A Study on the Population Ecology of Waterbirds at the Karaivetti Lake, Ariyalur District, Tamilnadu, South India

A STUDY ON THE POPULATION ECOLOGY OF WATERBIRDS AT THE KARAIVETTI LAKE, ARIYALUR DISTRICT, TAMILNADU, SOUTH INDIA.

Thesis submitted to BHARATHIDASAN UNIVERSITY, TIRUCHIRAPPALLI for the award of the degree of

DOCTOR OF PHILOSOPHY IN ZOOLOGY

By N. KARTHI, M.Sc., M.Phil. B.Ed., (Reg. No. 21679/Ph.D.1/Zoology/Full Time/October 2010)

Under the Guidance of Dr. G. SRIDHARAN, M.Sc., M.Phil., Ph.D.,

POST GRADUATE AND RESEARCH DEPARTMENT OF ZOOLOGY RAJAH SERFOJI GOVT. COLLEGE, (AUTONOMOUS), THANJAVUR – 613 005, TAMIL NADU, INDIA.

APRIL - 2014 Dr. G. SRIDHARAN, M.Sc., M.Phil., Ph.D., Associate Professor, PG and Research Department of Zoology, Rajah Serfoji Govt. College, (Autonomous) Thanjavur – 613 005, Tamil Nadu, India. Cell: +91-94421 56238 e-mail : [email protected]

Date:

CERTIFICATE

This is to certify that the thesis entitled “A STUDY ON THE POPULATION ECOLOGY OF WATERBIRDS AT THE KARAIVETTI LAKE, ARIYALUR DISTRICT, TAMIL NADU, SOUTH INDIA” submitted to Bharathidasan University, Tiruchirapalli, for the award of the Degree of Doctor of Philosophy in Zoology is a record of original research work done by Mr. N. Karthi, M.Sc., M.Phil., B.Ed., during his period of study in PG and Research Department of Zoology, Rajah Serfoji Govt. College (Autonomous), Thanjavur, Tamilnadu, India – 613 005, under my supervision and guidance. This work has not been previously formed the basis for award of any Degree/Diploma/Associate ship/Fellowship or other similar title to any candidate of any other University.

Thanjavur Dr. G. SRIDHARAN April - 2014 (Research Supervisor)

DECLARATION

I hereby declare that the thesis entitled “A STUDY ON THE POPULATION ECOLOGY OF WATERBIRDS AT THE KARAIVETTI LAKE, ARIYALUR DISTRICT, TAMIL NADU, SOUTH INDIA” submitted to Bharathidasan University, Tiruchirappalli, Tamil Nadu has been carried out by me under the supervision of Dr. G. Sridharan, M.Sc., M.Phil., Ph.D., Associate Professor of Zoology, Rajah Serfoji Govt. College, Thanjavur – 613 005, for the award of Degree of DOCTOR OF PHILOSOPHY IN ZOOLOGY. I also declare that this work has not been submitted earlier in whole or part for any other degree of diploma.

Place: Date: (N. KARTHI)

ACKNOWLEDGEMENT

First I wish to thank my Maatha, Pitha, Guru and Dheivam Almighty for blessing on me to complete this work successfully.

I am deeply indebted to Dr. G. Sridharan, M.Sc., M.Phil., Ph.D., Associate Professor, Dept. of Zoology, Rajah Serfoji Govt. College, Thanjavur, for suggesting the problem, scientific freedom, scholarly advice, constant guidance and encouragement throughout the study. Without him I could not have completed this research work. I can’t express my thanks to him.

I am grateful to Dr. K.Anbu, M.Sc., M.Phil., Ph.D., Principal, Rajah Serfoji Govt. College (Autonomous) Thanjavur, for his help in both academic and administrative tasks during the course of my research work.

I express my deep sense of gratitude to Dr. S. S. Rajendran, M.Sc., M.Ed., M.Phil., Ph.D., Head, Dept. of Zoology, Rajah Serfoji Govt. College, Thanjavur, for providing the necessary facilities in the Department to carry out the research work and for his encouragement.

I am thankful to all the Staff Members and all the Lab Assistants of Department of Zoology, Rajah Serfoji Govt. College, Thanjavur, for their valuable suggestions for the improvement of the thesis.

I express my sincere thanks to Dr. S. Raveendran, Associate Professor of Zoology, K.M. College, Adirapattinam, for his help and support in carrying out my work.

I extend my deep sense of gratitude to Dr. S. Asokan, Associate Professor of Zoology, A.V.C.College, Mannampandal, Mayiladuthurai, for his advices, guidance and encouragement throughout the research work. I am grateful to Dr. R. Nagarajan, Assistant Professor of Zoology, A.V.C.College, Mannampandal, Mayiladuthurai, and Mrs. Prof. Rajathi Assistant Professor of Zoology, Holy cross college, Tiruchirappalli, Dr. P. Mariyappan, Assistant Professor of Zoology, Mr. Krishnamohan, Assistant Professor of Mathematics and Mr.V.Murugeson, Assistant Professor of Statistics, for his help in statistical analysis and for the preparation of the thesis.

I am very much thankful to The Principal Chief Conservator of Forests and Chief Wildlife Warden who have given me permission to do the research work in Karaivetti Lake of bird sanctuary.

I would like to extend my thanks to Forest Guard, Mr.Palanivel, Pilot Watchers, Mr.Kalaivanan, Anti Poaching Watchers of Karaivetti birds sanctuary, Karaivetti VAO and Thirumanur PWD Engineer, who rendered help in sample, data collection and for their encouragement.

My hearty thanks to My Sister Ms. P.Ramya, Research scholar and his Family are due strenuous work in the preparation of my thesis.

I thank Mr.G.Sathishkumar, Research scholar, Department of Zoology and My Brothers Mr.N.Dinesh, Department of Physics, Mr.V.Vijay, Mr. M. Chandhrasekar, Mr.A.Thavaselvam, Mr. G.Anand and Mr.K.Udhaya who helped me initially identifying the birds and also for the collection of samples.

I express my sincere thanks to Mr. M.C. Vachanth, Mr. A. Elavarasan, Research scholars and Mr.Vigneshkumar, who evinced keen interested in this research and helped in Photography.

I thank to our Rajah Serfoji Govt. College Office Staffs for their help for preparation of my thesis.

I am very much thankful to Mr.Madhavan, Dr.Ravichelvan, Dr.Ravichandran, Mr. Dandraj, Mr. Sabarinathan, Mr. Mariyappan, Mr.Rajmohan, Mr. Bakiyaraj, Mrs. C. Lalitha, and Ms. Rajeswari for their valuable suggestion for the improvement of the thesis.

I would like to extend my thanks to Mr.Rengarajan, Mr.T.Prabu, Mr. S.R Manikandan, Mr.Dhanapal, Ms. Roopavathi, Ms.Papitha, Ms.Sangeetha, Mr.Kalai, Mr.Dass, Mr.Gnanamuthu, and Mr.Raju Research scholar for their valuable suggestion for the improvement of the thesis.

I express my sincere thanks to Dr. Ambethkar Hostel Warden, Mr. P. Mayavel, Mr. V. Palayan and Students for their help for preparation of my thesis.

I am extremely grateful to AmphiGene Laboratory, for their help in water sample analysis and identification of vegetations. Dr. Murugesan, and Mr. Muthuvel, Central for Marine Research Institute, Parangipettai, for helping me in the identification of the biological samples.

Words are inadequate to express my gratitude to my father Mr.K.Narayanan, mother Mrs. N. Saroja, and my brothers of Mr.N.Elayaraja and Mr. N.Dinesh for their patience and kind co-operation which enabled me to complete my research work.

(N. KARTHI) CONTENTS 1 INTRODUCTION 1 2 REVIEW OF LITERATURE 15 3 STUDY AREA 26 3.1 The Karaivetti lake 26 3.2 Regions of the lake 27 3.2.1. A Region 27 3.2.2. B Region 27 3.2.3. C Region 27 3.3 Meteorological factors of the study area 28 4. METHODS 29 4.1 Study period 29 4.2 Population Studies 29 4.2.1 Diving birds 29 4.2.2 Swimming birds 29 4.2.3 Large waders 29 4.2.4 Small waders 30 4.2.5 Aerial foragers 30 4.3 Determination of water quality factors 30 4.3.1. Physical factors 30 4.3.1.1 Water depth 30 4.3.1.2 Surface water temperature 30 4.3.2 Chemical factors of water sample 30 4.3.2.1 pH 31 4.3.2.2 Dissolved oxygen 31 4.3.2.3 Salinity 31 4.3.2.4 Silicate 31 4.3.2.5 Nitrite 32 4.3.2.6 Nitrate 32 4.3.2.7 Phosphate 32 4.3.2.8 Sulphate 33 4.3.2.9 Calcium 33 4.3.2.10 Chloride 33 4.4 Bottom soil analysis 34 4.4.1 Depth of Soil 34 4.4.2 Soil textural 34 4.4.3 Macro-nutrient analysis of Soil 34 4.5 Analysis of plankton 34 4.6 Analysis of benthic fauna 34 4.7 Threats and conservation issues 35 4.8 Analyses of Data 35 4.8.1 Waterbirds population calculations 35 4.8.1.1 Density of waterbirds 35 4.8.1.2 Diversity 35 4.8.1.3 Richness 36 4.8.2 Statistical tools 36 4.8.2.1 Difference between / among means 36 4.8.2.2 Multiple regression equation 37 4.8.2.3 Continuous variation 37 4.8.2.4 Dummy variables 37 5. OBSERVATIONS AND RESULTS 38 5.1 Waterbirds of Karaivetti lake 38 5.1.1 Phenology of waterbirds visitations to the Karaivetti lake 39 5.1.1.1 Month-wise visitations 39 5.1.1.2 Season-wise visitations 39 5.1.1.3 Category-wise comparison of visitations 40 5.1.1.3.1 Diving birds 40 5.1.1.3.2 Swimming birds 40 5.1.1.3.3 Large waders 41 5.1.1.3.4 Small waders 41 5.1.1.3.5 Aerial foragers 41 5.1.1.4 Fluctuations in the density of waterbirds species 41 5.1.1.4.1 Little Grebe 42 5.1.1.4.2 Little Cormorant 42 5.1.1.4.3 Indian Shag 42 5.1.1.4.4 Darter 42 5.1.1.4.5 Common Coot 43 5.1.1.4.6 Spotted - billed Pelican 43 5.1.1.4.7 Gadwall 43 5.1.1.4.8 Bar-headed Goose 43 5.1.1.4.9 Northern Pintail 44 5.1.1.4.10 Common Teal 44 5.1.1.4.11 Spot-billed Duck 44 5.1.1.4.12 Northern Shoveller 44 5.1.1.4.13 Garganey 45 5.1.1.4.14 Little Egret 45 5.1.1.4.15 Large Egret 45 5.1.1.4.16 Median Egret 45 5.1.1.4.17 Cattle Egret 46 5.1.1.4.18 Grey Heron 46 5.1.1.4.19 Purple Heron 46 5.1.1.4.20 Black-crowned Night -Heron 46 5.1.1.4.21 Indian Pond- Heron 47 5.1.1.4.22 Painted Stork 47 5.1.1.4.23 Asian Openbill - Stork 47 5.1.1.4.24 White Ibis 47 5.1.1.4.25 Black Ibis 48 5.1.1.4.26 Glossy Ibis 48 5.1.1.4.27 Eurasian Spoonbill 48 5.1.1.4.28 Common Moorhen 48 5.1.1.4.29 Purple Moorhen 49 5.1.1.4.30 White - breasted Waterhen 49 5.1.1.4.31 Pheasant - tailed Jacana 49 5.1.1.4.32 Little Ringed Plover 49 5.1.1.4.33 Black -Winged Stilt 50 5.1.1.4.34 Red- watt led Lapwing 50 5.1.1.4.35 Yellow -wattled Lapwing 50 5.1.1.4.36 Wood Sandpiper 50 5.1.1.4.37 Common Sandpiper 51 5.1.1.4.38 Little Stint 51 5.1.1.4.39 Whiskered Tern 51 5.1.1.4.40 Little Tern 51 5.1.1.4.41 Small Blue Kingfisher 52 5.1.1.4.42 Lesser Pied Kingfisher 52 5.1.1.4.43 White-breasted Kingfisher 52 5.1.1.5. Fluctuations in population parameters of Waterbirds groups 52 5.1.1.5.1 Monsoon I 53 5.1.1.5.1.1 Diving birds 53 5.1.1.5.1.2 Swimming birds 53 5.1.1.5.1.3 Large waders 53 5.1.1.5.1.4 Small waders 53 5.1.1.5.1.5 Aerial foragers 53 5.1.1.5.2 Post-Monsoon I 54 5.1.1.5.2.1 Diving birds 54 5.1.1.5.2.2 Swimming birds 54 5.1.1.5.2.3 Large waders 54 5.1.1.5.2.4 Small waders 54 5.1.1.5.2.5 Aerial foragers 54 5.1.1.5.3 Pre-Monsoon I 55 5.1.1.5.3.1 Diving birds 55 5.1.1.5.3.2 Swimming birds 55 5.1.1.5.3.3 Large waders 55 5.1.1.5.3.4 Small waders 55 5.1.1.5.3.5 Aerial foragers 55 5.1.1.5.4 Monsoon II 56 5.1.1.5.4.1 Diving birds 56 5.1.1.5.4.2 Swimming birds 56 5.1.1.5.4.3 Large waders 56 5.1.1.5.4.4 Small waders 56 5.1.1.5.4.5 Aerial foragers 57 5.1.1.5.5 Post-Monsoon II 57 5.1.1.5.5.1 Diving birds 57 5.1.1.5.5.2 Swimming birds 57 5.1.1.5.5.3 Large waders 57 5.1.1.5.5.4 Small waders 57 5.1.1.5.5.5 Aerial foragers 58 5.1.1.5.6 Pre-Monsoon II 58 5.1.1.5.6.1 Diving birds 58 5.1.1.5.6.2 Swimming birds 58 5.1.1.5.6.3 Large waders 58 5.1.1.5.6.4 Small waders 58 5.1.1.5.6.5 Aerial foragers 59 5.1.1.6 Year-wise comparison of density, diversity and richness of total waterbirds groups 59 5.1.1.6.1 Density 59 5.1.1.6.1.1 Density of grand total waterbirds 59 5.1.1.6.1.2 Density of total diving birds 59 5.1.1.6.1.3 Density of total swimming birds 60 5.1.1.6.1.4 Density of total large waders 60 5.1.1.6.1.5 Density of total small waders 60 5.1.1.6.1.6 Density of total aerial foragers 61 5.1.1.6.2 Diversity 61 5.1.1.6.2.1 Diversity of grand total waterbirds 61 5.1.1.6.2.2 Diversity of total diving birds 61 5.1.1.6.2.3 Diversity of total swimming birds 62 5.1.1.6.2.4 Diversity of total large waders 62 5.1.1.6.2.5 Diversity of total small waders 62 5.1.1.6.2.6 Diversity of total aerial foragers 62

5.1.1.6.3 Species richness 62 5.1.1.6.3.1 Species richness of grand total waterbirds 62 5.1.1.6.3.2 Species richness of total diving birds 63 5.1.1.6.3.3 Species richness of total swimming birds 63 5.1.1.6.3.4 Species richness of total large waders 63 5.1.1.6.3.5 Species richness of total small waders 63 5.1.1.6.3.6 Species richness of total aerial foragers 63 5.1.1.7 Evaluation of the influence of year, month and Regions of the lake on the density of waterbirds 64 5.1.1.8 Variation in the water quality features of the Karaivetti lake 65 5.1.1.8.1 Monsoon I 65 5.1.1.8.1.1 Water depth 65 5.1.1.8.1.2 Surface water temperature 66 5.1.1.8.1.3 Water pH 66 5.1.1.8.1.4 Dissolved oxygen 66 5.1.1.8.1.5 Salinity 66 5.1.1.8.1.6 Silicate 66 5.1.1.8.1.7 Nitrite 67 5.1.1.8.1.8 Nitrate 67 5.1.1.8.1.9 Phosphate 67 5.1.1.8.1.10 Sulphate 67 5.1.1.8.1.11 Calcium 67 5.1.1.8.1.12 Chloride 67 5.1.1.8.2 Post-Monsoon I 68 5.1.1.8.2.1 Water depth 68 5.1.1.8.2.2 Surface water temperature 68 5.1.1.8.2.3 Water pH 68 5.1.1.8.2.4 Dissolved oxygen 68 5.1.1.8.2.5 Salinity 68 5.1.1.8.2.6 Silicate 68 5.1.1.8.2.7 Nitrite 68 5.1.1.8.2.8 Nitrate 69 5.1.1.8.2.9 Phosphate 69 5.1.1.8.2.10 Sulphate 69 5.1.1.8.2.11 Calcium 69 5.1.1.8.2.12 Chloride 69 5.1.1.8.3 Pre - Monsoon I 69 5.1.1.8.3.1 Water depth 69 5.1.1.8.3.2 Surface water temperature 69 5.1.1.8.3.3 Water pH 70 5.1.1.8.3.4 Dissolved oxygen 70 5.1.1.8.3.5 Salinity 70 5.1.1.8.3.6 Silicate 70 5.1.1.8.3.7 Nitrite 70 5.1.1.8.3.8 Nitrate 70 5.1.1.8.3.9 Phosphate 71 5.1.1.8.3.10 Sulphate 71 5.1.1.8.3.11 Calcium 71 5.1.1.8.3.12 Chloride 71 5.1.1.8.4 Monsoon II 71 5.1.1.8.4.1 Water depth 71 5.1.1.8.4.2 Surface water temperature 71 5.1.1.8.4.3 Water pH 72 5.1.1.8.4.4 Dissolved oxygen 72 5.1.1.8.4.5 Salinity 72 5.1.1.8.4.6 Silicate 72 5.1.1.8.4.7 Nitrite 72 5.1.1.8.4.8 Nitrate 72 5.1.1.8.4.9 Phosphate 72 5.1.1.8.4.10 Sulphate 73 5.1.1.8.4.11 Calcium 73 5.1.1.8.4.12 Chloride 73 5.1.1.8.5 Post-Monsoon II 73 5.1.1.8.5.1 Water depth 73 5.1.1.8.5.2 Surface water temperature 73 5.1.1.8.5.3 Water pH 73 5.1.1.8.5.4 Dissolved oxygen 73 5.1.1.8.5.5 Salinity 74 5.1.1.8.5.6 Silicate 74 5.1.1.8.5.7 Nitrite 74 5.1.1.8.5.8 Nitrate 74 5.1.1.8.5.9 Phosphate 74 5.1.1.8.5.10 Sulphate 74 5.1.1.8.5.11 Calcium 75 5.1.1.8.5.12 Chloride 75 5.1.1.8.6 Pre - Monsoon II 75 5.1.1.8.6.1 Water depth 75 5.1.1.8.6.2 Surface water temperature 75 5.1.1.8.6.3 Water pH 75 5.1.1.8.6.4 Dissolved oxygen 75 5.1.1.8.6.5 Salinity 76 5.1.1.8.6.6 Silicate 76 5.1.1.8.6.7 Nitrite 76 5.1.1.8.6.8 Nitrate 76 5.1.1.8.6.9 Phosphate 76 5.1.1.8.6.10 Sulphate 76 5.1.1.8.6.11 Calcium 76 5.1.1.8.6.12 Chloride 77 5.1.1.9 Month-wise and season-wise comparison of fluctuations in water quality parameters 77 5.1.1.9.1 Water depth 77 5.1.1.9.2 Surface water temperature 77 5.1.1.9.3 Water pH 77 5.1.1.9.4 Dissolved oxygen 77 5.1.1.9.5 Salinity 78 5.1.1.9.6 Silicate 78 5.1.1.9.7 Nitrite 78 5.1.1.9.8 Nitrate 78 5.1.1.9.9 Phosphate 78 5.1.1.9.10 Sulphate 78 5.1.1.9.11 Calcium 79 5.1.1.9.12 Chloride 79 5.1.1.10 Evaluation of the effects of year, month, regions of the lake on the water quality Parameters 79 5.1.1.11 Variations in the bottom soil parameters of the Karaivetti lake 79 5.1.1.11.1 Soil texture analysis 80 5.1.1.11.2 Monsoon I 80 5.1.1.11.2.1 Soil depth 80 5.1.1.11.2.2 Electrical conductivity 80 5.1.1.11.2.3 Soil pH 80 5.1.1.11.2.4 Nitrogen 80 5.1.1.11.2.5 Phosphorus 81 5.1.1.11.2.6 Potassium 81 5.1.1.11.3 Post-Monsoon I 81 5.1.1.11.3.1 Soil depth 81 5.1.1.11.3.2 Electrical conductivity 81 5.1.1.11.3.3 Soil pH 81 5.1.1.11.3.4 Nitrogen 81 5.1.1.11.3.5 Phosphorus 82 5.1.1.11.3.6 Potassium 82 5.1.1.11.4 Pre-Monsoon I 82 5.1.1.11.4.1 Soil depth 82 5.1.1.11.4.2 Electrical conductivity 82 5.1.1.11.4.3 Soil pH 82 5.1.1.11.4.4 Nitrogen 83 5.1.1.11.4.5 Phosphorus 83 5.1.1.11.4.6 Potassium 83

