Core 9 with a mean rate of 0.28 g cm2 year1 (1.35 cm year1). Semi closed basin (Core 9) at the north of Bera Lake experienced four sediment fluxes in which organic-rich deposits accumulated with the rates of 0.43, 0.36, 0.54, 0.55 g cm2 year1 from 1996 until 2002. Organic-rich deposits settled with a mean rate of 0.13 0.04 and 0.1 0.07 g cm2 year1 at Core 5 and Core 1, respectively. CRS model dating placed a sediment flux of organic-rich deposits at cores 1 and 5 in 1996 with the rate of 0.17 and 0.2 g cm2 year1. The huge flood during the year 2007 in study area recorded at depths of 2–4 cm at Core 5 in which sediment accumulated with a rate of 0.1 g cm2 year1. The first appearance of 137Cs at the north of Bera Lake sediment column in 1954 calculated to be 7.93 Bq m2 value. A well-resolved peak appeared at depths of 39 cm with 15.35 Bq m2 activities. It depicts maximum 137Cs fallout during the year 1963, is in good agreement with 210Pb dates using CRS model. Clear correlation recorded between depths of this peak at sediment column of cores 2, 8, and 5. 3.8 Discussion 95

137Cs inventories in Core 9 are not compatible with dates which were calculated by CRS model. However, stratigraphic correlation of layers in Core 9 with other cores and lithology of layers veriﬁed 210Pb dates using CRS model. Other 137Cs peaks between depths of 0–38 cm in master Core 5 inferred reworked and erosion-induced 137Cs sources because of deforestation projects. Once again, 137Cs conﬁrmation horizons approved that CRS model can be applied to determine the chronology of Bera Lake sediments. The mean calculated sedimentation rate calculated to be 0.83 and 0.56 cm year1 at Core 5 and Core 1 based on stratigraphic depths of 137Cs horizons at Bera Lake sediment column. Sedimentation rate based on 137Cs horizons in Core 5 is in accordance to the mean sedimentation rate that is calculated by CRS model.

3.7 Sedimentation Map

Nine mean values of sedimentation rate from nine core samples were plotted and exported into spatial modeling and interpolation techniques (Ordinary point Kriging) to develop sedimentation map. Initial sedimentation map of Bera Lake was developed using Golden Software Surfer 7.0 and complementary mapping procedure was accomplished by ArcGIS 9.2 software (Fig. 3.21).

3.8 Discussion

Natural phenomenon like structurally tilting of Bera Lake basin was played a vital role in evolution of low land areas and trapping of water bodies (Hutchison and Tan 2009). Evidences, furthermore, support the effect of strike-slip faults in shaping of BLC valleys and control the elongate shape of wetlands and open waters. Accumulation of detritus sediments at the depths of 8–9 m Bera Lake has been happened 5,500–6,500 years BP (Wu¨st and Bustin 2004) due to a tilting and rapid steepening of the main valley. In addition, forest and reed swamps have developed mainly along depressions which already created by the strike-slip faults especially in the ﬁrst, third, fourth, and twelfth sub-catchments. Although physiographic parameters are playing minor roles in soil erosion process, their contribution to sedimentary processes is recognized signiﬁcant. These parameters remarkably affected the shape of sub-catchments and time of water concentration. Time of concentration in BLC is obtained 8.53 h. This value, furthermore, decreases in the order of 7.79 > 6.42 > 3.61 > 3.38 > 3.11 > 2.94 > 2.84 > 2.45 > 2.09 > 1.45 > 1.05 > 0.89 h in the sub-catchments 4, 12, 8, 3, 1, 5, 9, 2, 10, 6, 11, and 7, respectively. The contribution of sub-catchments in sediment transport to the sink areas in the similar rainfall intensity will therefore, follow reverse order of time of concentration. In other word, seventh sub-catchment 96 3 Sedimentation Rate in Bera Lake

Fig. 3.21 Sediment distribution and sedimentation rate map of Bera Lake requires the minimum time for transport and drainage of water and sediments in comparison with other sub-catchments. A total of 5,705 ha was determined for wetlands and open water areas, which are topographically located at lower than 20 m height from sea level. This area is a part 3.8 Discussion 97

10000 1.1 Deforestation Mean Sedimentation Rate 9000

0.9 Sedimentation Rate (g cm-2y-1) 8000

7000 0.7 6000

5000 0.5

4000

Deforestation (ha) 0.3 3000

2000 0.1 1000

0 -0.1 2006 1998 1994 1986 1978 1970 1962 1958 1950 1942 1934 1926 1922 1914 1906 1898 1890 1886 1878 1870 1862 2010 2002 1990 1982 1974 1966 1954 1946 1938 1930 1918 1910 1902 1894 1882 1874 1866

Date (yr)

Fig. 3.22 Correlation between deforestation phases and sedimentation rate of low lands which are represented between 0 and 2 slopes. The main stream at Bera Lake with a length of 23 km drains water and transports sediments northward and also widens with several retention pounds and open waters. This mean contribution of the main stream in terms of sediment supply into the Bear Lake calculated to be 90 %. In addition, the results reveal that the capability of Bera Lake for trapping of sediments will increase up to 70 % with an increase in water supply especially from the south inlet. The elongate shape and abundance of distributaries are other reasons for increase of sediment residual in Bera Lake. An estimation of sedimentation rate based on Bera Lake and trap efficiency has revealed that the annual accumulation rate is 12,547.14 m3. In conclusion, the relative sedimentation rate based on the Bera Lake areas (1,126,315 m2) can be estimated at 1.11 cm year1 per year. This rate is confirmed with the rate of 1.025 cm year1 which has been calculated using the 137Cs technique. Medium-term variation in the rate of sediment supply into Bera Lake and the lithology of the deposited sediments were studied through 210Pb dating using the CRS model. The chronology of sediment columns can be separated into two phases of prior and post land use changes in the catchment area. The pre-1970 period could also be divided into two periods of 1950 to 1970 and pre-1950, respectively. The actual clearance of forest by FELDA for oil palm plantations commenced in 1960 and two FELDA projects were implemented between the years 1960 and 1965, and between 1966 and 1970, respectively. Although, no published data is available for FELDA projects in the BLC at this range of time, a remarkable influx of sediment has been recorded between 1961 and 1966. During this period the mean sedimentation rate significantly increased to 0.9 g cm2 year1; a value comparable with values quoted by FELDA or other responsible government agencies in 1980 decade. A rapid sedimentation rate between the years 1961 to 1966 may be due to some natural reasons such as a wet season or a period of heavy rain fall. The long- term available and reliable rainfall data from 1961 shows some similarity with gained the mean sedimentation rate (Figs. 3.22 and 3.23). 98 3 Sedimentation Rate in Bera Lake

3000 1.2 Rainfall Mean Sedimentation Rate

2500 1.0 Sedimentation Rate Sedimentation (g y-1) cm-2

2000 0.8

1500 0.6 Rainfall (mm) 1000 0.4

500 0.2

0 0.0 1977 2003 2000 1991 1983 1982 1961 1996 1995 1987 1986 1978 1974 1973 1970 1969 1965 1964 1999 1990 2001 1971 1962 1998 1997 1994 1993 1992 1989 1988 1981 1980 1979 1976 1968 1967 2002 1985 1984 1972 1963 1975 1966 Date (yr)

Fig. 3.23 Correlation between rainfall and sedimentation rate

A moderate correlation between the rainfall data and sedimentation rate indicates that dramatic increase in sediment influx is probably due to some artificial reasons rather than natural. Tachibana (2000) stated that Malaysia has played an important role as suppliers in international wood markets since the 1960s. The BLC like other rainforest catchments in Malaysia has been significantly harvested for timber and log during the first Malaysia Plan (1960–1965). The real history of timber harvesting is not available and most official data is only available after 1970 with the contribution of government agencies in land development projects. Stratigraphic descriptions and the 210Pb dating using CRS model were clearly confirmed that the grey mud of Layer 1 was deposited prior to 1950 and the grey to dark sandy mud of Layer 2 was settled between the year 1950 and 1970 in Bera Lake. The low variation in composition and sedimentation rate of Layer 1 indicates a calm condition without an effective anthropogenic change. However, high contribution of organic matters in composition and significant variations in sedimentation rate in Layer 2 are comparable with natural and anthropogenic changes that have revealed in Fig. 3.13. According to Henson, five FELDA projects were carried out in Pahang State between 1970 and 1995. Land development phases were conducted between the years 1970 and 1975, 1976 and 1980, 1981 and 1985, 1986 and 1990, and between 1991 and 1995, respectively. Further phases of land development are still continued by the locals since 1995. Tan et al. (2009) reported that a typical oil palm land development project is comprised of six main stages, the most important of which is land clearing. The duration of land clearing and preparation for 2,000 ha of oil palm farm usually takes about 14 months. Severe and continuous exposure of Permian, 3.8 Discussion 99

Triassic–Jurassic continental rock units (Semantan Formation) during the FELDA projects has thus led to several tons of sediments being transported to Bera Lake wetlands and open waters. Deposition of the deeply eroded sediments in the Bera Lake basin started with the white sandy mud layer. A clear correlation between the start of FELDA land development projects in the catchment area and the increased sediment supply is affirmed by 210Pb dating and 137Cs horizons. A dilution of the atmospheric 210Pb fallout by increased sedimentation coincided with FELDA projects in the Bera Lake sediment column. Additionally, the normal process of sediment accumulation of pre-1970 was interrupted. For instance, the pre-1970 mean sedimentation rate in master Core 2 was calculated to be 0.06 0.02 g cm2 year1. This mean deposition rate increased dramatically to 1.13 g cm2 year1 after implementation of the first and second FELDA projects from 1972 to 1980. The fifth FELDA land development phases, was also recognized as a main contributor to deposition of the white sandy mud layer. An influx of sediment at the top of sediment column was correlated with a huge flood in December, 2007, when 1,200 mm of rain were precipitated in 11 days and the water level rose to drown the whole Bera Lake lowland area. This natural event was also verified remarkably by the highest reworked 137Cs activity at the top of the sediment column. The 137Cs value was 5 times greater than the value of the 1963 maximum artificial fallout of 137Cs in master Core 2. The 210Pb dating of core samples, however, points out that the environmental impact was not recorded uniformly in all parts of Bera Lake. For example, the impacts of the first FELDA project in the sediment profile at the north end of Bera Lake appeared 2 years later than those at the south end. Maximum sedimentation rates in the south, middle and north of Bera Lake were recorded in 1987, 1980 and 1974 with mean values of 3.3, 1.3, and 0.43 g cm2 year1, respectively. These influxes of sediments occurred during the first, second, and fourth FELDA development projects. Clear differences exist between sediment influx prior and post FELDA land development projects (Fig. 3.13). Sedimentation dramatically increased 22 times by the first and second phases when white sandy mud was deposited at Bera Lake. Land preparation in the BLC involved the burning of the felled trees. A remarkable charcoal horizon was detected at the lower contact of Layer 3 when terrestrial sediment was deposited in all sectors of Bera Lake. Plotting of 210Pb dating using the CRS model with deforestation phases revealed that significant sediment delivery from the catchment area into Bera Lake was delayed by 1–2 years. Organic-rich to peat sediments at the top of the Bera Lake sediment column were deposited mostly since 1994 when highly organic waste production was associated with the oil palm plantations. Available data (MPOC 2007) shows that oil palm plantations accumulate 8.3 t of biomass per year; a value that is 2.5 t more than a rain forest produces per year. In addition, the annual dry matter productivity of an oil palm plantation is about 36 t, as compared with about 26 t for a rain forest. 100 3 Sedimentation Rate in Bera Lake

According to the distribution of oil palm plantations and rainforest areas in Bera Lake, annual bio mass productivity was calculated to be 1.5 million cubic meters. This amount of biomass could potentially cover BLC at a rate of 0.4 cm year1. In such a situation, however, runoff will lead to organic matter and organic-rich sediments being the main sediments deposited in Bera Lake. The mean sediment supply after the fifth FELDA development project gradually decreased to 0.2, 0.21, 0.153, 0.29, 0.11, 0.08, 0.13, 0.24, and 0.17 g cm2 year1 in Cores 1, 2, 3, 4, 5, 6, 7, 8, and 9, respectively. A clear contribution of this research project towards knowledge is demonstrating the capability of 137Cs as an independent time marker and its usefulness in historical studies of sedimentation rates in Malaysia. Although 137Cs activity in soil and sediment profile of Malaysia is very low in comparison with that of the European and American continents, its vertical distribution appeared in an ideal form. Peaks in the 137Cs inventory furthermore, show excellent correlations with anthropogenic changes especially in the upper parts of the Bera Lake sediment columns. Strati- graphic dates based on records of fallout 137Cs and 210Pb supply rates to these core sites have remained relatively constant. The Bera Lake sediments could therefore, be dated by the CRS model. Another achievement and new finding in this research is the good correlation of the mean sedimentation rates based on a slope regression model and the stratigraphic dates of 137Cs time markers in Malaysia. In other word, the stratigraphic dates of 137Cs horizons (1954, and 1963) have confirmed application of slope regression model in which 210Pb unsupported values were plotted against cumulative mass depth. This study therefore, recommends application of a slope regression model as a simple dating method for further research in areas Malaysia with similar conditions as those at Bera Lake. Questions and uncertainties about the adverse impacts of land use changes on the sedimentation rates in Bera Lake have also been clearly answered in this study. The main objective of the present research has been successfully achieved with sedimentation rates in different parts of Bera Lake and the historical trend of deposition, calculated using several methods and results confidently confirmed methodologies and each others. Now the RAMSAR site decision makers could estimate adverse effects of previous land development projects on Bera Lake sedimentation rate. Therefore, they could provide a sustainable land use programme for further replanting in BLC area to avoid any redeposition phases.

3.9 Conclusion

1. Stratigraphic dates based on records of fallout 137Cs indicate that the rate of supply of 210Pb to Bera Lake has been relatively constant and afﬁrmed the applicability of the CRS model to providing a chronology of the Bera Lake sediments. 3.9 Conclusion 101

2. The assumptions necessary for application of the CIC model were not met in this study. 3. 210Pb and sediment flux and distribution are remarkably controlled by hydrological circulation and basin morphology. Maximum 210Pb and sedimentation rates, therefore, were calculated to be 159 2Bqcm2 year1 and 2.56 cm year1, in the semi-closed area at north of Bera Lake. 4. Although the low fallout 137Cs inventory in tropical regions is, and has been, shown by this and previous studies, the achieved results stress the ability of 137Cs for soil redistribution studies and as a confirmation time marker in sedimentation studies in tropical areas. 5. The well-resolved 137Cs peaks were recorded at similar depths of 40 cm in master Cores 2, 5, and 8, and indicate the 1963 maximum 137Cs fallout due to atmospheric bomb testing. This firmly emphasizes the accuracy of 210Pb dating using the CRS model in the present study. 6. The chronology of four individual stratigraphic layers showed that Layers 1, 2, 3, and 4, were deposited in Bera Lake before 1950, from 1950 to 1970, from 1970 to 1993, and in 1994, respectively. 7. The mean pre-1950 sedimentation rates in master Cores 2, 8, and 5, calculated at 0.06 0.02, 0.05 0.01, and 0.14 0.26 g cm2 year1, point out a uniform accumulation rate in the south and middle of Bera Lake and an increase northward along the main stream. 8. Layer 2 has been deposited in the south, middle and north of Bera Lake at rates of 0.35 0.34, 0.28 0.36, and 0.21 0.34 g cm2 year1, respectively. 9. Two vivid peaks in sediment flux were observed in Layer 2 and distinctively occurred in 1954 2 and 1962 2 with maximum rates of 1.88 and 2.74 g cm2 year1 in Cores 7, and 5, respectively. The first peak was induced by a non-documented natural event whilst the second one was caused by maximum timber extraction during the first Malaysia National Plan. 10. Severe erosion-induced deposits in Bera Lake accumulated with an influx of white sandy mud sediments in Layer 3 prior to, and post, maximum deforestation phases. These were deposited in the south, middle and north of Bera Lake at mean rates of 0.48 0.48, 0.54 1.2 and 0.17 0.12 g cm2 year1, respectively. 11. Different contributions of FELDA projects, in terms of sediment supply were recorded in different sections of Bera Lake. The fifth FELDA land development phase, however, was recognized as the main contributor to the deposition of the white sandy mud layer. 12. Sedimentation of the organic-rich sediments of Layer 4 in all parts of Bera Lake has involved an average rate of sediment flux of 0.2 0.1 g cm2 year1 since 1994, with high organic waste production associated with the oil palm plantations. 13. A clear sediment flux recorded at depths of 2–4 cm with maximum sedimentation rates of 0.32 and 0.29 g cm2 year1 in Cores 2 and 8, signaled a huge flood in 2007, when 1,200 mm of rain was precipitated in 11 days. This natural 102 3 Sedimentation Rate in Bera Lake

event was also remarkably verified by the highest reworked 137Cs activity at the top of the Bera Lake sediment columns. 14. Mean sedimentation rates based on the stratigraphic dates of fallout 137Cs in Cores 2, 3, and 8 reveal a close similarity with mean sedimentation rates determined 210 with a slope regression model where In Pbex was plotted against depth. 15. The mean sedimentation rate in the wetlands and open waters based on fallout 137Cs and the proportional conversion model was calculated to be 1.02 cm year1; a value which shows significant similarity with the sedimentation rate at Bera Lake of 1.11 cm year1 which was calculated using trap efficiency and sediment discharge values.

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Walling DE (1999) Linking land use, erosion and sediment yields in river basins. Hydrobiologia 410:223–240 Wu¨st RAJ, Bustin RM (2004) Late Pleistocene and Holocene development of the interior peat- accumulating basin of tropical Tasek Bera, Peninsular Malaysia. Palaeogeogr Palaeoclimatol Palaeoecol 211(3–4):241–270 Zapata F, Garcia-Agudo E (2000) Future prospects for the 137Cs technique for estimating soil erosion and sedimentation rates. Acta Geologica Hispanica 35(3–4):197–205 Chapter 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Abstract The catchment of Bera Lake in Pahang State, Peninsular Malaysia has experienced severe land use changes since 1972 with some 340 km2 (out of a total area of ~600 km2) having been converted to oil palm and rubber plantations and in some places, newly cleared for monoculture. The proportional model using the 137Cs radionuclide was recognized as being the most suitable conversion model for estimating soil redistribution in the catchment as the deforested land has been cultivated once in a medium-term range of 30–40 years. Thirty-ﬁve bulk core soil samples were taken to a depth of 25 cm in areas of different land use and known dates of tillage commencement in the catchment. Ten bulk core samples were also collected in the bottom sediments of wetlands and open waters to estimate accumulation rates in these sink areas. Individual land development districts with known elapsed times from start of tillage allowed determination of soil redistribution rates and preparation of a soil redistribution map. A mean soil erosion rate of 915 345 t h1 year1 was determined in areas of cleared land, whereas rates of 117 36, and 70 35 t h1 year1, were determined in areas of developing, and developed, oil palm and rubber plantations, respectively. The overall accumulation rate of eroded soils within the wetlands and open waters was determined to be 1.025 cm year1 since 1995. The Bera Lake catchment soil redistribution map is the ﬁrst attempt in Malaysia to map soil redistribution using the 137Cs technique on a catchment scale. The soil redistribution map will provide good guidelines for future soil conservation practices and sustainable land use programs.

Keywords Bera Lake catchment • 137Cs radionuclide • Land use changes • Proportional model • Soil redistribution

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 107 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2_4, © Springer Japan 2014 108 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

4.1 Introduction

Soil erosion and redistribution of eroded materials in the BLC has been investigated using radioisotopes. This is one of the most important objectives of the present research. In this chapter, the actual results of the applications of models in soil erosion and redistribution of eroded materials in the study area are presented. Finally, the results are presented in a soil erosion map of BLC. An important theme in reviewed literature is the application of radioisotopes to estimate rate of soil loss. (Ritchie and Ritchie 2005) has stated that the 137Cs technique is the only technique that can be used to make actual measurements of soil loss and redeposition quickly and efﬁciently. Analytical methods and modeling of soil erosion estimation using 137Cs have improved remarkably over the last four decades. According to Ritchie and Ritchie (2005) published papers on the 137Cs technique commenced in 1961 and approached maximum number in 1999 when new models have introduced by Walling and He (1999), Robbins (1980), and IAEA (1995). These fundamental researches were continued by Poreba (2006), and Mabit et al. (2008a, b) who have evaluated models as well as advantages and limitations of using 137Cs and 210Pb for assessing soil erosion. Several reviewed papers have also used this technique for estimating soil erosion around the world such as Garcia-Sanchez et al. (2009), Sidle (2009), Huh and Su (2008), Jiyuan et al. (2008), Li et al. (2007), Cha et al. (2006), Rezzoug et al. (2006), Stark et al. (2006), Yunfeng et al. (2005), and Reguigui and Landsberger (2005). There are several studies around the world which have used radioisotopes as tracers to detect historical events in watersheds and basins in order to ﬁnd sources of contamination and to emphasis the role of soil and sediment grain size and organic matters in radioisotope behavior (Covay and Beck 2001; Meyers and Lallier-verge´s 1999; He and Walling 1996; Matsunaga et al. 1995).