5.1.1.11.5 Monsoon II 83 5.1.1.11.5.1 Soil depth 83 5.1.1.11.5.2 Electrical conductivity 83 5.1.1.11.5.3 Soil pH 83 5.1.1.11.5.4 Nitrogen 84 5.1.1.11.5.5 Phosphorus 84 5.1.1.11.5.6 Potassium 84 5.1.1.11.6 Post-Monsoon II 84 5.1.1.11.6.1 Soil depth 84 5.1.1.11.6.2 Electrical conductivity 84 5.1.1.11.6.3 Soil pH 84 5.1.1.11.6.4 Nitrogen 85 5.1.1.11.6.5 Phosphorus 85 5.1.1.11.6.6 Potassium 85 5.1.1.11.7 Pre-Monsoon II 85 5.1.1.11.7.1 Soil depth 85 5.1.1.11.7.2 Electrical conductivity 85 5.1.1.11.7.3 Soil pH 85 5.1.1.11.7.4 Nitrogen 86 5.1.1.11.7.5 Phosphorus 86 5.1.1.11.7.6 Potassium 86 5.1.1.12 Month-wise and season-wise comparison of fluctuation in bottom soil parameters 86 5.1.1.12.1 Soil depth 86 5.1.1.12.2 Electrical conductivity 86 5.1.1.12.3 Soil pH 86 5.1.1.12.4 Nitrogen 87 5.1.1.12.5 Phosphorus 87 5.1.1.12.6 Potassium 87 5.1.1.13 Evaluation of the effects of year, month, regions of the lake on the water quality parameters 87

5.1.1.14 Variations in the biological parameters of the Karaivetti lake 87 5.1.1.14.1 Monsoon I 88 5.1.1.14.1.1 Plankton volume 88 5.1.1.14.1.2 Biomass of benthic annelid worms 88 5.1.1.14.1.3 Biomass of benthic molluscs 88 5.1.1.14.2 Post-Monsoon I 88 5.1.1.14.2.1 Plankton volume 88 5.1.1.14.2.2 Biomass of benthic annelid worms 88 5.1.1.14.2.3 Biomass of benthic molluscs 88 5.1.1.14.3 Pre-Monsoon I 89 5.1.1.14.3.1 Plankton volume 89 5.1.1.14.3.2 Biomass of benthic annelid worms 89 5.1.1.14.3.3 Biomass of benthic molluscs 89 5.1.1.14.4 Monsoon II 89 5.1.1.14.4.1 Plankton volume 89 5.1.1.14.4.2 Biomass of benthic annelid worms 89 5.1.1.14.4.3 Biomass of benthic molluscs 89 5.1.1.14.5 Post-Monsoon II 90 5.1.1.14.5.1 Plankton volume 90 5.1.1.14.5.2 Biomass of benthic annelid worms 90 5.1.1.14.5.3 Biomass of benthic molluscs 90 5.1.1.14.6 Pre-Monsoon II 90 5.1.1.14.6.1 Plankton volume 90 5.1.1.14.6.2 Biomass of benthic annelid worms 90 5.1.1.14.6.3 Biomass of benthic molluscs 90 5.1.1.15 Month-wise and season-wise Comparison of fluctuations in biological parameters 91 5.1.1.15.1 Plankton volume 91 5.1.1.15.2 Biomass of benthic annelid worms 91 5.1.1.15.3 Biomass of benthic molluscs 91

5.1.1.16 Evaluation of the effects of year, month, regions of the lake on the water quality parameters 92 5.1.1.17 Relationship of water quality parameters, Soil parameters and biological variables with waterbirds population characteristics 92 5.1.1.17.1 Density of waterbirds 92 5.1.1.17.1.1 Density of grand total waterbirds 92 5.1.1.17.1.2 Density of total diving birds 93 5.1.1.17.1.3 Density of swimming birds 93 5.1.1.17.1.4 Density of large birds 93 5.1.1.17.1.5 Density of small birds 93 5.1.1.17.1.6 Density of aerial foragers 93 5.1.1.17.2 Diversity of waterbirds 94 5.1.1.17.2.1 Diversity of grand total waterbirds 94 5.1.1.17.2.2 Diversity of total diving birds 94 5.1.1.17.2.3 Diversity of swimming birds 94 5.1.1.17.2.4 Diversity of large birds 94 5.1.1.17.2.5 Diversity of small birds 95 5.1.1.17.2.6 Diversity of aerial foragers 95 5.1.1.17.3 Species richness of waterbirds 95 5.1.1.17.3.1 Species richness of total waterbirds 95 5.1.1.17.3.2 Species richness of diving birds 95 5.1.1.17.3.3 Species richness of swimming birds 95 5.1.1.17.3.4 Species richness of large birds 96 5.1.1.17.3.5 Species richness of small birds 96 5.1.1.17.3.6 Species richness of aerial foragers 96 5.1.1.18 Relationship of water quality parameters, Soil parameters and biological variables with density of total waterbirds 96 5.1.1.18.1 Pearson correlation model to predict the density of total waterbirds in response to variation due to water quality parameters 96 5.1.1.18.2 Pearson correlation model to predict the density of total waterbirds in response to variation due to bottom soil parameters 97 5.1.1.18.3 Pearson correlation model to predict the density of total waterbirds in response to variation due to biological parameters 97 5.1.1.19 Socio-economic survey around the lake 97 5.1.1.20 Anthropogenic pressure 97 5.1.1.21 Agricultural pollution 98 6. DISCUSSION 99 6.1 Waterbirds and the Karaivetti lake 99 6.2 Phenology of individual bird visitation 99 6.3 Influence of water quality factors on waterbirds population Characteristics 101 6.3.1 Water depth 101 6.3.2 Surface water temperature 103 6.3.3 Water pH 104 6.3.4 Dissolved oxygen 104 6.3.5 Salinity 105 6.3.6 Silicate 105 6.3.7 Nitrite and Nitrate 106 6.3.8 Phosphate 106 6.3.9 Sulphate 107 6.3.10 Calcium 107 6.3.11 Chloride 108 6.4 Influence of bottom mud factors on waterbirds population Parameters 108 6.5 Influence of biological factors in waterbirds population Parameters 110 6.6 Other factors that influence waterbirds population parameters 111 6.7 Threats and Conservation issues 112 6.7.1 Conflicts with irrigation 112 6.7.2 Water quality 113 6.7.3 Fishing 113 6.7.4 Siltation 114 6.7.5 Weed invasion 115 6.7.6 Encroachment 115 6.7.7 Poaching of birds 115 6.7.8 Cattle grazing 116 6.7.9 Cattle washing 116 6.7.10 Fuel wood collection 116 6.7.11 Pollution 116 6.8 Managements recommendation 117 7. Summary 119 References I Appendixes Publications INTRODUCTION

1. INTRODUCTION

Ecosystem services are the benefits that people, society and the economy receive from nature. For example water provision and purification, food and storm control, carbon storage and climate regulation, food and materials provision, scientific knowledge, recreation and tourism. Understanding and communicating the economic, social and cultural value of ecosystem service (many of which nature provides “free”) is crucial to fostering better management, conservation and restoration practice. Recognizing, demonstrating, and capturing the values of ecosystem services related to water and wetlands can lead to better informed, more efficient, and fairer decision making (Russi et al.,2013).

Birds are involved in many important ecosystem function yet few have been qualified or studied directly as ecosystem service. The function and services provided by birds are crucial to understanding the importance of birds for ecosystem and for the people that benefit from them. Characteristics of most birds make them quite special from the perspective of ecosystems service because most birds fly, they can respond to irruptive or pulsed resources in ways generally not possible for other vertebrates. With understanding and valuing bird service we may assess the environmental consequences of bird declines and extinctions and communicate these findings to public. The ecosystem service provided by birds has made good progress toward this goal, but much remains to be done. Overall, the emphasize is on efforts to conserve bird populations and sustain avian biodiversity also preserve the diverse ecosystem services provided by birds, thus contributing to human well-being (Wenny et al.,2011).

Wetlands are the ecotones or transitional zones between permanently aquatic and dry terrestrial ecosystems. Ramsar Convention has defined wetlands as “areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six meters”. Wetlands are broadly defined as „land transitional between terrestrial and aquatic eco-systems

INTRODUCTION

where the water table is usually at or near the surface or the land is covered by shallow water‟ (Mitsch and Gosselink, 1986). Wetland systems directly and indirectly support lakhs of people, providing goods and services to them and have numerous functions. They provide habitat for plants and animals such as amphibians, fish, reptiles, mammals and birds. They help to control flood waters by acting like a giant sponge, absorbing water during heavy rainfall then slowly releasing it back into the ecosystem.

It assists in erosion control as they are often located between water bodies and high ground. The roots of the vegetation help to protect soil from high impact events such as wave action, heavy rainfall events etc. They are important culturally and for recreation activities and they enhance water quality as they act like giant kidneys, purifying and processing nutrients, suspended materials and other pollutants. (Dugan, 1990; Cladridge, 1991; Finlayson and Moser, 1991; Davies and Cladridge, 1993; Whigham et al., 1993). The value of each wetland is intimately tied up with the culture and needs of the people who exploit it and is dependant to a great degree upon its location. In a developing country like India, large number of people living around wetlands depends heavily on their resources for subsistence and traditional activities like fishing, grazing, farming, reed-gathering etc.

After the Ramsar (Iran) convention on wetlands in 1971, the international community became conscious of the ecodevelopment of these unique ecological systems and today a number of Indian and International Organizations such as the Bombay Natural History Society (BNHS), the International Waterfowl Research Bureau (IWRB), The International Union for Conservation of Nature and Natural Resources (IUCN) and the World Wide Fund for nature (WWF), have been identifying the wetlands, suggesting conservation technologies and educating people regarding the needs, use and importance of conservation of wetlands and their fauna and flora (Asthana, 1979; Cowardin et al., 1979; Yadava and Varshney, 1982; Chatrath, 1992; and Mishra, 1999).

India‟s wealth of wetlands includes both natural as well as man-made wetlands. In fact the proportion of the country‟s land area under man-made wetlands

INTRODUCTION

is about 1.8 times higher than its area under natural wetlands. According to the Ministry of Environment and Forests (MOEF, 1995) report, area of man-made wetlands was around 25, 89,266 ha, and that of natural wetlands was 14, 50,871 ha, rivers, streams, springs, flood plains, a variety of lakes (including chaurs, jheels, beels, sarovar etc.), ponds and marshes are commonest natural wetlands. Each of these wetlands have varying degrees of biodiversity potential and socio-economic value. Though the natural wetlands are endowed with greater diversity of microhabitats and they have high biodiversity values, the potential of large number of shallow man-made wetlands as waterfowl and fish habitats cannot be under estimated. Biodiversity of these wetlands has been facing serious threats from the factors like pollution, siltation, invasion of exotic species, eutrophication, encroachments and over exploitations of natural resources. Due to the dynamic nature of the ecosystems and the anthropogenic impacts on them, the status of wetland biodiversity in India had changed drastically in the recent past (Mishra, 1999).

Fresh water lakes, one of the important types of wetlands, play a vital role in the economics of their respective regions, especially with reference to agriculture, fishing, livestock maintenance and drinking water facilities of the adjacent areas. These wetlands have also been recognized as providing many other benefits such as habitats for wildlife, water quality improvement, flood protection and recreation and aesthetic values. Fresh water wetlands and their biodiversity values are nowadays misused by mankind by several ways. Some of them are unscientific ways of fishing, poaching and hunting of waterbirds, cattle washing, improper irrigation, fuel wood collection, medicinal plant collection, encroachment, siltation, human defecation, weed invasion, detergent pollution, pesticide and fertilizer pollution and sewage disposal.

Wetlands are also called as “biological supermarkets” because of extensive food chain and rich biodiversity that they support. They play major roles in the landscape by providing unique habitats for a wide range of flora and fauna (Mitsch and Gosselink, 2000). Wetlands support and maintain a diverse community of birds (Duncan et al., 1999). Wetland birds are broadly defined as „birds ecologically

INTRODUCTION

dependent on wetlands‟ and include recognized groups popularly known as wildfowl, waterfowl, shorebirds and waders (Jayson, 2002). Man has been aware of the link between birds and wetlands for thousands of years. These habitats are useful for birds for breeding, nesting and rearing of young (Acuna et al., 1994). Declining number of wetlands associate birds is partly attributed to the loss of wetlands (Duncan et al., 1999; Mads et al., 2002).

There had been a lot of earlier reports on the use of various kinds of wetlands by a variety of waterbirds both in India (Ramamurthy, 1965; Anjaneyalu and Vasanthi.R. 1989; Sampath and Krishnamoorthy, 1990; Nagarajan, 1990; Pandiayan, 1999) and also in abroad. (Almer, et.al.1974; Batzer and Resh, 1982; Salmon, 1988; Malhotra et.al., 1990) Sridharan, G. 2003, Vachanth, M. C. 2013. The fresh water lakes in the Cauvery delta region of Tamilnadu, southern India, are major attractions of migratory waterbirds. The Vaduvoor Lake, Udhayamarthandapuram Lake, Karaivetti Lake, Kallaperambur Lake and Thirumeni Lake are the major ones although a few smaller water bodies are also used by waterbirds. Among them the Vaduvoor Lake, Udhayamarthandapuram Lake and Karaivetti Lake are already declared as bird sanctuaries and Kallaperambur Lakes have been proposed as bird sanctuary.

There had been a few scientific studies in the Udhayamarthandapuram Lake (Gnanasundaram, 1991; Paramanandam, 1991; Balamurali, 1995) Vaduvoor Lake (Sridharan, 2003; Vachanth, 2008; Ramesh, 2008; Thavakumar, 2008) and Kallaperambur Lake (Balamurugan, 2009). But the other lakes had not been given proper attention in terms of wildlife research even though some voluntary and non- government organizations conduct periodic bird watching and nature camps there. In fact the comment of Wolstencroft et al., (1989) that “although a considerable amount of wetland research has been undertaken in India, the great majority of information have come from a small number of well known sites such as Keolado Ghana, Point Calimere, Chilka Lake and the Sunderbans of specific regions such as Gujarat and Ladakh” unfortunately still holds good even now for this region. So the present study was undertaken in the Karaivetti Lake, Tamilnadu, Southern India, to fill up this lacuna to some extent.

INTRODUCTION

The provisioning service of birds is not studied to the extent the other services are documented. However, the use of Guano as a nutrient and the historical reports on its trade as a product is well known. In India, there is very little emphasis to this birds product. However, birds play an important role in providing nutrients to water bodies. Roy et al. (2011).

The word „guano‟ has been used to refer both bat and bird droppings in general and it were derived from the word „quichua‟ language means droppings of sea birds. This has been considered as one of the world‟s best natural manure. The process of guano formation starts as plants / animals that are eaten by insects that are eaten and digested by birds and finally it is deposition the floors on sand / on water / on rocks. Bird guano consists of ammonium oxalate, rate and phosphates and the unleashed guano contains 8 to 16 % of nitrogen, 8 to 12% phosphoric acid and 2 to 3 % equivalent potash (Szpak et al.,2012).Guano provides certain ecosystem services in wetland ecosystems including; Soil builder – improves the texture of soil. Lawn treatment – promotes healthy color and growth. Soil cleanser – microbes help to clear any toxins in the soil. Fungicide – when fed to plants through the leaves. Nematocide – decomposing microbes help control nematodes. Compost activator – microbes speed up decomposition.

The nature and degree of waterbirds use of a wetland is generally taken as an indicator of the quality of a wetland. So, a proper understanding of the ecological process in them is essential to devise conservation measures for waterbirds that depend on them and for the management of these resources in a sustainable of physico-chemical and biological features of wetlands that influence their use by waterbirds. The density and diversity of waterbirds had been reported to be influenced by a variety of factors. Weather condition such as rainfall, temperature, humidity, wind velocity and cloudiness had been reported to influence waterbirds densities (Custer and Osborne, 1977; Goss-Custard, 1985; Teylor and Tullock, 1985; and Briggs and Holmes, 1988). A positive correlation between the Magpie Geese density and seasonal rainfall was reported by wild fowls to leave U.K. during September to March 1986-87 (Salmon, 1988). Seasonal fluctuations in waterbirds populations were reported by Fox and Salmon, (1988), Vachanth, M. C. 2013.

INTRODUCTION

Water quality features of the wetlands such as water level, water temperature, salinity, water pH, dissolved oxygen, phosphate, silicate, nitrite, nitrate, ammonia, specific conductivity, total alkalinity, hardness, chloride, sulphate, sodium, potassium, calcium, magnesium, sulphate/chloride, Na/Mg, K/Mg, Ca/Mg, Na/K, Ca/K, Na/Ca, and Na+k/Ca/Mg were regarded as factors, that could influence waterbirds species richness, diversity and density (McMohan, 1967, 1968; Stewart and Kantrud, 1971; Patterson, 1976; Nilsson and Nilsson, 1978; Swanson et al., 1978; and Murphy et al., 1984). According to Murphy et al., (1984) the inclusions of hydrological considerations in waterbirds habitat evaluation had considerable merits because levels of primary productivity in the aquatic systems and their trophic structure and total biomass throughout the aquatic food web are mediated via a host of interacting physical and chemical factors (Hutchinson, 1957; and Wetzel, 1975).

Mittal et al., (1990) had stated that functioning of an ecosystem and its ability to support life forms depends to a greater extent on the physico-chemical characteristics of its water. Hydrology and physico-chemical factors were reported to influence wader densities (Compere and Symoens, 1987; and Mepham, 1987). Wide variations in the waterbirds populations associated with the levels of dissolved oxygen, carbon-di-oxide, alkalinity, salinity, calcium and magnesium had been reported by Sampath and Krishnamoorthy, (1990) at Kaliveli tank, Tamilnadu, India. Murphy et al., (1984) found that the waterbirds density was most influenced by hydrologic features of the habitat such as phosphate, water pH, alkalinity, hardness and temperature in the Taiga ponds, Alaska, U.S.A. The authors also found that water depths and area, and silica content also accounted significantly for the same. The authors had further reported that nitrite, nitrate and ammonia in the waters to influence heavily the variations in the waterbirds density. Role of hydrologic characteristics on waterbirds population dynamics had been documented by Swanson et al., (1978) also.

The metabolism, physiology and behavior of aquatic organisms are directly related to the temperature of the aquatic environment (Wetzel and Likens, 1979). Extreme temperatures restrict the growth and distribution of plants, animals and

INTRODUCTION

microbes. A close correlation between water temperature and fish abundance and diversity was reported by Hoff and Ibara, (1977) in the Slocum river estuary, southeastern New England. Murphy et al., (1984) had stated that water temperature is a regulating factor for the diversity of waterbirds. Water level is another important hydrological feature of the wetlands which influence water bird species richness, density and diversity (Batzer and Resh, 1982; Constant et al., 1988; Pyrovets and Crivelli, 1988; Breininger and Smith, 1990; Velasquez, 1992; Nagarajan and Thiyagesan, 1996; Sridharan, 2003).

The measurement of dissolved oxygen is one of the most frequently used and the most important of all chemical methods available for the investigation of the aquatic environment (Wetzel and Likens, 1979). Dissolved oxygen provides valuable information about the biological and biochemical reactions going on in waters; it is a measure of one of the important environmental factors affecting aquatic life and of the capacity of water to receive organic matter without causing nuisances. Waterbirds density variations associated with the level of dissolved oxygen had been reported by Sampath and Krishnamoorthy, (1990) at Kaliveli tank, Tamilnadu, India. Lelek, (1988) had stated that dissolved oxygen is the factor that could influence waterbirds species richness, diversity and density through their effects on the various aspects of flora and fauna composition of wetland ecosystems.

Natural waters exhibit wide variations in their relative acidity and alkalinity, not only in actual pH values, but also in the total amount of dissolved material producing the acidity or alkalinity. Moyle, (1946) stated that, water bodies having total alkalinity more than 200.0 mg/l were highly productive. Similarly Alikuhni, (1957) noticed that, highly productive waters have to be more than 100.0 ppm alkalinity. The concentrations of these compounds and the ratios of one to another determine the observed pH and the efficiency of buffering of a given body of water (Wetzel and Likens, 1979). The lethal effects of most acids appear when pH < 5.0 and of most alkalis near pH 9.5, although the tolerances of most organisms are considerably more restricted within these pH extremes. Thus, the buffering capacity of natural waters to resist changes in pH can be of great importance to the

INTRODUCTION

maintenance of life. Odum, (1971) regards “Soil and waters of low pH (acid) are quite frequently deficient in nutrients and low in productivity”.

High pH values were reported to be associated with high photosynthetic removal of CO2 by algal plankton (Atkins, 1925) and as such regarded as an environment conducive to high plankton productivity. Low pH values would also result in the fewer taxa of several invertebrates important to water fowls (Longcore et al., 1987; Mcnicol et al., 1987). pH was reported to influence habitat diversity and abundance of aquatic invertebrates (McNicol et al., 1987, Townsend et al., 1987 and Parker et al., 1992), fish (Brown and Turnpenny, 1988) and amphibians (Cummins, 1988). Consequently, the waterbirds which depend on them should also respond to variations in wetland pH (Balamurali, 1995), Vachanth, M. C. 2013. Water pH was regarded as the factor that could influence waterbirds species richness diversity and density through their effects on the various aspects of flora and fauna composition of aquatic ecosystems (Douglass and Relmchen, 1988; Graveland, 1990; Gibbs et al., 1991 and Vickery, 1991).

According to Schell and Krekes, (1989) that acidic lakes may be inferior waterfowl habitats, atleast in the sense that they have less vegetation for shelter and substrate for invertebrates and fewer vertebrates. Water acidity was found to influence the distribution of waterfowl broods in Southern New Brunsnick, Canada i.e., in pH greater than 5.5 the waterfowls are more (Parker et al., 1992). The variation in pH was the principal factor that determines waterbirds diversity in the Pichavaram wetlands (Nagarajan and Thiyagesan, 1996, Sugathan, R. 1982).

The dissolved bicarbonate has a marked effect on the properties of the water, the bicarbonate changes the pH of the water, increases the alkalinity of the water, and imparts hardness to the water (Wetzel and Likens, 1979). The amount of dissolved salts in water is of major importance to the maintenance of life and in the treatment of the water for domestic and industrial use. In addition to bicarbonates, carbonates and hydroxides, other minerals that often dissolve in water in moderate amounts are silica and the chlorides, sulfates and nitrates of calcium, magnesium, sodium and potassium.

INTRODUCTION

- Inorganic carbon as dissolved CO2 and HCO 3 is the primary source of carbon for photosynthesis by algae and large aquatic plants in natural waters. This utilization is balanced by respiratory production of CO2 by most organisms and by influxes of CO2 - and HCO 3 from incoming water and from the atmosphere.

Waterbirds density variation associated with the levels of CO2, alkalinity, salinity had been reported by Sampath and Krishnamoorthy, (1990); at Kaliveli tank, Tamilnadu, India. Hynes, (1970) stated that, in order to safeguard the fisheries interest 25 mg/l of free carbon di oxide has been recommended as upper limit. Moreover, Sharma et al., (1978) have pointed that, the absence of free carbon dioxide is usual in unpolluted water bodies. Hydrological features of the wetlands such as salinity (Barr, 1986; Velasquez, 1992), turbidity (Barr, 1986; McNicol and Wayland, 1992), electrical conductivity (Douglass and Relmchen, 1988; McNicol and Wayland, 1992), hardness (Murphy et al. 1984), alkalinity (McNicol and Wayland, 1992, Relton, A. 1998) and chlorophyll levels (Gogate, 1960, Reginald, L.R., et al., 2007) were regarded as the factors that could influence waterbirds species richness, diversity and density though their effects on the various aspects of floral and faunal composition of wetland ecosystems.

Salinity had been reported to influence to a large extent the succession and dominance of various aquatic organisms. Diatoms were found to be high in the North Canada coast when the salinity was low (Ramamurthy, 1965). The author had further observed the mesoplankton populations were controlled by the diatom availability as their abundance coincided with the diatom maxima. Salinity was reported to influence prawn and fish diversity and abundance (Ramachandran et al., 1965) and wader population density, richness and diversity (Nagarajan, 1990 and Sridharan, 2003).

Silicates play a very important role in fresh water ecosystems (Maitland, 1990). Ramachandran et al., (1965) had stated that the concentration of silicates together with salinity could influence the composition, succession and dominance of various aquatic organisms. As such, the silicates could influence the waterbirds

INTRODUCTION

populations be indirectly via their impacts on aquatic micro and macro-faunal availability and diversity (Nagarajan, 1990 and Sridharan, 2003). Compounds of nitrogen and especially those of phosphorus are major cellular components of organisms. Moyle, (1946) opined that optimum concentration of phosphorus for sustainable and a moderate production was found to be between 0.1 to 0.2 ppm. Banerjee et al., (1990) stated that, about 0.2 to 0.5 ppm of phosphate in water column is a good indication of pond productivity. Since the availability of these elements may be less than the biological demand, they can regulate or limit the production of organisms in fresh water ecosystems (Wetzel and Likens, 1979). Other elements such as iron and sulfur are essential cellular constituents but are required in relatively low concentrations in relation to availability in fresh waters. The major cations, calcium, magnesium, sodium and potassium are usually required in very low quantities, but their concentrations in fresh water can influence the osmoregulation of organisms.

Banerjee et al., (1990) mentioned that, pond water containing more than 1.0- pp, nitrate nitrogen is considered to be good for optimum production of fishes. Dykyjova et al., (1978) have stated that, when intense macrophytic growth is taking place the nitrate contents are very low or nil. Nitrites were reported to be very low during periods of high primary productivity (Ramamurthy, 1965). The limiting effects of nitrites and phosphate on the productivity in the ecosystem and the consequent faunal (prey) distribution and abundance, as it is well documented that the above nutrients play a vital role in the productivity of many aquatic ecosystems (Moyle, 1949; Hutchinson, 1957; Ramamurthy, 1965; Wetzel, 1975; Nilsson & Nilsson, 1978; Richardson et al., 1978; Stauffer, 1991). For example, a causal connection between lake productivity and bird density was established in nutrient-loaded Swedish lakes (Nilsson & Nilsson 1978 and Sridharan, 2003), Vachanth, M. C. 2013.

Gogate, (1960) estimated the chlorophyll content of sea water, which is an index of the phytoplankton standing crop and found that there was an inverse relationship between phosphate and chlorophyll. Relationship between phytoplankton abundance and nitrites, nitrates and phosphates was established by Anjaneyalu and

INTRODUCTION

Vasanthi, (1989). Distribution of waterfowl broods were found to be influenced by calcium, total phosphorus and dissolved organic carbon in Northern Wisconison Lake in Canada (McNicol and Wayland, 1992). Significant influences of nitrites, nitrates and phosphates on waterbirds population parameters had been reported by Nilsson and Nilsson, (1978); Murphy et al., (1984); Nagarjan and Thiyagesan, (1996) and Sridharan, (2003), Vachanth, M. C. 2013.

Characteristics of bottom sediments in the wetlands could also influence the faunal and floral community structure in them. Electrical conductivity was reported to influence macrophyte growth (Barke and Smart, 1986). Meshram, (2003) stated that, macrophytes stimulate the growth of phytoplankton and help in recycling of organic matter. Benthic macro invertebrates were reported to be sensitive to pH changes in the soil (Bell, 1971; Okland, 1980; Haines, 1981 and Eilers et al., 1984). So, the waterbirds which depend on them should also show population fluctuations in response to benthic substrate qualities (Nilsson and Nilsson 1978; Murphy et al., 1984; Nagarjan 1990 and Sridharan, 2003).

The ecology of waterbirds is closely tied to the distribution and abundance of food resources. The role of food abundance on waterbirds densities has been well established (Schroeder, 1973; Swanso and Meyer, 1973; Hoffman et al., 1981; Kaminski and Prince, 1981; Murkin et al., 1982; Hafner et al., 1986; Murkin and Kadlec 1986; Raffaelli et al.. 1989; Sjoberg 1989 and Parker et al.. 1992). Similarly, biotic interactions between primary producers, aquatic invertebrates, fish and birds are gradually becoming better understood and appreciated with reference to the impact of trophic interactions on avian reproductive success (Cynthia and William, 2000). Biotic factors that play a major role in influencing waterbirds densities in a habitat include the availability of planktons, macro fauna such as fish, crabs, prawns etc., and benthic invertebrates (Krull, 1970; Nilsson, 1972; Sugden, 1973; Krapu, 1974; Royamam 1977; Krapu and Swanson, 1978 and Joyner, 1980). According to Royama, (1977) and Joyner, (1980) one of the biotic factors that play a major role in influencing waterbirds densities in a habitat is the availability of plankton. Malhotra et al., (1990) had emphasized that the specific visitations of waterbirds of the Gharaha

INTRODUCTION

wetlands of Jammu, India, were correlated to the seasonal variations in the benthos, plankton and nektons. Invertebrate prey densities influenced the population size of Little Egrets in Camargue, the delta of the Rone river in the southern France (Hafner et al., 1986). The annual variations in the usage of Platte and North Platte rivers in South-Central Nebroska, U.S.A. by migrant sandhill cranes had been found to be caused by differences in the earthworm availability near the soil surface (Krapu et al., 1984).

Importance of the availability of Pila virens on the abundance of Openbill Storks at Kolleru Lake, Andhra Pradesh, India, was documented by Johnson et al., (1990). For many waterfowls benthic invertebrates (especially chironomids) are an important dietary component that influences habitat selection (Safran et al., 1997). For example number of chironomous midges larvae and Eogammarus (Gammaridae) influence the abundance of Mallard population in Suisu Marsh, Solono University, Canada (Batzer et al., 1993). Parker et al., (1992) had stated that abundance of aquatic invertebrates was most influencing the use of wetlands by insectivorous water fowl.

A critical review of the foregoing literature had suggested that the waterbirds species diversity and density could be influenced by the habitat quality, as opined by Todt, (1989). Usher, (1992), the species richness is often affected by the size of the habitat and that diversity is positively correlated with habitat size. The size of a wetland is often a crucial determinant of water bird richness and abundance (Akihisa and Satoshi, 2001), trophic status and or shallowness are also major factors influencing water bird richness and abundance (Suter, 1994). Sandpipers were strictly sensitive to the size of the habitat for their breeding success (Peter and Malcolm, 1994). Habitat are influenced the habitat diversity in many instances (Douglas and Lake, 1994). Several studies indicated the relationship between habitat parameters and aquatic bird density (Davis and Smith, 1998; Mark, 2006).

The present study was aimed to study the influence of habitat quality on the waterbirds species density, diversity and richness at Karaivetti Lake. The impacts various hydrologic, mud and biotic factors at the lake viz. water temperature, depth,

INTRODUCTION

pH, electrical conductivity, turbidity, dissolved oxygen, salinity, nitrate, nitrite, phosphate and silicate (hydrologic factors), soil temperature, electrical conductivity, soil pH, soil nitrogen, phosphorus, potassium and soil texture (soil factors) and availability of plankton and the benthic invertebrates (prey availability) on the monthly and seasonal fluctuations in the waterbirds species richness, density and diversity in the lake, were assessed.

Agriculture is the most important occupation of the people in the catchments of Karaivetti Lake. With the advent of green revolution in agriculture and the drive towards more core production, this area has seen the use of excessive amounts of fertilizers and pesticides. The farmers in this area are most illiterates as far as knowledge regarding the consequences of agrochemical is concerned and this aggravates the situation. Along with the harm agrochemicals is concerned and this aggravates the situation. Along with the harm agrochemicals cause to the farmers and the consumers of so produced crops, it also affects the lake nearby adversely. Consequently, the waterbirds might also be affected as Dev, (1992) reported for the Chilka Lake, India, where the dwindling number of birds in the lake might be because they are becoming victims to bio-magnification of hydrocarbons like DDT and gammahexene.

Waterbirds in the lake are bio-indicators they notify us of certain changes occurring in our environment. For example, they have been used extensively as both indicators and predictors of environmental consequences of using Agro-chemicals (Hardy et al., 1987). They are among the numerous fauna that may be at risk from the use of Agricultural pesticides (Mineau et al., 1990). From economic vies point, the arrival of Abdims stork, (Ciconia abdmiii) notify the local farmer in the northern Nigeria that the rainy season is approaching. Many bird species are pollinators, sunbird belonging to the family Nectranidae patronizes nectar of most flowering plants and several of them are insectivores that aid in checking insects population explosion that could assume pest status. Typical examples of such species include Cattle Egret (Bubulcus ibis), Abdims stork (Ciconia abdmiii) and Abysinian rollers (Crocias abysinica) (Derek, 1992). Besides, the beauty of birds particularly water

INTRODUCTION

birds has made bird watching a very useful way of spending leisure and generating revenue from both local and international tourists. According to Prasad et al., (2002) agricultural conversion and hydrological alterations are the two acute reasons for the loss of wetlands India. In the Indian subcontinent due to rice culture, there has been a loss in the spatial extent of wetlands (Prasad et al., 2002). So, an assessment of extent of pesticide and fertilizer use in the villages in the catchments area of the lake was also made during the present study, to evaluate the threat to the lake and its waterbirds population due to pesticide pollution.

Further studies of socio-economic aspects of the villages surrounding the lake are essential to assess fully the conflicting interests between development and conservation and to derive suitable management measures. So, a socio-economic survey in the nearby villages of the Karaivetti Lake was also undertaken in the present study.

Based on the above considerations, the objectives of the present research were designed as follows: 1. To assess the waterbirds richness and species composition in the lake during various months and seasons of the study period. 2. To estimate the variations in water quality parameters in the lake and to evaluate their relative importance to the use of this lake by waterbirds. 3. To record variations in the soil parameters in the lake and to evaluate their relative importance to the use of this lake by waterbirds. 4. To find the availability of plankton in order to understand the productivity of the lake and to correlate with the waterbirds usage of the lake. 5. To investigate the availability of benthic prey viz. annelid worms and molluscs of the lake and correlate them with the abundance, richness and diversity of waterbirds. 6. To record the threats and conservation issues of this bird sanctuary. 7. To recommend management measures for the conservation of this valuable lake fresh water resource and its avifauna. The present study was conducted during October 2010 to September 2012 in the Karaivetti Lake.

REVIEW OF LITERATURE

2. REVIEW OF LITERATURE

Wetlands support highly valuable pools of biodiversity and genetic resources, but unsustainable development is threatening the biowealth, and even causing species extinction (Khan, 2000). The major activities responsible for wetlands loss are urbanization, drainage for agriculture and water system regulation (Shine and de Klemm, 1999). Bellrose, (1977) found waterfowl densities and propagation to be related to the number of wetlands per square mile; generally, waterfowl densities and propagation increased as the number of wetlands increased.

Over 50% of wetlands in the world have been lost in the past century, and the remaining wetlands have been degraded to different degrees because of the adverse influences of human activities (Fraser and Keddy, 2005). The characteristics of wetlands near the surface are specific containing typical physical, chemical and biological features supporting the aquatic avifauna (Phalke, 2006).

Wetlands have been famously described as “biological supermarkets” because of the exclusive food webs and rich biodiversity they support as “kidneys of the landscapes” because of the functions they perform in the hydrological and chemical cycles (Mitsch and Gosselink, 1993, Pandit, S.J et al., 2001, Kamala, V et al., 2013). Wetlands dependent species are often rare, threatened or found only in a very restricted geographical area. Freshwater lakes and rivers contain just 0.008 per cent of the world’s water but are of great importance for biodiversity as they contain twelve percent of all animal species (Shine and de Klemm, 1999).

Ousudu Lake one of the important wetlands of Puducherry. The periodical survey of the avian fauna in the selected sites of the Ousudu Lake reveals the presence of 41 species belong to 18 families. In general, the species to the order pelicaniformes, Podicipediformes, Ciconiiformes, Anseriformes, falconiformes, Gruiformes, Charadriiformes, apodiformes, Coraciiformes and Passeriformes were found in the Ousudu Lake. However, the Relative density varies with seasons as summer > monsoon > winter. The study on the survey of Avianfauna would be useful

REVIEW OF LITERATURE

for future initiatives in studying ecotourism and conserving the Ousudu Lake, an important wintering area for migratory birds and more suitable for aquatic birds. (Bassouvalingam Kumaran., et al., 2012).

Most studies on waterbirds and their habitats on managed wetlands focus on species richness and abundance/density of waterbirds, which reflect habitat use by waterbirds. Species richness, population abundance and the derived indexes (Wolter et al., 2005) are also generally used as succession criteria in evaluating wetland restoration (Neckles et al., 2002; Konisky et al., 2006). Habitat use, however, might not correctly reflect the habitat requirements of waterbirds or the quality of wetland habitats (Van Horne, 1983, Tatu K. and Pathak, B., 2012).