4.2 Soil Sampling and Sample Analyses

Soil erosion due to numerous land development projects over the last four decades is recognized as one of important issues at BLC. Soil loss estimation and determination of land development contribution in terms of sediment supply is an important objective of applied limnology. Soil sampling is a vital stage in soil erosion studies using 137Cs and 210Pb techniques. A review of sampling procedures for estimating soil erosion shows that the use of 137Cs is a privileged sampling method. Mabit et al. (2008a) has stated that this kind of sampling method is relatively simple and cost-effective and can be completed in a short time, depending on the sampling density and size of area investigated. Site disturbing during sampling is minimal and will not interfere with seeding and cultivation operations. Furthermore, no disturbing of natural runoff and erosion processes might occur with the installation of bounded erosion plots. 4.2 Soil Sampling and Sample Analyses 109

Fig. 4.1 Soil sampling integrated land use scheme

It is evident that successful soil erosion estimation of a large catchment depends on the setting-up of a proper sampling strategy. For this study, land use districts of the same cultivation date and geological setting (Fig. 4.1), low 137Cs activity and accessibility by roads were the main factors that have affected the sampling pattern. Thirty-ﬁve bulk samples have been taken to a depth of 25 cm with a core sampler of 5 cm diameter at sites of different land use (Fig. 4.2). Ten bulk core samples were also collected to a depth of 25 cm in the bottom sediments of wetlands and open water. At each sampling site, six cores of 95.37 cm2 in area were collected in view of the low 137Cs activity in tropical areas, Malaysia. Undisturbed original forest in the RAMSAR site was provided the best opportunity to ﬁnd nine sites for reference samples. The reference sites samples have been chosen at open areas having low slope gradients (grass and bamboo lands) without erosion and sedimentation evidences. Incremental depth sampling to measure 137Cs activity with depth at these reference sites was carried out at 2 cm intervals using a scrapper plate with a cutting edge and having a rectangular metal frame of 875 cm2 in area. The sampling was carried out to a depth of 24 cm where rock fragments were the main soil component and there was only a small clay fraction (Fig. 4.3). 110 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Fig. 4.2 Bulk core samplers in soil sampling from BLC

Fig. 4.3 Scrapper plate applied to take reference samples

4.3 Soil Type of Catchment Area

Soil types of eastern BLC has been surveyed by (Tharamarajan 1980). His study revealed 26 mapping units which have been implemented before FELDA land development projects and these maps are not available. Several soil types and soil 4.3 Soil Type of Catchment Area 111

Table 4.1 Soil particle size distribution at different land use areas Sample ID Land use Clay (%) Silt (%) Sand (%) Classification 1 Oil palm 3.58 30.74 65.68 Sandy loam 2 Oil palm 7.15 34.94 57.91 Sandy loam 3 Oil palm 7.27 48.34 44.40 Loam 4 Oil palm 10.46 54.14 35.40 Silt loam 5 Oil palm 4.84 24.19 70.97 Sandy loam 6 Oil palm 6.31 43.09 50.60 Sandy loam 7 Oil palm 3.14 20.04 76.82 Loamy sand 8 Oil palm 3.34 30.67 65.99 Sandy loam 9 Oil palm 3.46 26.08 70.45 Loamy sand 10 Oil palm 5.11 28.47 66.42 Loamy sand 11 Oil palm 7.36 60.08 32.56 Silt loam 12 Oil palm 6.80 39.46 53.74 Sandy loam 13 Rubber farm 6.70 51.84 41.47 Silt loam 14 Oil palm developing 18.25 58.97 22.78 Silt loam 15 Oil palm developing 8.35 11.03 80.62 Loamy sand 16 Oil palm developing 7.56 47.31 45.13 Loam 17 Oil palm developing 7.10 48.07 44.83 Loam 18 Oil palm developing 8.03 48.39 43.58 Loam 19 Oil palm developing 7.60 46.61 45.79 Loam 20 Oil palm developing 5.04 32.53 62.44 Sandy loam 21 Oil palm developing 7.45 53.26 39.30 Silt loam 22 Cleared land 11.05 40.88 48.07 Sandy loam 23 Cleared land 11.67 60.46 27.87 Silt loam 24 Cleared land 4.17 38.21 57.62 Sandy loam 25 Cleared land 8.52 48.76 42.72 Loam 26 Cleared land 6.03 43.82 50.15 Sandy loam 27 Reference 4.50 35.79 59.71 Sandy loam 28 Reference 6.44 45.88 47.69 Sandy loam 29 Reference 7.14 36.73 56.12 Sandy loam 30 Reference 8.04 52.55 39.41 Silt loam 31 Reference 4.12 29.42 66.46 Sandy loam 32 Reference 8.53 53.41 38.05 Silt loam 33 Reference 7.36 60.89 31.75 Silt loam 34 Reference 9.38 53.13 37.50 Silt loam 35 Reference 9.78 50.10 40.12 Silt loam texture have been classified in BLC. Classified soil texture and soil map are presented in Table 4.1 and Fig. 4.4, respectively. A significant correlation between the soil texture and land use was found at some sub-catchments. Similar soil texture classification in the adjacent land uses and sub-catchments resulted in a selective method in which similar soil texture districts were polygonized. Current soil texture (Fig. 4.4) indeed has been revealed effects of land use change and conversion of original forests to oil palm and rubber plantations. The dominate soil texture in natural rainforest has been Loamy to Silt loam which has changed to Sandy loam and Loamy sand after development of oil palm forests. Furthermore, substrate rocks 112 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Fig. 4.4 Soil texture classiﬁcation at BLC have dictated soil texture at northeast of catchment where granite rocks are controlling distribution of sandy grain size particles and Loamy sand soil texture. Field observations and laboratory analysis showed the soils of the BLC to be Ferralsols; the soils with brownish yellow, yellow and red colors, having developed on Permian, and Triassic sedimentary and igneous rocks. Post-Semantan Redbeds Formation has signiﬁcantly dictated soil characteristics in terms of texture and color especially in the fourth sub-catchment. Ferrasols have been appeared with maximum, and average, thickness of 1, and 0.2 m, respectively. Organic-rich clays and peat are also found in the central part, and along the main channel, of Bera Lake.

4.4 Soil Redistribution Models

In qualitative approaches to estimate soil redistribution in any area, the 137Cs inventory at individual sampling points needs to be compared with a reference inventory from a site representing the local fallout input and where there is neither erosion nor deposition. A measured inventory value for an individual sampling point that is less than the reference value is thus indicative of erosion, whereas 4.4 Soil Redistribution Models 113

Table 4.2 List of parameter requirements for individual models Model Parameters required Proportional model and Simplified Tillage depth, bulk density, year of tillage commencement mass balance model Mass balance model Tillage depth, year of tillage commencement, proportional factor, relaxation depth, annual fallout fluxa Mass balance model with tillage Tillage depth, tillage constant, proportional factor, relaxation depth, slope length and slope gradient for each section of the transect, annual fallout fluxa Diffusion and migration model Diffusion coefficient, relaxation depth, migration coefficient, annual fallout fluxa Profile shape model Profile shape factor aOnly required for 137Cs models an inventory value greater than the reference value pointed out deposition. Poreba and Bluszcz (2008) has noted that different empirical and theoretical models have been developed to convert 137Cs measurements to quantitative estimate of erosion and deposition rates (Rogowski and Tamura 1970; Walling and Quine 1990; Walling and He 1999). A PC-compatible software package has been introduced by Walling and He (1999), contains an advanced model that can be used for both cultivated and uncultivated areas as well as contribution of fallout 210Pb and 7Be radionuclides. The Proportional Model, Mass Balance I, II, and III, Profile Distri- bution Model and Diffusion and Migration Model were developed for cultivated and uncultivated land in different situations (Walling and He 1999). Application of each model requires establishment of several parameters and the recognition that the individual model, is different in terms of its underlying assumptions, process description and representation of temporal variation (Walling 1999) (Table 4.2). Application of the models to the study area revealed problems in estimating erosion rate on deforested land, as the FELDA districts had been first cleared of natural forest and exposed before being planted with, and covered by, oil palms or rubber trees. The mass balance models could be not used under these conditions as the models assume that the soil is cultivated every year or most years, and the soil is well-mixed with 137Cs uniformly distributed within the plough layer. Although the proportional model, which has been used by some researchers to estimate erosion rates on cultivated land, has been shown to be inappropriate for normal cultivated soils, it can in fact be also suitable for soils that were cultivated initially and then remain uncultivated (Walling 1999). For this model the amount of soil loss is calculated from the ratio of the 137Cs measured at a sampling point to the local reference inventory; the proportion of the original 137Cs (represented by the reference inventory) thus indicating what has been lost. It is also necessary to assume that little or no erosion occurred under the original forest cover. This is a reasonable assumption for the BLC area which was covered by dense rainforest prior to deforestation and development. In addition, it can be assumed that activities associated with the forest clearance are responsible for the mixing and existence of 114 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

137Cs into the plough layer or tillage depth. The equation for this model can be written as follows (Walling and Quine 1990):

BdX Y ¼ 10 ð4:1Þ 100TP where: Y ¼ Mean annual soil loss (t ha1 year1); d ¼ Depth of the plough or cultivation layer (m); B ¼ Bulk density of soil (kg m3); 137 X ¼ Percentage reduction in total Cs inventory deﬁned as (Aref A)/(Aref 100) T ¼ Time elapsed since the initiation of 137Cs accumulation or commencement of cultivation, whichever is later (year); 137 2 Aref ¼ Local Cs reference inventory (Bq m ); A ¼ Measured total 137Cs inventory at the sampling point (Bq m2); P ¼ Particle size correction factor for erosion. According to Turner and Gillbanks (2003) the mean tillage depth for cultivated oil palm/rubber farms has been 0.3 m. The default value for the particle size correction factor for erosion of P ¼ 1 in the PC-compatible models (Walling 1999) was used in the running of proportional model. Details of the other conversion model with their advantages and limitations are available in Walling (1999).

4.5 137Cs and 210Pb Inventories in Soil Samples

Atomic bomb-derived nuclides, however, are difficult to detect in the soil profiles of equatorial areas. Previous studies in Malaysia (Neergaard et al. 2008; Othman et al. 2003), Indonesia (Barokah et al. 2007; Suhartini 2006), Vietnam (Hien et al. 2002; Hai et al. 2008), Philippine and Sri Lanka IAEA (2003), and in Taiwan (Chiu et al. 1999) have highlighted the applicability of 137Cs in measuring rates of soil redistribution in tropical areas have also emphasized the low activity of 137Cs (<400 Bq m2) in accordance with that in tropical Australia (Hancock et al. 2008). The expected low activity of 137Cs in Malaysia was thus anticipated in this study and affected the sampling strategy. The reported mean 137Cs reference inventory in Indonesia has been varied 261 37 and 286 47 Bq m2 (Barokah 2007; Suhartini 2006), varied between 450 280 and 170 160 Bq m2 in Philippines (IAEA 2003). The 137Cs inventory at the reference sites has been ranged between 237 and 1,097 Bq m2 in Vietnam (Hien et al. 2002; Hai et al. 2008), diverse between 154 and 317 Bq m2 in Taiwan (Chiu et al. 1999), and in tropical Australia was varied 129 and 209 Bq m2 (Hancock et al. 2008). The mean value of the 137Cs reference inventory was calculated to be 125.39 36 Bq m2 with the coefficient of variation (CV) being 0.29 and ranged 85–193 Bq m2. 137Cs reference inventory in study area is in the range of 137Cs 4.5 137Cs and 210Pb Inventories in Soil Samples 115

Fig. 4.5 Variation of 137Cs activity with depth at the reference site

inventory in tropical Australia and Philippines and lower than reference inventories in neighbor countries. Mabit et al. (2008b) has stated that the CV of reference samples in forested sites is large (0.19–0.47), but low in pasture and grassland sites (0.051–0.41). The CV of the reference samples is of low-variance and therefore, considered to be reliable information for assessment of the base level of 137Cs with moderate spatial variability in fallout inputs. Reference samples in the study area have an average clay content of 7.25 %, while the average silt and sand contents are 46.43, and 46.31 %, respectively. When the 137Cs inventory in all samples was compared with the soil particle sizes, it showed a moderate correlation with silt sized particles (r ¼ 0.4; p < 0.05), but a weak correlation (r ¼ 0.2; p < 0.05) with sand sized particles. A strong positive correlation (r ¼ 0.74; p < 0.05) was found between 137Cs inventory and ﬁne grain size (mud fraction) of reference samples. The data thus highlights the important role of parent rocks and rate of soil disturbing in the study area in terms of 137Cs adsorption in the soil proﬁle. Strong negative correlations between 137Cs inventory (r ¼ 0.7; p < 0.05) and TOC (r ¼ 0.92; p < 0.05) versus depth found in reference sample (Fig. 4.5). For the depth range of 0–4 cm, the forest soils mainly consist of organic material with little inorganic compounds and thus show low 137Cs activity. The scattered plan of sampling as well as variations in slope gradient, parent rocks and rate of soil mixing during planting of oil palm and rubber has caused variation in 137Cs activity and particle size distributions of samples (Table 4.3). It is 116 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Table 4.3 137Cs inventory, grain size distribution, and classification of studied samples Bulk Sample density Csl37 Clay SOI Sand ID Land Use (kg m3) (Bq m2) (%) (%) (%) Classification 1 Oil palm 1,405 103.72 3.58 30.74 65.68 Sandy loam 2 Oil palm 1,472 79.40 7.15 34.94 57.91 Sandy loam 3 Oil palm 1,275 69.91 7.27 48.34 44.40 Loam 4 Oil palm 1,137 97.46 10.40 54.14 35.40 Silt loam 5 Oil palm 1,130 45.00 4.84 24.19 70.97 Sandy loam 6 Oil palm 1,996 47.22 6.31 43.09 50.60 Sandy loam 7 Oil palm 1,178 67.71 3.14 20.04 76.82 Loamy sand 8 Oil palm 1,533 77.44 3.34 30.67 65.99 Sandy loam 9 Oil palm 1,230 79.53 3.46 26.08 70.45 Loamy sand 10 Oil palm 1,200 2.20 5.11 28.47 66.42 Loamy sand 11 Oil palm 1,573 36.50 7.36 60.08 32.56 Silt loam 12 Oil palm 935 246.64 6.80 39.46 53.74 Sandy loam 13 Rubber farm 1,258 167.80 6.70 51.84 41.47 Silt loam 14 Oil palm 1,623 30.83 18.25 58.97 22.78 Silt loam developing 15 Oil palm 1,231 59.04 8.35 11.03 80.62 Loamy sand developing 16 Oil palm 1,300 41.26 7.56 47.31 45.13 Loam developing 17 Oil palm 1,230 78.35 7.10 48.07 44.83 Loam developing 18 Oil palm 1,478 43.88 8.03 48.39 43.58 Loam developing 19 Oil palm 1,140 60.48 760 46.61 45.79 Loam developing 20 Oil palm 1,580 45.00 5.04 32.53 62.44 Sandy loam developing 21 Oil palm 1,478 51.92 7.45 53.26 39.30 Silt loam developing 22 Cleared land 1,791 20.84 11.05 40.88 48.07 Sandy loam 25 Cleared land 1,407 1.74 11.67 60.46 27.87 Silt loam 24 Cleared land 989 43.64 4.17 38.21 57.62 Sandy loam 25 Cleared land 1,409 72.37 8.52 48.76 42.72 Loam 26 Cleared land 1,536 17.10 6.03 43.82 50.15 Sandy loam 27 Reference 1,290 85.00 4.50 35.79 59.71 Sandy loam 28 Reference 1,359 96.40 6.44 45.88 47.69 Sandy loam 29 Reference 1,314 98.00 7.14 36.73 56.12 Sandy loam 30 Reference 941 137.60 8.04 52.55 39.41 Site loam 31 Reference 1,754 100.01 4.12 29.42 66.46 Sandy loam 32 Reference 1,366 193.00 8.53 53.41 38.05 Site loam 33 Reference 1,166 153.40 7.36 60.89 31.75 Site loam 34 Reference 1,246 157.00 9.38 53.13 37.50 Site loam 35 Reference 1,164 108.10 9.78 50.10 40.12 Site loam 4.6 Soil Loss Estimation 117 to be noted that soils in the developed lands covered by oil palm and rubber plantations have a sandy loam texture. Soil profile in areas still being developed or covered by young oil palm and rubber plantations has a loamy texture. In other word, young oil palm states have a short duration of exposure and erosion rather than developed lands.

4.6 Soil Loss Estimation

Individual analyzed samples of each FELDA district show clearly the effects of the dates of start of deforestation on the soil loss and erosion rate in the BLC (Table 4.4). This study shows that different land use in areas of similar topographic and parent rocks results in different rates of soil loss in the BLC. The results show the mean percentage soil loss for developed oil or rubber plantations in the different subcatchments is 55 22 % with a CV of 0.41. The mean value of erosion, therefore, gained is 70 35 t h1 year1 with a CV of 0.5. The tillage depth was 250 kg m2 (ca. 25 cm) and results meaning that 137.5 kg m2 (or ca. 13.75 cm) has been lost by erosion since then land clearance. The mean erosion rate during the first, second, third, and the fourth FELDA land development projects based on their tillage beginning date has been 0.58 0.15, 0.47 0.17, 0.71 0.41, and 1.13 0.13 cm year1, respectively. The maximum amount of soil redistribution was obtained 119 t h1 year1 in the north-east of catchment Bera-Selatan (4) oil palm district. The bedrock comprises red colored, continental facies rocks, mainly areno-argillaceous strata with rudaceous and carbonaceous bands of the Redbeds Formation (This is probably the Tembeling Formation). As a result, there is the maximum erosion rate of 1.56 cm year1 here (Fig. 4.6). On the other hand, the lowest soil loss, erosion magnitude and medium-term erosion rate gained was 27.72 %, 30.42 t h1 year1, and 0.35 cm year1, respectively, in Triang-Selatan (1) oil palm district which was developed in 1979 in the north west of the catchment. Intense surface erosion here led to removal of the fine grains and increasing concentrations of coarse grains at the soil surface (Fig. 4.7a); a feature similar to that of a desert pavement. Stone pillars (Fig. 4.7b) are common features in the study area where a gravel sized particle forms the cap rock for a column of fine grains. Continued erosion leads to collapse of the pillars and repetition of the surface erosional processes. Literature shows that most of previous studies in neighbored countries have been applied 137Cs technique in the different land use scheme or conversion models in comparison with the BLC. Nonetheless, the Proportional model was used in Seri Lanka and Philippines (IAEA 2003) to estimate soil redistribution in a converted rainforest to the monoculture (tea and coffee farms) showed an erosion rate of 43 and 33 t h1 year1, respectively. These values have been calculated in the quite smaller farms, non-machinery deforestation, and different tillage commencement. They could be comparable with the lowest magnitude of erosion in developed lands in BLC although the overall situations have been quite different. 118 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Table 4.4 Soil loss, erosion magnitude, and erosion rate at BLC Elapsed Sample Sub- Soil lost Erosion time Erosion rate ID catchment Land use (%) (t ha1year1) (year) (cm year1) 1 1 Oil palm 21.12 36.49 32 0.29 2 2 Oil palm 44.67 65.75 30 0.50 5 3 Oil palm 27.48 40.43 26 0.35 4 4 Oil palm 2,917 35.53 28 0.35 5 4 Oil palm 67.30 121.21 27 0.83 6 8 Oil palm 56.32 86.47 39 0.48 7 10 Oil palm 64.92 58.83 25 0.87 8 11 Oil palm 49.52 87.59 25 0.66 9 12 Oil palm 58.79 90.40 25 0.78 10 12 Oil palm 97.80 140.83 25 1.30 11 12 Oil palm 81.09 153.06 25 1.08 12 12 Oil palm 27.79a 26.09a 25a 0.37a 13 9 Rubber farm 14.48a 34.15a 16a 0.24a 14 4 Oil palm developing 71.48 144.96 16 1.49 15 5 Oil palm developing 57.09 131.78 16 1.19 16 6 Oil palm developing 70.01 170.65 16 1.46 17 2 Oil palm developing 45.40 55.85 16 0.95 18 7 Oil palm developing 56.12 155.52 16 1.17 19 8 Oil palm developing 68.28 186.23 16 1.42 20 2 Oil palm developing 68.64 108.33 16 1.43 21 9 Oil palm developing 63.82 176.93 16 1.33 22 8 Cleared land 84.85 1,519.73 3 9.43 23 1 Cleared land 98.79 1,389.92 3 10.98 24 6 Cleared land 56.05 638.96 3 6.23 25 8 Cleared land 47.40 667.90 3 5.27 26 7 Cleared land 82.90 1,273.34 3 9.21 aRemark of soil accumulation and deposion rate

Soil erosion rates in planted oil palm/rubber farms in previous studies (Leigh and Low 1973; Malmer 1990; Shallow 1956; Douglas et al. 1992; Paramananthan and Eswaran 1984) have been reported as 56 20 t h1 year1. This value which has been calculated using the Universal Soil Loss Equation (USLE) appears to under- estimate soil erosion when compared with the results of the Proportional model and 137Cs fallout radionuclide inventory. Further work, therefore, is needed to calibrate the empirical USLE Method with the 137Cs technique in order to estimate soil erosion in the BLC. Although different assumptions and parameters in 137Cs technique and USLE dictated different soil erosion values, but oil palm plantations have developed in a similar situation in different parts of Malaysia. One form of land use which inﬂuenced soil redistribution in the BLC is developing oil palm/rubber plantations. They involve land with partially covered ground surfaces as well as partially covered with very young planted trees, or areas of re-planted oil palm. The updated land use map and a published Report (Henson 1994)show 4.6 Soil Loss Estimation 119

Fig. 4.6 137Cs inventories, soil loss and soil erosion rate controlled by land use types

Fig. 4.7 Intense surface erosion and its feature in exposed areas that such areas were mainly cleared by local residents after nomination of the BLC as a RAMSAR site and after prohibition of FELDA development projects in 1994. Tillage commencement dates of the areas of developing plantations are thus assumed to be 1995 with the total elapsed period being 16 years. The results clearly conﬁrmed the erosion magnitude of developing lands with a mean soil erosion rate of 117 31 t h1 year1 and a CV of 0.3. The mean soil loss percentage in these 120 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Fig. 4.8 Intense surface erosion observed at recent cleared and exposed lands developing areas was furthermore, calculated to be 63 9 with a CV of 0.14. This indicates that values of soil loss in the developing lands have been similar for the past two decades with the lowest variance. According to the tillage depth (250 kg m2) and tillage commencement date, soil loss and the mean medium-term soil erosion rate in the developing lands has been 156.5 kg m2 (or ca. 15.56 cm) and 1.57 0.24 cm year1, respectively. The maximum rate of erosion determined for developing lands is 1.79 cm year1 in the RAMSAR site district where there has been encroachment by local residents. Field observations show that most of the recent land being developed in the BLC is being cultivated with rubber trees. Rubber trees are preferred to that of oil-palm by the local residents in view of easier land preparation, maintenance, and harvesting (Henson 1994). The erosion magnitude in BLC is comparable with soil erosion in the Seberang Perai Selatan area, Penang State, Peninsular Malaysia, where the highest contribution of soil loss among cultivated lands was recorded for rubber states to be 122 t h1 year1. This value is much higher than that of oil palm plantations with a soil loss of 34 t h1 year1 (Shamshad et al. 2008a). Serious erosion is found at cleared lands in the BLC. Recent encroachments into the RAMSAR site by local residents have been detected at 187 locations where the ground surface is entirely cleared and exposed to weathering and erosion processes. A satellite image (Spot 5, 2009) of spatial resolution 10 m served as the base for recognizing cleared lands in the BLC. It can therefore, be assumed that tillage of cleared lands started in 2008 as normal land clearing and preparation takes 12–14 months for a 2,000 ha land development project (Tan et al. 2009). Such situation, led to a mean soil loss percentage of 74 21 with a CV of 0.29 from cleared lands. Maximum, minimum, and mean soil loss magnitudes of 1266, 532, and 915 345 t h1 year1 respectively, with CV of 0.4 were calculated for the newly open lands. As a result, the medium-term mean erosion rate is currently 7.4 2.1 cm year1 with a CV of 0.29 in the cleared lands at BLC (Fig. 4.8). The maximum rate of erosion furthermore, occurs in cleared lands in the subcatchment 1 at the north of the BLC with a value of 9.88 cm year1. The results show that the erosion rate in cleared lands in the RAMSAR site is about half the 4.7 Nutrient Content in Bera Lake Catchment Soil Proﬁle 121

Fig. 4.9 Burning as land preparation procedure observed at north of study area value that has calculated for areas that were previously covered by oil palm and recently cleared for replanting of oil palm/rubber. Site preparation burning as one of phases of land development has caused a signiﬁcant increase in soil loss from the BLC (Henson 1994). The importance of forest burning in the increase of soil loss rates has reported by Field and Carter (2000). Further studies need to evaluate forest burning in BLC, but available evidences of forest burning in the land preparation clearly manifested in Bera Lake sediment column as the charcoal horizon especially at lower contact of white sandy mud deposits. Recent felled-land burning can be found at the north of the study area where some land has been converted to rubber smallholdings (Fig. 4.9). Models calibrated for cultivated lands have usually assumed very low soil loss from natural forest (Walling 1999). Ling et al. (1979), Wiersum (1985, unpublished), Northcliff (1990, unpublished), Malmer 1990, and Shamshad et al. (2008a) have estimated soil loss from Malaysian natural rainforests to be 10, 6.2, 5.1, 0.036 and 0tha1 year1, respectively. These values were determined using the USLE equation. Although it can be assumed that soil erosion in the natural rainforest at BLC is very low, ﬁeld observations show that recent encroachments into the forest area for timber and other natural products have led to erosional features as gullies and landslips. A mean soil erosion value of 7 t ha1 year1 from the just mentioned studies has been used to illustrate soil loss from the original forest at BLC.

4.7 Nutrient Content in Bera Lake Catchment Soil Proﬁle

Agronomic activities are well-known anthropogenic projects which have signiﬁ- cantly changed features of Malaysian rainforests. Progressive global demands for oil palm as well as a suitable agro-climatic situation and Malaysian land development projects since 1961 have contributed to establish 20 million hectares of planted land. Although oil palm plantations are introduced as sustainable agricultural practices (Basiron 2006), they signiﬁcantly affect soils and sediments nutrient concentrations 122 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Table 4.5 Nutrient contents, 137Cs activity, and physical properties of soil samples Bulk density Cs-137 Land use (kg m3) TC (%) TN (%) (Bq m2) Clay (%) Silt (%) Sand (%) Developed oil palm and rubber plantations (n ¼ 12) Mean 1,400 1.22 0.13 66.11 5.72 37.66 56.62 STDEV 261 0.62 0.07 30.22 2.41 13.13 15.21 CV 0.19 0.51 0.53 0.46 0.42 0.35 0.27 Developing oil palm farms (n ¼ 8) Mean 1,369 1.33 0.13 64.28 8.45 44.22 47.33 STDEV 173 0.31 0.02 41.15 3.80 14.33 16.07 CV 0.13 0.23 0.16 0.64 0.45 0.32 0.34 Cleared land (n ¼ 5) Mean 1,426 1.09 0.11 31.14 8.29 46.43 45.29 STDEV 290 0.20 0.02 27.50 3.21 8.77 11.11 CV 0.20 0.18 0.20 0.88 0.39 0.19 0.25 Natural forest (n ¼ 9) Mean 1,254 2.40 0.16 137.52 7.21 45.74 46.31 STDEV 234 1.14 0.05 51.53 1.87 9.97 11.87 CV 0.19 0.48 0.31 0.37 0.26 0.22 0.26

(MPOC 2007; Chiew and Rahman 2002; Wakker 2004). In this section, is discussed the nutrient contents, physical properties, and inventories of 137Cs and 210Pb that have analyzed in 35 samples collected from the four groups of land uses in the study area (Table 4.5). Clear variations in nutrient contents and radioisotopes inventories are obtained due to different land uses in the BLC. The geographical distributions of nutrients in the catchment area are presented in Figs. 4.10 and 4.11. The lowest nutrients contents and 317Cs activity obtained are in cleared lands with TOC and TN mean values of 1.09 0.2 % and 0.11 0.02 % with coefficient variations of 0.18 and 0.2, respectively. In this situation, the maximum 137Cs loss has been recorded in cleared land where the lowest mean activity of this fallout radionuclide is determined to be 31.14 27.5 with a coefficient variation of 0.88, in the cleared lands furthermore, percentage losses of carbon, nitrogen and 137Cs that have occurred are 52 %, 31.2 % and 74 %, respectively. A significant negative correlation (r ¼0.82, p < 0.05) between 137Cs content and TOC was obtained in soil samples collected from cleared land. Developed oil palm and rubber plantations are another land use group where deforestation and land development has contributed significantly to decrease nutrient contents and radioisotopes inventories. These areas have already experienced phases of land clearance and development, though the nutrient cycle has only marginally improved. The mean values of TOC and TN obtained are therefore, 1.22 0.62 % and 0.13 0.07 % with coefficient variations of 0.51 and 0.53, respectively. Carbon, nitrogen and 137Cs percentage losses in developed oil palm plantations were calculated to be 49 %, 18.75 %, and 55 %, respectively. Continuous erosion has removed fine particles and a coarsening of soil texture is the dominant process in developed lands in BLC. Therefore, unsupported 210Pb activities in most of the samples were not detected Fig. 4.10 TOC values at different land use districts

Fig. 4.11 TN values at different land use districts 124 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment with the gamma spectrometer. The results show that the average nitrogen loss frequency in the lands being developed for oil palm plantations is similar to that of developed oil palm areas. However, the percentage losses in carbon and 137Cs were 44.6 %, and 62.0 %, respectively. Cultivation of new forest has thus improved carbon contents in the lands being developed. Organic matter has also been derived from the trunks, fallen leaves, and remaining roots and from felled palm tree in replanted area.ss. Chiew and Rahman (2002) showed that the release of EFB in oil palm plantations rebuilt nutrient cycles and increased leaf N, P, K and Mg over and above the effects of EFB or N alone. A mean value of 24,000 1.14 (2.4 %), and 1,600 0.05 mg kg1 (1.6 %) was obtained for carbon and nitrogen contents in rainforest samples. PFE in BLC was nominated as the ﬁrst RAMSAR site in Malaysia, 1994 and the surrounding developed lands established as a buffer zone. Local residents have been deforesting small areas in the RAMSAR site since 1994 and leaving destructive effects on BLC ecosystems. This is in spite of government regulations stipulating that any project beyond 500 ha should have an EIA (ECD 2002).

4.8 Soil Accumulation Rate in Wetlands and Open Waters

Wetlands and open waters covering some 57 km2 in area are recognized as natural soil traps and retention pounds within the BLC. Large amounts of eroded soil has accumulated in Bera Lake sink area which show many depositional features such as sediment dumping in wetlands, narrowing of water bodies by sand barriers and serious depth reduction. In the present study, organic-rich sediments in the uppermost layer of the Bera Lake sediment column were studied in order to ﬁnd out the fate of eroded soil. The study is based on the 137Cs inventory in organic-rich Layer 4, until a depth of 25 cm, similar to the depth of soil samples analyzed for their 137Cs inventory in source area (Table 4.6). The organic-rich layer can be recognized

Table 4.6 137Cs inventory and accumulation rate in wetlands and open waters samples Layer Submerged Sample thickness Porosity Weight bulk density Inventory Accretion Accretion rate ID (m) (%) (kg) (kg m3) (Bq m2) (%) (t ha1 year1) 1 0.22 81.00 0.06 445 367.70 60.97 21.32 2 0.19 79.30 0.09 171 1,139.11 87.40 17.75 3 0.23 79.70 0.09 148 1,097.71 86.93 16.44 4 0.16 89.80 0.06 148 361.52 60.31 5.71 5 0.21 79.10 0.09 143 1,389.44 89.67 9.97 6 0.20 79.40 0.09 169 1,153.38 87.56 22.77 7 0.15 74.00 0.06 134 367.41 60.94 11.14 8 0.20 80.00 0.09 167 1,274.82 88.74 24.70 9 0.25 86.00 0.10 248 4,386.80 96.73 33.23 10 0.16 70.00 0.09 169 2,360.93 93.92 36.28 4.9 Soil Redistribution Map 125 by its very low submerged bulk density (194 93 kg m3), high porosity (0.87 0.07), and very low inorganic content. The 137Cs inventories in samples from the wetlands and open waters were compared with the main reference sample which shows 143.5 Bq m2 137Cs inventory of the same bulk core diameter. The mean 137Cs inventory in submerged soil samples was determined to be 1,390 1,216 Bq m2 with a coefficient variance of 0.87. A great enrichment in 137Cs inventory is thus recognized in the studied samples. Geographical parameters like the dendritic pattern of wetlands and water bodies play an important role in 137Cs enrichment in their sediments. For instance, samples which were collected from semi closed areas at the north of Bera Lake had the highest inventory that was up to four times the value of open water samples. The accretion frequency and rate was also morphologically controlled in the study area. A mean accretion rate of 20 9tha1 year1 with a coefficient variance of 0.49 achieved for the wetlands and open waters. This study indicates that after implementation of the fifth Malaysian land development project between 1990 and 1995 (Henson 1994) oil palm/rubber states were established as the mature forests. Annual biomass productivity based on MPOC (2007) report and an occupied area of rainforest and oil palm/rubber plantations was calculated to be 1.5 million tonnes. Potentially, organic-matter could make a cover the whole of catchment area with 0.4 cm thickness. Therefore, the dominate run-off load and the accumulated soils in the sink area have been organic-rich due to abundance biomass production. The elapsed time for accumulation of organic-rich soils in the study area is assumed to be 16 years after development of mature oil palm/rubber states. Therefore, the mean soil accumulation rate in the wetlands and open waters determined to be 1.025 cm year1.

4.9 Soil Redistribution Map

The soil redistribution mapping technique is based on 137Cs variability as introduced by Mabit et al. (2007, 2008b) where geostatistics was coupled with a GIS in order to create a map of soil redistribution. The method is applicable to small catchments with uniform land use and topographic conditions. Soil redistribution mapping in this study is based on land use and dates of tillage commencement as well as similarities in soil textures and geological setting of each sub-catchment. The FELDA land development districts with certain dates of tillage and elapsed time were the basic units for mapping. Soil erosion values obtained for cleared land with similar elapsed times were extended to other cleared lands within the same sub-catchment. Mean values of soil loss from undisturbed Malaysian rainforest were obtained from previous studies considering natural forest in the BLC. Mean accretion rates for sink areas in BLC furthermore, is based on ten bulk core samples in the wetlands and open waters. The soil redistribution map of BLC (Fig. 4.12)is the ﬁrst attempt in applying the 137Cs technique in Malaysia. It illustrates well erosional and depositional trends in one of the largest catchments in Malaysia. 126 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Fig. 4.12 Soil erosion rate map of BLC

This map prepared valuable guideline for soil conservation and management practices. Decision makers can focus on districts where soil erosion is in a critical condition and experienced intensive erosion.

4.10 Discussion

Soil erosion is a natural process in which different phenomenon occurs. It can occur in short to long-term periods, depending on the original rock, climate, and topographic situations. Human activities have also more recently significantly contributed to shortening soil loss periods. Sedimentary processes immediately started after soil erosion to redistribute eroded soils. Soil erosion at BLC area is controlled by several natural and artificial factors. The low drainage density (2.248 km km2) and semi elongate shape (Horton form factor, 1.12), as well as low slope degree (0–2) of BLC indicates that physiographic factors play a minor role in soil erosion. The tendency to generate surface runoff is therefore, mostly dictated by other factors. On the other hand, physiographic factors have increased infiltration and vegetation cover in the study area. Climate also plays an important role in the study area as in other tropical countries. 4.10 Discussion 127

The mean humidity of 70–90 %, heavy rainfall with a maximum amount of 2,600 mm and the low evapotranspiration rate of 4–4.5 mm/day have an effective impact on soil erosion in the study area. Deep chemical weathering can therefore, be expected in the original bedrock. The Bera and Semantan Formations which are entirely composed of sedimentary rocks cover 96.7 % of the BLC. Their lithology mainly comprises deeply weathered brown-yellowish argillaceous, arenaceous to rudaceous rocks. Undifferentiated strata of massive mudstone, tuffaceous sandstone, siltstone, and conglomerates also outcrop under the soil profiles in the study area. Secondary iron oxide concre- tions as a result of intense chemical weathering of the bedrock are located at lower contact of Bera Formation. Joints and fractures have also increased the depth of chemical and physical weathering. The overall evidence demonstrates that the bedrock is susceptible to weathering and thus contributed significantly to generation of erodible soil profiles. The contribution of natural parameters in soil erosion rates for natural rainforest in different parts of Malaysia have been reported in previous studies (Ling et al. 1979; Malmer 1990; and Shamshad et al. 2008b) using the USLE equation. The mean soil erosion rate has been reported to be 7 4tha1 year1. However, natural parameters have played different roles in the varied type of land uses especially converted lands to agricultural states. The PFE in BLC was nominated as the first RAMSAR site in Malaysia, 1994 and the surrounding developed lands established as a buffer zone. Natural rainforest covered the entire (593.1 km2) BLC prior to land development. The natural forest cover, however, has decreased dramatically to 300.24 km2 by the end of 1994. Despite government regulations stipulating that EIA Reports are needed for any project involving 500 ha and more, the local residents are disregarding this regulation by deforesting smaller areas in the RAMSAR site since 1994. The work of the local residents has thus increased the area of cleared land, rubber and oil palm plantations to 340 km2 (57.3 %) in 2009. This study has demonstrated that land clearing is an on-going process without any proper management practices in the study area. Site preparation by burning is one of the land development phases that have caused a significant increase in soil loss in the BLC (Henson 1994). The importance of forest burning to increase the rate of soil loss has been reported by Field and Carter (2000). A mean soil erosion rate based on previous work using the USLE equation (Leigh and Low 1973; Malmer 1990; Shallow 1956; Paramananthan and Eswaran 1984) was reported to be 56 20 t h1 year1. This value which was calculated using the USLE appears to quite under-estimate soil erosion when compared with the results of the Proportional model (70 35 t h1 year1) and 137Cs fallout radionuclide inventory. In the Seberang Perai Selatan area of Penang State, Malaysia, soil erosion in rubber plantations was reported to have the highest value amongst cultivated lands with a soil loss of 122 t h1 year1 (Shamshad et al. 2008b). The rate of soil loss from rubber plantations in Penang State is close to the mean value of soil loss (117 31 t h1 year1) which has been estimated by the 137Cs technique in the BLC. 128 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

Soil loss from cleared land at two small catchments at Sipitang (Midmore et al. 1996), and at Ulu Segama (Malmer 1990), Sabah, Malaysia calculated using the USLE equation was found to be 6.60, and 16 t ha1 year1, respectively. In these cases, the calculated soil erosion magnitude is under-estimated in comparison with the soil erosion rate (915 345 t h1 year1) calculated with the 137Cs technique in the BLC. It is evident that the size of catchment area al o plays an important role in determining the soil loss by any technique. For instance, Walling (1982) estimated soil erosion in the Cikeruh and Cigulung catchments in tropical Java with areas of 250, and 43 km2 area, at 112, and 10.85 t ha1 year1, respectively. Further work, therefore, is needed to calibrate the empirical USLE Method with the 137Cs technique to estimate soil erosion in the BLC. All in all, soil erosion rate studies using the USLE equation at several catchments in Malaysia indicate under-estimated rates in comparison with soil erosion rates which were calculated with the 137Cs technique at BLC. One of the main contributions in knowledge which has been gained in this research is selection of the Proportional Model from several available models for conversion of soil loss frequency to soil erosion rate. In other words, this model was recognized as the best model for catchments which were deforested once and covered by oil palm and rubber plantations. All assumptions such as exact date of tillage and soil disturbance occasions were met in this model. Although, the Mass Balance I, II, III are known to be more advanced models to reduce uncertainties in calculations, they are not suitable for farms and cultivated lands where there is annual ploughing. Direct communication with Professor Dess Walling from Exeter University who developed the conversion models, has confirmed application of the Proportional Model to estimate soil erosion rate in such catchments which are the most common agricultural style in the Malaysia. The 137Cs technique has allowed preparation of a soil erosion rate map (Fig. 4.8) for BLC where certain land use districts show actual rates of have soil loss based on cultivation dates. According to this map, the annual soil erosion from source areas is calculated to be 4.5 million tones which could potentially cover the whole wetlands and open waters at a rate of 6 mm/year. The 137Cs technique has revealed that the deposition rate in the mentioned sink areas has been 1.025 cm year1 since 1994. Therefore, this research has been successful in achieving one of its main objectives in that it has shown how much and where soil resources of BLC have been removed since and after deforestation phases. The erosion map can also be used as a base map for soil conservation and management practices in the BLC area. According to Tan et al. (2009) oil palm plantations last for about 25 years and they will then be replanted with new oil palm trees or other agricultural crops. In view of this, it can be assumed that the Bera Lake oil palm plantations are old and need replanting. The results of this study can therefore, be used as a guideline for decision makers to take an appropriate policy to approach a sustainable land use scheme at any replantation districts. One of expected environmental impacts of land use changes in BLC is the interruption and disturbance in carbon and nitrogen cycles. Carbon and nitrogen exchange occur by biogeochemical processes among several media like biosphere, pedosphere, geosphere, hydrosphere, and atmosphere of the Earth. The cyclic 4.10 Discussion 129 movement of nutrients is recognized as one of the most important cycles of the earth and allows for nutrients to be recycled in organic and inorganic forms. Rainforests, wetlands and open waters are the main storages of nutrients and they play vital roles in nutrient cycles. Bera wetlands and open waters were introduced as sites of peat accumulation in Malaysia (Phillips and Bustin 1998). Wu¨st and Bustin (2001) have properly stated that there is low ash peat accumulation in the study area. Interruption of, and changes in, the coalification mechanism due to land use changes over the recent decades, however, has been the main gap in their studies. Evaluation of the effects of land use changes on the nutrient cycle in the BLC area and open water was thus considered to be one of the objectives of the present research. This objective was studied by comparing nutrient contents in different land use districts in the catchment area and application of radioisotopes for historical reconstruction of nutrient variations in Bera Lake. Similar to other independent time markers, particular charcoal and organic matter horizons in sediment columns were highlighted to verify 210Pb resultant dates using the CRS model. The highest and the lowest values of TOC were calculated to be 3.8 and 0.14, and 1.09 0.2 %, for rainforest, and cleared lands, respectively. Similarly, the highest and the lowest values of TN were determined at 0.27 and 0.01 %, for rainforest, and cleared lands. The maximum 137Cs loss has furthermore, been recorded in cleared land where the lowest mean activity of this fallout radionuclide was determined to be 31.14 27.5 with a coefficient variation of 0.88. Several mechanisms have contributed to decreasing nutrient contents in the BLC, particularly in cleared land. Clear-felling and burning are two major procedures in land preparation (Tan et al. 2009) for oil palm planting and this has been extensively used by FELDA in the BLC. Malmer (1996) investigated effects of forest burring in the Mendolong catchment area in Malaysia and reported that concentrations of nutrients in suspended load during clear-felling and after burning rose 10–100 times higher than normal conditions. Trammell et al. (2004) estimated that adverse effects of forest burning in terms of nitrogen loss will be equivalent to 4.5 years of atmospheric input. Oxidation and volatilization of nutrients stored in all kinds of fineable vegetation, leaching, surface run/off, and convection of ash are the main mechanisms which promote nutrient loss from ecosystems during and after burning of deforested lands (Fisher and Binkley 2000). In addition, Grigal and Bates (1992) introduced forest burning as one of main reasons to consume nutrients especially nitrogen and some phosphorus by volatilization and escape to the atmosphere. Another destructive effect of forest burning in the land clearing process reported by Debano et al. (1998) which hydrological properties of the soil are significantly decreased. The volume and rate of air and water movement through soil is mainly controlled by pore size and space. Loss of aggregation from the destruction of organic matter binding mineral soil particles decreases pore volume and impedes flow of air and water through the soil. This process affected cleared land in the BLC in terms of bulk density with some 10 % increment on average. 130 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

4.11 Conclusion

1. The 137Cs technique and the proportional model as a conversion method were recognized as suitable methodology for estimation of soil redistribution in Malaysian land development schemes where there has been only a single cycle of deforestation followed by cultivation. All assumptions such as the exact date of tillage and soil disturbance occasions were met in this model. 2. A strong positive correlation (r ¼ 0.74, p < 0.05) was recognized between 137Cs inventories and porosity values of soil samples. Conversely, a significant negative correlation (r ¼ 0.75, p < 0.05) was seen between 137Cs inventories and bulk density values of soil samples. 3. A strong depth-wise negative correlations (r ¼0.92; p < 0.05) between the 137Cs inventories and TOC contents was found in reference samples. 4. FELDA land development districts with specific elapsed times from the start of clearing of the original rainforest, and rates of erosion, provided an opportunity to create a soil erosion map of the catchment area. 5. Mean soil erosion rates of 917 345, 117 36, and 70 35 t h1 year1, were determined in areas of cleared land, developing oil palm and rubber plantations, and developed oil palm and rubber plantations, respectively. 6. The mean erosion rate during the first, second, third, and fourth FELDA land development projects based on their dates of starting tillage has been determined at 0.58 0.15, 0.47 0.17, 0.71 0.41, and 1.10 0.10 cm year1, respectively. 7. Mean medium-term soil erosion rates of 7.4 2.1, 1.6 0.23, and 1.13 0.31 cm year1, have been determined in areas of cleared land, developing oil palm and rubber plantations, and developed oil palm and rubber plantations, respectively. 8. The annual soil erosion from source areas was calculated to be 4.5 million tones which could potentially cover the entire wetlands and open waters at a rate of 6 mm/year. 9. It is concluded that the eroded soils have accumulated in the wetlands and open waters within Bera Lake at a rate of 1.025 cm year1 since 1995. 10. Site preparation by burning is one of the land development phases that have caused a significant increase in soil loss from the Bera Lake catchment. Loss of aggregation from the destruction of organic matter binding mineral soil particles decreases pore volume and impedes flow of air and water through the soil. 11. The prepared erosion map can be used as a base map for future soil conservation and management practices in the Bera Lake catchment area and as a guideline for decision makers to adopt the appropriate policy and approach for sustainable land use schemes at any re-plantation districts. 12. This research firmly recommends using the 137Cs technique and erosion mapping method for other similar catchments in Malaysia. 4.11 Conclusion 131

13. Comparison of soil erosion rates in the Bera Lake catchment in the present study with the 137Cs technique with those employing the USLE equation in other studies show that the USLE equation under-estimates the rates of soil erosion. 14. It is concluded that the nutrient cycle in the Bera Lake catchment is dominantly controlled by the type of land use especially during, and after, the FELDA and local land development projects since 1972. 15. The mean TOC value decreases in the order of 2.4 1.14, 1.33 0.31, 1.22 0.62, and 1.09 0.2 %, respectively, in natural forest, oil palm/rubber developing lands, developed oil palm/rubber plantations, and cleared lands. 16. The mean TN value decreases in the order of 1.6 0.05, 0.13 0.02, 0.13 0.7, and 0.11 0.02 %, in natural forest, oil palm/rubber developing lands, developed oil palm/rubber plantations, and cleared lands, respectively. 17. A strong negative correlation (r ¼ 0.82, p < 0.05) between 137Cs content and TOC was obtained in soil samples collected from cleared land. 18. The burning of felled trees plays the most important role in disturbing the nutrient cycle and self-regulating of developed and developing oil palm soil in the Bera Lake sediment profiles. 19. A clear relationship was established between charcoal and POC horizons and the 210Pb dates of the five deforestation phases by FELDA, especially in the south and the middle of Bera Lake. 20. Total concentration of nutrients in the sediment profiles in the main open water and north of Bera Lake decreased in the order of TOC>K>TN>S>Mg>Ca. 21. It has been concluded that there is upward eutrophication and increase of C/N ratio in the Bera Lake sediment column with maximum values in the topmost organic-rich layer. 22. Nutrient fluxes have been documented with 210Pb dating and CRS model resultant dates as well as validated by 137Cs horizons where organic carbon and nitrogen have increased significantly in white sandy mud and organic-rich deposits in agreement with periods of FELDA land development. 23. The unique fate of nutrients which have been released from the source areas during and after FELDA projects has been revealed in this research. Bera Lake significantly recycles nutrients and stores them in the uppermost layer of the sediment column as organic-rich deposits. 24. Hieratical cluster analysis clearly revealed a strong similarity between nutrients (TOC, TN) contents and Fe, Mn, Zn, As, Ni, Cd, Ca, and V concentrations in the Bera Lake sediment columns. In other words, nutrients as well as Fe and Mn oxides are responsible for enriching harmful metals. 25. Clear eutrophication especially in the north of the basin, indicates that Bera Lake is on the verge of considerable ecological risk when algae bloom, 2 reduction of dissolved oxygen, high levels of NO3 , and reduction of fish population are expected. 132 4 Soil Erosion Rate and Nutrient Loss at the Bera Lake Catchment

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Abstract The Bera Lake basin is a lacustrine mire system and the largest natural lake in Peninsular Malaysia. Three cores were collected from the lake sediment column in order to assess Bera Lake sediment quality and ecological risks for aquatic life and human health. An index analysis approach (Cf,Cd,Er, and IR) and the fallout 210Pb and 137Cs radioisotopes were applied to assess impacts of environmental evolutionary Changes at Bera Lake. Sediment chronology was conducted using the Constant Rate of Supply (CRS) model with the resultant sediment ages being verified by 137Cs horizons. Although the general contamination factors indicates low risk conditions in the Bera Lake basin, the risks associated with individual layers is regarded as moderate to considerable. Five deforestation phases were manifested in the dated sediment cores with distinct variations in heavy metal fluxes since 1972. These phases are in excellent agreement with the dates of land clearance and development projects undertaken over the recent decades. This study highlighted capability of contamination factors and chronological methods in environmental evolutionary studies which its catchment has extensively experienced land use changes. The destiny of fluxed heavy metal into a lake could be revealed using this methodology.