The most abundant and spectacular winter migrants to the Indian subcontinent are the ducks and waders that constitute 85 per cent of migrant winter bird populations (Alfred et al., 2001).The Indian sub-continent supports more than 1200 species of birds, which contribute more than 15% of the world’s bird species (Salim Ali, 2002).

Waterbirds diversity and abundance in a newly constructed wetland in south Bengal, the wetland began to attract a rich diversity of waterbirds and with the passage of time has proved it’s proved its potentiality to achieve the status of a wetland of International importance. Since 2005, it continues to support Greylag Goose at population exceeding 1% threshold, and from 2007 onwards harbours Ruddy Shelduck at population exceeding 1% threshold. The populations of majority of the important species have been increasing; it is expected to achieve the status of a Ramsar wetland soon, provided we keep the wetland undisturbed and allow it to follow its own course by implementing monitoring programmes on a long-term basis. (Anirban et al., 2012).

Species composition, diversity and abundance of birds were assessed. Sixty four (64) species of wetland birds were enumerated. Fourteen (14) environmental variables were correlated with the wetland birds species richness among which most

REVIEW OF LITERATURE

of the variables were positively correlated with bird species richness except water depth, dissolved oxygen, total hardness and chloride. A strong correlation of bird species was noted with benthos density (r = 0.98).Birds species richness was also positively correlated with macrophytic biomass (r = 0.8), orthophosphate (r = 0.75), and conductivity (r = 0.64). It was observed that bird species richness had a strong negative correlation with water depth and dissolved oxygen. (Satish Balapure et al., 2011).

During 2007-2011 we recorded 199 species at Nandur-Madhyameshwar Bird Sanctuary (Koparde et al., 2012). One of the ecological paradoxes haunting the scientist at the Everglades has been that such large populations of aquatic birds received support in an ecosystem that has been characterized as extremely nutrient- poor. A total of 222 species of birds have been recorded at Nalsarovar. Of these, 122 species (57%) have been waterbirds species (GEER, 1998; Paint et al., 2001).

One of the major reasons for Nalsarovar having high bird species richness and abundance is the diversity of 10 different types of habit components In addition, the immediate environs have agricultural land and it also provide foraging opportunity to birds like cranes, ducks and some shorebirds. However, the Open Water, Habitat and Emergent Aquatic vegetation, have been the main habitat components in the Nal Wetland. (Tatu and Pathak, 2012) Terrestrial plants also occur on islets and shoreland. The terrestrial flora mainly consists of Prosopis juliflora, Zyipbus, Tamarix and Salvadora species (Plandit et al., 2001).

A study examines the habitat use, habitat characteristics and abundance of three species of herons (Catile egret, Little Egret and Pond heron) in seven wetlands habitats in Malappuram and Kozhikode district Kerala, India. The use of various micro-habitats of wetland by the species, the threats to the wetland in the study area and need for their conservation for survival of these bird species are highlighted. (Seedikkoya, et al., 2011).

REVIEW OF LITERATURE

A survey of literature in reference to the ecological aspects of the lakes has revealed that very little work has been done and comprehensive ecological studies are almost non-existent. It can however be mentioned that studies of such a nature carry a great importance in not only for wetland management but also for bird conservation especially the migratory avian fauna. Sporadic efforts have, however been made to study the ecological components of the lakes (Jabeen, 1988; Naseem, 1988; Sharif, 1992 and Ali et al., 1997).

Lind, (1979) and Verry, (1985b) carried out limnological studies for wetlands. Bird population parameters such as species richness, relative density and diversity of birds are frequently used as indicators of habitat quality (Nilsson and Nilsson, 1978; Weller 1978 and Sampath and Krishnamoorthy, 1990).

Beecher, (1942) found a correlation between physical characteristics of wetland vegetation to aquatic birds. Haramis et al., (1986) reported that suitable habitats provide foods required by wintering waterfowls and allow birds to maintain a favorable energy balance. Kantrud, (1986) stated that wetlands near agricultural areas often became highly eutrophic from barnyard and feedlot runoff water. He also reported that dissolved salts and residues from agricultural chemicals moved into wetlands and irrigation practices altered the hydrology and vegetation of the wetlands, which affects the value of wetlands to the waterfowls and other birds.

Chughtai, (1979) studied the limnological study of Rohi nallah and noted a significant decrease in total hardness, total alkalinity, total dissolve solids and conductivity which might have been result of dilution of pond by the rain. Davis et al., (1976) found that an increase in water hardness significantly increased the iron, manganese and nickel in water. Water quality affects the abundance, species composition, stability, productivity and physiological condition of indigenous populations of aquatic communities. Therefore, the nature and health of the aquatic communities is an expression of the quality of water.

REVIEW OF LITERATURE

Comparatively, high dissolved oxygen at Kagal tank is correlated with the presence of littoral and submerged vegetation and high plankton density might be responsible for accelerated rate of photosynthesis in this tank. Banarjee et al., (1990) stated that pond water with 5.0 to 10.0 ppm is considered ideal for fish production. Consideration of water quality are important in waterbirds habitat evaluation because a host of interacting physical and chemical factors can influence the levels of the primary productivity in aquatic systems and thus influence trophic structure and total biomass throughout the aquatic food web (Hutchinson, 1957 and Wetzel, 1975). A relationship between water quality in the wetlands and waterfowl numbers had already been indicated (Patterson 1976; Nilsson and Nilsson 1978 and Murphy et al., 1984).

Correlations have been reported between wetland pH and waterbirds distribution and abundance for the Dipper Cinclus cinclus in the streams of southwest Scotland (Vickery, 1991), between pH and waterbirds use of wetland habitats in central and eastern Maine, U.S.A. (Gibbs et al., 1991) and between pH and habitat selection by insectivorous waterfowl in 65 small lakes near Sudbury, Ontario (McNicol and Wayland, 1992). Because “pH might be considered an indicator of overall productivity that can cause habitat diversity” (Minns, 1989) and has shown significant correlations with species richness of phytoplankton (Almer et al., 1974), diversity and abundance of aquatic invertebrates (Townsend et al., 1983; Eilers et al., 1984; Longcore et al., 1987; McNicol et al., 1987 and Parker et al., 1992), fish (Brown and Turnpenny, 1988) and amphibians (Cummins, 1988), the waterbirds which depend on these organisms as prey should also respond to variations in wetland pH. Longcore et al., (2006) reported that a water pH in the alkaline range supported higher macro invertebrates and thereby attracted more ducks to the water bodies under investigation.

In India, some lakes and reservoirs have been studied for water quality and fishery purposes (Kartha and Rao, 1992; Ravikumar et al., 2006; Nural Alom and Zaman, 2006; Tiwari and Shukla, 2007 and Sridhar et al., 2006). According to Vannucci, (1988), salinity is inversely correlated with biomass production. These

REVIEW OF LITERATURE

microscopic animals (zooplankton) and plants (phytoplankton) flourished when the salinity remained low.

Salinity is an important factor in the management of salt ponds for waterbirds habitats. Generally, water of high salinity is harmful to waterbirds. Waterbirds that drink highly saline loses body weight by dehydration (Purdue and Haines, 1977 and Hannam et al., 2003) and waterbirds avoid water of highly salinity even for roosting because salts reduce the waterproofing of feathers and thus increases the energy costs of thermoregulation (Rubega and Robinson, 1977). Euliss et al., (1989) reported that high salinity water may cause carbonate to precipitate on tail feather of Ruddy Ducks (Oxyura jamaicensis), which erodes the feather and interferes with diving and flying. Water salinity also affects the species composition of aquatic plant communities and consequently, indirectly affects herbivorous waterbirds. In the two coastal lagoons of Denmark, Chara and Potamogeton plants, which are high quality foods for herbivorous waterbirds (mute swans Cygnus olor), are vulnerable to high salinity and were more likely to be found in the lagoon with fresh or slightly brackish water, while Ruppia plants, which are relatively low quality foods for herbivorous waterbirds, are tolerant of high salinity and were abundant in the lagoon with high salinity (Holm, 2002; Holm and Clausen, 2006).

Water salinity also determines the distribution of zoo benthos and aquatic animals and thus influences the use of foraging sites by waterbirds. The effects of water salinity on zoo benthos and aquatic animals are taxa dependent. Velasquez, (1992) and Tekekawa et al., (2006) found that chironomid fly larvae, amphipods, and copepods predominate in relatively low-salinity water but are replaced by brine- adapted organisms such as Artemia and Ephydra in high-salinity water.

The freshwater resource is becoming day by day at the faster rate of deterioration of the water quality is now a global problem. There is an extensive literature, which stresses deterioration of water quality (Tiwari and Mishra, 1986; Tiwari and Ali, 1978; and Khulab, 1989). The zooplankton community is influenced

REVIEW OF LITERATURE

by the physico chemical parameters of the water also bring about seasonal changes in their life process and population dynamics (Nayak, 1989).

In addition to the habitat variables other variables related to the characteristics of sediments (organic matter content and particle size) and water quality (clarity, temperature, dissolved oxygen and pH) can also directly or indirectly affect the growth of aquatic plants, and determines invertebrate abundance (Rehfisch, 1994). Particle size of sediments determines how water and oxygen penetrate sediments and thus affects the presence of meiofauna and infaunal and epifaunal invertebrates (Little, 2000). Water transparency and temperature affect the growth of algae (Nielsen et al., 2002). The temperature of water also affects the hatching of invertebrate eggs and the development of invertebrate fauna (Rehfisch, 1994). Kersten et al., (1991) have demonstrated that the dissolved oxygen in the water affects the foraging of waterbirds by changing the vertical distribution of prey.

The two most important nutrients contributing to anthropogenic or cultural eutrophication are nitrogen and phosphorous. Both these nutrients are present in sufficient concentrations in fresh waters to maintain a healthy ecosystem, but anthropogenic activities may alter their concentrations contributing to algal blooms. Much of the nitrogen and phosphorous entering the lakes is derived from soils.

Electrical conductivity is a measure of the ionic composition of the mud and as such play a vital role in the release of the nutrients from the soil as well as their uptake by the plants (Nagarajan, 1990). Barke and Smart, (1986) observed the electrical conductivity in the sediments of the North American lakes to influence the macrophyte growth in them. Nagarajan, (1990) opined that the electrical conductivity might influence the salinity and nutrient levels in the aquatic environment and thereby the productivity and prey populations and ultimately the waterbirds.

Hutchinson, (1957) stated that “a deficiency of phosphorus is more likely to limit the productivity of any region of earth’s surface than the deficiency of any other metal”. Nilsson and Nilsson, (1978) stated that phosphorus in the bottom soil to be the

REVIEW OF LITERATURE

best predictor of waterbirds density as it is directly related to lake productivity. Patrick and Reimer, (1966) reported phytoplankton as an important indicator of pollution. Fogg et al., (1973) stated that algal growth was particularly abundant in alkaline water. Lenihen and Fletcher, (1978) reported that uncontrolled discharge of effluents could reduce the variety of aquatic life to the point at which it became septic and completely unacceptable for most purposes.

Organisms like plankton are highly sensitive to temperature changes. Green algae grow best between 30 – 35oC. Heated water affects the oxygen supply of a water body. Warmer water holds less oxygen than cooler water. Some organisms are indirectly affected by an increase in temperature because they cannot tolerate the lower oxygen content of water (McKinney and Schoch, 1998).

Phytoplankton respond quickly to environmental changes because of their short life cycles, hence their standing crop and species composition are more likely to indicate the quality of water in which they are found. They strongly influence certain non-biological aspects of water quality (such as pH, colour, odour etc.) in a very practical sense, they are a part of water quality (APHA, 1995). Ge et al., (2009), found a steady, negative correlation between vegetative cover and waterbirds density. Freshwater algal biodiversity and associate physico-chemical factors were studied in India by Veereshakumar and Homani (2006).

Appearance and massive growth of phytoplankton in water bodies depend not only on factors such as light and temperature but also on the nutrient load, which affect species composition (Riegman et al., 1990). According to El-Gindy and Dorham, (1992), the interactions between various physico-chemical and biological factors are the causative regulators for seasonal variation and standing crop of phytoplankton.

The population of zooplankton is influenced by rainfall and water temperature and it can be summarized on the basis of their numerical strength. Information on the distribution of Rotifers in ponds of Delhi and some Asian lake is available in the

REVIEW OF LITERATURE

works of (Pejler, 1974). Zooplanktons are used as bioindicators for the detection of pollution load also take part in the amelioration of polluted wastewater (Mukhopadhyay et at., 2007).

Krull, (1970) described the macrophyte and macro invertebrate associations, which are important for waterfowl abundance. Murkin and Kadlee, (1986) and Kaminski and Prince, (1981) compared the relationships between the densities of waterfowl and macro invertebrate. Succession pattern of plants, invertebrates and ducks in a manmade lake, in Northern Sweden was studied by Danell and Sjoberg, (1982).

Many studies have indicated that there is a strong correlation between vegetation structure and bird diversity (Losito and Baldassarre, 1995; Froneman et al., 2001; Erwin and Beck, 2007). Fishes and invertebrates exposed to organic contaminants may be induced to produce higher levels of enzymes capable of transferring many contaminants to occasionally more toxic metabolites (Conner and Huggett, 1998). Greeson and Clark, (1984), reported wetland importance ecologically and studied factors such as hunting, trapping and fishing.

Moore and Guan, (1999); Lehmann et al., (1997) developed GIS database for lake ecosystem. And a detailed study of bird’s habitat, breeding and protected areas was made by Jarvinen and Koskimies, (1990); Grigorieve, (2000) and Virkkala and Liehu, (1990). Crowder and Bristow, (1988) studied that eutrophication, pollution and sediment load act synergistically to cause deterioration of wetland habitat. They further studied that the farming practices such as drainage and intensive crop production through run-off are major contributors to sediment load and eutrophication. Chaudhary, (1992) in a supplementary report stated that due to drainage, the water level of the Kharal Lake is decreasing. Kent and Styner, 1979 estimated agricultural run-off from the catchments of lakes.

Waterbirds use diverse foods, including seeds (dabbling ducks, cranes), leaves (geese), tubers and rhizomes (geese, swans), invertebrates (shorebirds, waterfowl) and

REVIEW OF LITERATURE

some vertebrates, such as fish and amphibians (wading birds), the amounts, composition and spatiotemporal dynamics of these foods largely affect the use of foraging habitats by waterbirds and can be important indicators of habitat quality (Davis and Smith, 1998; Taft and Haig, 2005 and Hartke et al., 2009). Although food abundance is generally used in assessing habitat quality of waterbirds, food accessibility, which often differs from food abundance, greatly influences habitat use by waterbirds (Bolduc and Afton, 2004).

The loss or impairment of wetland ecosystem is usually accompanied by irreversible loss in both the valuable environmental functions and amenities important to the society (Zentner, 1988).The loss and degradation of wetlands has negatively affected waterbirds, which depend on wetland habitats. How to provide high quality habitats for waterbirds through effective management is a critical issue in waterbirds conservation (Weber and Haig, 1996; Erwin, 2002 and Taft et al., 2002). With the continuous loss of natural wetlands globally, we can expect artificial wetlands to become increasingly important as habitats for waterbirds (Czech and Parsons, 2002).

Overgrazing may cause a decrease in primary productivity (Reinold et al., 1975) an increase in water turbidity (Logan, 1975) and areas devoid of vegetation (Bassett, 1980). Khan, (1992) studied the population trends of waterfowl species due to increase in human and livestock activities. Pospahala et al., (1974) studied that the intensive agriculture can severely effect duck population in the presence of an adequate wetland base. Frayer et al., (1983) and Tiner, (1984) have estimated in California and Lowa, over 90% of the original wetlands have disappeared and it is largely due to the wetland drainage for agricultural expansion. Lane and Munro, (1983) reviewed the rainfall and wetlands in the southwest of Western Australia. They explained the water level affected by rainfall and the attraction of waterfowl species towards the wetlands.

Studies are available about the conservation efforts and management of wetlands and waterfowl. Some of the workers gave a special emphasis to these management issues like Bellrose and Low, 1978; Addy and MacNamara, 1948;

REVIEW OF LITERATURE

Burger, 1973; Oetting, 1982l; Peppard, 1971; Britton, 1982; Fredrickson and Reid, 1988b; Larsson, 1982 and Stotts, 1971. Adamus et al., 1987, has developed wetlands evaluation techniques, Carey and Gill, 1983, studied habitat improvement of wetlands; Cooke, 1988, evaluated lake and reservoir restoration and management techniques. Ecology and management implications of lakes were reviewed by Cooke et al., 1986; Duebbert, 1969; Eckert et al., 1978; Piehl, 1986 and Weller, 1978.

Workers evaluated the factors responsible for birds decline and possible ways and means to rehabilitate the bird population to a normal level. Timothy, (1999); Gole, (1989); Beazley, (1993); Ahmed (1995); Dugon (1989); Robinson and Bolen, (1984), evaluated the wetlands management and tell the ways for the regulation of birds by management. They also explain their importance and threats faced by migratory birds. Threatened birds and important wetland birds are described in Stattersfield and Capper, (2000).

Morrison and Antas, (1987); Newman, (1993); Sanderson and Bellrose, (1969); Piehl, (1986); Caughley and Sinclair, (1994); Stabb, (1989); Weller, (1978) and Ricketts, (2001) explained a conservation strategy for the migratory species evaluating all the factors responsible for declining the bird population and suggestion for improving the habitat used by the salt marsh bird. Many studies have indicated that effective management plays a critical role in enhancing habitat quality of wetlands for waterbirds (Erwin 2002; Balcombe et al., 2005).

Abundant food attracts large numbers of waterbirds and is important for the formation of waterbirds colonies in breeding periods (Bancroft et al., 1994). However, increasing food for waterbirds through wetland management can be difficult. Although the enhancement of nitrogen and phosphorous levels in water bodies increases productivity (Frost et al., 2009), which improves the species richness and abundance of waters (Acuna et al., 1994; Hoyer and Canfield 1994; and Holm and Clausen, 2006).

STUDY AREA

3. STUDY AREA

3.1 The Karaivetti lake The study was carried out in Karaivetti lake, situated between 100 58’ 01” N and 790 11’ 07” E, covering an area of about 442.37 hectares, of Thirumanur taluk, Ariyalur district, Tamil Nadu, South India (Fig.3.1 to 3.3 ). The lake was established in April 5, 1999 as one of the largest freshwater lakes in southern Tamil nadu. The lake is located 50 km from Tiruchirappalli, 35 km from Thanjavur and 12 km from Ariyalur town. The International name is Karaivetti Wildlife Sanctuary. The lake has also been identified as one of the Important Bird Areas (IBA) and the bird area code No.IN268 in India by Indian bird conservation network (Islam and Rahmani 2004), 8gthe sanctuary is a large irrigation tank located in the northern alluvial plains of the Kaveri River (Mattur dam). It is fed during the northeast monsoons by the Pullambadi canal and Kattalai canals, an aqueduct from the Kaveri via the Venganoor reservoir and dam. It is one of the three interconnected reservoirs. It attracts a variety of birds such as Cormorants, Darter, Painted Stork, Open bill Stork, White Ibis, Glossy ibis, Spot bill Duck, Bar-headed Goose, Spot billed pelican, Purple Moorhen, Common Teal, Pheasant - Tailed Jacana, Little tern, and White breasted kingfisher. There are seven watch towers one on northern side, three on eastern side, and three on southern side. Lake has two bunds for observing the birds.