Keywords Bera Lake • Contamination factors • CRS model • Ecological risk Assessment • Radioisotopes 210Pb and 137Cs

5.1 Introduction

Determination of the chemical composition and quality of the sediments at Bera Lake and its’ ecological risk assessment are important goals of applied limnology. In addition, applied limnology has highlighted medium-term heavy metal ﬂuxes into the Lake and contamination of distinct strata. Sediment quality assessments furthermore, will reveal ecological risks due to sediment pollution and provide vital data for ecological risk management of Bera Lake. This chapter discusses the

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 135 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2_5, © Springer Japan 2014 136 5 Sediment Quality and Ecological Risk Assessment of Bera Lake chemical composition of the Bera Lake sediments as well as cluster analyses of the major and minor metals in analyzed samples. Literature was reviewed in order to identify sediment quality guidelines and evaluation methods. The profitable indices which are used remarkably in this research project were Xu (2005), Caeiro et al. (2005), CBSQG (2003), EPA (2001), and NOAA (2000). International standard guidelines motivated this research to evaluate the Bera Lake sediment quality in terms of relevant human health and aquatic life. In addition, literature review revealed that useful and elaborate sediment quality methods were initially presented by Mu¨ller (1979), Hakanson (1980, 1994), Tomlinson et al. (1980), Persaud et al. (1993), Burton (1998), Pataki and Cahi (1999), GIPME (1999), and Sutherland and Tolosa (2000). Hakanson (1980, 1994) has introduced methodology which is widely used by many researchers around the world. This method evaluates sediment quality of lakes with given contamination factor, contamination degree, ecological risk for individual heavy metals, and ecological risk index for basin. Another functional factor is enrichment factor (GIPME 1999; Sutherland and Tolosa 2000) which would significantly reveal environmental events in sediment columns. As a result, the reviewed literatures have significantly improved current research in terms of analytical methods and sediment chronology models. In addition, Olubunmi and Olorunsola (2010), Yao-guo et al. (2010), Aikpokpodion et al. (2010), Ahmad and Shuhaimi (2009, 2010), Dauvalter et al. (2009), Ebrahimpour and Mushrifah (2009), Nayaka et al. (2009), Sultan and Shazili (2009), Yang et al. (2009), Hai-Ao and Jing-Lu (2009), Tang et al. (2009), Honglei et al. (2008), Kamala-Kannan et al. (2008), Mingbiao et al. (2008), Rippey et al. (2008) are some of the latest studies which have frequently used analytical methods and sediment quality indices to find ecological risk assessment of individual heavy metals and degree of contamination of basin. These references show worldwide acceptance of the methodology that was decided to be used. Another theme in literature review was to recognize historical pollution trends in the lake sediment column using radioisotopes. Numerous previous studies such as Ariztegui et al. (2010), Ciszewski et al. (2008), Fa´varo et al. (2006, 2007), Hakanson et al. (1996), Xue et al. (2007), Yang et al. (2006), Appleby (2004), and Yamamoto et al. (1998) have remarkably highlighted the capability of radioisotopes especially 210Pb as the most profitable tools for detection of historical change in the rate of contamination in the lake sediment profile. These references thus have given incentives to investigate environmental impacts of anthropogenic events at BLC on sediment pollution over the last few decades. Nutrients cycle in a soil profile has been interest of several published papers (Craft and Richardson 1998; Guo et al. 2003; Mabit et al. 2008; Martinez et al. 2010) around the world. Nutrient content and their cycles have repeatedly studied for their importance in sustainable agriculture, and tracing of anthropogenic effects at catchment area. Similar to soil profile, lake sediments have widely investigated for historical variations in order to find environmental markers for tracing of eutrophication in watershed area with association of heavy metal contamination (Ueda et al. 2009; Flower et al. 2009; Rippey et al. 2008; Routh 5.2 Chemical and Pollution Analysis 137 et al. 2007; Alvarez-Iglesias et al. 2007; Bonotto and de Lima 2006; Covay and Beck 2001; Hongve et al. 1995; Nagao et al. 1999). Various studies in the Peninsular Malaysia have been reviewed (Tanaka et al. 2009; Sultan and Shazili 2009; Neergaard et al. 2008; Wu¨st et al. 2003; Phillips and Bustin 1998; Midmore et al. 1996; Malmer 1990), were agreed importance of nutrient content in soils and sediments as indicator of soil erosion, sedimentation and eutrophication effects. The visible gap in these studies is revealed as the geochronology of nutrient contents variations in a lake sediment column using radioisotopes. For example, Neergaard et al. (2008) investigated soil erosion due to shifting forest to agriculture lands using 137Cs technique, but the author not studied geochronology of deposited sediments in sink area which induced from eroded lands. Present study is the foremost attempt in order to trace nutrient fate due to land use changes in the one of the large catchment in Malaysia using 210Pb and 137Cs radioisotopes.

5.2 Chemical and Pollution Analysis

According to Method 3052 (Kingston and Jassie 1998), weighed samples of 0.25 g 1 were mixed with reagents, including 9 mL of HNO3 , 2 mL of HCl, and 3 mL of HF. Digestion procedures were continued using a Multiwave 3000 Oven with ramping and holding times of 5 and 10 min, respectively. Semi-digested samples eventually were fully digested by an additional 18 mL of saturated boric acid solution (H3BO4) during complexation, followed by a holding time of 10 min in a Multiwave 3000 Oven. Digested samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS) Model Agilent Technologies 7500 Series. Sediment data in this study are reported on a dry weight mg kg1 basis. Quality control. The analytical data quality was guaranteed through accomplishment of laboratory quality assurance and quality control methods, including the use of standard operating procedures, calibration with standards, analysis of reagent blanks, recovery of samples and analysis of replicates. All sediment analyses were performed by the quality-accredited laboratory of Geology, University of Malaya for the analyses of the sediment proﬁles, which were carried out at the Hydrogeo laboratory. Intra- and inter laboratory quality assurance and control (QA/QC) formed an integral part of the analysis schemes, e.g. by regular validation with reference sediment samples, the use of control charts and of replicates. Freshwater lake sediment standard reference material (SRM no. 4354) was used for the quality control test and quantitative analysis. Six replicate samples, each with a mass of 0.25 g, were weighed, digested and analyzed by ICP-MS in a similar manner as the sediment samples. The blank and standard solutions were prepared for metallic elements in the order of 1, 2, 3, 10, 20, and 50 ppm. The percentage recoveries of the metallic elements in the samples ranged from 81.7 % (Ca) to 110 % (Mg). Results of the repeated and reference samples were found in an acceptable limit range (75–125 %) for all analyzed metals and metalloids (Table 5.1). 3 eietQaiyadEooia ikAssmn fBr Lake Bera of Assessment Risk Ecological and Quality Sediment 5 138

Table 5.1 Quality control results of ICP-MS using SRMs (4354) freshwater lake sediment standard samples Elements (mg/kg) A1 Fe Na Mn Mg Ca K Pb Cu Zn As Ni Cr ICP 15,495 552 23,098 67 1,906 264 449 13 1,980 50 8,664 352 1,967 82 10 1 2,312 40 94 9 139 88 220 1 results SRMs 15,000 26,000 1,800 430 1,800 10,600 2,400 11 2,400 88 150 9 22 Recovery 103.3 88.8 105.9 104.4 110.0 81.7 82.0 90.9 96.3 106.8 92.7 87.0 90.9 % 5.4 Ecological Risk Assessment Models 139

5.3 Nutrient Content Analysis

A total of 65 samples of Core 5 and Core 6 with a mass of 1–1.5 g were weighed and mixed with 1–2 mL of HCl 1 M to remove inorganic carbons, and were dried about 10 h at 100–105 C to remove the HCl. Then, 0.5–2 mg samples were weighed and analyzed for Total Carbon (TC) and Total Nitrogen (TN) using PerkinElmer 2400 Series II CHNS/O Elemental Analyzer. This analytical method quantitatively determines the total amount of nitrogen and carbon in all forms in soil, botanical, and miscellaneous materials using a dynamic ﬂash combustion system coupled with a GC separation system and TCD system. The analytical method is based on the complete and instantaneous oxidation of the sample by “ﬂash combustion” which converts all organic and inorganic substances into combustion gases (N2,NOx,CO2, and H2O). The method has a detection limit of 0.01 % for carbon and 0.04 % for nitrogen and is generally reproducible within 5 % (relative). TOC was measured by removal of carbonates from samples using HCl (1 N) according method which presented by Schumacher (2002). An organic analytical standard (Acetanilide-C6H5NH) was used for quality control test and quantitative analysis. The quality control procedure was performed using Acetanilide standard sample as conditioner. Five blank-tin aluminum samples were tested. The calibration continued when positive results of C < 50, H: 100–200, and N < 16 were obtained. Then, three replicates Acetanilide samples, each with a mass of 0.5–2 mg, were weighed, and analyzed by Perkin Elmer 2400 Series II CHNS/O Elemental Analyzer. The calibration factors for carbon, hydrogen and nitrogen were respectively 71.09 0.3, 6.71 0.3, and 10.36 0.3 %, according to the instrumental instruction. The organic analytical standard (Acetanilide) was run for every four samples. CHN analysis was continued when the Acetanilide samples gained in the range of calibration factors.

5.4 Ecological Risk Assessment Models

The wide range of sediment quality indices have been used for the assessment of sediment quality and ecological risk in Bera Lake, Cf,Cd,Er, and RI (Hakanson 1980), and EF (GIPME 1999). According to Hakanson’s work, a sedimentological risk index for toxic substances in aquatic systems needs to four factors, (1) heavy metal concentration, (2) Cf and Cd, (3) Toxic factor, and (4) Sensitivity or response of environment.

X7 X7 i ¼ 7 ¼ C01 ð : Þ Cd Cf i 5 1 i¼1 i¼1 Cn where Cf and Cd are the contamination factor and degree of contamination, respectively. Seven heavy metals that have essentially analyzed for this purpose are 140 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

i i As, Zn, Pb, Ni, Cd, Cr, Cu. Further, C0 1 and Cn are the heavy metal concentration in the superﬁcial sediment (0–1 cm) and natural or pre-industrial reference concentration level, respectively. There are four categories for contamination factor, i.e., (1) low contamination for which Cf < 1, (2) moderate contamination for which 1 Cf 3, (3) considerable contamination for which 3 Cf 6, and (4) very high contamination for which Cf 6. The categories deﬁned by Hakanson (1980) for contamination degree are (1) low contamination for which Cd <8, (2) moderate contamination for which 8 Cd 16, (3) considerable contamination for which 16 Cd 32, and (4) very high contamination for which Cd 32.

X7 X7 ¼ i ¼ i i ð : Þ RI Er Tr Cf 5 2 i¼1 i¼1

i where the requested potential ecological risk is RI for lake, and Er is potential i ecological risk factor for each individual heavy metal. In addition, Tr is the toxic i response factor for the given heavy metals. Hakanson (1980) presented Tr values for seven heavy metals, i.e., Cr ¼ 2; Zn ¼ 1; Cu ¼ Ni ¼ Pb ¼ 5; As ¼ 10; and Cd ¼ 30. Further, Hakanson (1980) provided categories for indices and grades of potential i < ecological risk of heavy metal pollution, i.e., (1) low risk for which Er 40, i (2) moderate risk for which 40 Er 80, (3) considerable risk for which i i 80 Er 160, (4) great risk for which 160 Er 320, and (5) very great risk for i which Er 320. Furthermore, categories for potential ecological risk index were deﬁned as (1) low risk for which RI < 150, (2) moderate risk for which 150 RI 300, (3) considerable risk for which 300 RI 600, and (4) very high risk for which RI 600. The EF is another sediment quality index which has been widely used in this research. This index was introduced initially by Loring et al. (1995) and has been further developed by Sutherland and Tolosa (2000) for the evaluation of anthropogenic effects. The EF can be used to differentiate between the metals that are present due to anthropogenic effects and the metals from natural sources so that the extent of anthropogenic inﬂuence can be estimated. M =N Obs EF ¼ ð5:3Þ M =N Nat

ðM= Þ where EF is the metal EF for the sediment N Obs is the metal: normalizer ratio M observed for the sediment; and =N Nat is the natural metal: normalizer ratio. Elemental concentrations, including metal concentrations, can be compared with reported natural occurrences of the metals in the sediment and/or in crustal rocks by normalizing against geochemical markers (e.g., Al and Li) of the predominant natural mineralogical phase (GIPME 1999). Five contamination categories were identiﬁed by Sutherland and Tolosa (2000) on the basis of the EF, i.e., (1) deﬁciency to minimal enrichment for which EF < 2; (2) moderate enrichment for which 5.5 Standard Levels of Heavy Metal 141

2 < EF < 5; (3) signiﬁcant enrichment for which 5 < EF < 20; (4) very high enrichment for which 20 < EF < 40; and (5) extremely high enrichment for which EF > 40. The Normalaizer Al was used for calculating of EF of major and minor elements at Bera Lake sediment column. Index of Geoaccumulation (Igeo) introduced by Mu¨ller (1979) for ﬁnding out metals contamination in sediment, by comparing gained concentration of heavy metals with background levels of each individual metals (Eq. 5.4).

¼ ½= : ð: Þ Igeo Log2 Cn 1 5 Bn 5 4 where Cn is given metal levels and Bn is the background value of the given element in the study area and 1.5 is the background matrix correction factor owing to lithogenic effects. Index of Geoaccumulation classiﬁed by Mu¨ller (1979)as (1) zero value unpolluted for which Igeo ¼ 0, (2) unpolluted to moderately polluted for which 0 < Igeo < 1, (3) moderate polluted for which 1 < Igeo < 2, (4) moderate to strongly polluted for which 2 < Igeo < 3, (5) strongly polluted for which 3 < Igeo < 4, (6) strong to very strongly polluted for which 4 < Igeo < 5 and (7) very strongly polluted for which Igeo > 5.

5.5 Standard Levels of Heavy Metal

The most common method to reveal adverse effects of heavy metals in sediments for aquatic life and human health is to compare their concentrations with the sediment quality guidelines which have been developed by the various environmental protection agencies. In this research, ISQG, PEL (CCME 1995), CBSQG (CBSQG 2003), LEL, and SEL (Persaud et al. 1993) sediment quality guidelines were used to compare the heavy metal concentrations observed in the sediment cores from Bera Lake (Table 5.2). The lowest effect level (LEL) is a measure of contamination that has no effect on the majority of the sediment-dwelling organisms indicating that the sediments are clean to marginally polluted. Contamination in sediments that exceeds the lowest effect level may require management plans.

Table 5.2 Sediment quality indices which were applied in this study (mg kg1) Sediment quality indices V As Cr Zn Cu Ni Pb Mn Cd Fe LEL 6 26 120 16 16 31 460 0.6 17,000 ISQG 5.9 37.3 123 35.7 35 0.6 CBSQG 9.8 43 120 32 23 36 460 0.99 20,000 PEL 150 17 90 315 197 93.1 3.5 SEL 33 110 270 110 50 110 1,100 9 25,000 142 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

Table 5.3 Major and minor metals background levels in Bera Lake Element Al Na K Fe Mg Ca Natural value (%) 9.68 2.60 1.10 0.78 0.17 0.10 Element V Cr As Li Sr Zn Mn Cu Pb Ni Co Cd Natural value 112.94 56.00 52.59 48.77 39.00 32.02 27.77 25.89 17.59 16.34 2.77 0.19 (mg/kg)

The severe effect level (SEL) indicates a heavily polluted condition that is likely to affect the health of sediment-dwelling organisms. Heavy metal concentrations that exceed the SEL require further toxicity analysis. In addition, management plans should include controlling the source of the contamination and removing the polluted sediment (Persaud et al. 1993). The PEL represents the lowest limit of the range of chemical concentrations that are usually or always associated with adverse biological effects. The ISQG and the PEL are used to deﬁne three ranges of chemical concentrations for a particular chemical, i.e., those that are rarely (PEL) associated with adverse biological effects (CCME 1995). The CBSQGs, as developed, only involve effects to benthic macro-invertebrate species. Several databases created by toxicological research projects have established the cause and effect correlations of sediment contaminants to benthic organisms and benthic community assessment endpoints (CBSQG 2003). The guidelines do not consider the potential for bioaccumulation in aquatic organisms, subsequent food chain transfers, or effects on humans or wildlife that consume the upper food chain organisms.

5.5.1 Background Concentration of Heavy Metals in Bera Lake Sediments

Calculation of ecological risk indices requires background values, or pre-land use change concentrations, of metals. Physico-chemical analyses of Bera Lake sediments from the lower part of cores (depths exceeding 32 cm) can be considered to provide data that representative of the sediments that were deposited under natural and normal conditions. Average values of major and minor elements in the lower layers of the core are therefore, assumed to be background values (Table 5.3). Deposition of major and minor elements at Bera Lake has occurred under natural conditions with some minor variations since the creation of the wetlands and Bera Lake about 4,500 BP (Morley 1981). Over the last four decades, however, Bera Lake has experienced ﬂuxes in lithogenic and anthropogenic derived metals since part of the drainage catchment was cleared for oil palm monoculture. Evidence of 5.6 Heavy Metal Concentration in Bera Lake Sediments 143

Fe 45000

40000 Concentration (mg/kg) 35000 30000 25000 20000 15000 10000 5000 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Depth (cm)

Fig. 5.1 Variation in Fe concentration prior and post land use changes (Core, 5) this is distinctly seen in Fig. 5.1 which shows concentration of Fe was constant until depth of 32 cm. Then, concentration has experienced signiﬁcant upward variation, signaling the anomalies in Fe ﬂux into Bera Lake.

5.6 Heavy Metal Concentration in Bera Lake Sediments

Minimum, maximum and mean values as well as standard deviations and coefficients of variation for each individual metal were determined in all the core samples. High concentrations of Cr, Ni, Cu, Zn, and Pb were found in the south of Bera Lake, while the highest mean values of Fe, K, V, Mn, Co, As, and Cd were recorded in the north of the Lake. The highest concentrations of Ca, Mg, Na, Li, and Sr were furthermore, found in the deepest part or in the middle of Bera Lake. The highest percentage levels of the major metals were that of Al (15.4 %) and Fe (3.9 %) while the highest concentrations of trace metals were those of V (157 mg kg1) and As (160 mg kg1). The highest concentration of 160 mg kg1 of As was found in Core 3 at the exit point of the lake at a depth of 58 cm. In the Bera Lake sediments, Cd had the lowest recorded concentration among the heavy metals with a maximum value of 0.2 mg kg1 at the main sediment entry point of Bera Lake. An increasing trend northwards in concentrations of Fe, K, V, Mn, Co, As, Cd, and Sr were observed in the Bera Lake sediment profiles, whilst there was a corresponding decreasing trend in concentrations of Cr, Ni, Cu, Zn, and Pb. Dramatic upward variations (CV, 48–78 %) in concentrations of metals were also observed in the sediment columns of the Lake. The results therefore, show that chemical composition trends are significantly controlled by environmental changes and physico-chemical conditions in the Bera Lake basin. The Mn/Fe ratio is a good indicator of redox condition with low concentrations of Mn coinciding with low Mn/Fe ratios and high C concentrations (Koinig et al. 2003). The calculated Mn/Fe ratio in Cores 1, 2, 3, 4 and 5, are 0.007, 0.0027, 0.003, 0.018, and 0.003, respectively. An upward decrease in the Mn/Fe ratio was also found in all 144 5 Sediment Quality and Ecological Risk Assessment of Bera Lake the Bera Lake sediment profiles. According to Koinig et al. (2003)Mn2+ mainly precipitates as MnCO3 and it is therefore, also dependent on pH. Conditions at Bera Lake were found to be acidic with a measured pH < 5; a value that is in agreement with that of Wu¨st and Bustin (2004). As pH decreases, MnCO3 become less stable and the mobility of Mn increased and the Mn/Fe ratio thus reduced.

5.6.1 Pearson Correlation Coefﬁcient

Countless studies support the importance of statistical methods for identifying similarities and dissimilarities in origins, conditions of storage and the distribution, of metals (Brereton 2007; Einax et al. 1997). Calculated Pearson correlation coefficients of metal levels in the five sediment profiles of Bera Lake are presented in Tables 5.4. Significant positive and negative r values with p-value < 0.05 are highlighted in Table 5.4. Strong positive and significant correlations (r 0.7) were observed in the five sediment cores and are summarized in Table 5.5. A strong positive correlation between Li and Al, K, Mg, and Sr with r-values of 0.89, 0.82, 0.91, and 0.83, respectively, at the south of Bera Lake is observed. The Al value also increases with increasing K, Mg, and Sr concentrations as well. Cr, Cu and K concentrations with r-values of 0.76 and 0.72 furthermore, show strong positive correlations. The concentration of Sr also showed strong positive correlation with Mg and Na with r-values of 0.82, and 0.84. The sediment profile in Core 4 reveals a clear correlation between Fe and Co, Ni, An, As, And Cd metals. In such condition, Mn shows a vivid correlation with Fe, Co, Ni, Zn, As, and Ca with high r-values. A positive correlation between the alkaline metals as Li, Al, Cr, Mg, Na, and Sr is also seen in the middle and north of study area. Similar similarities of Al and Cr, K, Mg, Na, and Sr metals settled at the middle and the north of Bera Lake sediment profiles. Table 5.6 shows a variation in Mn with other metals in different parts of Bera Lake. This is in agreements with concentrations of Fe, Co, Zn, and As in the middle of Bera Lake, though some metals as Fe and Zn are enriched with Mn in the north of the study area. There is a remarkable positive affinity between concentrations of Co and Zn and As in the middle of the study area. Co furthermore, showed a positive correlation with Pb only in the north of Bera Lake. A positive correlation between cations Mg, Sr, K, and Na exists in all sections of the Bera Lake sediments.

5.6.2 Cluster Analysis

The Hieratical Cluster Analysis (HCA) method is an unsupervised technique that can be applied to reveal any natural populations in the analyzed metals. This method is a common statistical technique in ecological studies to recognize Table 5.4 Correlation coefﬁcients of Bera Lake sediment proﬁles 145 Sediments Lake Bera in Concentration Metal Heavy 5.6 Variables Li Al V Cr Mn Fe Co Ni Cu Zn As Cd Pb K Ca Mg Na Sr (a) Li 1 Al 0.893 V 0.032 0.019 1 Cr 0.535 0.471 0.194 1 Mn 0.381 0.210 0.128 0.484 1 Fe 0.466 0.570 0.071 0.153 0.475 1 Co 0.442 0.339 0.189 0.645 0.503 0.036 1 Ni 0.093 0.055 0.139 0.603 0.058 0.076 0.209 1 Cu 0.147 0.142 0.088 0.765 0.249 0.034 0.511 0.772 1 Zn 0.353 0.406 0.326 0.252 0.098 0.421 0.060 0.040 0.129 1 As 0.210 0.069 0.256 0.452 0.387 0.218 0.299 0.069 0.090 0.075 1 Cd 0.291 0.183 0.452 0.354 0.035 0.331 0.326 0.032 0.262 0.542 0.104 1 Pb 0.209 0.320 0.417 0.396 0.050 0.260 0.093 0.329 0.219 0.040 0.308 0.020 1 K 0.820 0.799 0.105 0.721 0.476 0.292 0.458 0.221 0.424 0.466 0.209 0.309 0.283 1 Ca 0.392 0.456 0.208 0.085 0.549 0.897 0.097 0.018 0.070 0.455 0.349 0.319 0.156 0.254 1 Mg 0.910 0.942 0.015 0.537 0.225 0.592 0.332 0.023 0.198 0.411 0.066 0.246 0.363 0.848 0.533 1 Na 0.626 0.657 0.318 0.446 0.327 0.245 0.321 0.017 0.176 0.828 0.113 0.484 0.042 0.748 0.214 0.640 1 Sr 0.826 0.815 0.036 0.572 0.451 0.315 0.398 0.001 0.140 0.592 0.293 0.328 0.205 0.841 0.218 0.817 0.836 1 (continued) 4 eietQaiyadEooia ikAssmn fBr Lake Bera of Assessment Risk Ecological and Quality Sediment 5 146

Table 5.4 (continued) Variables Li Al V Cr Mn Fe Co Ni Cu Zn As Cd Pb K Ca Mg Na Sr (b) Li 1 Al 0.930 1 V 0.430 0.419 1 Cr 0.915 0.978 0.295 1 Mn 0.677 0.645 0.800 0.528 1 Fe 0.889 0.802 0.671 0.731 0.911 1 Co 0.369 0.395 0.497 0.357 0.676 0.600 1 Ni 0.265 0.259 0.523 0.159 0.687 0.545 0.446 1 Cu 0.069 0.060 0.128 0.095 0.228 0.254 0.415 0.110 1 Zn 0.883 0.878 0.620 0.830 0.852 0.928 0.636 0.524 0.042 1 As 0.112 0.040 0.003 0.046 0.121 0.036 0.651 0.076 0.443 0.109 1 Cd 0.621 0.714 0.373 0.683 0.528 0.560 0.231 0.460 0.088 0.646 0.017 1 Pb 0.452 0.385 0.257 0.394 0.508 0.592 0.801 0.245 0.627 0.570 0.676 0.171 1 K 0.977 0.912 0.383 0.900 0.620 0.829 0.264 0.194 0.055 0.841 0.232 0.584 0.336 1 Ca 0.442 0.503 0.474 0.450 0.610 0.516 0.348 0.598 0.540 0.675 0.084 0.453 0.082 0.474 1 Mg 0.984 0.954 0.395 0.950 0.656 0.865 0.410 0.226 0.083 0.885 0.015 0.631 0.490 0.963 0.414 1 Na 0.986 0.904 0.435 0.881 0.691 0.887 0.358 0.249 0.105 0.869 0.133 0.582 0.455 0.982 0.421 0.971 1 Sr 0.926 0.830 0.372 0.805 0.580 0.781 0.221 0.200 0.009 0.769 0.294 0.543 0.279 0.952 0.401 0.900 0.938 1 . ev ea ocnrto nBr aeSdmns147 Sediments Lake Bera in Concentration Metal Heavy 5.6 (c) Li 1 Al 0.968 1 V 0.211 0.196 1 Cr 0.922 0.959 0.203 1 Mn 0.613 0.549 0.136 0.418 1 Fe 0.293 0.208 0.258 0.091 0.855 1 Co 0.627 0.587 0.131 0.481 0.978 0.817 1 Ni 0.190 0.249 0.129 0.284 0.407 0.257 0.455 1 Cu 0.129 0.161 0.215 0.223 0.079 0.151 0.103 0.009 1 Zn 0.578 0.562 0.001 0.430 0.928 0.749 0.923 0.431 0.178 1 As 0.402 0.338 0.390 0.308 0.737 0.663 0.754 0.584 0.222 0.614 1 Cd 0.070 0.078 0.151 0.132 0.354 0.445 0.276 0.231 0.030 0.212 0.237 1 Pb 0.072 0.004 0.163 0.079 0.646 0.789 0.624 0.075 0.048 0.599 0.321 0.285 1 K 0.802 0.758 0.410 0.693 0.871 0.744 0.888 0.348 0.042 0.771 0.694 0.206 0.525 1 Ca 0.184 0.257 0.312 0.415 0.467 0.629 0.414 0.078 0.543 0.477 0.236 0.423 0.501 0.121 1 Mg 0.948 0.947 0.410 0.912 0.646 0.409 0.681 0.274 0.165 0.583 0.501 0.015 0.180 0.897 0.207 1 Na 0.770 0.715 0.377 0.640 0.900 0.791 0.906 0.339 0.063 0.795 0.696 0.223 0.589 0.992 0.174 0.859 1 Sr 0.790 0.796 0.124 0.694 0.717 0.468 0.722 0.310 0.038 0.732 0.469 0.111 0.292 0.746 0.046 0.782 0.748 1 (continued) 4 eietQaiyadEooia ikAssmn fBr Lake Bera of Assessment Risk Ecological and Quality Sediment 5 148

Table 5.4 (continued) Variables Li Al V Cr Mn Fe Co Ni Cu Zn As Cd Pb K Ca Mg Na Sr (d) Li 1 Al 0.564 1 V 0.075 0.098 1 Cr 0.426 0.009 0.018 1 Mn 0.007 0.248 0.554 0.355 1 Fc 0.360 0.333 0.558 0.054 0.826 1 Co 0.073 0.015 0.854 0.148 0.647 0.586 1 Ni 0.028 0.065 0.856 0.206 0.831 0.739 0.938 1 Cu 0.441 0.086 0.632 0.132 0.106 0.318 0.551 0.425 1 Zn 0.140 0.245 0.629 0.212 0.713 0.622 0.711 0.765 0.103 1 As 0.124 0.230 0.822 0.124 0.576 0.515 0.897 0.836 0.494 0.677 1 Cd 0.222 0.051 0.867 0.027 0.431 0.552 0.854 0.794 0.644 0.603 0.789 1 Pb 0.173 0.321 0.841 0.136 0.731 0.677 0.826 0.864 0.512 0.715 0.699 0.711 1 K 0.338 0.427 0.152 0.390 0.144 0.216 0.269 0.137 0.567 0.079 0.046 0.401 0.050 1 Ca 0.248 0.065 0.355 0.557 0.577 0.439 0.388 0.514 0.091 0.419 0.335 0.338 0.431 0.104 1 Mg 0.534 0.958 0.034 0.050 0.171 0.256 0.146 0.081 0.100 0.069 0.061 0.208 0.194 0.406 0.047 1 Na 0.203 0.507 0.257 0.286 0.066 0.210 0.331 0.216 0.658 0.077 0.088 0.447 0.136 0.958 0.005 0.462 1 Sr 0.140 0.285 0.583 0.226 0.334 0.397 0.746 0.644 0.572 0.353 0.525 0.667 0.528 0.675 0.167 0.369 0.688 1 . ev ea ocnrto nBr aeSdmns149 Sediments Lake Bera in Concentration Metal Heavy 5.6 (e) Li 1 Al 0.268 1 V 0.446 0.106 1 Cr 0.863 0.392 0.439 1 Mn 0.078 –0.304 0.579 –0.058 1 Fe 0.020 0.860 –0.234 0.172 –0.480 1 Co –0.712 –0.070 –0.014 –0.480 0.314 0.050 1 Ni –0.206 0.018 –0.599 –0.288 –0.420 0.269 0.006 1 Cu 0.133 –0.259 0.139 –0.155 0.311 –0.272 –0.149 –0.107 1 Zn –0.201 –0.197 0.598 –0.255 0.650 –0.349 0.491 –0.363 0.300 1 As –0.292 –0.372 –0.203 –0.111 0.094 –0.249 0.282 0.177 –0.715 –0.150 1 Cd –0.284 0.344 –0.245 –0.166 –0.310 0.449 0.260 0.454 –0.309 –0.161 0.069 1 Pb 0.025 –0.508 0.562 –0.191 0.527 –0.599 0.020 –0.164 0.625 0.674 –0.256 –0.209 1 K 0.141 0.556 0.156 0.212 –0.129 0.316 0.235 –0.028 –0.022 0.159 –0.383 0.202 –0.174 1 Ca –0.736 –0.104 –0.110 –0.564 0.328 0.095 0.867 0.117 –0.349 0.335 0.531 0.294 –0.054 –0.096 1 Mg 0.102 0.902 0.202 0.291 –0.136 0.751 0.248 –0.100 –0.289 0.061 –0.285 0.384 –0.412 0.686 0.152 1 Na –0.025 0.631 0.122 0.083 –0.057 0.467 0.413 –0.021 –0.076 0.294 –0.327 0.296 –0.201 0.928 0.148 0.813 1 Sr 0.797 0.350 0.050 0.832 –0.243 0.231 –0.565 0.023 –0.180 –0.522 0.008 –0.206 –0.414 0.194 –0.607 0.145 0.043 1 Bold values show important similarities 5 eietQaiyadEooia ikAssmn fBr Lake Bera of Assessment Risk Ecological and Quality Sediment 5 150 Table 5.5 Correlation values between concentration of major and minors Core 2 Core 6 Core 5 Core 4 Core 1 Object1 Object2 Similarity Object1 Object2 Similarity Object1 Object2 Similarity Object1 Object2 Similarity Object1 Object2 Similarity Li Al 0.89 Li Al 0.93 Li Al 0.97 Li Cr 0.86 Al Mg 0.96 Li K 0.82 Li Cr 0.92 Li Cr 0.92 Li Sr 0.80 V Pb 0.84 Li Mg 0.91 Li K 0.98 Li K 0.80 Al Fe 0.86 Mn Fe 0.83 Li Sr 0.83 Li Mg 0.98 Li Mg 0.95 Al Mg 0.90 Mn Ni 0.83 Al K 0.80 Li Na 0.99 Li Na 0.77 Cr Sr 0.83 Mn Zn 0.71 Al Mg 0.94 Li Sr 0.93 Li Sr 0.79 Fe Mg 0.75 Fe Ni 0.74 Al Sr 0.81 Al Cr 0.98 Al Cr 0.96 Co Ca 0.87 Co Ni 0.94 Cr Cu 0.76 Al K 0.91 Al K 0.76 K Na 0.93 Co Zn 0.71 Cr K 0.72 Al Mg 0.95 Al Mg 0.95 Mg Na 0.81 Co As 0.90 Fe Ca 0.90 Al Na 0.90 Al Na 0.72 Co Cd 0.85 Ni Cu 0.77 Al Sr 0.83 Al Sr 0.80 Ni Zn 0.76 Zn Na 0.83 V Mn 0.80 Cr Mg 0.91 Ni As 0.84 K Mg 0.85 Cr K 0.90 Mn Fe 0.85 Ni Cd 0.79 K Na 0.75 Cr Mg 0.95 Mn Co 0.98 As Cd 0.79 K Sr 0.84 Cr Na 0.88 Mn Zn 0.93 K Na 0.96 Mg Sr 0.82 Cr Sr 0.81 Mn As 0.74 Na Sr 0.84 Mn Fe 0.91 Fe Co 0.82 Mn Zn 0.85 Co Zn 0.92 Fe Zn 0.93 Co As 0.75 Co Pb 0.80 K Mg 0.90 K Mg 0.96 K Na 0.99 K Na 0.98 K Sr 0.75 K Sr 0.95 Mg Na 0.86 Mg Na 0.97 Mg Sr 0.78 Mg Sr 0.90 Na Sr 0.75 Na Sr 0.94 . ev ea ocnrto nBr aeSdmns151 Sediments Lake Bera in Concentration Metal Heavy 5.6

Table 5.6 Contamination factor and degree of contamination for cores 2, 5, and 6 Cf Cd Heavy Metal Cr Ni Cu Zn Cd Pb As Core no. 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 Depth (cm) 63–65 1.0 1.0 0.8 1.3 1.0 0.7 0.9 6.6 61–63 1.0 0.9 0.8 0.9 1.0 0.6 0.8 5.9 59–61 1.1 1.0 1.0 1.4 1.1 1.9 0.7 1.5 1.1 1.1 1.2 1.7 0.9 1.1 7.1 9.6 57–59 1.1 1.0 1.0 1.2 1.1 1.1 1.1 0.9 1.0 1.0 0.9 1.2 2.1 1.1 1.0 0.9 1.0 1.3 1.1 1.0 0.9 8.4 7.0 7.5 55–57 1.1 1.0 1.0 1.0 0.9 0.9 1.0 1.1 1.4 0.6 0.9 1.3 1.1 1.0 1.0 0.9 0.5 1.3 1.0 0.9 1.0 6.7 6.4 7.9 53–55 0.9 1.0 1.1 0.7 0.9 0.9 1.0 0.7 1.1 1.0 0.9 1.5 1.1 1.0 1.0 1.7 0.6 1.3 0.9 0.8 0.9 7.2 5.8 7.8 51–53 0.6 1.0 1.0 0.6 0.9 1.0 0.6 1.0 1.0 0.4 1.0 1.3 0.1 1.0 1.0 1.4 0.9 0.7 1.4 0.9 0.8 5.2 6.7 6.9 49–51 1.2 1.0 1.0 1.1 0.9 1.1 1.1 0.8 1.0 4.3 0.9 1.3 2.1 1.1 1.0 1.1 0.6 1.0 1.0 0.8 1.0 11.8 6.2 7.4 47–49 0.5 1.0 1.0 0.7 0.9 0.9 0.5 0.8 1.0 0.8 0.8 1.3 1.1 1.0 1.0 1.1 1.1 0.9 1.1 1.1 1.0 5.7 6.7 7.0 45–47 1.0 1.0 1.0 1.2 1.0 0.9 1.4 1.1 0.9 0.7 0.8 0.6 1.1 1.1 1.0 0.8 2.4 1.0 1.2 1.7 1.0 7.4 9.0 6.4 43–45 1.2 0.8 1.0 1.0 0.8 0.9 1.0 1.2 0.9 0.7 0.8 0.6 1.1 1.1 1.0 0.7 1.9 0.7 0.9 1.5 1.1 6.4 8.1 6.1 41–43 1.1 0.9 1.0 1.6 0.8 1.0 1.3 2.2 0.9 0.7 1.0 0.6 1.1 1.0 1.0 1.0 3.1 0.7 1.0 1.7 1.1 7.7 10.6 6.3 39–41 1.1 1.0 1.0 0.9 0.9 1.1 1.1 1.3 0.9 0.6 0.9 0.6 0.1 1.1 1.0 0.8 3.2 1.0 0.9 1.8 1.1 5.5 10.2 6.7 37–39 1.2 0.9 1.0 1.0 0.8 1.2 1.0 1.8 0.9 0.5 1.1 0.6 0.1 1.1 1.0 0.4 3.0 1.1 0.7 1.7 1.1 4.8 10.5 6.9 (continued) Table 5.6 (continued) Lake Bera of Assessment Risk Ecological and Quality Sediment 5 152 Cf Cd Heavy Metal Cr Ni Cu Zn Cd Pb As Core no. 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 2 6 5 Depth (cm) 35–37 1.0 1.0 1.0 0.9 0.8 1.3 0.9 1.1 1.0 0.6 0.8 0.7 1.1 1.0 0.9 0.9 2.3 1.5 0.9 1.5 1.6 6.4 8.5 8.1 33–35 1.0 1.0 1.0 1.7 0.9 1.2 1.2 1.2 1.2 0.8 0.8 0.7 0.1 1.0 1.0 0.8 2.3 1.4 1.0 1.8 1.3 6.6 8.9 7.7 31–33 1.1 1.0 0.9 1.0 0.8 0.9 0.9 1.3 0.8 1.4 0.7 0.6 1.1 1.0 1.0 0.6 2.3 0.8 0.9 1.7 1.0 6.9 8.8 6.0 29–31 1.3 1.0 0.5 1.9 0.9 0.9 1.6 1.1 0.9 0.5 0.7 0.6 1.1 1.0 1.0 0.8 2.2 1.6 0.9 1.5 0.9 8.1 8.3 6.4 27–29 1.2 1.1 0.8 1.3 1.3 1.2 1.0 0.9 0.8 0.5 0.9 1.3 0.1 1.0 1.0 0.7 1.9 1.3 0.9 1.7 1.0 5.7 8.7 7.4 25–27 1.1 1.0 0.5 1.3 1.1 1.1 1.1 1.3 0.9 0.8 0.9 1.5 1.1 1.0 0.1 0.9 1.6 1.6 1.2 1.8 1.1 7.4 8.6 6.6 23–25 1.1 1.0 0.4 1.1 0.9 1.5 1.0 1.0 0.8 0.5 0.8 3.1 1.1 1.0 1.0 0.6 0.9 1.0 0.7 1.5 1.5 6.2 7.1 9.3 21–23 1.0 1.0 0.8 1.1 0.8 1.3 1.1 0.9 0.8 0.6 0.8 2.7 0.1 1.0 2.0 1.0 0.5 0.4 1.0 1.3 1.4 5.9 6.2 9.4 19–21 1.0 1.0 0.8 1.1 0.8 1.0 1.4 0.8 1.3 0.5 1.1 2.4 1.1 1.0 0.9 1.0 0.6 1.0 0.9 1.4 1.5 7.1 6.6 8.8 17–19 1.1 0.9 0.7 2.3 1.1 1.2 1.6 1.2 0.9 0.4 2.1 2.1 0.1 1.1 1.0 1.0 0.9 0.9 0.9 1.6 1.4 7.4 8.8 8.3 15–17 1.0 0.7 0.7 1.2 0.8 1.0 1.0 1.5 0.8 0.6 2.4 2.5 0.1 1.1 1.0 1.0 0.0 0.5 1.0 1.2 1.2 6.0 7.7 7.9 13–15 0.6 0.9 0.9 0.9 1.0 1.0 0.1 0.8 0.9 0.6 1.8 2.5 0.1 1.1 0.1 1.0 0.0 0.0 1.0 1.2 1.3 4.2 6.8 6.6 11–13 0.5 0.8 0.9 0.8 1.1 1.2 0.6 0.8 1.0 0.6 2.0 2.4 0.1 1.1 2.0 0.6 0.0 0.2 1.1 1.1 1.2 4.4 6.9 8.9 8–11 0.5 0.8 0.8 0.8 1.3 1.3 0.6 0.8 1.7 0.7 2.2 2.9 0.1 1.1 0.9 1.3 0.4 0.3 1.2 1.3 1.5 5.1 7.8 9.5 6–8 0.5 0.8 0.8 0.8 1.3 1.0 0.8 0.9 0.8 0.8 2.3 2.5 0.1 1.1 0.9 1.3 0.4 0.2 1.3 1.4 1.3 5.5 8.1 7.5 4–6 0.5 0.8 0.8 0.7 1.1 1.0 0.5 1.0 1.2 0.5 2.1 2.3 1.1 1.1 2.0 0.8 0.4 0.7 1.0 1.4 1.6 5.0 7.7 9.7 2–4 1.4 0.8 0.8 1.9 1.2 1.2 1.6 0.8 0.9 1.8 2.0 2.1 1.1 1.1 1.0 0.6 0.3 0.5 1.2 1.3 1.5 9.6 7.4 8.0 0–2 0.9 0.8 0.8 1.4 1.2 1.2 1.4 1.2 0.9 1.1 2.3 2.0 1.1 1.1 2.0 0.5 0.7 0.5 1.3 1.4 1.3 7.7 8.7 8.8 5.6 Heavy Metal Concentration in Bera Lake Sediments 153

Dendrogram

Sr K Mg Al Li Ca Fe Na Zn Cd Cu Ni Cr Co Mn As Pb V

0.96 0.76 0.56 0.36 0.16 -0.04 -0.24 -0.44 -0.64 Similarity

Fig. 5.2 Clusters and relationships between major and minor metals in Core 2

Dendrogram

Pb Co As Cu Na Li K Mg Sr Cr Al Ca Ni Zn Fe Mn V Cd

0.91 0.71 0.51 0.31 0.11 -0.09 -0.29 -0.49 -0.69 -0.89 Similarity

Fig. 5.3 Clusters and relationships between major and minor metals in Core 6 relative sources and physico-chemical conditions of the depositional media. Graphic interpoint distances between all of the metals in the Bera Lake sediment columns in the form of two-dimensional plots or dendogram are shown in Figs. 5.2, 5.3, 5.4, 5.5, and 5.6. Clusters that are analyzed are based on complete linkages. The resultant clusters indicate signiﬁcant positive correlations between the closest metals and similar clusters plotted in the closest distance. On the other hand, signiﬁcant negative correlations are found between analyzed metals plotted at maximum distances and separate clusters. 154 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

Dendrogram

Mg Al Fe Na K Cr Li Sr Mn V Pb Zn Cu Ca Co As Cd Ni

0.86 0.66 0.46 0.26 0.06 -0.14 -0.34 -0.54 -0.74 Similarity

Fig. 5.4 Clusters and relationships between major and minor metals in Core 4

Dendrogram

Co Mn Zn Fe As Ni Cd Ca Cu V Na K Sr Al Li Mg Cr Pb

0.89 0.69 0.49 0.29 0.09 -0.11 -0.31 -0.51 -0.71 -0.91 Similarity

Fig. 5.5 Clusters and relationships between major and minor metals in Core 5

Similarities and dissimilarities between the analyzed metals in the south of Bera Lake are represented in three classes (Fig. 5.2). A positive correlation with different r-values is calculated for Classes 1 and 2. On the other hand, metals Co, Mn, As, Pb, and V, which do not cluster so well in class 3 show a signiﬁcant negative correlation with other metals where plotted in classes 1 and 2. Maximum similarity in the middle of Bera Lake appeared in class 2 between metals Na and Li, and with both of them and K and Sr, and in the pair between Cr and Al (Fig. 5.3). Classes 1 and 2 indicate moderate positive correlations between 5.7 Bera Lake Sediment Quality 155

Dendrogram

Fe Mn Zn Ni Co As Cd Ca Cr Mg Al Li Na K Sr Cu Pb V

0.93 0.73 0.53 0.33 0.13 -0.07 -0.27 -0.47 -0.67 -0.87 Similarity

Fig. 5.6 Clusters and relationships between major and minor metals in Core 1 the concentrations of clustered metals. Both classes furthermore, show negative correlations with metals clustered in class 3. A negative r-value for instance, represented the correlations between the concentrations of Fe and Na or Zn and Li. At the north of Bera Lake, minimum distances in classes 1 and 2 appear between metals Co and Mn, and between Na and K, respectively. On the other hand, a maximum distance appeared between concentrations of Pb and Co. Class 3 includes metals which show significant negative correlation with concentration of metals in classes 1 and 2 (Fig. 5.4). A general trend of metal populations is recognized in the sediment profiles of the semi-closed area in the northwest of Bera Lake (Core 1). The first group of metals involves Fe, Mn, Zn, Ni, Co, As, Cd, and Cr classified in class 1 with a positive r-value. Class 2 includes metals Mg, Al, and Li with an implied maximum positive correlation. In this part of Bera Lake, although Na, K, Sr, Cu, Pb, and V are in clear agreement with each together, they show negative correlations with metals classified in classes 1 and 2 (Fig. 5.6).