Twenty one species of aquatic vegetations were recorded from this lake, Invasion by the aquatic weed Ipomoea aquatica is noticed which a cause for degradation of the lake is. The lake is also harbouring 21 species of fishes, majority of them being edible and twenty six species of planktons which includes eight species of phytoplanktons and eighteen species of zooplanktons. It also harbours two species of annelid worms and five species of molluscs. Lists of aquatic vegetation, fishes, planktons, annelid worms and molluscs are given in Appendix - I to V.

Surrounding the lake there are 4 villages with a human population of 16,009, majority of them belonging to backward community. Pollution by the use of pesticides such as Monocrotophos, BHC, Piendal, Lucid Power, Agent Plus, Piropaan

STUDY AREA

Paas, and Karatae and fertilizers such as DAP (Di-Ammonium Phosphate), Potash and Urea in the surrounding villages. Exploitation of fishery resources of the lake and poaching of birds by people during night hours are some of the major conservatory issues of the lake. There is also a conflict between the local villagers who use this lake water for irrigation and the Forest Department regarding the maintenance of water level and planted Cassia trees along the northern and western banks of the reservoir.

3.2 Regions of the lake The entire lake of 442.37 hectare is imaginarily demarcated in to three regions viz, A, B, & C. The A region is having an area of 72 hectors, B region of 94 hectare and C region of 80 hectare and remaining 196.37 hectare is covered by deep forest .The demarcation of the regions is based on the depth contour, factors like pollution, vegetation and human interference (Fig. 3.4 and 3.5). To have representative data, the regions A, B and C were further subdivided into three sub divisions each viz. A1, A2, A3, B1, B2, B3 and C1, C2 & C3 respectively and water and bottom soil samples were taken from each.

3.2.1 A Region This region is of open water habitat with less human activity and less aquatic vegetations it has one inlet. (Fig. 3.6 to 3.8).

3.2.2 B Region This region is also a open, deep water habitat and is slightly polluted by domestic sewage and by frequent use of local people for bathing, washing, cattle washing etc. There is one outlet in this region. (Fig. 3.9 to 3.12).

3.2.3 C Region This region is open shallow water with less human activity and characterized by thick aquatic vegetations mostly Ipomoea sp, It has four outlets and an overflow canal. (Fig. 3.13 to 3.26).

STUDY AREA

3.3 Metrological factors of the study area The rain because of the north-east monsoon to the study area during October to December results in about 78.07 % of the total rainfall in a year and so is the deciding factor for various seasons at the study area. Based on rainfall, seasons ware distinguished at the study area namely, Monsoon (October to December), Post- monsoon (January to March), summer (April to June) and Pre-monsoon (July to September). Since the lake dried out during April to July data for only eight months from October to March covering only three seasons namely Monsoon and Post- monsoon Pre-monsoon were collected for two consecutive years from October 2010 to September 2012 for the present study.

Average monthly temperature and total monthly rainfall in the month studied during the study period of the study area are shown in figs. 2.15 and 2.16 respectively, within the months studied the coolest month was November and the warmest month was March in both the years of study. Highest rainfall was recorded in November during first year and in November during the second year of the study period.

METHODS

4. METHODS

4.1 Study Period Data were collected from October 2010 to September 2012 i.e. during three seasons viz., Monsoon (October, November and December), Post-monsoon (January February and March) and Pre-monsoon (August and September) for two consecutive years.

4.2 Population Studies Waterbirds densities were made for the entire lake by total counts once in a week by following the method of Splinder et al., (1981). Bird watchers and local volunteers assistance was also obtained during the census operations. Field binoculars (7 x 50) and 60 x spotting scope were used to observe birds from all sides of the lake. The birds were identified with the help of their special features. (Grimmet et al, 1998; Ail and Ripley, 1995, 1996) (Manakadan and pittie, 2001; Bibby et al, 1992; and Sutherland, 1997), (Ali 1969; Woodcock, 1979; and Sonobe and Usui, 2000).

The waterbirds were grouped categorically into five groups on the basis of their activities as diving birds, swimming birds, large waders, small waders and aerial foragers.

4.2.1 Diving birds Waterbirds Medium to large sized having stream-lined body with legs set far back. They are experts in diving and well adapted to dive and catch aquatic prey. e.g. Little Grebes, Little Cormorant, Common Coots.

4.2.2 Swimming birds Birds are associated with the surface of the water column. e.g. Spot-bill Duck, Common Teal.

4.2.3 Large waders Large, long legged birds that wade into the shallow water in search of prey e.g. Large Egret, Purple Heron.

METHODS

4.2.4 Small waders Small birds of shallow open expanses of water such as Little Ringed Plover, Common Sandpiper.

4.2.5 Aerial foragers Birds that search for prey by flying over the water surface and diving from air to capture individual prey items. e.g. Little Tern, White-breasted Kingfisher.

4.3 Determination of water quality factors Once in a week from three stations in each region of the lake the following water quality factors were measured.

4.3.1 Physical Factors 4.3.1.1 Water depth A rod marked in centimeter scale was used to obtain depths of water columns at 9 different areas of the 3 regions and the average depth of water column at each region was calculated (Murphy et al. 1984).

4.3.1.2 Surface water temperature At 6.00 am the Surface water temperature was measured. Temperature was measured with a standard centigrade thermometer from all the 9 stations of 3 regions. Water temperature was measured 0.1 m below the water level.

4.3.2 Chemical Factors of water samples Ten chemical variables were measured in the water samples i.e. pH, dissolved oxygen, salinity, silicate, nitrite, nitrate, phosphate, sulphate, calcium and chloride. The water samples for water chemistry measurements were collected from 9 stations of 3 regions in separate vessel (1 liter capacity) and were analyzed separately (Murphy et al., 1984). Except for dissolved oxygen estimation the water samples were fixed with chloroform. Various methods used to measure the above variables were as follows.

METHODS

4.3.2.1 pH With the help of portable pen type electronic pH meter pH of the water samples were determined. The pH meter was immersed in the water and pH values were read directly from the digital screen.

4.3.2.2 Dissolved Oxygen By Winkler’s method the dissolved oxygen contents were estimated. The water samples were collected in narrow mouthed glass stoppered amber coloured bottles without air bubbles. 40% manganous chloride solution 1 ml was added to each sample followed by the addition of one ml of alkaline iodide solution for fixing the oxygen. After ten minutes one ml of concentrated sulphuric acid was added to dissolve the manganous hydroxide precipitate. After acidification fifty ml of sample was transferred into a conical flask and added two to three drops of one percent freshly prepared starch for producing blue colour. Then it was titrated against 0.025 N sodium thiosulphate solutions. The titration was stopped when the blue colour disappeared. The amount of dissolved oxygen was calculated in ml/l (Michael, 1986).

4.3.2.3 Salinity Chlorinity method was used for determining salinity. Five ml of the sample was taken in the conical flask and three drops of five percent potassium chromate was added for indicating purpose. Then it was titrated against 0.1 N silver nitrate solutions. The titration was concluded at the first appearance of brick red colour.

Titre value (ml) x N of AgNO3 x 1000 x 35.5 Chloride (mg/l) = ------Volume of the sample (ml)

4.3.2.4 Silicate Calorimetric method of Theroux et al., (1950) was used to estimate silicate. In this method the amount of yellow silicomolybdic acid formed by the reaction of silica in the water samples with ammonium molybdate was measured calorimetrically. In a conical flask 100 ml of the sample was taken and 2 ml of 10 % ammonium molybdate solution was added. Then it was followed by addition of 3 or 4 drops of 50 %

METHODS

sulphuric acid by mixing thoroughly. After 5 minutes the yellow colour developed was read at 420 nm in a Spectronic – 21 (Baush and Lomb). Simultaneously a reagent blank was prepared and compared with the sample. The silicate amount was obtained directly from a standard graph. The amount of silicate present in the sample was expressed as ppm (Theroux et al., 1950).

4.3.2.5 Nitrite By the calorimetric Griess –Ilosvay method described by Klein, (1973) was used for nitrite estimation. Here, the reddish-purple colour formed by the diazotization of sulfanilic acid by the nitrite present in the sample and the coupling naphtha amine was measured. In this method 100 ml of sample was collected in a conical flask and 2 ml of sulfanilic acid followed by 2 ml of alpha – methylamine were added. The reddish-purple colour developed was measured against a reagent blank at 530 nm in a Spectronic – 21 (Bausch and Lomb). By using the OD values, the amount of nitrite (ppm) was derived from a standard graph.

4.3.2.6 Nitrate Phenol disulfonic acid colorimetric method described by Trivedy and Goel, (1986) was followed for the determination of nitrate. In this method, the nitrates in the water samples were reacted with 1, 2, 4 – phenol disulphonic acid to produce a yellow alkaline colour for calorimetric measurements. Fifty ml of the sample was taken in a conical flask and an equal amount of silver sulphate solution was added. After heating, the filtrate was evaporated in a porcelain basin to dryness. After cooling the dried filtrate was dissolved in 2 ml of phenol disulfonic acid and diluted to 50 ml. then 6 ml of 30 % liquid ammonia was added. The yellow colour developed was read against a reagent blank at 410 nm in a Spectronic – 21 (Bausch & Lomb). The concentration of nitrate (ppm) was calculated from the standard graph by using the OD values obtained.

4.3.2.7 Phosphate The determination of phosphate was made by the colorimetric method of Trivedy et al., (1987). In this method, the phosphate in the water samples was treated

METHODS

with a molybdate to form phosphomolybdic acid which was then reduced by stannous chloride to produce a blue pigment (Trivedy et.al., 1987), the intensity of which was measured calorimetrically. Fifty ml of water sample was taken in a conical flask. Two ml of ammonium molybdate solution and five drops of stannous chloride were added and mixed thoroughly. The blue colour developed was read at 690 nm in a Spectronic – 21 (Bausch and Lomb). A reagent was blank prepared simultaneously and compared with the sample. The phosphate contents for the corresponding OD (Optical Density) values were directly read from a standard graph. Phosphate content of the sample was measure in ppm.

4.3.2.8 Sulphate The sulphate was estimated by the calorimetric method of Barium chloride turbid metric method. In this method 100 ml of sample in 250 ml flask was added with 5 ml of conditioning reagent. The mixture is stirred well and while doing so, 3 gram of barium chloride crystals are added. After addition of barium chloride crystals the solution was stirred. After 4 minutes read at 420 nm in a Spectronic – 21 (Bausch and Lomb). The concentration of sulphate form the standard curve.

4.3.2.9 Calcium The calcium contents were estimated by the EDTA method – Complex metric titration. In this method 50 ml of sample in a conical flask is added with 2 ml of 10 N NaOH solutions along with 100 mg of mureoxide indicator to produce pink colour. This solution was titrated against EDTA until the pink colour changes to purple. Volume of EDTA consumed x 1000 Calcium (mg/l) = ------Volume of sample

4.3.2.10 Chloride The chloride of the water sample was determined by Argent metric titration. In this method 50 ml of sample was added with 1 ml of potassium chromate indicator and titrated against 0.014 N silver nitrate solutions until a persistent red tinge appears.

METHODS

4.4 Bottom soil analysis At three different stations in each region in each month by a Naturalist’s dredge (size 32.14 cm, depth 32 cm) bottom samples were collected. The dredge was towed slowly for a distance of 30 cm.

4.4.1 Depth of Soil A rod marked in centimeter scale was used to obtain depths of soil columns at 9 different areas of the 3 regions and the average depth of soil column at each region was calculated (Murphy et al. 1984).

4.4.2 Soil texture Soil textural analysis was done at the Soil Testing Laboratory, Trichy. Soil analysis was by mechanical analysis as per the international pipette method (Piper, 1966).

4.4.3 Macro-nutrient analysis of soil For the estimation of the level of soil macro-nutrients like nitrogen, phosphorus and potassium, mud pH and mud electrical conductivity, the soil samples collected were sent to the Soil Testing Laboratory, Trichy and the results were obtained directly from them.

4.5 Analysis of plankton By using plankton net the plankton was collected (upper aperture 20 cm; depth 30 cm; lower aperture 5 cm). The plankton was collected in all the regions by dragging the net for 0.8 meters at each side. The plankton collected was stored in 5 % formalin for later identification (Raju, 1986). Volume of plankton was determined from the sediment formed.

4.6 Analysis of benthic fauna The bottom soil samples were collected at 3 different regions in each region in each month by a Naturalist’s dredge (size 32.14 cm, depth 32 cm). The dredge was towed slowly for a distance of one foot (30 cm). The mud collected was sieved

METHODS

through a 0.4 mm sieve and the animals filtered were preserved in 5 % formalin (Strin, 1981). All the animals were weighed to the nearest milligram after removing excess formalin and water with a blotting paper (Danell and Sjoberg, 1982). Molluscs were weighed totally with their shells (Sjoberg and Danell, 1981).

4.7 Threats and conservation issues The threats to the Karaivetti Lake were assessed during the study period by enquire made to local villagers and also by direct observations in and around the lake area. Data on threats and conservation issues such as fishing operations by local people, shooting of birds, exploitation of roosting trees, encroachment of lake area by farmers, improper irrigation schedule which leads to erratic water levels, invasion of cattle and human for bathing, washing etc., silt depositions, invasion of weeds and pesticide and fertilizer, industries pollution from the lake catchment area were documented during the study period.

4.8 Analyses of Data 4.8.1 Waterbirds population calculations 4.8.1.1 Density of waterbirds The individual and total waterbirds densities for different months, years, climatic seasons and regions of the lake were calculated as numbers per hectare (Nagarajan and Thiyagesan, 1996). The density was also calculated for all ecological groups.

4.8.1.2 Diversity In order to investigate the variations in the diversity of bird species and ecological groups during months of the study period, year and regions of the lake the species diversity was calculated using Shannon-Wiener index (Shannon and Wiener, 1949). The diversity index is s H’ = - ∑ (pi) ( log10pi ) i = 1 s = number of species pi = proportion of individuals of a given species

METHODS

4.8.1.3 Richness Species richness was measured by the number of waterbirds species recorded on different regions of the lake during weekly censuses (Verner, 1985). The species richness was also enumerated for all ecological groups.

4.8.2 Statistical tools Basic statistics viz. arithmetic mean and standard deviation were calculated for all the replicate variables and are given as X ± 1 SD. Statistical analyses were performed by using Window based statistical packages viz. Microsoft Excel, MINITAB (Ryan et al., 1992) and SPSS (Statistical Package for Social Science; Nie et al., 1975). Pearson Correlation model to predict the various values in the physico- chemical and biological parameters were used. Mainly parametric tests viz. Analysis of Variance (ANOVA) and Multiple Regression equations were used to test hypotheses. Appropriate data transformations were made wherever needed. For hypothesis testing P < 0.05, P < 0.01 and P < 0.001 were considered and these levels of significance were indicated at appropriate places. Statistical inferences were made by following Sokal and Rohlf, (1981) and Zar, (2000).

4.8.2.1 Difference between / among means The variations between the years and among the months and regions of the lake in the bird population characteristic features viz. density, diversity and richness were tested using two-way and three-way Analysis of Variance (ANOVA). The variations in the water quality, soil and biological parameters with reference to year, months and area (regions of the lake) was also tested using two-way and three-way analysis of variance. In all the analysis of variance the interaction terms were also included to investigate the effect of interaction among the factors. Analysis of Variance (ANOVA) is robust to non-normal data. The consequences of non-normality error were not too serious, for ANOVA, since means will follow the normal distribution more closely than the distribution of the varieties themselves (Sokal and Rohlf, 1981). Hence the Analysis of Variance was used to explore the significance in the differences (Nagarajan et al., 2002a; 2002b).

METHODS

4.8.2.2 Multiple regression equation Multiple regression equation models were developed for the bird population characteristic features (density, diversity and richness) and ecological group-wise density, diversity and richness to investigate the influence of water quality, soil and biological parameters by using both steps-up and step-down procedures. In general the regression models make the following assumptions about the nature of data (Nagarajan et al., 2002a).

4.8.2.3. Continuous variation The variables entered in the multiple regression equations were the water quality parameters viz. water depth, surface water temperature, pH, dissolved oxygen, salinity, silicate, nitrite nitrate, phosphate, sulphate, calcium, and chloride, the soil parameters including soil depth, electrical conductivity, pH, nitrogen, phosphorus, and potassium and biological parameters viz. biomass of benthic annelid worms and molluscs and volume of plankton.

4.8.2.4. Dummy variables In order to control the variation due to the season and region of the lake on the bird population parameters, the year, month, region of the lake were entered as dummy variables in all the regression equations (Nagarajan 2000). The dummy codes used for the different factors are given in table 4.1.

Table 4.1 Dummy codes used in regression

S.No Factors Dummy Codes 1 2 3 4 5 6 7 8 1 Year 2010- 2011 2011-2012

2 Month Oct Nov Dec Jan Feb Mar Aug Sep

3 Region A B C

OBSERVATIONS AND RESULTS

5. OBSERVATIONS AND RESULTS

5.1 Waterbirds of Karaivetti Lake Forty three species of waterbirds were recorded in the Karaivetti Lake during the study period (Table. 5.1). Among them one species belongs to Poeicipediformes, four species to Pelecaniformes, 14 species to Ciconiiformes, seven species to Anseriformes, four species of Gruiformes, 10 species to Charadriiformes and three species to Coraciiformes, These birds were ecologically classified into five groups namely, Divers (Little Grebe, Tachybaptus ruficollis, Little Cormorant, Phalacrocorax niger, Indian Shag, Phalacrocorax fuscicollis, Darter, Anhinga melanogaster, Common Coot, Fulica atra), Swimming Birds (Spotted - billed Pelican Pelecanus philippensis, Gadwall, Anas strepera, Bar-headed Goose, Anser indicus, Northern Pintail, Anas acuta, Common Teal, Anas crecca, Spot-billed Duck , Anas poecilorhyncha, Northern Shoveller, Anas clypeata, Garganey, Anas querquedula), Large waders (Little Egret, Egretta garzetta, Large Egret, Casmerodius albus, Median Egret, Mesophoyx intermedia, Cattle Egret, Bubulcus ibis, Grey Heron, Ardea cinerea, Purple Heron, Ardea purpurea, Black-crowned Night –Heron, Nycticorax nycticorax, Indian Pond- Heron, Ardeola grayii, Painted Stork, Mycteria leucocephala, Asian Openbill – Stork, Anastomus oscitans, White Ibis, Threskiornis melanocephalus, Black Ibis, Pseudibis papillosa, Glossy Ibis, Plegadis falcinellus, Eurasian Spoonbill, Platalea leucorodia, Common Moorhen, Gallinula chloropus, Purple Moorhen Porphyrio porphyrio), Small Waders (White - breasted Waterhen, Amaurornis phoenicurus, Pheasant - tailed Jacana, Hydrophasianus chirurgus, Little Ringed Plover, Charadrius dubius, Black -Winged Stilt, Himantopus himanotopus, Red- watt led Lapwing, Vanellus indicus, Yellow - wattled Lapwing, Vanellus malabaricus, Wood Sandpiper, Tringa glareola, Common Sandpiper, Actitis hypoleucos, Little Stint, Calidris minuta), and Aerial Foragers (Whiskered Tern, Chlidonias hybridus, Little Tern, Sterna albifrons, Small Blue Kingfisher, Alcedo atthis, Lesser Pied Kingfisher, Ceryle rudis, White-breasted Kingfisher, Halcyon smyrnensis).