5.7 Bera Lake Sediment Quality

Sediment quality indices were compared with Fe, As, Ni, Cr, Cd, Zn, Cu, and Pb levels to assess the pollution status at Bera Lake. These selected metals were recognized to be the most common metals for comparisons with the threshold limits of standard levels (Table 5.7). The overall levels of Zn and Cd metals plot below the LEL in all of the Bera Lake sediment proﬁles. There is, however, marked enrichment in Zn and Cd levels at the north of the study area. Cu levels in different parts of the study area indicate slight contamination with copper levels appearing to Table 5.7 Ecological risk index for individual metals and for basin in Cores 2, 5, and 6 Lake Bera of Assessment Risk Ecological and Quality Sediment 5 156 Er IR Heavy Metal Cr Ni Cu Zn Cd Pb As Core no. 2 6 5 2 6 5 2 6 5 2652 6 5 26 526526 5 Depth (cm) 63–65 1.9 4.9 4.2 1.3 6.0 3.3 9.3 30.9 61–63 2.0 4.3 4.2 0.9 5.9 2.9 8.5 28.6 59–61 2.3 2.0 5.0 7.2 5.4 9.3 0.7 1.5 31.9 66.1 6.0 8.4 8.9 10.7 60.2 105.2 57–59 2.1 2.0 2.0 6.0 5.6 5.7 5.5 4.4 4.9 1.0 0.9 1.2 63.9 66.1 30.0 4.5 5.2 6.3 10.6 10.1 9.4 93.6 94.2 59.5 55–57 2.1 2.0 2.1 5.2 4.5 4.5 5.0 5.7 7.0 0.6 0.9 1.4 32.0 6.0 29.9 4.7 2.6 6.5 9.6 9.0 9.5 59.3 30.8 60.8 53–55 1.8 2.0 2.1 3.5 4.3 4.7 4.9 3.6 5.5 1.0 0.9 1.5 31.9 5.9 30.0 8.6 3.0 6.4 8.9 7.9 9.4 60.6 27.6 59.7 51–53 1.2 2.0 2.1 2.8 4.7 4.9 3.2 5.0 4.9 0.4 1.0 1.3 2.9 5.9 30.1 7.2 4.4 3.6 14.4 8.9 8.3 32.2 32.0 55.2 49–51 2.4 2.0 2.0 5.3 4.7 5.6 5.3 4.0 4.9 4.3 0.9 1.3 63.8 66.1 29.9 5.4 3.0 5.0 10.0 8.3 9.5 96.6 89.1 58.3 47–49 0.9 2.0 2.0 3.5 4.6 4.3 2.5 4.2 5.0 0.8 0.8 1.3 31.9 5.9 30.0 5.4 5.5 4.6 11.0 10.7 9.8 56.1 33.8 56.9 45–47 2.0 2.0 2.0 6.2 4.9 4.5 6.8 5.4 4.6 0.7 0.8 0.6 32.0 66.0 30.0 4.1 11.9 4.9 12.2 16.7 10.3 63.9 107.7 56.9 43–45 2.4 1.6 1.9 5.0 3.9 4.4 4.9 6.2 4.4 0.7 0.8 0.6 32.0 66.1 30.0 3.3 9.7 3.6 8.7 14.6 10.5 57.0 102.9 55.4 41–43 2.3 1.8 1.9 7.9 4.0 5.1 6.3 10.9 4.7 0.7 1.0 0.6 32.0 5.9 29.9 4.8 15.5 3.5 9.6 16.8 10.7 63.6 55.9 56.4 39–41 2.2 1.9 1.9 4.7 4.7 5.5 5.4 6.6 4.7 0.6 0.9 0.6 2.9 66.2 30.1 3.8 15.9 4.9 9.0 17.5 11.1 28.6 113.8 58.8 37–39 2.3 1.9 1.9 5.0 4.2 5.9 4.8 9.2 4.5 0.5 1.1 0.6 2.9 66.0 30.0 2.0 14.9 5.7 7.0 17.4 11.3 24.4 114.6 60.0 35–37 2.1 2.0 2.1 4.7 4.2 6.7 4.7 5.3 4.9 0.6 0.8 0.7 31.9 5.9 27.0 4.6 11.7 7.7 9.1 15.0 15.8 57.6 44.9 64.8 33–35 2.0 2.1 1.9 8.7 4.3 6.1 6.0 5.8 6.0 0.8 0.8 0.7 2.9 6.0 30.0 4.1 11.5 6.9 10.3 17.5 12.5 34.7 47.9 64.2 31–33 2.2 2.1 1.9 4.8 3.8 4.4 4.6 6.4 4.2 1.4 0.7 0.6 32.0 5.9 30.1 2.8 11.7 4.2 8.7 17.4 9.7 56.5 48.0 55.1 29–31 2.6 2.1 1.0 9.4 4.4 4.3 7.9 5.5 4.4 0.5 0.7 0.6 32.0 5.9 30.0 4.2 10.9 7.8 9.2 14.6 9.2 65.9 44.1 57.4 27–29 2.3 2.2 1.5 6.5 6.4 6.1 5.1 4.4 4.2 0.5 0.9 1.3 2.9 6.0 30.0 3.5 9.5 6.4 9.1 16.5 9.9 29.9 46.0 59.5 25–27 2.2 2.1 1.0 6.7 5.4 5.4 5.3 6.3 4.3 0.8 0.9 1.5 31.9 5.9 30.0 4.4 8.1 7.8 12.3 17.9 10.5 63.7 46.5 60.6 23–25 2.2 2.1 0.9 5.5 4.3 7.5 5.0 4.9 4.1 0.5 0.8 3.1 31.9 5.9 30.1 3.1 4.6 4.8 7.3 15.2 14.9 55.7 37.8 65.5 21–23 1.9 2.0 1.7 5.6 4.0 6.3 5.3 4.4 4.2 0.6 0.8 2.7 2.9 5.9 60.1 4.8 2.3 2.0 10.2 13.0 14.0 31.4 32.5 90.9 19–21 2.1 2.0 1.5 5.7 4.0 4.9 7.2 4.2 6.6 0.5 1.1 2.4 31.9 5.9 27.1 4.8 3.0 5.2 9.4 13.6 14.9 61.7 33.8 62.5 . eaLk eietQaiy157 Quality Sediment Lake Bera 5.7 17–19 2.1 1.7 1.5 11.5 5.6 5.9 7.9 6.0 4.7 0.4 2.1 2.1 2.9 66.0 30.1 4.8 4.3 4.7 9.5 16.0 13.9 39.2 101.8 62.8 15–17 2.0 1.4 1.5 6.1 3.9 5.1 5.2 7.5 4.1 0.6 2.4 2.5 2.9 66.0 30.1 5.2 0.1 2.7 10.2 11.5 12.5 32.1 92.9 58.5 13–15 1.2 1.8 1.7 4.7 5.0 4.9 0.5 4.0 4.4 0.6 1.8 2.5 2.9 66.1 30.1 4.8 0.1 0.2 9.6 12.2 12.7 24.2 91.1 56.5 11–13 1.0 1.7 1.8 4.1 5.3 6.1 3.0 3.9 4.9 0.6 2.0 2.4 2.9 6.0 60.2 3.1 0.1 1.0 11.4 11.5 11.6 26.2 30.4 88.1 8–11 1.0 1.7 1.7 4.1 6.3 6.5 2.8 4.1 8.6 4.5 2.2 2.9 2.9 5.9 27.1 6.3 1.8 1.6 11.9 12.6 15.0 33.5 34.6 63.3 6–8 1.0 1.6 1.7 3.9 6.3 5.2 4.2 4.4 4.0 0.8 2.3 2.5 2.9 66.1 27.1 6.4 2.2 0.8 12.6 13.9 12.8 31.7 96.8 54.1 4–6 1.0 1.6 1.7 3.7 5.3 5.1 2.5 4.9 6.0 0.5 2.1 2.3 32.0 66.0 60.2 4.0 1.9 3.6 9.6 13.7 15.9 53.3 95.5 94.8 2–4 2.9 1.6 1.6 9.7 6.0 5.8 7.9 4.0 4.6 1.8 2.0 2.1 32.0 132.1 30.1 3.1 1.4 2.5 11.6 12.5 14.5 68.9 159.6 61.3 0–2 1.9 1.6 1.7 7.0 5.9 6.2 6.8 6.2 4.5 1.1 2.3 2.0 31.9 132.0 60.2 2.6 3.4 2.5 12.6 14.5 13.2 63.9 166.0 90.2 158 5 Sediment Quality and Ecological Risk Assessment of Bera Lake a 1 Cd (mg/kg) 0.9 0.8 0.7

0.6 Core2 ISQG 0.5 Core6 LEL 0.4 Core5 0.3 Core4 Core1 0.2 0.1 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm) b 120 Cu (mg/kg) SEL 110 100 90 80 Core2 70 60 Core6 50 Core5 40 Core4 30 ISQG Core1 CBS 20 Q 10 0 LEL 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm) c 120 Pb (mg/kg) SEL 110 100 PEL 90 80 70 Core2 60 Core6 50 Core5 CBSQ 40 Core4 ISQG 30 Core1 LEL 20 10 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm)

Fig. 5.7 (a–c): Contamination levels in compare with the SQG. (d–f): Contamination levels in compare with the SQG. (g, h): Contamination levels in compare with the SQG exceed the LEL and SBSQ limits, especially in the top of Cores 1 and 4 and in the middle of Core 6, and above the SEL (120 mg kg1). The Bera Lake sediments furthermore, are assessed to be slightly to moderately contaminated by Ni metals, especially in the southern and northwest sections. The results show that background values of Ni plot remarkably below the LEL, though their concentrations exceed the LEL value with increasing organic matter in the uppermost layer. 5.7 Bera Lake Sediment Quality 159

Standard levels compared with Pb levels from different parts of the study area show the Bera Lake sediments to be slightly contaminated by Pb metal at the sites of Cores 1, 2 and 4. Lead levels plotted higher than the LEL (31 mg kg1) and far from the SEL limit (120 mg kg1). The Bera Lake sediment profiles therefore, indicate a general upward decline in Pb levels except in Core 4 where there is a reverse trend. Iron is recognized as a plentiful metal in the Bera Lake sediments. Sediment quality assessment shows that concentration of Fe in Cores 1, 4, and 6 plots below the LEL and ISQG levels. On the other hand, iron concentrations in the top of Cores 5 and 6 plots above the SEL and the sediments are severely contaminated by Fe metal. Assessment of the Bera Lake sediments using standard limits revealed a significant contamination by arsenic throughout the study area. Maximum, minimum, and average values of As in the five studied cores are much higher than the severe effective level. The arsenic background value calculated furthermore, exceeds the LEL in all sections of Bera Lake. Chromium levels in the sediment profiles were compared with standard values to assess the pollution status of Bera Lake. The results show that Cr levels plot above the LEL, ISQG, and CBSQG threshold limits in all of the Bera Lake sediments. Chromium has also caused moderate pollution at depths of 15–40 cm in the Bera Lake sediment profiles (Fig. 5.7).

5.7.1 Ecological Risk Assessment of Bera Lake Sediment

Preceding sections of this Chapter have explained the significant contribution of lithogenic and organic-bond metals in terms of the Bera Lake sediment pollution. The results furthermore, reveal the special clustering of metals in different parts of the study area. The reconstruction of the history of Bera Lake as well as documenting of land use changes using anomalies in sediment profiles is one of the main objectives of the present research project. From the data that was obtained and following Hakanson’s (1980) method, calculations were made to determine the parameters Cf,Cd,Er, and RI (Tables 5.7, and 5.8). Calculations have been based on the seven heavy metals identified in Hakanson’s method as well as another 11 major and minor elements. The EF for all layers of the three cores was calculated according to instructions provided in the Global Investigation of Pollution in the Marine Environment (GIPME 1999). In this research, it was assumed that each 2 cm layer was once the uppermost layer or the surface layer at some point in time. The contamination factors and degrees of contamination were therefore, calculated separately for individual layers. In this section, resultant 210Pb dates are compared with vertical variations in ecological risk indices to document historical impacts of land use change in Bera Lake sediment quality. Figures 5.8, 5.9, and 5.10 illustrate historical variations of EF values in sediment columns in the south, middle and north of Bera Lake, respectively. 160 5 Sediment Quality and Ecological Risk Assessment of Bera Lake d 150 Zn (mg/kg) 140 130 CBS 120 QLE 110 L 100 90 Core2 80 Core6 70 60 Core5 50 Core4 40 30 Core1 20 10 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm) e 60 Ni (mg/kg) SEL 50

40 Core2 30 Core6 Core5 CBSQ 20 Core4 LEL Core1 10

0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm) f 120 Cr (mg/kg) SEL 110 100 PEL 90 80 70 Core2 60 Core6 50 Core5 CBSQ ISQG 40 Core4 30 Core1 LEL 20 10 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm)

Fig. 5.7 (continued) 5.7 Bera Lake Sediment Quality 161

g 4.5 Fe (%) 4

3.5 x10000 3 Core2 SEL 2.5 Core6 2 CBS Core5 Q 1.5 Core4 LEL 1 Core1 0.5 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm) h 100 As (mg/kg) 90 80 70 60 Core2 50 Core6 40 Core5 SEL 30 Core4 Core1 PEL 20 CBSQ 10 ISQG LEL 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 Depth (cm)

Fig. 5.7 (continued)

5.7.1.1 Ecological Risk Assessment at South of Bera Lake

Lower risk indicators of 8, 40, and 65 were obtained for the degree of contamination, ecological risk indices for all metals, and ecological risk, samples from the south basin of Bera Lake, respectively (Tables 5.6, and 5.7). In distinct strata at depths of 0–15, 29, 33, 49, and 57 cm, however, Bera Lake appears to have experienced influxes of heavy metals and sediments that have given rise to moderate to significant contamination by some individual pollutants (Fig. 5.8). Organic matter at depths of 0–15 cm have also selectively controlled concentration of heavy metals where calculated contamination factors indicate low contamination for Cu, Zn, Li, Ni, V, Cd, Cr, Na, K, Mg, and Ca. This top layer appears to be enriched moderately and contaminated with Co, As, and Mn, the metals that cluster in class 3. The general increase of the EF from the bottom to the top of the sediment column from the south end of Bera Lake is an indication of the significant role of organic matter especially since 1994. A huge flood in December, 2007 was the main reason for considerable increment in concentrations of Ni, Fe, As, Cd at a depth of 3 cm where ecological risk indices indicated moderate risk. The results also emphasize the significant effects of Cd and As on the values of ecological risk indices in the Bera Lake basin. 162 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

Table 5.8 POC (dry weight) Particulate organic carbon % Drywt content in analyzed samples of master Cores 2, 5, and 6 Depth (cm) Core2 Core 6 Core5 0–3 0.00 4.92 0.00 3–5 0.00 6.61 0.00 5–7 9.44 2.88 0.00 7–9 47.51 0.00 7.47 9–11 62.45 0.00 7.70 11–13 45.59 0.00 0.00 13–15 17.34 0.00 0.00 15–17 0.00 0.47 0.00 17–19 0.00 0.00 0.00 19–21 0.00 0.00 0.00 21–23 8.39 0.38 0.00 23–25 6.27 0.53 0.00 25–27 1.13 0.58 0.00 27–29 2.54 0.69 0.00 29–31 2.58 0.67 0.00 31–33 0.76 0.00 0.00 33–35 0.47 0.00 0.00 35–37 0.00 3.59 0.00 37–39 0.00 11.21 1.36 39–41 0.37 1.43 0.75 41–43 4.16 0.00 0.43 43–45 1.17 0.00 0.44 45–47 2.77 0.00 0.33 47–49 0.00 0.00 0.00 49–51 0.00 0.00 0.53 51–53 0.00 0.66 0.09 53–55 0.00 0.00 0.10 55–57 0.00 4.03 1.62 57–59 0.00 2.20 0.00 59–61 0.00 14.11 0.00 61–63 0.00 0.71 0.00

The EF has revealed clear evidence of heavy metal fluxes especially in the white sandy mud and organic-rich layers (0–39 cm). Based on the resultant dates, the south or main entrance to Bera Lake has experienced two major enrichments of heavy metals in 1986 and in 1994–1995 during the fourth and fifth FELDA projects, and two minor influxes of heavy metals between 1971 and 1979, and in 1991, due the first to third, and fifth, FELDA land development projects, respectively (Fig. 5.8). In view of this, it can be said that, the fourth and additional fifth, FELDA developments projects have played a major role in exposure of weathered bed rock. Therefore, moderate levels of enrichment associated with Cr, Cu, Ni, Cd, As, Pb, Zn, Fe, Co, V, Mn, Sr, Ca, K, and Na were found at depths of 37–39, 29–31, and 17–21. Enrichment continued considerably with Cr, Ni, As, Pb, Co, V, Mn, K, and Na where EF values increased more than 20. 5.7 Bera Lake Sediment Quality 163

Fig. 5.8 Historical changes of EF value at the south of Bera Lake

Exchangeable cation ratios also significantly support the variations in the plots of EF values versus depth. The pre-1970 mean exchangeable cation ratio was calculated to be 4.79 0.76, though during the first, second, fourth and fifth FELDA projects it increased to 6.99, 7.78, 6.66, and 11.8, respectively. The mean exchangeable cation ratio for organic-rich deposits (Layer 4) was calculated to be 4.3 1.15 which represents a negative correlation with organic compounds.

5.7.1.2 Ecological Risk Assessment at Middle of Bera Lake

As with Core 2, the ecological risk indices and EF (of 2 to 5) for Core 6 at the top of the sediment column (0–18 cm) were controlled signiﬁcantly by organic matter (Fig. 5.9). A low contamination level at the uppermost layer is induced by lithogenic metals (Cu, Co, Li, Cr, Pb, Sr, Na, Al, Mg, and K). On the other hand, this layer is contaminated moderately by organic bond metals (Zn, Fe, V, Ni, Mn, and Ca) which cluster together in class 2. At depths in the range of 18–50 cm, heavy metal inﬂux into the middle of Bera Lake increased the ecological risk indices from moderate to considerable contamination. White sandy mud layers (18–43 cm) 164 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

Fig. 5.9 Historical changes of EF value at the middle of Bera Lake which were deposited during and after deforestation phases in the catchment area, are moderately contaminated by Cu, Zn, Pb, As, Mn, Co, and Ca but polluted considerably by Pb at a depth of 38–43 cm (Tables 5.7 and 5.8). These anomalies are in agreement with the influx of 137Cs recorded in 1964, 1983, and 1993. It appears that variations in 137Cs value are controlled by anoxic condition due to re-dissolution of heavy metals combined with horizontal transport to adequately oxygenated parts of Bera Lake. Similar conditions for re-dissolution of major elements and 210Pb has been reported by Robbins et al. (1978) for Lake Erie. Minor peaks of enrichment of heavy metals at the middle part of Bera Lake are also in agreement with the dates of the third and fifth FELDA land development projects. A general upward increase in EF values of Ni, Cd, Zn, Fe, V, Mn, and Ca organic bond metals at the middle of the Bera Lake sediment column, signals the significant role of organic matter especially since 1993. Furthermore, at depths in the range of 50–73 cm, natural conditions have dominated the concentration of heavy metals. A minor influx of Cu, Pb, and Ni was, however, recorded at a depth of 60 cm in 1955. Although, the sediment column in the middle of Bera Lake was 5.7 Bera Lake Sediment Quality 165

Fig. 5.10 Historical changes of EF value at the north of Bera Lake classiﬁed in the low risk category, after Cd (moderate risk), the highest Er values were for As, Pb, and Cu (though they are still considered to be low risk). A vivid decrease in the exchangeable cation ratio was obtained for organic-rich deposits in the uppermost layer of the sediment column. The FELDA land development projects apparently have had a minor contribution to variation of the exchangeable cation ratio. The maximum value appears at a depth of 68 cm which indicates a natural event in the catchment area in 1943. Sediments were moderately enriched by Pb metal during this event.

5.7.1.3 Ecological Risk Assessment at the North of Bera Lake

The organic-rich layer (0–24 cm) showed an increase in the degrees of contamination and EF by Co, Fe, Mn, Zn, Cd, As, Cu, Ni, and Ca metals especially since 1994. On the other hand, those metals (Al, Li, Mg, Cr, and Pb) that clustered together in class 3 represent a lower degree of contamination in this layer. 166 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

There is a distinct difference between the degree of contamination, EF and ecological risk index before, and after, the FELDA land development projects in the northern part of Bera Lake. Contamination factors prior to land use changes in the catchment area were in the non-contaminated mode with the EF of all major and minor elements being less than a factor of 2 or minimal contamination. On the other hand, three remarkable influxes of heavy metals occurred in the northern Bera Lake sediment profile between 1971 and 1974, 1981 and 1983, and between 1986 and 1994 during the first to fourth FELDA land development phases. Enrichment of heavy metals mainly occurred during deposition of the white sandy mud sediments. Normalizing values of metals with Al in this layer, show that the white sandy mud deposits were enriched moderately by a wide range of lithogenic and organic-bond metals (Cr, Cu, Ni, Cd, As, Pb, Zn, Fe, Co, V, Mn, Sr, Ca, K, and Na). The strong affinity of As, Cr, Cu, and Ni for aquatic particles, particularly iron and manganese oxides is also demonstrated in their deposition at Bera Lake in association with these materials. This fact can be clearly correlated with the significant increase of Fe and Mn concentrations in the Bera Lake sediment profile since 1972 after land use change. The organic-rich layers in the uppermost part of the north Bera Lake sediment profile are more highly enriched with Fe, Mn and Co as compared with similar layers in the middle part of the basin. A significant correlation was obtained between the exchangeable cation ratio and EF at the north of Bera Lake. The pre-1970 mean exchangeable cation ratio was calculated to be 5.02 0.33, a quite similar value to that in the south of the study area. This ratio, however, dramatically increased to 10.85 and 9.90 during the first and second FELDA projects. It then decreased to 4 during the third and fourth land development phases. Another peak of 5.20 in this ratio was obtained when the fifth FELDA project started. The mean exchangeable cation ratio for organic-rich deposits was calculated to be 3.64 0.26 which is lower than the background value prior to anthropogenic activities.