OBSERVATIONS AND RESULTS

Since 1988, the Spotted Billed Pelican is a globally “Near threatened” Species, (IUCN 2007). Among the birds observed in the lake Spotted Billed Pelican, Bar-headed Goose, Darter, Painted stork and White ibis are under, “Near threatened” category of the classification by Birdlife International 2009.

5.1.1 Phenology of waterbirds visitations to the Karaivetti Lake 5.1.1.1 Month-wise visitations Occurrence of different waterbirds species during different months of the study period at the Karaivetti Lake had been given in the (Table 5.2). The Little Grebe, Spotted - billed Pelican, Little Cormorant, Darter, Little Egret, Large Egret, Median Egret, Cattle Egret, Grey Heron, Purple Heron, Black-crowned Night –Heron, Indian Pond- Heron, Asian Openbill - Stork, White Ibis, Glossy Ibis, Eurasian Spoonbill, Common Teal, White - breasted Waterhen, Purple Moorhen, Common Coot, Little Ringed Plover, Red- watt led Lapwing, Yellow -wattled Lapwing, Wood Sandpiper, Common Sandpiper, Whiskered Tern, Little Tern, Small Blue Kingfisher, Lesser Pied Kingfisher, White-breasted Kingfisher occurred at the lake in the all the months of study period. Indian Shag was seen in August and September of 2011. Painted Stork and black Ibis were not recorded in the lake during August of both years. Gadwall was not found in the month of October and November of both years. Bar-headed Goose was not visited in October, November and September 2012. The Northern Pintail was not seen in the lake during February and March 2011 and during February, March and August during 2012. Spot-billed Duck, Garganey, Common Moorhen, Black -Winged Stilt and Little Stint didn‟t visit in month of August and September 2011 and 2012. Northern Shoveller was not observed during October, August and September of both year of study period. Pheasant - tailed Jacana was not found in the month of August -2011 and August, September of 2012.

5.1.1.2 Season-wise visitations Occurrence of different waterbirds species during different seasons of the study period at the Karaivetti Lake had been given in the (Table. 5.3). Little Grebe, Spotted - billed Pelican, Little Cormorant, Darter, Little Egret, Large Egret, Median Egret, Cattle Egret, Grey Heron, Purple Heron , Black-crowned Night –Heron, Indian

OBSERVATIONS AND RESULTS

Pond- Heron, Painted Stork, Asian Openbill - Stork, White Ibis, Black Ibis, Glossy Ibis, Eurasian Spoonbill, Gadwall, Northern Pintail, Common Teal, White - breasted Waterhen, Common Coot, Purple Moorhen, Little Ringed Plover, Red- wattled Lapwing, Yellow-wattled Lapwing, Wood Sandpiper, Common Sandpiper, Whiskered Tern, Little Tern, Small Blue Kingfisher, Lesser Pied Kingfisher, and White-breasted Kingfisher occurred in all the seasons of the study period. Indian Shag could not be observed during the Pre-monsoon seasons of first year of the study (August and September 2011). The Bar-headed Goose, Spot-billed Duck, Northern Shoveller, Garganey and Common Moorhen were not found during the Pre-monsoon I (August and September 2010-2011) and Pre-monsoon II (August and September 2011-2012) of the study period. The Pheasant - tailed Jacana were not recorded in the Pre-monsoon II (August and September 2012) of Second year of study period. The Black -Winged Stilt and Little Stint was not found in the pre-monsoon season of both the years.

5.1.1.3 Category- wise comparison of visitations Phenology of visitations of five categories of waterbirds species viz. divers, swimming birds, large waders, small waders and aerial foragers, to the Karaivetti Lake had been depicted in figures5.1 to 5.5.

5.1.1.3.1 Diving Birds Among the diving birds the Little Grebe, Little cormorant, Darter and Common coot were found in the lake during all the months of study in both years while the Indian shag visited the lake only during October to March in first year (Fig 5.1) but the stag was extended months of October to September in the second years of study period (Fig 5.1).

5.1.1.3.2 Swimming Birds Among the Swimming birds Spotted- billed pelican, Common Teal were found in the lake in all the months of both years of study. (Fig 5.2) The Bar-headed Goose arrived at the lake earlier in the second year than the first year. Gadwall didn‟t visit in October and November in both year of study. Northern Pintail was not

OBSERVATIONS AND RESULTS

recorded during February and March of first year and March in Second year of study. Northern Shoveller was arrived during the month of November to March in both years. Spot-billed Duck and Garganey left the lake in August to September in both years of the study (Fig 5.2).

5.1.1.3.3 Large Waders Majority of the large waders arrived at the lake in all months of both years of study period, were Little Egret, Large Egret, Medium Egret, Cattle Egret, Grey Heron, Purple Heron, Black-Crowned Night-Heron, Indian pond-Heron, Asian Openbill – Stork, White Ibis, Glossy Ibis, Eurasian Spoonbill and Purple moorhen (Fig 5.3). Among the large waders Painted Stork and Black Ibis were not found in month of August of both years. Common Moorhen was not recorded in the month of August and September of both years (Fig 5.3).

5.1.1.3.4 Small Waders Among the small waders White - breasted Waterhen, Little Ringed Plover, Red- wattled Lapwing, Yellow -wattled Lapwing, Wood Sandpiper, Common Sandpiper were recorded in all months of both years the study (Fig 5.4). The Pheasant - tailed Jacana, Black -Winged Stilt and Little Stint were avoided the month of August and September in both years of Study (Fig 5.4).

5.1.1.3.5 Aerial Foragers When compared with other visitations of species aerial foragers were the highest recorded. All the aerial foragers species occurred in the lake during all the months of both years of study (Fig 5.5).

5.1.1.4 Fluctuations in the density of waterbirds species The population fluctuation of the 43 waterbirds species recorded in the Karaivetti Lake during the study period has been given in Fig. 5.6 to 5.48.

OBSERVATIONS AND RESULTS

5.1.1.4.1. Little Greb Density of Little Grebe peaked in the Karaivetti Lake during January in first year of study and December during second year of study while in the first year the birds were very meager during March in first year and September during second year (5.6).

5.1.1.4.2. Little Cormorant

Little Cormorant density peaked in the lake during December of first year and January of second year. However another peak was observed at November during both years of the study (Fig. 5.7).

5.1.1.4.3. Indian Shag

Density of Indian Shag got a peak in the lake during August of both the years of study but the peak was smaller during March in the both years of study (Fig. 5.8).

5.1.1.4.4. Darter A large beak was noted for Darter during September in second year of study period while the birds were during the month of August scanty during both years of the study. During first year, the density was high in the month of March (Fig. 5.9).

OBSERVATIONS AND RESULTS

5.1.1.4.5. Common Coot The population of Common Coot reached a peak in December during both years of study period, while another peak was noted during February in the second year of study (Fig. 5.10).

5.1.1.4.6. Spotted - billed Pelican The Spotted-billed Pelican attained a maximum density during September of second year and August of first year. In general the density was lower in the month of January during both years of study (Fig. 5.11).

5.1.1.4.7. Gadwall

March of first year and January of second year are period of peak for arrival of Gadwall at the lake (Fig. 5.12).

5.1.1.4.8. Bar-headed Goose Bar - headed Goose was more in the month of March in both years of study while density was seen during the months of October, November, August and September of both years (Fig. 5.13).

OBSERVATIONS AND RESULTS

5.1.1.4.9. Northern Pintail

The maximum population of Northern Pintail was noticed in September during first year and November during the second year (Fig. 5.14).

5.1.1.4.10. Common Teal The density of Common Teal attained peak in December during the first year and the highest peak was noticed in November during the second year. During January to September the population was almost same in both years (Fig. 5.15). 5.1.1.4.11. Spot-billed Duck The top most peak was noted in the month of December and in February another peak was noticed in second year. An opposite trend in population fluctuation was observed during October to January between the two years of study (Fig. 5.16). 5.1.1.4.12. Northern Shoveller

The highest peak of Northern Shoveller was observed in January during first year and March in for second year (Fig. 5.17).

OBSERVATIONS AND RESULTS

5.1.1.4.13. Garganey The density of Garganey travelled almost same in both years, where December attained maximum in both years of study and the lowest was noted during August and September in both years (Fig. 5.18).

5.1.1.4.14. Little Egret Density of Little Egret was more in the month of January and February during first year and December during the second year. In the second year there was a sudden fall in its density during February (Fig. 5.19).

5.1.1.4.15. Large Egret

The Large Egret population was higher in the months of November and December of first year and November of second year (Fig. 5.20).

5.1.1.4.16. Median Egret

Maximum numbers of Median Egrets were noticed in November during the first year and September during the second year (Fig. 5.21).

OBSERVATIONS AND RESULTS

5.1.1.4.17. Cattle Egret Density of Cattle Egret was more in the month of December in both years of study. There was a gradual decreasing trend in its density in the month of December to August (Fig. 5.22).

5.1.1.4.18. Grey Heron

The Grey Heron was peaked in November of first year and December of Second year while it was reduced during August in first year of study (Fig. 5.23).

5.1.1.4.19. Purple Heron

During first and second year of study the Purple Heron was almost stable up to March. It attained a highest peak during the month of August in the first year (Fig. 5.24).

5.1.1.4.20. Black-crowned Night –Heron There was an increasing trend in the density of Black - Crowned Night - Heron during October to December of both years. In both years of study period, the population was noted more in December than it was decreased in both years of study (Fig. 5.25).

OBSERVATIONS AND RESULTS

5.1.1.4.21. Indian Pond- Heron The population of Indian Pond - Heron attained peak in December of both years of study. It was noted that during August month of first year there were no birds (Fig. 5.26).

5.1.1.4.22. Painted Stork Density of Painted Stork was peaked in December during the first year and November during second year, similar pattern of population fluctuation was observed during study period. Thereafter there was sudden fall in August during the both years of study (Fig. 5.27). 5.1.1.4.23. Asian Openbill – Stork

The Asian Openbill - Stork was more during the month of November in the second year and peak was noted in August and March of first year (Fig. 5.28).

5.1.1.4.24. White Ibis The White Ibis had an increasing trend in the density from October to January of first year, but October to December in Second year while it was decreasing in the density from January to August in first year, December to March in Second year, After March an opposite trend in population fluctuation was noticed during August between the two years of study (Fig. 5.29).

OBSERVATIONS AND RESULTS

5.1.1.4.25. Black Ibis

Peaks in the population of Black Ibis were noticed in March of first year and November during the second year (Fig. 5.30).

5.1.1.4.26. Glossy Ibis

The Glossy Ibis was noticed in September during first year and November during the Second year (Fig. 5.31).

5.1.1.4.27. Eurasian Spoonbill Similar pattern of population fluctuation was observed for Eurasian spoonbill during the months from October to March in both years. Thereafter there was sudden peak in August during the second year while a sudden drop in August of first year (Fig. 5.32).

5.1.1.4.28. Common Moorhen

Same trend was noted in the density of Common Moorhen from December to September in both years. While the peak was in November during second year and September in the first year (Fig. 5.33).

OBSERVATIONS AND RESULTS

5.1.1.4.29. Purple Moorhen The density of Purple Moorhen had an opposite trend in population fluctuation during October to December and February to August. There was an increasing trend in the density of first year, while decreasing trend in the second year (Fig. 5.34).

5.1.1.4.30. White - breasted Waterhen The population of White - Breasted Waterhen showed two peaks November and August of second year, where as in both the month there was a decreasing hind in first year (Fig. 5.35).

5.1.1.4.31. Pheasant - tailed Jacana

The largest peak of Pheasant - tailed Jacana was attained during the month of December in second year and was nil in August of the first year (Fig. 5.36).

5.1.1.4.32. Little Ringed Plover Density of Little Rigged Plover was peaked in the month of October and November during the first year. In the second year of study the peak was during October, December, and January and also in September (Fig. 5.37).

OBSERVATIONS AND RESULTS

5.1.1.4.33. Black -Winged Stilt

The population of Black - Winged Stilt was attained the maximum in January of first year and December of second year (Fig. 5.38).

5.1.1.4.34. Red- watt led Lapwing

The population of the Red - wattled Lapwing was maximum in the month of November of first year and March during the second year (Fig. 5.39).

5.1.1.4.35. Yellow -wattled Lapwing

Density of Yellow - wattled Lapwing was higher in the month of November and December of second year (Fig. 5.40).

5.1.1.4.36. Wood Sandpiper The population of Wood Sandpiper during both years, there was decreased pattern of population was noted the highest peak was in October during both years of study period (Fig. 5.41).

OBSERVATIONS AND RESULTS

5.1.1.4.37. Common Sandpiper

The Common Sandpiper was observed in December during first year and November during the second year of study (Fig. 5.42).

5.1.1.4.38. Little Stint A high density of Little Stint was observed in the month of December during the first year. The population was lesser in the month of August in both years of study (Fig. 5.43).

5.1.1.4.39. Whiskered Tern The pattern of population fluctuation of Whiskered Tern was similar from December to September in both years of study. There was maximum in January during the first year, and November during the second year (Fig. 5.44).

5.1.1.4.40. Little Tern

The Little Term population was maximum in the month of November and December of first year and March and October of second year (Fig. 5.45)

OBSERVATIONS AND RESULTS

5.1.1.4.41. Small Blue Kingfisher

Peaks in the population of Small Blue Kingfisher were obtained in the month of December during the second year and December during the first year and also a second peak in second year (Fig. 5.46). 5.1.1.4.42. Lesser Pied Kingfisher The density of Lesser Pied Kingfisher had an increasing hind in the month of January, September and October of first year and there exist an operate lifted in second year (Fig. 5.47).

5.1.1.4.43. White-breasted Kingfisher The White-breasted Kingfisher occurred more in numbers in December during the first year. In second year of study, there were two peaks in population one during March and another during January (Fig.5.48).

5.1.1.5 Fluctuation in population parameters of waterbirds groups. A detailed account of density, diversity and richness of different waterbirds species and categories during different months and seasons of the study period and in different regions of the Karaivetti Lake is given in Table 5.4 to 5.9, (Fig 5.49 - 5.91).

OBSERVATIONS AND RESULTS

5.1.1.5.1 Monsoon - I (October, November and December 2010) 5.1.1.5.1.1 Diving birds Little Grebe was predominant diver during November and December 2010 (Fig. 5.49 to Fig. 5.53), compared to October 2010. The region was more occupied, where as region of „A‟ was lower in all months of monsoon. The Darter was relatively higher in the month of November and the remaining birds of divers were attained the highest population during the month of December (Table 5.4).

5.1.1.5.1.2 Swimming birds The Spotted - billed Pelican, Common Teal, Garganey were recorded more in the month of December where as the density of Northern Pintail and Spot - billed Duck was higher in October. Gadwall, Bar - headed Goose were represented only in December 2010 of this season (Fig. 5.54 to Fig. 5.61). Population of Northern Shoveller was not recorded in the month of October (Table 5.4).

5.1.1.5.1.3 Large waders The Median Egret, Grey Heron, Purple Heron, and Glossy Ibis were relatively higher in the month November than that of other months. Remaining birds of were recorded more during the month of December 2010 (Fig. 5.62 to Fig. 5.77). Majority of large waders were found in the region „C‟ (Table 5.4).

5.1.1.5.1.4 Small waders White - breasted Waterhen, Little Ringed Plover and wood Sandpiper densities were recorded high during the month of October, where as Black -Winged Stilt, Common Sandpiper and Little Stint were more in the month of December (Fig. 5.78 to Fig. 5.86). The Pheasant - tailed Jacana, Red wattled Lapwing and Yellow - wattled Lapwing November – 2010 (Table 5.4).

5.1.1.5.1.5 Aerial foragers December was the greatest recorder in all Aerial foragers expects Lesser Pied Kingfisher in the season of 2010 (Fig. 5.87 to Fig. 5.91) (Table 5.4).

OBSERVATIONS AND RESULTS

5.1.1.5.2 Post - Monsoon I (January, February, March 2011) 5.1.1.5.2.1 Diving birds The Little Grebe, Darter and Common Coot were arrived more in the month of January where Little Cormorant was much recorded during the month of February 2011 (Fig. 5.49 to Fig. 5.53). The Density of Indian Shag was not recorded in the month of March of this season (Table 5.5).

5.1.1.5.2.2 Swimming birds The population of Spotted - billed Pelican, Gadwall and Bar - headed Goose were increased from January to March of the season where as common teal and Northern Shoveller were decreased during the season of 2011(Fig. 5.54 to Fig. 5.61). The Northern pintail was recorded only in the month of January. Density of spot - billed duck, and Garganey were relatively higher in the month of February than the other month of season (Table 5.5).

5.1.1.5.2.3 Large waders The Cattle Egret, Glossy Ibis, Common Moorhen and Purple Moorhen were higher in the month of February while Asian Openbill - Stork and Black Ibis were high recorded during the month of March (Fig. 5.62 to Fig. 5.77).Remaining large waders were more arrived during the month of January in the season of 2011 (Table 5.5).

5.1.1.5.2.4 Small Waders The common sandpiper was not found in the month of January 2011. Density of White - breasted Waterhen, Little Ringed Plover, and Black -Winged Stilt, Wood Sandpiper and Little Stilt were reached highest population during the month of January 2011(Fig. 5.78 to Fig. 5.86). Pheasant - tailed Jacana, Red- wattled Lapwing and Common Sandpiper were recorded during the month of February. The Yellow – wattled Lapwing was more in the month of March (Table 5.5).

5.1.1.5.2.5 Aerial Foragers Population of little tern reached high in the month of March (Fig. 5.87 to Fig. 5.91) than the remaining aerial foragers (Table 5.5).

OBSERVATIONS AND RESULTS

5.1.1.5.3 Pre - Monsoon I (August and September 2011) 5.1.1.5.3.1 Diving birds Densities of diving birds were higher in population during the month of August (Fig. 5.49 to Fig. 5.53) when compared with other months of the season, except darter (Table 5.6).

5.1.1.5.3.2 Swimming birds The Spotted - billed Pelican and Common Teal, were more during the month of August where as Gadwall, Northern Pintail were recorded high in the month of September (Fig. 5.54 to Fig. 5.61). The Bar - headed Goose, Spot billed Duck, Northern Shoveller and Garganey were not visited during both months of the season. No birds were recorded in all months of season in region „A‟ (Table 5.6).

5.1.1.5.3.3 Large waders The Little Egret, Large Egret, Median Egret, Cattle Egret, Grey Heron, Indian Pond Heron, Painted Stork, Asian Openbill Stork, Oriental While Ibis, Black Ibis, Glossy Ibis, Eurasian Spoonbill and Purple Moorhen were not visited during the month of August 2011(Fig. 5.62 to Fig. 5.77). Density of Purple Heron was more in the region of „B‟ but not recorded in the region of „A‟ and „C‟. Population of Common Moorhen was not found in both month of the season. Other large waders were found only during the months of September of this season (Table 5.6).

5.1.1.5.3.4 Small waders The region of „A‟ was not having White - breasted Waterhen, Little Ringed Plover, Red - wattled Lapwing, Yellow - wattled Lapwing, Wood Sandpiper and Common Sandpiper in the month of August (Fig. 5.78 to Fig. 5.86). The Black - Winged Stilt and Little Stint were not arrived during the both months of the season. August month was not preferred by Pheasant - tailed Jacana. Populations of small waders were greatly recorded during the month of September (Table 5.6).