5.8 Nutrient Fate in Bera Lake Sediments

Clear variations and some anomalies in TOC and TN were recorded in the analyzed core samples. Concentration of other important nutrients (K, Mg, Ca) in the same samples were used to support interpretation of accumulation conditions in Bera Lake sediments over the last decades. The sulfur contents of Bera wetlands and Lakes reported by Wu¨st et al. (2003) of 0.05–0.5 % are comparable with those for freshwater peat deposits. Total concentration of nutrients in the sediment proﬁles at the main open water and north of Bera Lake decreased in the order of TOC > K > TN > S > Mg > Ca. Figures 5.11 and 5.12 illustrate historical variations of nutrient contents in master cores 5 and 6, respectively. The acidic condition of Bera Lake sediments (pH; 4.2 and 5.2) has been shown by Wu¨st et al. (2003) and by in-situ water chemistry analyses using Hydrolab5 in this research project. In such environments the total C is equal to total organic . uretFt nBr aeSdmns167 Sediments Lake Bera in Fate Nutrient 5.8

Fig. 5.11 Historical variations of nutrient contents at the middle of Bera Lake 6 eietQaiyadEooia ikAssmn fBr Lake Bera of Assessment Risk Ecological and Quality Sediment 5 168

Fig. 5.12 Historical variations of nutrient contents at the north of Bera Lake 5.8 Nutrient Fate in Bera Lake Sediments 169

Fig. 5.13 Charcoals which found from different layers in studied cores

C. Reported TOC in this research involves carbon content of sediments as well as POC which is found in specific strata. Charcoal, roots, pieces of barks and stems were recognized as the main POC which are found abundantly in distinct layers (Figs. 5.11 and 5.12). Table 5.8 shows the POC contents in terms of the dry weight of samples in master cores 2, 6, and 5 which serve as indicators for the south, middle, and north of Bera Lake, respectively. These components were interpreted as signals of environmental events that released large amounts of POC into the basin (Fig. 5.13). For example, Field and Carter (2000) reported that the percent of organic matter content in the sediment derived from burnt lands during the first storm event was relatively high at 56 % with remarkable amounts of suspended charcoal carried to the sink area. Evidence of land development projects is remarkably revealed in POC contents, especially that from depths of 20–34, and 15–40 cm, in cores 2 and 6, respectively. These ranges of depth represent layer 3 comprising white sandy mud which accumulated between 1970 and 1993. Maximum POC content in layer 3 of cores 2 and 6 was calculated to be 8.36 and 11.21 % which indicate the fifth and first FELDA land development projects, separately. The contribution of the POC content reaches 62.45 % in layer 4 of Core 2 which is mainly composed of organic-rich deposits. Master cores 2, 6, and 5 shows that POC content in the Bera Lake sediment column accumulated in layers 2 and 1, respectively. Maximum POC content in grey to dark sandy mud sediments (layer 2) in cores 2 and 5 were calculated to be 4.16 and 1.36 %, respectively. Pre-1950 deposits at Bera Lake (Layer 1) contain a remarkable POC content (14.11 %) especially in Core 6 at a depth of 60 cm. This appears to signal a natural event which released significant amounts of organic matter into the sink area. The results also reveal that nutrient contents in the sediment profiles significantly controlled the rate of nutrient supply and physico-chemical conditions at Bera Lake. While Ca, Mg, and K 170 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

Dendrogram

Pb Co As Cu Na Li K Mg Sr Cr Al TOC Ca Ni Cd TN Fe Zn Mn V

0.87 0.67 0.47 0.27 0.07 -0.13 -0.33 -0.53 -0.73 -0.93 Similarity

Fig. 5.14 Similarities in chemical media of elements and TOC and TN at Core 6

Dendrogram

Co Mn TN Zn TOC Fe As Ni Cd Ca Cu V Na K Sr Al Li Mg Cr Pb

0.87 0.67 0.47 0.27 0.07 -0.13 -0.33 -0.53 -0.73 -0.93 Similarity

Fig. 5.15 Similarities in chemical media of elements and TOC and TN at Core 5 contents have been significantly sensitive to physico-chemical conditions of the basin, TOC and TN contents indicate more the rate of nutrient supply from source areas. Hierarchal cluster analyses indicate proper similarities in chemical conditions in which nutrients and metals were deposited in the Bera Lake sediment column (Figs. 5.14 and 5.15). Figure 5.15 illustrates a significant correlation between the TOC content and Ca, Ni, and Cd metals. Maximum similarities furthermore, are seen between the 5.8 Nutrient Fate in Bera Lake Sediments 171 accumulation of TC and Fe, Zn, Mn, and V metals. Class 3 also indicators of metals bounded to the organic matters and which mostly enriched with existing of them. At the north of Bera Lake, organic-bond metals as well as Cu cluster in classes 1 and 2. A significant positive correlation also appears between TOC and Fe, and between TN with Mn, and Co metals. These groups show high similarities in accumulation media with As, Ni, Cd, Ca, Cu, and V metals. Metals which cluster with nutrients, however, show minimum similarities with lithogenic metals in terms of chemical conditions during accumulation. This trend appears clearly in Figs. 5.14 and 5.15 in which there is a negative correlation between Mg and K concentrations and TOC and TN values. Three influxes of organic carbon into the middle of Bera Lake sediment profile were recorded at depths of 68, 40, and 20 cm, respectively in 1948, 1970, and 1991. The deepest peaks are related to a natural event or an artificial one when large amounts of POC and organic rich deposits settled. The second peak showed the remarkable contribution of maximum deforestation at the start of the FELDA projects with accumulation of a certain charcoal horizon. The youngest peak represents a remarkable change in chemical media of the basin and the commencement date of organic-rich deposition in layer 4. The TN content has also increased coinciding with accumulation of organic-rich deposits. The C/N value as an indicator of eutrophication therefore, decreased significantly and showed an upward decreasing trend in the middle of the Bera Lake sediment column. This shows that in situ vegetation and algae have played minor roles in the production of organic carbon. On the other hand, the contribution of forest burning and land preparation has been earlier explained in the introduction. These processes continuously have promoted TN content in the sink area. Different variation trends in nutrient content were recorded in the north of Bera Lake in comparison with other parts of the basin. A sharp and significant variation was recorded in nutrient content prior to, and after, land development projects. In this part of basin, eutrophication increased in two remarkable steps. These steps appear clearly in the upward decrease of K and Mg as lithogenic-bond nutrients. An upward increase in eutrophication furthermore, started from 1973 in the sediment column at the north of Bera Lake. This trend reached a maximum level which coincided with the third FELDA land development project in 1985. A constant rate of nitrogen has been recorded from 1985 until the present-day, indicating continuous deforestation and nitrogen release to the sink areas. Reworked 137Cs furthermore, shows two peaks in agreement with influxes of nutrients into the north of the basin especially in 1975 and 2001. A clear correlation in TOC, TN, and Ca values appeared especially from the depth of 24 cm, and from 1985. An increasing upward trend in the C/N value has dominated the north of Bera Lake. There is therefore, a negative correlation between the middle and the north of the basin. Evidence indicates that chemical media in the north of Bera Lake created a condition where nutrients were significantly preserved in contrast to the middle of basin. According to US Taxonomy, Bera Lake sediment would be classified as being high organic nitrogen sediment because of nitrogen enrichment. 172 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

5.9 Discussion

The literature review has revealed that the influx of contaminates can be used as an environmental changes and an independent time marker for reconstructing the history of lakes over the past few decades. Literature also shows that the long- term investigation of pollution can be separated into a pre-, and post-, 1950 industrialization period. Long-term variations in concentrations of heavy metals in a lake sediment profile can be investigated by comparing the pre-, and post-, industrialization times using radioisotopes. A remarkable gap in previous works in the study area was identified to be the medium-term sediment quality and ecological risk assessment. The multidisciplinary importance of Bera Lake especially in terms of aquatic life and related human health also encouraged this research to define and determine the Bera Lake sediment quality assessment as one of the main objectives of study. The research also intended to correlate environmental impacts of land use change to heavy metal fluxes into the Bera Lake. It was initially thought that the influx of heavy metals involved contaminants but this was not so when compared with sediment quality guidelines to determine threshold of pollution. In other words, contaminants could be not harmful to human health when compared with earlier, and present-day standard limits of pollution and toxins. A wide range of sediment quality standards and ecological risk assessment indices have therefore, been applied to achieving the objectives of the present research. The contribution of natural and anthropogenic events has been evaluated in terms of their effects on the creation of dissolved loads and accumulation at Bera Lake based on resultant data. The composition of the sediment at Bera Lake remarkably reveals the overall parent rock combination. There are apparently Al-bearing deposits in the Bera Formation (Permian) and Triassic granite intrusion. These rock units have been deeply weathered with a thick pale, bleached layer and in situ secondary minerals. In addition, there are outcrops of the Redbeds Formation (Jurassic), especially in the west and northwest of the study area. This formation is mainly responsible for promoting Fe contents in the soil and sediment profiles of the area. MacDonald (1970) identified iron-rich strata as being mineral ores in the Bera Lake catchment thus indicating them as iron-bearing sources for increasing Fe contents in the sink areas. Deposition of erosion-induced sediments in the Bera Lake basin started with deposition of a massive white sandy mud (Layer 3). There is good agreement with the results of the cluster analyses and the vertical variations in sediment composition in layer 3. The first population of elements which was associated with deposition of the white sandy mud involves lithogenic Na, K, Sr, Al, Li, Mg, Cr, and Pb metals. A deep positive correlation with a significant Pearson coefficient r-value existed for this metal group in all sections of Bera Lake. Cluster analyzing properly revealed their relationships and classified them in a nearest distance and similar group. Correlation of 210Pb dates in the Bera Lake sediment column and heavy metal enrichment, implied effects of land clearing in FELDA projects in aggressive chemical weathering and sediment supply of exposed rocks. 5.9 Discussion 173

Based on the resultant dates, the south and main entrance to Bera Lake has experienced two major enrichments of heavy metals in 1986, and in 1994–1995 during the fourth and fifth FELDA projects, and two minor influxes of heavy metals between 1971 and 1979, and in 1991, due to the first to third, and fifth, FELDA land development projects, respectively. In view of this, it can be said that, the fourth and additional fifth FELDA land developments projects have played a major role in exposure of weathered bed rock and the moderate to significant enrichment of Ni, Cu, Cr, and Zn heavy metals in the southern part of Bera Lake. Low contamination degrees and EF were obtained from cores in the deepest part of Bera Lake where the minimal to moderate EF of heavy metals especially Zn, Fe, Ni, Cu, Cr, and Pb is in agreement with the influx of 137Cs recorded in 1964, 1983, 1993, and appears to be controlled by anoxic conditions due to re-dissolution of heavy metals combined with horizontal transport to adequately oxygenated parts of the Bera Lake. Similar conditions of re-dissolution of major elements and 210Pb has been reported by Robbins et al. (1978) for Lake Erie. Minor peaks of enrichment of heavy metals in the middle part of Bera Lake are also in agreement with the dates of the third, fifth FELDA land development projects. There is a distinct difference between the degree of contamination, EF and ecological risk index both pre- and post-, FELDA land development projects in the northern part of Bera Lake. Contamination factors prior to land use changes in the catchment area were in a non-contaminated mode with the EF for all major and minor elements being under the factor of 2 or minimal contamination. On the other hand, three main influxes of heavy metals occurred in the northern Bera Lake sediment profile between 1971 and 1974, between 1981 and 1983, and between 1986 and 1994, during the first to fourth FELDA land development phases. Enrichment of heavy metals mainly occurred during deposition of white sandy mud sediments where Zn, Fe, As, Mn, V and Co has been moderately to significantly enriched. The strong affinity of As, Cr, Cu, and Ni for aquatic particles, particularly iron and manganese oxides is also demonstrated in their deposition at Bera Lake in association with these materials. This fact can be clearly correlated with the significant increase of Fe and Mn concentrations in the Bera Lake sediment profile since 1972 after land use change. Sediment profile interpretation of Bera Lake and its 210Pb dating has emphasized the accumulation of organic-rich to peaty sediments in the top 20 cm (uppermost layer) of the sediments since 1993 due to high organic waste production associated with oil palm plantations. Layers with as much as 20 % organic matter include roots, bark, stems, charcoal, and other organic debris. Although many local land developments have occurred during the last two decades, most of the original FELDA districts have been in place for quite some- time, and the present runoff thus mostly contains organic materials. Agricultural development in the catchment areas has thus dictated that the Bera Lake sediments in the wetlands will be biomass and other organic matter after stabilization of the planted forests. These materials are a well-known sanctuary for microorganisms to absorb inorganic heavy metals, which they then transform to organic forms. Cluster analyses revealed a clear correlation between the deposition of organic-rich 174 5 Sediment Quality and Ecological Risk Assessment of Bera Lake sediments and a specific group of metals involving Fe, Mn, As, Zn, Cu, Ni, V, Co, Ca and Cd metals. Vanadium, which is known as an indicator of oil pollution (Anke et al. 2005) also falls into this cluster and agrees with the spread of organic-bond heavy metals. The results revealed that its level in studied samples is close to its concentration in shales (100–130 mg kg1) which are one of the dominant lithology in the catchment area. The clear increase in concentration of V furthermore, coincided with the start of the FELDA land development phases. Fuel consumption is an unavoidable item for machinery during land preparation and plantation stages and this has released large amounts of V to the soil and sediments. Arsenic is significantly associated with contamination in the Bera Lake sediments. Agronomic projects and the geological setting of the study area as nonpoint sources have mainly contributed to the arsenic present. Burning of felled land during land preparation is apparently responsible for the oil palm plantations promoting the arsenic content of Bera Lake deposits. Arsenic is present naturally in the aquatic and terrestrial environments owing to weathering of rock and soil. Further study, however, is needed to estimate the real distribution of arsenic in the Bera Lake large catchment. Arsenic appears in the organic-bond group of metals in Bera Lake and indicates the importance of organic matter in enrichment of this metal. Iron and manganese oxides are well known for their ability to absorb and enrich other metals like As, Cr, Cu, and Ni. They play an important role in encouraging deposition of the other metals in the bed sediments. The fate and persistence of As, Cr, Cu, and Ni is also intricately connected with the fate and persistence of iron oxides. The Mn/Fe ratio values for Cores 1, 2, 4, 5, and 6 revealed the important role of iron oxide at Bera Lake. These values are also influenced by redox conditions, pH, and microbial activity in the sediments. The sediments therefore, act as an important route of exposure to aquatic organisms for As, Cr, Cu, and Ni. These metals account for adverse biological effects in the organic-rich sediments of Bera Lake. For instance, the many expected adverse effects by Arsenic include a decline in benthic invertebrates, mortality expansion, and behavioral changes (CCME 1995). Benthic organisms are exposed to both particulate and dissolved forms of the metals in interstitial and overlying waters. They also exposed to sediment- bound As through surface contact and ingestion of sediment. Inorganic heavy metals are the predominant form in the sediment, the water column, and interstitial water. Microorganisms in the sediments can transform inorganic forms of heavy metals into organic forms, which can perfectly collect in aquatic organisms. Microorganisms provide the biochemical link in the cycling of metals in aquatic systems. The methylated forms found in interstitial waters are by-products of microbial action (CCME 1995). Dose–response models expressed on the metals exposures to at a particular site as main reason for their adverse effects. In addition, the sensitivity of individual species of aquatics account for adverse effects of metals. Bera Lake is a sink area which provided progressively enriched metals with maximum exposure to aquatics. 5.9 Discussion 175

A previous study (Wu¨st et al. 2002) and field tests indicated that the pH values of Bera Lake sediments and water column are between 4.4 and 5. This acidic condition of Bera Lake may be the result of acid rain, the decomposition of organic matters 2 (release of carbon dioxide) and the incremental addition of SO4 (sulfate) and NO3 ions, leading to a reduction in the exchangeable cations ratio, i.e., (K+Na)/(Ca +Mg), and organic matter preservation in the uppermost layer of the sediment profile. In such conditions, bottom-dwelling decomposing bacteria begin to die off and leaf litter and dead plant and animal materials begin to accumulate. With regards to heavy metals, the degree to which they are soluble usually determines their toxicity. A rule of thumb indicates that the lower the pH, the more toxic the metal as they are more soluble then. The first contribution of this research to knowledge was the introduction of the background values of each individual metal which can use for ecological risk assessments at any natural and artificial lake in Malaysia. Normalizing metals using the Al value is recognized as being much better than using the Li metal. Background values were calculated for individual metals with minor uncertainty. The validity of background values was well confirmed by ecological risk assessment indices in which they successfully revealed any anomalies and variations in the Bera Lake sediment columns. The results furthermore, have confidently supported the capability of the selected methods in achieving the research objectives. The research has remarkably contributed to knowledge in terms of the introduction of EF and the exchangeable cation ratio between other contamination factors as the best indicators of anthropogenic activities at any lake sediment profiles. The lowest capability in order to show effects of land use changes or influx of heavy metal was recognized for Igeo. Identification of the most toxic metals between the analyzed major and minor elements has been another achievement of the present research. Places in Bera Lake where contamination was above the upper pollution threshold were revealed in this research project. The study also remarkably emphasized that Fe, Mn, Co, Ni, Cd, Cu, Ca and Zn are the best indicators of organic matter enrichment under acidic conditions. On the other hand, lithogenic K, Na, Sr, Al, Li, Mg, and Pb metals can be used as indicators of land use change in further studies especially in Malaysia. This study therefore, has appropriately introduced the best materials and methods for further ecological risk assessments in Malaysia and in so doing has achieved one of the objectives of the project. Decision makers at the RAMSAR site can therefore, now find answers to their questions on why the fish population has dramatically decreased in Bera Lake and why seasonal emigrant birds do not choose the wetlands and open waters of the area. Land use changes have seriously affected the nutrient cycle in the wetlands and open waters. Interruption in natural accumulation trends has been remarkably illustrated in the historical study of nutrient contents in the Bera Lake sediment columns. Different rates of eutrophication in the middle and north of Bera Lake have also emphasized the effects of morphological and hydrological factors in creating semi-closed areas and increasing nitrogen enrichment. 176 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

25 10000 TOC&POC Deforestation 9000 20 8000 Deforestation Area (ha) 7000 15 6000 5000 10 4000

TOC & POC % 3000 5 2000 1000 0 0 1986 1984 1979 1976 1974 1971 1969 1967 1964 1962 1959 1957 1981 2009 2006 2004 2001 1999 1996 1994 1991 1989 1954 1952 1949 1947 1944 1942 1939 Year

Fig. 5.16 Clear increment of organic carbon at the north of Bera Lake since 1980

In the tropics, intense chemical weathering and leaching of minerals leads to a shortage of nutrients. Nutrients are therefore, limited and plants adopt an ability for strong nutrient recycling (Reading et al. 1995). Land development projects at Bera Lake catchment have significantly promoted nutrient release and redistribution. The upward decreasing trend in the C/N and exchangeable cation (K + Na)/(Ca + Mg) ratios at the middle of Bera Lake clearly emphasizes the effects of land development projects in upward increasing eutrophication. A similar C/N ratio trend has been reported by Wu¨st and Bustin (2001) from areas in the south of the Bera lake catchment where water discharge is relatively proper. They have stated that low C/N values signal low bacterial activity and low organic matter decomposition. On the other hand, nutrients like TOC, particulate organic carbon and nitrogen were properly conserved after the onset of land development projects. Two clear shortages in nitrogen contents that appear coincide with the first and third FELDA projects. Overall chemical results like exchangeable cation ratio, dissolved oxygen and pH have demonstrated a good media for conservation of nutrients at the north of Bera Lake since 1980. In addition, the increased production of biomass from clear-cutting of existing forests and after establishment of oil palm plantations has resulted in an influx of organic carbon into Bera Lake. The results showed that significant conservation of nutrients in the south and middle of the study area only commenced later from 1991 (Fig. 5.16). The C/N ratio has increased to a value of 24; a value similar to that at Paya Belinau in the south of the study area as reported by Wu¨st & Bustin (2001). The lower hydrological circulation in those semi-closed basins seemingly leads to minor 5.9 Discussion 177

0.9 10000 TN Deforestation 0.8 9000

0.7 8000 Deforestation Area (ha) 7000 0.6 6000 0.5 5000 0.4 4000 0.3 Ttotal Nitrogen % 3000

0.2 2000

0.1 1000

0.0 0 2009 2001 1999 1993 1991 1983 1980 1974 1972 1964 1962 1956 1954 1947 1946 1938 2007 2005 2003 1997 1995 1970 1968 1985 1958 1950 1948 1940 1966 1989 1987 1978 1976 1960 1952 1945 Date (yr)

Fig. 5.17 Nitrogen content in Bera Lake and deforestation phases correlation

DO and more anoxic and acidic depositional media. Cluster analyses properly revealed a negative association of lithogenic metals in the organic-rich mud in the uppermost layer of the Bera Lake sediment column. Low mineralization of organic material is an expected process in this part of the Bera lake sediment profile. The fixation of potassium (K) and sodium (Na) entrapment at specific sites between clay layers tends to be lower under acid conditions. In such situations, calcium (Ca) which is known as an organic bound element can exchange potassium position. This means that after the onset of land development projects, potassium availability has increased and led to increases in vegetation cover especially Pandanus over the Bera Lake wetlands and open waters. This process is more common in the north of the study area than in other parts. The Bera Lake water quality analyses furthermore, showed a remarkable northward increase in NO3 contents as indicator of the rate of eutrophication. 210Pb dates using the CRS model have also been verified by the stratigraphic nutrient dates and charcoal horizons. The overall variation in nutrient contents versus depth also appears to be in good agreement with anthropogenic activities in the catchment area (Fig. 5.17). The present study has thus adequately answered questions about the environmental impacts of land use changes on nutrient redistribution. The unique destiny of nutrients which have been released from source areas during and after FELDA projects have been shown in this research. Signif- icant recycled nutrients are found in the uppermost layer of the Bera Lake sediment column as organic-rich deposits. 178 5 Sediment Quality and Ecological Risk Assessment of Bera Lake

5.10 Conclusion

1. Natural or background values of the 6 major and 12 trace metals for fresh water natural lakes in Malaysia have first been introduced in this study. These values can extensively be used for ecological risk assessments at other fresh water lakes in Malaysia. 2. This study confidently recommends analyzing concentrations of Pb, As, Ni, Cu, Zn, and Cr, and then normalizing them by Al, for further sediment quality assessments at any catchment in order to estimate effects of land use change. 3. This research project introduced Fe, Mn, Zn, Cd, V, Co, and Ca metals as excellent indicators of eutrophication in lakes where their catchment area have experienced deforestation or afforestation. 4. The highest concentrations of major elements recorded were those of Al and Fe with values of 15.4, and 3.9 %, respectively. The highest concentrations of trace metals were that of V and As with values of 157, and 160 mg kg1, respectively. 5. A northward increase in concentrations of Fe, K, V, Mn, Co, As, Cd, and Sr is seen in the Bera Lake sediment profiles. Under the same conditions, however, the concentrations of Cr, Ni, Cu, Zn, and Pb metals levels significantly declined. 6. Statistical analyses revealed two major metal populations bonded to terrestrial and organic-rich sediments. The first group with moderate to significant similarity included Li, Al, Pb, Cu, Cr, Na, Mg, Sr, and K metals. The second group which is associated with deposition of organic-rich sediments included Fe, Mn, As, Zn, Cu, Ni, Co, Ca and Cd metals. 7. Sediment quality guidelines indicated severe pollution of the Bera Lake deposits by As metalloid, and in the northern part by Fe metal. The Bera Lake sediment profiles are furthermore moderately polluted by Cu, Cr, and Ni metals. 8. The overall evidence clearly demonstrates the important role of land use changes by FELDA from 1972 in the physico-chemical contamination of the sediments at Bera Lake. 9. The effects of FELDA land development projects were remarkably manifested in the values of ecological risk indices. They showed that the white sandy mud (Layer 3) is moderately to considerably contaminated mostly by lithogenic metals, while the organic-rich deposits (Layer 4) are moderately to considerably polluted by organic-bond elements particularly As, Fe, Zn, and Mn metals. 10. Four moderate to significant enrichment peaks in metal concentration as documented by 210Pb dates using the CRS model, are in excellent agreement with heavy metal fluxes and ecological risk enhancements in the white sandy mud and organic-rich layers during and after FELDA projects. 11. A significant correlation exists between the exchangeable cation ratio and heavy metals enrichment. The pre-1970 mean exchangeable cation ratio at Bera Lake, which was 5.02 0.33, faced a dramatic increase to 10.85, and 9.90, during the first and second FELDA projects, respectively. References 179

12. Organic-rich deposits in the top layer of the Bera Lake sediment column serve as a sanctuary for microorganisms that absorb inorganic heavy metals, especially Fe, Mn, As, Zn, Cu, Ni, Co, and Cd, and transform them to organic forms. 13. The Mn/Fe ratio as an indicator of redox condition was tested in the studied cores and revealed a decreasing trend upwards which coincided with increasing eutrophication and acidic condition in the Bera Lake sediment column. 14. Overall sediment and water quality assessment was revealed that bottom-dwelling decomposing bacteria begin to die, whereas leaf litter, dead plant and animal materials begin to be deposited. Aquatic life is threatened by some toxic metals especially As, Fe, and Cr, whose values exceed severe effective levels (SEL).

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Abstract Soil and sediment management plan is important part of an applied limnology in order to mitigate soil erosion and sediment delivery to the sink areas. This chapter is addressed some management practices for approaching sustainable land use scheme and soil and lake conservation. Further, it aimed to achieve sustainable planning regulation for assessing environmental impacts of land uses and relevant guidelines and policies. Application of radioisotopes for soil conservation and watershed management also is presented in this chapter. Management issues involving the catchment as well as the open waters and wetlands of Bera Lake have been revealed through previous chapters. A broad and integrated management practice is proposed for each of these management issues. Specific management actions, including on-ground works and targeted scientific investigations, are recommended to meet each of the management objectives. On-ground practices comprise mechanical and agronomic methods which are supported by research and monitoring and socio-economic controlling practices. This book firmly recommends applying an integrated management plan from watershed to lake area in order to protect natural resources and to achieve the sustainable land use scheme.