5.1.1.5.3.5 Aerial foragers Densities of Aerial foragers were more during the month of September (Fig. 5.87 to Fig. 5.91) than the month of September and with the other months of the season (Table 5.6).

OBSERVATIONS AND RESULTS

5.1.1.5.4 Monsoon - II (October, November and December 2011) 5.1.1.5.4.1 Diving birds Populations of all divers were higher during the month of December. Little Cormorant was recorded same in the months of November and December of 2011(Table 5.7) (Fig. 5.49 to Fig. 5.53).

5.1.1.5.4.2 Swimming birds The Spotted – billed Pelican was more in the month of November. Gadwall was seen only in the month of December. Bar - headed Goose and Northern Shoveller didn‟t visit during the month of October (Fig. 5.54 to Fig. 5.61). Population of Common Teal was least recorded in the month of October and during November it was recorded more. Spot - billed Duck and Garganey was gradually increased from October to December (Table 5.7).

5.1.1.5.4.3 Large waders The Little Egret, Medium Egret, Eurasian Spoonbill and Oriental White Ibis were visited more in the month of December, while lesser in October (Fig. 5.62 to Fig. 5.77). The population of Large Egret, Asian Open bill - Stork, Black Ibis, Glossy Ibis, Painted Stork, Purple Heron and Purple Moorhen were relatively higher in the month of November then that of other months. The Cattle Egret and Indian Pond Heron population were recorded same in the month of November and December. Density of Grey Heron was gradually increased. Population of Black - Crowned Night-Heron was poor during the month of October and higher in the month of December. Common Moorhen more visited during the month of October - 2011 (Table 5.7).

5.1.1.5.4.4 Small waders Density of White – breasted Waterhen, Common Sandpiper, Wood Sandpiper and Little Stint were noted high during the month of November where as in November the density of Little Ringed Plover very meager in (Fig. 5.78 to Fig. 5.86). The Pheasant - tailed Jacana, Black - Winged Stilt and Yellow - wattled Lapwing

OBSERVATIONS AND RESULTS

reached higher density during the month of December 2011. Population of Red - wattled Lapwing and Little Stint were more in the month of October (Table 5.7).

5.1.1.5.4.5 Aerial foragers The Whiskered Tern and Lesser Pied Kingfisher were recorded maximum in the month of November and Small Blue Kingfisher was more in the month of December 2011 (Fig. 5.87 to Fig. 5.91) (Table 5.7).

5.1.1.5.5 Post - monsoon II (January, February, March 2012) 5.1.1.5.5.1 Diving birds Diversity of Little Grebe and Common Coot were recorded more in the month of February (Fig. 5.49 to Fig. 5.53). The Little Cormorant and Darter were found high, during the month of January. Population of India Shag was very low during all the months of season 2012. Divers were not recorded in the month of in region „A‟ except Darter (Table 5.8).

5.1.1.5.5.2 Swimming birds The Northern Pintail was only recorded during the month of January not in other months of this season 2012 (Fig. 5.54 to Fig. 5.61). Population of Spot - Billed Duck showed great in density during the month of February, ware as other swimming birds were more in the month of January 2012 of this season (Table 5.8).

5.1.1.5.5.3 Large waders Majority of the large waders liked more the month of January (Fig. 5.62 to Fig. 5.77). The Median Egret, Purple Heron and Glossy Ibis population were similar during the months of January and February of this season 2012 (Table 5.8).

5.1.1.5.5.4 Small waders The White - breasted Waterhen, Pheasant - tailed Jacana, Little Region Plover, Black - winged Stilt, Yellow - wattled Lapwing, Wood Sandpiper and Little Stint arrived more in the month of January of the season 2012 and Common Sandpiper in the month of February (Fig. 5.78 to Fig. 5.86). The population of Red wattled Lapwing was more in the region of „C‟ in all the months of this season (Table 5.8).

OBSERVATIONS AND RESULTS

5.1.1.5.5.5 Aerial foragers The population of Small Blue Kingfisher showed same during the month of January and February (Fig. 5.87 to Fig. 5.91). Density of Little Tern was more in the month of February. Remaining Aerial foragers were high in the month of January (Table 5.8).

5.1.1.5.6 Pre - monsoon II (August and September 2012) 5.1.1.5.6.1 Diving birds Density of Little Grebe was similar in both months of season 2012 (Fig. 5.49 Fig. 5.53). Population of Darter was not found in the month of August, while September it was very meager. The Little Cormorant was more in the month of September, Indian Shag and Common Coot were recorded low in the month of September, when compared with other months of this season (Table 5.9).

5.1.1.5.6.2 Swimming birds The Bar - headed Goose, Northern Shoveller, Garganey and Spot - billed Duck were not recorded in both months of this season. Whereas Northern Pintail was recorded only in the month of September (Fig. 5.54 to Fig. 5.61). Population of Common Teal recorded very meager in both months of the season 2012 (Table 5.9).

5.1.1.5.6.3 Large warders The Little Egret and Black - crowned Night - Heron arrived very less in both months of this season (Fig. 5.62 to Fig. 5.77). Density of Large Egret, Median Egret, Cattle Egret and Purple Heron were more recorded during the month of September, where as Grey Heron, Indian Pond-Heron, Open bill - Stork, Oriental white Ibis, Glossy Ibis and Eurasian Spoonbill visited in August. The common moorhen was not recorded during both months of the season; where as Painted Stork and Block Ibis were not found in the month of September (Table 5.9).

5.1.1.5.6.4 Small waders The Pheasant - tailed January, Black - Winged Stilt and Little Stint didn‟t visit the lake during both months of this season 2012 (Fig. 5.78 to Fig. 5.86). Density of

OBSERVATIONS AND RESULTS

White - breasted Waterhen, Yellow - wattled Lapwing and Common Sandpiper, were reported more during the month of August 2012. Remaining small waders were found in the month of September (Table 5.9).

5.1.1.5.6.5 Aerial foragers Density of Aerial foragers was more in the month of August, as well as in all the regions of this season (Fig. 5.87 to Fig. 5.91) (Table 5.9).

5.1.1.6 Year-wise comparison of density, diversity and richness of waterbirds groups Variations in density, diversity and richness with regard to total waterbirds, diving birds, swimming birds, large waders, small waders and aerial foragers across the two years of study at the Karaivetti Lake had been shown in Figure 5.92 – 5.109.

5.1.1.6.1 Density 5.1.1.6.1.1 Density of grand total waterbirds In the first year of study i.e., October 2010 to September 2011 density of total waterbirds was the highest in the month of December and least in the month of August (Fig. 5.92). On the other hand, the density of total waterbirds was highest during November and least was recorded in the month of September in second year of the study. Thus the density of waterbirds was higher during post monsoon months in the first year and during monsoon months in the second year. Region „C‟ of the lake had more density of waterbirds than the other two regions during all the seasons in both the years of study (Fig. 5.92).

5.1.1.6.1.2 Density of total diving birds The density of diving birds were highest in the month of December in both years of study to 2011-2012 and least in the month of March during the first year of study i.e., October 2010-September-2011(Fig. 5.93). On the other hand the least in the month of October during the second year of study i.e., October 2011 to September 2012. With regard to seasonal variations, the density of diving birds was higher during monsoon months of both years. Region „C‟ of lake had more density of diving birds than the other two regions during first and second year (Fig. 5.93).

OBSERVATIONS AND RESULTS

5.1.1.6.1.3 Density of total swimming birds The density of swimming birds was highest in December and January, least in October during the first year of study i.e., October - 2010 to 2011(Fig. 5.94). On the other hand the density of diving birds was highest in November least in August and September of second year i.e., October - 2011 to September - 2012 (Fig. 5.94). This indicated that density of swimming birds a top during the post moon soon months of first year and monsoon month of second year of study. Region „C‟ of the lake was more dementedly swimming birds during monsoon and post-monsoon months of first year of study, while region „B‟ had higher density of swimming birds during pre- monsoon of first year of study. During the second year Region „C‟ of lake had more density of swimming birds in the monsoon and pre-monsoon (Fig. 5.94).

5.1.1.6.1.4 Density of total large waders The Density of large waders was highest in the month of December of both years of study i.e., October - 2010 and September - 2012 and least in the month of August during second year of study (Fig. 5.95). On the other hand large waders were not showed their density during the month of August in first year i.e., October - 2010 and September – 2011. So there was a year-wise difference with regard to the density of the large waders as it was higher during the post-monsoon months in the first year and during monsoon months in the second year of study. Region „C‟ of the lake had more density of large waders than the other two regions during all the seasons. Region „A‟ had the least density of large waders in all the seasons of both years of study (Fig. 5.95).

5.1.1.6.1.5 Density of total small waders The density of small waders were highest in the month of November during the first year of study i.e., October - 2010 to September - 2011 (Fig. 5.96). On the other hand density of small waders was peaked in December and least in August during the first and September of second year of study i.e., October - 2010 to September – 2012. Thus the density of small waders was higher during the monsoon months of both years of study. Region „C‟ of the lake was more in the density of small waders in both years of study but the Region of „B‟ was changed during the month of August of pre-monsoon of first year. (Fig. 5.96)

OBSERVATIONS AND RESULTS

5.1.1.6.1.6 Density of total aerial foragers During the first year of study i.e. October- 2010- September-2011, the density of aerial foragers were the highest in the month of December and least in the month of August (Fig. 5.97). On the other hand aerial foragers were highest in November and least in September, during the second year of study i.e., i.e., October - 2011 to September - 2012. This showed that the total waterbirds density was highest during the post-monsoon of first year and monsoon season of second year of study. The density of total waterbirds in the Region „C‟ of the lake was more than the other two regions during both years of all seasons (Fig. 5.97).

5.1.1.6.2 Diversity 5.1.1.6.2.1 Diversity of grand total waterbirds The diversity of total waterbirds was highest in the month of September of both years of study. It was least in the month August during the first year (October - 2010 and September – 2011) and in the month of November during the second year (i.e., October - 2011 to September -2012) (Fig. 5.98). This showed that the total waterbirds diversity was highest during the monsoon season of first year, but in second year the post monsoon was highest recorded. The diversity of total waterbirds in the region „A‟ was more than the other two regions during the monsoon. The region „A‟ was recorded more in the season of monsoon of October and December, but region „C‟ was greatly recorded in the month of November in second year of study. During post monsoon region of „A‟ was not occupied in the month of March. In second year the pre-monsoon region was peaked more in the month of September (Fig. 5.98).

5.1.1.6.2.2 Diversity of total diving birds During the first year of study i.e., October - 2010 to September - 2011 (Fig. 5.99) the diversity of diving birds were higher in the month of September than that of other months. Even though the diversity of diving birds was more in the month of September but during the second years of study it was more in the month of August. Diversity of diving birds was not recorded in the month of March and least in the month of August of first year. March was reported with least in second year of study.

OBSERVATIONS AND RESULTS

Region of „A‟ was peaked in all seasons of study expect post-monsoon of March and pre-monsoon of August during first year and March of post-monsoon in the second year of study (Fig. 5.99).

5.1.1.6.2.3 Diversity of total swimming birds The diversity of swimming bird was highest in the month of October and least in the month of August in first year of study (October-2010 to September-2011) (Fig. 5.100), whereas in the second year (i.e., October-2011 to September-2012) January was recorded more and least in the month of November (Fig. 5.100).

5.1.1.6.2.4 Diversity of total large waterbirds Diversity of large waders were recorded high in the month of September during pre-monsoon of both years of study (Fig. 5.101) and August was not recorded during first year. In second year population was less in the month of March in post monsoon (Fig. 5.101).

5.1.1.6.2.5 Diversity of total small waders Diversity of small waders were more in the month of March and meager in the month of August of first year 2010-2011 (Fig. 5.102). While February was recorded higher in post monsoon of second year (Fig. 5.102).

5.1.1.6.2.6 Diversity of total aerial foragers The diversity of aerial foragers were more in October during first year (October 2010 to September 2011) (Fig. 5.103) and in September during second year (October 2011 to September 2012). The diversity of aerial forgers was least in the month of August during first year and March of second year (Fig. 5.103).

5.1.1.6.3 Species richness 5.1.1.6.3.1 Species richness of grand total waterbirds The Richness of total waterbirds were almost same in the months of December of monsoon January, February and March of post monsoon of first year (October - 2010 to September - 2011) (Fig. 5.104). Least recorded in the month of August in monsoon and post monsoon of January in second year of study (Fig. 5.104).

OBSERVATIONS AND RESULTS

5.1.1.6.3.2 Species richness of total diving birds The species richness of diving birds were same during the months of October, November and December of monsoon, January and February of post monsoon of first year least in the month of March of first year (October - 2010 to September - 2011) (Fig. 5.105). During second year all seasons were recorded more except post- monsoon of March and pre-monsoon of August of the study period (Fig. 5.105).

5.1.1.6.3.3 Species richness of total swimming birds During both the years of study, the species richness of swimming birds were more in January and least in August than the other months of both years of study (Fig. 5.106). Thus the richness of swimming birds was the highest during post-monsoon months of first year, monsoon of second year of study (Fig. 5.106).

5.1.1.6.3.4 Species richness of total large waders The species richness of large waders was recorded same in monsoon and post- monsoon of both months expect in the month of March in second year of study (Fig. 5.107). August of pre-monsoon was not recorded in the first year of study and March of post monsoon was least recorded during second year of study (Fig. 5.107).

5.1.1.6.3.5 Species richness of total small waders The Species richness of small waders were more in monsoon, February and March of post monsoon (October - 2010 to September - 2011) (Fig. 5.108). On the other hand the richness of small waders showed higher in monsoon of October and February of post monsoon where least in August of pre-monsoon in during both years of the study period (Fig. 5.108).

5.1.1.6.3.6 Species richness of total aerial foragers During both the years of study the species richness of aerial foragers were same in all regions except the month of August of pre-monsoon in the first year (October - 2010 to September - 2011) (Fig. 5.109) and in the second year, March of post monsoon of study (Fig. 5.109).

OBSERVATIONS AND RESULTS

5.1.1.7 Evaluation of the influence of year, month and regions of the lake on the density of water bird. Result of the three - way ANOVA performed to evaluate the influence of variations due to years; months and area (regions) of the lake, on the diversities of different categories on waterbirds at the Karaivetti Lake had been given in tables 5.10 to 5.15. The density of total waterbirds as well as different ecological groups of waterbirds viz., divers, surface swimmers, large waders, small waders and aerial foragers, were significantly influenced by the year, month and area (regions) of the lake.(P<0.005). The total density of waterbirds were significantly (P<0.05) influenced by all the two-way interactions between year, month and area (regions of the lake) as well as three way interactions between these three variables had significant effect on the density of all waterbirds (Table 5.10). The diving birds of Little Grebe, Little Cormorant, Indian Shag, Darter and Common Coot were significantly influenced by the year, month and area, same as in two-way and three-way ANOVA (Table 5.11).

Among swimming birds, Gadwall and Bar-headed Goose were not significantly influenced by the year. Density of Garganey was not significantly influenced by the two-way interactions between year, area and month (regions of the lake). However three-way interactions between these three variables had significant effect on the densities of all swimming birds. For all the remaining species of swimming birds found in this lake viz. Spotted - billed Pelican, Gadwall, Northern Pintail, Common Teal, Spot-billed Duck and Northern Shoveller year, month and area (region) of the lake had significant effect on their densities in this lake (Table 5.12).

Results of the three-way ANOVA to evaluate the influence of year, month and area (regions) of the lake on different species of large waders in the Karaivetti Lake had been given in (Table 5.13). The Little Egret, Large Egret, Median Egret, Cattle Egret, Grey Heron, Black-crowned Night-Heron, Indian Pond-Heron, Painted Stork, Asian Openbill-Stork and Oriental White Ibis were significantly influenced by all the three factors viz. year and month wise variations were not significant with regard to the densities of Purple Heron (P>0.05). Only the area wise is not significant on Glossy ibis. The effect of interaction between of year, area and month had not significant.

OBSERVATIONS AND RESULTS

The two way interaction between month and area on Glossy Ibis. Only the densities of Black-crowned Night-Heron, Common Moorhen and Black Ibis were not significantly influenced by year and area (Table 5.13).

Little Ringed Plover was not significantly influence among the small warders (P>0.05) the variable of years of the lake. Among them remaining small waders were significantly influenced by the three variables viz. year, month and area. Densities of Little Ringed Plover, Red-wattled Lapwing, Wood Sandpiper and Common Sandpiper were not significantly influenced by the two-way interaction between the months and area (regions of the lake). However three-way interactions between variable of years, months and regions of three variables had no significant effect only on the densities of Little Ringed Plover (P>0.05) (Table 5.14).

Densities of all the aerial foragers were significantly (P<0.05) influenced by all the three factors viz. years, months and area (regions) of the lake. The Lesser Pied Kingfisher was not significant. In two way interactions between variable of years, months and regions while three way interactions between years, months and regions. However Small Blue Kingfisher no significant variable between years, months and regions. The Whiskered Tern was not significant only in two way interactions between months and regions (Table 5.15).

5.1.1.8 Variation in the water quality features of the Karaivetti Lake. Variations in the water quality of the Karaivetti Lake during different months and seasons of the study period has been given in tables 5.16 to 5.21 and comparison between the first year and second year of study with regard to different variables have been depicted in fig 5.110 to 5.121.

5.1.1.8.1 Monsoon I (October, November and December 2010) 5.1.1.8.1.1 Water depth The depth of the lake during monsoon was (81.07 ± 15.01 cm) with October 2010 recording higher depth (87.42 ± 15.96 cm) than November 2010 and December 2010. Region „B‟ had higher in water depth, than „A‟ and „C‟ during October 2010

OBSERVATIONS AND RESULTS

while during November 2010 region „B‟ recorded the highest mean water Depth „A‟ the least „C‟ during December 2010. Region „B‟ was more than region „A‟ and „C‟ (Table 5.16).

5.1.1.8.1.2 Surface water temperature The Surface water temperature of lake during monsoon was 28.84 ± 1.18 with October 2010 recording higher temperature 30.00 ± 0.00 than November 2010 and December 2010. Regions „C‟ had higher in water temperature than „A‟ and „B‟ during October 2010, while during November 2010 region „C‟ recorded the highest mean water temperature, where „A‟ the least (Table 5.16). During December 2010 Region „B‟ was higher recorded when compared with region of „A‟ and „C‟ (Table 5.16).

5.1.1.8.1.3 Water pH The pH values of the lake water recorded higher during October 2010 November 2010 and December 2010 of monsoon. Correspondingly overall mean pH of the lake waters was 8.22 ± 0.41 (Table 5.16).

5.1.1.8.1.4 Dissolved oxygen The dissolved oxygen level was higher during November 2010 in the region of „A‟ with a overall mean value of November was 4.82 ± 0.35 mg/l. While the overall mean of dissolved oxygen level of the lake was 4.12 ± 1.04 mg/l (Table 5.16).

5.1.1.8.1.5 Salinity The overall mean salinity value during this season was (0.12 ± 0.08 ppm) with the December 2010 values (0.16 ± 0.09 ppm) higher than October 2010 values 0.14 ± 0.02 and November 2010 values (0.06 ± 0.02 ppm); region „C‟ of lake had higher mean salinity (0.18 ± 0.11 ppm) (Table 5.16).