Keywords Management plan • Mechanical and agronomic • Natural resources • Socio-economic • Soil conservation • Sustainable land use

6.1 Introduction

Soil and sediment management plan is important part of an applied limnology in order to mitigate soil erosion and sediment delivery to the sink areas. For this purpose several watershed management plans were gathered and reviewed to provide a basis for the major sediment management scheme of study area. The

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 183 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2_6, © Springer Japan 2014 184 6 Watershed Management Practices oldest, and newest, management plans in Malaysia with regard to soil erosion and lake management have presented by Paramananthan and Eswaran (1984), and Sharip and Jusoh (2010), respectively. Problems induced by land use change have been discussed in Paramananthan and Eswaran (1984) work. Sharip and Jusoh (2010) has emphasized the role of an integrated lake basin management plan at Chini Lake watershed area in terms of natural resources protection. His management plan has been focused especially on Chini lake water quality as an ecological index, but the plan does not present solution to reduce soil loss in the catchment area and sedimentation rate in lake and thus mitigate Chini Lake water pollution. Other attempts for management of natural resources in Malaysia have been presented by Malmer (1990), Zulkifli et al. (1990), Dorall and Sinniah (1997), Chee and Abdulla (1998), DANCED (1998), and Mutert et al. (1999). These researches have studied different aspects of natural resources conservation. For example, Malmer (1990) emphasized forestry treatments, while agronomic management practices have been presented by Mutert et al. (1999), and Chee and Abdulla (1998). In addition, Dorall and Sinniah (1997) and DANCED (1998) introduced the GIS based and integrated management plan for BLC area for sustainable natural resources protection. These researches were the results of the AWB integrated management project at Bera Lake. Several attempts to access this management plan were not successful. Some of management practices for approaching sustainable land use scheme and soil and lake conservation have studied by Hui (2010), SPA (2010), and Sullivan (2004). Hui (2010) and Sullivan (2004) for instance have focused on sustainable soil management practices and control of sedimentation in sink areas. In addition, SPA (2010) is sustainable planning regulation for assessing environmental impacts of land uses and relevant guidelines and policies. Application of radioisotopes in terms of soil protection and watershed management have been published by Jun and ZhiYun (2007), IAEA (2001, 2004). For example Jun and ZhiYun (2007) was applied 137Cs as a technique to quantify soil conservation capacities of different ecosystems. Detailed application of fallout 137Cs and 210Pb radionuclides, for sustainable watershed management have presented by IAEA (2001, 2004) in which several kinds of approaches for mitigat- ing of soil erosion and sedimentation rates have listed. There is a long history of study on management plans for sustainable land and water resources in Malaysia with the first interim national forestry policy formu- lated in 1952. This national forestry policy which is currently being implemented in all States in Peninsular Malaysia was revised in 1992 to take into account the latest developments in forestry, in particular, the involvement of local communities in forest development and conservation of biological diversity (Kamaruzaman and Wan Ahmad 2003). Besides the national forestry policy, the IWRM and IRBM are concepts that have been supported in Malaysia for more than a decade as a result of rising water demands, deteriorating water quality in rivers, and environmental challenges in the form of floods, droughts and climate change (Sharip and Jusoh 2010). 6.1 Introduction 185

The Third National Agricultural Policy (1998–2010) focuses on agricultural programmes which aim at high productivity while ensuring conservation and utilization of natural resources on a sustainable basis. Introduction of integrated agriculture with the main emphasis on agroforestry, mixed farming, rehabilitation of marginal land, recycling of organic waste, mulching, cover cropping, composting, organic farming, and soil and water conservation are some of the measures taken to support sustainable agriculture in Malaysia (Ahmad 2001). Malaysia has enacted the following legislations related to land use and environment protection: (i) Land Conservation Act 1960 which relates to the conservation of hill land and the protection of soil from erosion, (ii) Environmental Quality Act 1974 which relates to the prevention, abatement, control of pollution and enhancement of the environment and for the purposes connected therewith, and (iii) National Forestry Act, 1984 which provides for the administration, management and conservation of forests and forestry development within the states of Malaysia and for related purposes (Ahmad 2001). In November 1994, Malaysia became a contracting party to the Convention on Wetlands of International Importance (RAMSAR) Convention. The AWB initiated an integrated management project at Bera Lake with DWNP being the lead management agency (Chong 2007). This project commenced in June 1996, with the aim of conserving the biodiversity of Tasek Bera and its catchment area. The project ended in June 1999 with the publications of several reports, including those on anthropology (Surut 1988), faunal and floral studies by the Forest Research Institute of Malaysia (1997), Giesen (1998) and an ecological and geological report by Wu¨st and Bustin (2001). Although Phillips and Bustin (1998) carried out a preliminary investigation into the peat deposits and the geological evolution of the northern area of Tasek Bera, the most detailed and complementary studies about coalification in Bera Lake and Wetlands was that by Wu¨st et al. (2002, 2003, 2008), and Wu¨st and Bustin (2004). From 1998, the Bera Lake area receives routine monitoring and enforcement attention from personnel of the fisheries, forestry and wildlife depart- ments, while channel clearance (organic matters) is contracted out annually to local residents by the Drainage and Irrigation Department. In terms of management activities, the RAMSAR Site District Site Officer has recently conducted a study on the biodiversity of Bera Lake. The Bera Lake catchment includes natural forest (RAMSAR site) and buffer zone, and the wetlands and open waters which have been highlighted in this research as a territory of multidisciplinary importance. The main drawback that has been recognized in previous national and local studies is the lack of detailed soil and sediment management plans. Available reports have never presented management practices for soil erosion control at land development projects as well as sediment transport and sedimentation mitigation in wetlands and open waters. The majority of land development projects before 1994 and the third National Agricultural Policy (1998–2010) by government agencies or by local stockholders, furthermore, have been carried out without such management practices. 186 6 Watershed Management Practices

6.2 Soil and Sediment Management Plan

Previous Chapters have presented the results of detailed investigations of soil and nutrient redistribution in the catchment of, and eutrophication and sedimentation at, Bera Lake. Management issues involving the catchment as well as the open waters and wetlands of Bera Lake have been revealed through reviews of published literature and current research achievements. Land development projects have been recognized as unavoidable activities that have continuously encroached on areas of natural rainforest since 1960. The re-planting of the oil palm plantations in the Bera Lake catchment has furthermore, been anticipated as there is a limit (25 years) to the time-span and effective duration of oil palm plantations. Eutrophication and clear changes in sedimentation regimes at Bera Lake are the impacts of management issues within the catchment area over the last four decades. A broad and integrated management practice is proposed for each of these management issues (Fig. 6.1). Speciﬁc management actions,

Management Plan

Mechanical Agronomic Research & Socio-Economic Methods Methods Monitoring Controlling

Soil Counter Line Hydrological Job/Skill Conservation Cultivation Stations Creation Practices

Crop Weather Settlements Retention Pond Management Stations Monitoring

Flora and Fauna Check Dams Mulcing Stewardship Business Ethics

Organic Wast Stream & River Social Organic Soil Loss Plots Reintegrate Investment Fertilizer

Terracing & Sil Pits

Bera Lake Reshaping or Dredging

Fig. 6.1 A comprehensive management plan, suggested for Bera Lake catchment 6.2 Soil and Sediment Management Plan 187

Fig. 6.2 Soil erosion risk depicts priority management practices in study area including on-ground works and targeted scientiﬁc investigations, are recommended to meet each of the management objectives. It is to be noted that in the overall management plan proposed in Fig. 6.1, emphasis is on the management issues relevant to one of the main objectives of this research project, i.e. soil and sediment redistribution in the Bera Lake catchment, wetlands and open waters. Suggestions and recommendations are supported by several international publications (Darabaris 2008; Erickson and King 1999) Malaysian management plans (Ismail 2005; Turner and Gillbanks 2003; Ahmad 2001; Sharip and Yusop 2007) as well as the results of this present study.

6.2.1 Mechanical Methods

6.2.1.1 Soil Conservation

Soil conservation practice is one of the main important management measures that is confidently recommended for the Bera Lake catchment. An erosion risk (ER) map (Fig. 6.2) has been prepared based on the soil erosion rate map which was 188 6 Watershed Management Practices mapped using fallout 137Cs radionuclide. The soil erosion risk zoning was carried out using zoning values described in published papers in Malaysia (ECD 2002; Yusof and Baban Serwan 1999) as well as the results of this present study. Published papers for instance, have classified soil erosion exceeding 150 t haÀ1 yearÀ1 as having high erosion risk, though the application of fallout 137Cs radionuclide shows two main ranges of soil erosion between 600 and 1,000, and exceeding 1,000 t haÀ1 yearÀ1 at study area. Soil erosion risk in the Bera Lake catchment was thus separated into five zones, i.e., (1) Very low erosion risk with ER < 50, (2) Low erosion risk with 50 ER 150, (3) Moderate erosion risk with 150 ER 600, (4) High erosion risk with 600 ER 1,000, and (5) Extreme high erosion risk with ER > 1,000 t haÀ1 yearÀ1. The soil erosion risk map demarcates several districts where different scales of on-ground management practices are needed. Cleared lands fall under the critical erosion risk and indicate the serious management issues in the Bera Lake catchment. Similar soil conservation strategies, however, cannot be recommended for newly cleared land as their land use schemes are not similar to those where there is annual cultivation. Cover crops, mulching, terracing, and no-tillage farming are applicable strategies that can be used to mitigate erosion risk in the polygons of Fig. 6.2. This map is a key management plan for complementary soil conservation scenarios. Current areas of critical erosion risk have been mostly created by local residents who have received limited education about environmental protection methods. Land use stewardship by government agencies is therefore, a vital step to prevent illegal land development as well as conserve water and soil resources.

6.2.1.2 Construction of Retention Pond

A retention basin can be used to manage storm water runoff to prevent flooding and downstream erosion as well as improve water quality in an adjacent river, stream, lake or bay. It is an artificial lake with vegetation around the perimeter, and includes a permanent pool of water in its design (ASCE 1998). Retention Ponds are increasingly being used in the agricultural sector and are often fairly small, typi- cally less than one acre. Such hydrological structures are recommended to be constructed along breaks in slope of the main stream in the Bera Lake sub-catchments (Fig. 6.3) where divergent currents terminate in the swamp forests. Managing and controlling floods, sediments, pollution, and nutrient discharge into the sub-catchments is part of the sediment management plan which can be achieved with the construction of retention ponds. Their design and dimensions need to be determined by further hydrological studies in order to compute real water and sediment discharges from the individual sub-catchments.

6.2.1.3 Check Dams

Check dams are another recommended management practice for the Bera Lake catchment. Their primary beneﬁts are to reduce scour and channel erosion by 6.2 Soil and Sediment Management Plan 189

Fig. 6.3 Suggested retention ponds at Bera Lake sub-catchments reducing ﬂow velocity and encouraging settlement of sediment. The secondary purposes are preventing pollution, removing pollutants, and allowing recovery of nutrients and fertilizers. A check dam is a small device constructed of rock, gravel bags, sandbags, ﬁbre rolls, or other proprietary product placed across a natural or man-made channel or drainage ditch (USEPA 1992). Check dams are effective in small channels with a contributing drainage area of 0.8–4 ha. Their design is dictated by runoff, slope, available materials, and management practices purposes. A detailed study needs to be carried out prior to the selection of the actual sites for construction of check dams in BLC.

6.2.1.4 Stream Reintegrate

Water-way management is identiﬁed as another necessary practice in the Bera Lake catchment. Field observations have highlighted the need to clear water-ways in the study area from deposited sediments (Fig. 6.4) and organic particles. The current situation of streams in the area, especially those in oil palm estates, is that they cannot handle runoffs causing overbank erosion and the loss of nutrients. Forested 190 6 Watershed Management Practices

Fig. 6.4 Reduction in water way capacity due to sedimentation

buffer strips (ODNA 2000) can be another solution for stream management in Bera Lake. This is a multipurpose management practice which is suitable in study area. The cultivation of fruit trees in a buffer zone along most streams in the BLC is another multi-beneﬁciary management practice recommended for local residents. Construction of water-way, especially at junctions of streams can reduce over bank erosion. The present situation of water-ways is that they are not suitable for runoff, resulting in retrogressive erosion at streams banks (Fig. 6.5). Slope pipe drains are another solution to control soil erosion in the study area. These pipes can convey concentrated runoff from bare soil especially those is developed land districts. Temporary or permanent culvert crossings furthermore, are a larger scale management practice as compared with slope pipes. Culverts can bypass maximum amounts of water from natural and artiﬁcial lands to properly control runoff.

6.2.1.5 Terracing and Silt Pits

Terracing can be highlighted as a proper safeguard for oil palm plantations that involve steep ground slopes, i.e. slopes exceeding 22 (Turner and Gillbanks 2003). 6.2 Soil and Sediment Management Plan 191

Fig. 6.5 Retrogressive bank erosion at BLC

For slopes exceeding 10 or 15, terracing is highly recommended. If steep land is planted without proper preparation, however, as through planting were on ﬂat land, then there will be very adverse results, both economic and environmental. Terrac- ing is a good solution to stop excess water running freely away and serves the dual purpose of erosion control and water conservation. Terracing can also incorporate silt traps as non-continuous excavations along the contour; a continuous excavated section left every few meters to stop water actually running along them. The excavated earth is used to erect a continues earth bank (Turner and Gillbanks 2003). For planting terraces, the distance between each terrace would be the nominal limiting distance between palms, e.g. for 143 palms haÀ1 this would be 9 m (Fig. 6.6). In the study area, ground slopes exceeding 10 are mostly observed in sub-catchments 1, 4, 6, 7, 9, 11, and 12. The management practice of terracing is thus strongly recommended in the replanting of oil palm replantation at the BLC, together with the construction of silt traps to control soil and nutrients loss.

6.2.2 Agronomic Methods

6.2.2.1 Contour Line Cultivation

Contour cultivation refers to all tillage practices or mechanical activities as planting and tillage, that are carried out along the contours of an area. In low rainfall regions the primary purpose of contour cultivation is to conserve rain water by allowing it to inﬁltrate into the soil as much as possible. In humid regions, however, its basic 192 6 Watershed Management Practices

Fig. 6.6 Diagram of planting terrace construction (after Turner and Gillbanks 2003) purpose is to reduce soils erosion and/or soil loss by retarding overland flow. In this farming system the furrows between the ridges made on the contours will hold the runoff water and infiltrate it into the soil and in this way, reduce both runoff and soil erosion. Contour farming gives a better result in fields of relatively uniform slope and is not practical in fields having irregular topographical features. The use of grassed water-ways in conjunction with a contour farming system will furthermore, be essential in reducing the development of gulleys. Contour cultivation is most efficient for reducing runoff and soil erosion from gentle land slopes. Intense rain storms on steeper slopes allow the water to accumulate behind the ridges until it overflows and runs downhill. Contour line cultivation is a recommended management practice to mitigate soil erosion as well as conserve water and nutrients in the cultivated land at Bera Lake catchment. This method should be used during the renovation and replanting of oil palm and rubber plantations in the area.

6.2.2.2 Crop Management

Agro forestry, mixed farming, and cover crops are three effective measures (Table 6.1) in crop management practice in order to save water and soil resources and maximize income (Ahmad 2001). Among the agro forestry systems that have been developed in Malaysia are direct inter-row integration, block planting, perimeter or border planting, and hedge planting system. The choice of timber species is 6.2 Soil and Sediment Management Plan 193

Table 6.1 Agro forestry system, The Third National Agriculture Policy (Ahmad 2001) Main crop Viable projects Undergoing research Rubber Rubber + Cash crops Rubber + Fruit trees Rubber + Sheep Rubber + Rattan Rubber + Poultry Rubber + Timber trees Rubber + Apiculture Rubber + Medicinal plants Rubber + Mushroom Rubber + Bamboo Oil palm Oil palm + Cash crops Oil palm + Timber trees Oil palm + Sheep Oil palm + Rattan Oil palm + Cattle Oil palm + Medicinal plants Timber species Timber species + Cash crop Timber species + Fruit trees Timber species + Tobacco Timber species + Medicinal plants Timber species + Cash crops Timber species + Cash crops + Medicinal plants + Medicinal plants Timber species + Apiculture Timber species + Animal rearing important as it should be fast growing, light branching, deep rooting, self pruning, resistant to drought, diseases and pests, having soil improvement characteristics and having a high survival rate under adverse condition. In Malaysia, Teak (Tectona grandis) and Sentang (Azadirachta excelsa) have been identiﬁed as suitable timber species for commercial production (Ahmad 2001). Crop management is an inevitable practice in the Bera Lake catchment especially in areas of developing oil palm and rubber where the plantations are imma- ture and the soil surface is still exposed to physical and chemical weathering agents. Mature oil palm and rubber plantations in the study area (Fig. 6.7) can be evaluated on their potential for integration into buffalo, cattle, sheep and goat rearing. This practice can reduce stress on the rain forest (RAMSAR site) in terms of the food requirements for local residents. The cattle furthermore, can provide organic fertilizer and contribute to complete carbon and nitrogen cycles in cultivated land. FELDA can also develop a systematic scheme of multi-farming in the developed lands in order to reduce food demands from the natural resources.

6.2.2.3 Mulching

According to the conservation practice standard code 484 (NRCS 2011), mulching implies the application of plant residue or other suitable materials produced off site, to the land surface. This management practice serves multi beneﬁts to conserve soil moisture, reduce energy use associated with irrigation, moderate soil temperature, provide erosion control, suppress weed growth, facilitate the establishment of vegetative cover, improve soil quality, and reduce airborne particulates. This practice is strongly recommended in The Third Malaysia National Agriculture Policy especially for oil palm plantations and growing of vegetables. Annual 194 6 Watershed Management Practices

Fig. 6.7 Feasibility of mature oil palm integrate into cattle feeding biomass productivity in the Bera Lake catchment was potentially calculated to be 1.5 million tons. Effective management of the biomass especially in the mature oil palm plantations and wetlands will provide a great opportunity for producing mulch for soil, water, and nutrient resources conservation in study area.

6.2.2.4 Organic Waste and Organic Fertilizer

Burning and waste disposal are two management issues in developed lands as the Bera Lake buffer zone. The high biomass productivity of tropical rainforests and forested lands also introduces organic waste as an issue in the Bera Lake catchment. In oil palm estates, dead fronds are aligned along rows of planted palms. The use of empty fruit bunches as mulch is also a popular practice. Most empty fruit bunches, however, were previously burnt to produce ash as a substitute for potash. It has recently been found that empty fruit bunches when used as mulch on planted oil palm seedlings, can hasten maturity to within 20 months as compared with 30 months for seedlings without empty fruit bunch mulch. The optimum rate of empty fruit bunch as mulching is 25 t haÀ1 for newly transplanted seedlings (Ahmad 2001). Field observations were conﬁrmed by the application of organic waste as a management practice in mature oil palm plantations. Figure 6.8a, b shows application of empty fruit bunches to control soil redistribution from sheet and gully erosions, respectively. 6.2 Soil and Sediment Management Plan 195

Fig. 6.8 Application of empty fruit bunches (EFB) for soil redistribution controlling (A) EFB controls sheet erosion (B) Shows EFB usage in trapping of eroded soil from gully

Remaining trunks and bunches furthermore, have been used as a soil cover especially in newly opened lands at sub-catchments 6 and 8. Systematic disposal and application of organic wastes by government agencies and locals is thus one of the strong recommendations for effective nutrient recycling as well as water and soil conservation in the study area.

6.2.3 Research and Monitoring

Literature reviews and results of the current research project have emphasized the need for continued research programmes and monitoring of natural resources. The multidisciplinary importance of the Bera Lake catchment also highlights the need for a comprehensive research and monitoring program. The Director of the RAMSAR site is presently mainly monitoring biological aspects of the study area as well as the water quality at 5 stations. The present research has answered the questions of the Director of the RAMSAR site in terms of the dramatic drop in populations of the birds and ﬁshes at Bera Lake. Several distinct layers of the Bera Lake sediments are polluted by heavy metals and in toxic conditions for aquatic life. The Bera Lake catchment nevertheless, includes developed land and natural habitats that are suffering from management issues which need a broad research and monitoring program. This study ﬁrmly recommends the following topics for research and monitoring programmes as their objectives are based on gaps in the present data as well as importance of the study area. 1. Hydrological stations: Measurement is fundamental to assessing water resources and understanding the processes involved in the hydrologic cycle. The Bera Lake catchment needs the construction of two permanent gauges with auto- recording and remote control, at the entrance and outlet of the main open water in order to identify long-term variations in water and sediment discharge, water 196 6 Watershed Management Practices

quality, water balance and fluctuations. Temporary hydrological gauges are also recommended for each sub-catchment in order to identify seasonal and long- term water and sediment discharge. These proposed hydrological stations will provide significant data for determining the agricultural water balance, predicting flood, designing irrigation schemes and managing agricultural productivity. They will also provide valuable information on geomorphological changes, such as erosion or sedimentation, assessing the impacts of natural and anthropogenic environmental change on water resources, and assessing contaminant transport risk and establishing environmental policy guidelines. 2. Soil loss plots: Literature reviews show that on-ground soil loss measurements in the Bera Lake catchment have never been performed and the application of fallout 137Cs radionuclide in present study is the first attempt. Construction of soil loss plots in the study area is thus strongly recommended in order to estimate real soil erosion and run-off especially from cleared and under developing lands. Their design and monitoring, however, will needs a comprehensive study in order to formulate an appropriate model. 3. Weather stations: Currently, the Fort Iskandar weather station is responsible for climate information on the Bera Lake catchment. Available records of this station are, however, not complete and reliable for proper scientific studies. A large catchment as the Bera Lake (with an area of ~600 km2) which is located between two main mountain ranges requires a more comprehensive weather station with facilities for wireless equipment. The construction of weather stations especially at the RAMSAR site and FELDA administration sites for recording long-term weather data for management purposes is thus also very strongly recommened. 4. Flora and Fauna Stewardship: The literature review has revealed valuable information about the biological aspects of the study area. The flora and fauna diversity at Bera Lake is being investigated by staff at the RAMSAR site and by University of Malaya biologists. These studies mostly involve the main open water, but a comprehensive management plan will require a complete program of flora and fauna stewardship in the whole of the catchment area. Field observations and conversation with local residents has revealed the importance of the natural flora and fauna to the economy of settlements in the area. The wild species and livestock are therefore, an active parts of the Bera Lake catchment and will require a complete management program for conservation of the natural resources.

6.2.4 Socio-Economic Controlling

The fourth angle of a comprehensive management plan that has been recognized is socio-economic monitoring (Darabaris 2008). The settlements and their socio- economic issues are directly affecting the natural resources in the Bera Lake catchment. Jobs and skill creation, business ethics and social investments are the References 197 main topics of this monitoring. The Bera Lake catchment is the sanctuary of a group of indigenous rainforest people (Semelai). This community today numbers about 4,000; some 1,500 of whom live in the Bera Lake catchment (Chong 2007). As with other indigenous people, the Semelais have a strong affinity with their natural surroundings. Over generations, they have adapted to survival in the area through utilizing the natural resources. They use the plants and flowers around Bera Lake for medicinal purposes, as prophylactics, as intoxicants and as aphrodisiacs (DANCED 1998). Their economy entirely depends upon the natural resources in the Bera Lake catchment. Some of the indigenous people are work in the FELDA plantations as laborers. The main management practice in socio-economic monitoring is the need for special education programmes that will improve the agricultural skills as well as business ethics of the indigenous people (Sharip and Yusop 2007). Educated indigenous people will definitely conserve and harvest the natural resources properly. FELDA can also play an important role by improving the skills of staff to conserve soil and water resources, especially in the buffer zone (cultivated lands). These management practices will provide a guarantee to reduce the adverse environmental impacts of re-planting oil palm plantations.

Conflict of Interests The authors certify that there is no conflict of interest with any financial organization regarding the material published in the book.

Acknowledgments The study discussed in the book was ﬁnancially supported by the Postgraduate Grant (PG008-2013), UMRG (RG257-13AFR) and FRGS (FP038-2013B).

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Documented Land Use History at BLC Since 1972

M. Gharibreza and M.A. Ashraf, Applied Limnology: Comprehensive View 201 from Watershed to Lake, DOI 10.1007/978-4-431-54980-2, © Springer Japan 2014