5.1.1.8.1.6 Silicate The mean silicate level was 1.52 ± 0.38 mg/l in October 2010 During November (1.30 ± 0.77 mg/l) and December (3.33 ± 1.0 mg/l) during this season (Table 5.16).

OBSERVATIONS AND RESULTS

5.1.1.8.1.7 Nitrite Overall mean nitrite levels of the lake during October 2010 was 1.06 ± 0.06 mg/l and during November 2010 was 0.01 ± 0.01 mg/l while during December 2010 was 0.70 ± 0.58 mg/l with region „C‟ recorded higher levels of nitrites than the other regions in all the months of this seasons (Table 5.16).

5.1.1.8.1.8 Nitrate The overall mean nitrate levels of the lake noted from least of 0.01 to the highest value of nitrate was 14.88 ± 1.5 mg/l during December 2010. The region „C‟ recorded higher nitrate levels in overall mean of nitrate (Table 5.16).

5.1.1.8.1.9 Phosphate The overall mean phosphate level was least (0.05 ± 0.04 ppm) during December 2010 and the highest was 0.51 ± 1.22 ppm during October 2010 of the season (Table 5.16).

5.1.1.8.1.10 Sulphate The sulphate level was higher during December 2010 (0.48 ± 0.13 mg/l) in the region of „B‟ of the lake, with overall mean value of December 2010 was more (0.33 ± 0.12 mg/l)than October and November 2010 when the overall mean sulphate level of the lake was 0.28 ± 0.20 (Table 5.16).

5.1.1.8.1.11 Calcium The Calcium of the lake water remained fluctuations. Overall mean water calcium recorded during December (41.71 ± 8.05 mg/l) was higher than that of the other months of this season and region „B‟ had the more calcium level in December month of this season (Table 5.16).

5.1.1.8.1.12 Chloride The overall chloride level of the water during this season was (32.12 ± 12.48 mg/l) with region „C‟ had the highest mean value of chloride in the month of November 2010 (Table 5.16).

OBSERVATIONS AND RESULTS

5.1.1.8.2. Post - Monsoon I (January, February and March 2011) 5.1.1.8.2.1 Water depth The overall mean water depth recorded during January 2011 (69.0 ±13.54 cm) was higher than that of the other month of this season and the region „B‟ had the deepest water levels (85.0±4.08 cm) in all three months of this season (Table 5.17).

5.1.1.8.2.2 Surface water temperature The overall mean surface water temperature during this season was 29.36 ± 0.59 (oC) with region „C‟ recording higher temperature during January 2011 (Table 5.17).

5.1.1.8.2.3 Water pH The mean water pH value of the lake water was 8.92 ± 0.34 during February 2011. The greatest pH was noticed in the other months of season (Table 5.17).

5.1.1.8.2.4 Dissolved oxygen The dissolved oxygen level higher value in the region of „A‟ during the month of January 2011, where the overall mean was 2.29 ± 1.11 mg/l of this season (Table 5.17).

5.1.1.8.2.5 Salinity The overall mean salinity of the lake during this season was (3.18 ± 11 ppm) with February 2011 recording higher values (0.28 ± 0.3 ppm) and March 2011 (0.1 ± 0.1 ppm) (Table 5.17).

5.1.1.8.2.6 Silicate The overall mean silicate level was (3.18 ± 1.1 mg/l), with recording higher values (4.05 ± 1.46 mg/l) than January 2011 (2.85 ± 0.81 mg/l) and March 2011 (2.88 ± 1.46 mg/l) (Table 5.17).

5.1.1.8.2.7 Nitrite The nitrite level was highest during February 2011 and lowest during January 2011 of the post-monsoon of first year (Table 5.17).

OBSERVATIONS AND RESULTS

5.1.1.8.2.8 Nitrate The nitrate content of the lake water showed higher mean during February 2011 (18.71 ± 2.74 mg/l) and the overall mean was (16.46 ± 5.71 mg/l) (Table 5.17).

5.1.1.8.2.9 Phosphate The overall mean phosphate level of the lake water during this season was (0.1 ± 0.22 ppm) with February 2011 recorded higher mean value of this season, whereas during March didn‟t recorded phosphate (Table 5.17).

5.1.1.8.2.10 Sulphate The sulphate value of the lake water fluctuated very little during the season as the mean value was 0.68 ± 0.49 (Table 5.17).

5.1.1.8.2.11 Calcium The mean calcium of the lake waters was the highest value during January 2011 (42.25 ± 23.68) (Table 5.17).

5.1.1.8.2.12 Chloride The mean value of chloride of the lake water was relatively more during February 2011 than the other months of January and March 2011(Table 5.17).

5.1.1.8.3 Pre - monsoon I (August and September 2011) 5.1.1.8.3.1 Water depth The overall mean water depth recorded during August 2011 (44.83 ± 12.38 cm) and September was 28.80 ± 0.92 cm. The highest mean value was recorded during the region of „B‟ in the month of September 2011 (Table 5.18).

5.1.1.8.3.2 Surface water temperature The overall mean surface water temperature during this season was 28.80 ± 0.92oC with region „C‟ recorded higher temperature during September 2011 (Table 5.18).

OBSERVATIONS AND RESULTS

5.1.1.8.3.3 Water pH The overall mean pH values during this season was 8.14 ± 0.38 with August 2011 recorded higher pH values 8.18 ± 0.43 than September 2011 (8.11 ± 0.71) (Table 5.18).

5.1.1.8.3.4 Dissolved oxygen The overall mean dissolved oxygen of the lake was 4.73 ± 0.69 mg/l during August 2011. It got decreased to 3.82 ± 0.51 mg/1 during September 2010 (Table 5.18).

5.1.1.8.3.5 Salinity The mean of salinity values was higher during September 2011 (0.08 ± 0.01 ppm) (Table 5.18).

5.1.1.8.3.6 Silicate The mean silicate level in the lake water was 10.20 ± 5.31 mg/l during August 2011 and 2.63 ± 1.38 mg/1 during September 2011, with an overall mean value of 5.48 ± 5.0 mg/1 for the entire season (Table 5.18).

5.1.1.8.3.7 Nitrite The mean nitrite value of the lake water remained almost unchanged throughout this season as the mean value was 0.02 ± 0.01 mg/1 in both the months of this season (Table 5.18).

5.1.1.8.3.8 Nitrate There was an increase in nitrate value in lake water of both the months of season during August 2011. When compared to September 2011 and the mean value were 0.01 ± 0 mg/1 and 0.02 ± 0.01 mg/1 for August 2011 and September 2011, respectively (Table 5.18).

OBSERVATIONS AND RESULTS

5.1.1.8.3.9 Phosphate The phosphate content of the lake water showed an increasing trend as it was 0.03 ± 0.01 ppm and 0.06 ± 0.01 ppm during August and September months of this season respectively (Table 5.18).

5.1.1.8.3.10 Sulphate There was decreased in sulphate value in lake water of both the months of lake during September 2011. When compared to August 2011 the mean values were 0.67 ± 0.29 mg/1 and 0.38 ± 0.25 mg/1 for August 2011 and September 2011, respectively (Table 5.18).

5.1.1.8.3.11 Calcium The overall mean calcium level of the lake was 60.33 ± 9.42 mg/1 during August 2011. It was decreased to 45.80 ± 7.04 mg/1 during September 2011 (Table 5.18).

5.1.1.8.3.12 Chloride The overall mean chloride level of the lake water was 28.15 ± 4.17 mg/1 and 32.81 ± 3.14 mg/1 during August 2011 and September 2011, respectively (Table 5.18).

5.1.1.8.4 Monsoon II (October, November and December 2011) 5.1.1.8.4.1 Water depth The mean water depth was 74.04 ± 12.65 cm during October 2011, 70.5 ± 13.87 cm during November 2011 and 74.25 ± 12.55 cm during December 2011 and with an overall mean of 72.93 ± 12.78 cm for the entire seasons (Table 5.19).

5.1.1.8.4.2 Surface water temperature The overall mean surface water temperature during this season was 27.42 ± 1.25 oC with October 2011 recording the highest mean surface water temperature 28.22 ± 0.94 oC among the three months (Table 5.19).

OBSERVATIONS AND RESULTS

5.1.1.8.4.3 Water pH There was a decrease in pH value in lake water of all the months of the lake. During October 2011 the pH 8.48 ± 0.25, November 2011 8.42 ± 0.35 and December 8.41 ± 0.33 (Table 5.19).

5.1.1.8.4.4 Dissolved oxygen The overall mean dissolved oxygen level of the lake was 4.71 ± 0.67 mg/l during October 2011. It was increased to 5.08 ± 0.56 mg/l and 5.51 ± 1.62 mg/l for November 2011 and December 2011 respectively (Table 5.19).

5.1.1.8.4.5 Salinity The overall salinity value was higher during November 2011 (0.11 ± 0.07 ppm) (Table 5.19).

5.1.1.8.4.6 Silicate The silicate value of the lake water fluctuated very little during this season as the mean value was 2.33 ± 1.11 mg/l (Table 5.19).

5.1.1.8.4.7 Nitrite The mean nitrite values of the lake water remained almost unchanged in all regions of October 2011, (0.01 ± 0.01 mg/l), 0.04 ± 0.03 mg/l for November 2011 and 0.28 ± 0.48 mg/l for December 2011 respectively (Table 5.19).

5.1.1.8.4.8 Nitrate The nitrate content of the lake water showed same during the months of October 2011 and December 2011 of all regions but it was not in the month of December 2011 (0.06 ± 0.08 mg/l) (Table 5.19).

5.1.1.8.4.9 Phosphate The overall mean phosphate level of the lake water during this season was 0.14 ± 0.14 ppm with November 2011 recording a slightly higher the other months of this season (Table 5.19).

OBSERVATIONS AND RESULTS

5.1.1.8.4.10 Sulphate The sulphate was 0.07 ± 0.01 mg/l during October 2011, 6.7 ± 0.39 mg/l for November 2011 and 0.08 ± 0.09 mg/l for December 2011 the overall mean of the season was 0.14 ± 0.14 mg/l (Table 5.19).

5.1.1.8.4.11 Calcium The overall mean in the water calcium level 29.51 ± 9.92 mg/l with a maximum recorded during the month of October 2011 (38.5±3.55 mg/l) (Table 5.19).

5.1.1.8.4.12 Chloride The overall mean of chloride was 61.89 ± 26.36 mg/l during December 2011, it was the highest chloride value of the lake and 53.54 ± 10.79 mg/l was least chloride value during the month of November 2011(Table 5.19).

5.1.1.8.5 Post - Monsoon II (January, February and March 2012) 5.1.1.8.5.1 Water depth The mean water depth was 71.0 ± 13.75 cm during January 2012, 49.33 ± 9.24 cm during February 2012 and 50.25 ± 10.75 cm during March 2012, with a overall mean of 57.69 ± 15.28 cm for the entire seasons (Table 5.20).

5.1.1.8.5.2 Surface water temperature The overall mean surface water temperature during this season was 28.18 ± 1.20 oC with January 2012 recorded the highest mean surface water temperature 29.27 ± 0.86 oC among the three months of this season (Table 5.20).

5.1.1.8.5.3 Water pH The overall mean pH of the lake water was 8.66 ± 0.05 during this season with March 2012 recorded higher mean pH values (9.04 ± 0.28) than the other months of this season (Table 5.20).

5.1.1.8.5.4 Dissolved oxygen The mean dissolved oxygen level was 4.95 ± 1.34 mg/l during January 2012, 8.89 ± 0.2 mg/1 during February 2012 with region „A‟ having lower dissolved oxygen levels than the other regions of the lake in all the months of this season (Table 5.20).

OBSERVATIONS AND RESULTS

5.1.1.8.5.5 Salinity The overall mean salinity of the lake during this season was 0.38 ± 0.4 ppm with February 2012 recording higher values (0.78 ± 0.35) than January 2012 (0.20 ± 0.16 ppm) and March 2012 (0.03 ± 0.01 ppm) (Table 5.20).

5.1.1.8.5.6 Silicate The silicate value of the lake water was higher during the month of February 2012 (3.69 ± 0.96 mg/l) lower during the month of January 2012 (1.59 ± 1.05 mg/l) (Table 5.20).

5.1.1.8.5.7 Nitrite The nitrite value of the lake water not fluctuated that same value as former level 0.04 ± 0.02 mg/l but during the January 2012 was slightly fluctuated (0.04 ± 0.03 mg/l) (Table 5.20).

5.1.1.8.5.8 Nitrate The overall mean nitrate level of the lake water during this season was 0.04 ± 0.05 mg/l with February 2012 recording higher values (0.09 ± 0.03 mg/l) than January 2012 (0.02 ± 0.01 mg/l ) and March 2012 (0.01 ± 0.01 mg/l) (Table 5.20).

5.1.1.8.5.9 Phosphate The mean phosphate level of the lake water was 0.09 ± 0 ppm in both months of February 2012 and March 2012, lowest value of phosphate was recorded during January 2012 (0.1 ± 0.02 ppm) (Table 5.20).

5.1.1.8.5.10 Sulphate The sulphate level was decreased in all the months of this season the mean sulphate values were 1.12 ± 0.74 mg/l during January 2012, 0.28 ± 0.24 mg/l during February and 0.17 ± 0.09 mg/l during March 2012 (Table 5.20).

OBSERVATIONS AND RESULTS

5.1.1.8.5.11 Calcium The overall mean calcium level in the lake during this season was 34.67 ± 9.44 mg/l, with March 2012 recording higher values (44.13 ± 7.02 mg/l) than January 2012 (27.24 ± 4.64 mg/l) and February 2012 (35.81 ± 8.45 mg/l) (Table 5.20).

5.1.1.8.5.12 Chloride The overall mean chloride level in the lake during this season was 45.98 ± 20.40 mg/l with January 2012 recording higher values (59.40 ± 27.20 mg/l) (Table 5.20).

5.1.1.8.6 Pre - monsoon II (August and September 2012) 5.1.1.8.6.1 Water depth The overall mean water depth was 74.67 ± 13.93 cm during August 2012 and 76.59 ± 13.24 cm during September with region „B‟ having more water depth during both the months of this season (Table 5.21).

5.1.1.8.6.2 Surface water temperature The overall mean surface water temperature during this season was 29.21 ± 0.90 oC with September 2012 recorded higher temperature (29.63 ± 0.57 oC) than August 2012 (28.67 ± 1.0 oC) (Table 5.21).

5.1.1.8.6.3 Water pH The mean pH value of the lake waters was 8.14 ± 0.48 during August 2012. It got increased to 8.38 ± 0.51 during September 2012 (Table 5.21).

5.1.1.8.6.4 Dissolved oxygen The dissolved oxygen level got increased in all the regions of the lake during August 2012 and February 2012 and the mean dissolved oxygen values also were increased during both months of seasons, where 4.14 ± 1.18 mg/l for August 2012 and 4.41 ± 0.59 mg/l for September 2012 (Table 5.21).

OBSERVATIONS AND RESULTS

5.1.1.8.6.5 Salinity The overall mean salinity of the lake water during this season was 0.07 ± 0.05 ppm with August 2012 recorded higher values (0.03 ± 0.03 ppm) than September 2012 (0.1 ± 0 ppm) (Table 5.21).

5.1.1.8.6.6 Silicate The overall mean silicate level in the lake during this season was 3.63 ± 1.38 mg/l with September 2012 recorded higher values 4.07 ± 1.24 mg/l than August 2012 (3.04 ± 1.42 mg/l) (Table 5.21).

5.1.1.8.6.7 Nitrite The overall mean nitrite level of the lake water during this season was 0.05 ± 0.07 mg/l the nitrite level got increased in both month of season, where during August 2012 all regions were same value (Table 5.21).

5.1.1.8.6.8 Nitrate The mean nitrate value of the lake water during this season 0.02 ± 0.01 mg/l with September 2102 recorded higher values (0.02 ± 0.01 mg/l) than August 2012 (0.01 ± 0 mg/l) (Table 5.21).

5.1.1.8.6.9 Phosphate The mean phosphate level of the lake water was 0.21 ± 0.14 ppm in the month of August 2012 and 0.16 ± 0.22 ppm in the month of September the overall mean of the season was 0.18 ± 0.19 ppm (Table 5.21).

5.1.1.8.6.10 Sulphate The overall mean water sulphate during this season was 0.85 ± 0.56 mg/l with August 2012 recorded higher sulphate (1.31 ± 0.52 mg/l) than September 2012 (0.51 ± 0.27 mg/l) (Table 5.21).

5.1.1.8.6.11 Calcium The mean value of calcium value of the lake water was 60.28 ± 13.50 mg/l during August 2012. It got decreased to 53.67 ± 2.87 mg/l during September 2012 (Table 5.21).

OBSERVATIONS AND RESULTS

5.1.1.8.6.12 Chloride The overall mean chloride level of the lake water during this season was 27.89 ± 4.01 mg/l with September 2012 recorded higher chloride (28.23 ± 3.22 mg/l) (Table 5.21).

5.1.1.9 Month-wise and season-wise comparisons of fluctuation in water quality parameters Comparisons of month-wise and season-wise variation in different water quality parameters in different region of the lake during the study period have been shown in (Figure. 5.110 to 5.121).

5.1.1.9.1 Water depth The water depth was recorded higher during October 2010 and the least depth in August 2011 in the first year of study and in the second year, the highest depth was recorded during September 2011 and the least depth during March 2012. Overall the surface water depth was higher during monsoon season in both year of study (Fig 5.110).

5.1.1.9.2 Surface water temperature With regard to surface water temperature during all month of first year, except March and August were recorded with less fluctuations between them. The highest recorded was noted during the month of September in both year of study. Overall the surface water temperature was higher during monsoon and post-monsoon of study period (Fig 5.111).

5.1.1.9.3 Water pH The pH value was more during February in both the year of study, where as March and August was recorded lower during first and second year of study. High pH was recorded during monsoon season of study period (Fig 5.112).

5.1.1.9.4 Dissolved oxygen The dissolved oxygen content of the lake water for the first year showed increasing trend from October to November while December to March decreased. In

OBSERVATIONS AND RESULTS

the second year followed an alternative increasing and decreasing trend from October to September. The dissolved oxygen level increased and decreased respectively. The monsoon season was more recorded during this study period (Fig 5.113).

5.1.1.9.5 Salinity The salinity level of the lake water recorded high during December of first year and February of second year of study. In post-monsoon the salinity level of the water was high (Fig 5.114).

5.1.1.9.6 Silicate The silicate level was higher during February during both years of the study and November was lowest first year of study where as March in the second year of study (Fig 5.115).

5.1.1.9.7 Nitrite During first year of study the nitrite level of the lake water remains very low during November, August and September of first year, then the highest during February of first year and December of second year. The post-monsoon was the highest recorded (Fig 5.116).

5.1.1.9.8 Nitrate The nitrite level of the lake water during November, August and September were remaining same. When compared with other months February had higher in first year of study, but January had more in second year (Fig 5.117).

5.1.1.9.9 Phosphate The phosphate level was peaked during October of first year, but all regions of February were more in phosphate level of first year. In second year of study October was recorded high the season-wise comparison of phosphate was recorded more during monsoon than that of other seasons (Fig 5.118).

5.1.1.9.10 Sulphate The sulphate level was higher during February in first year of study but in second year more in August (Fig 5.119).

OBSERVATIONS AND RESULTS

5.1.1.9.11 Calcium From October to December of calcium level of the lake water in an increasing trend and from January to March it was in a decreasing trend in first year of study, where as in second year opposite trend was recorded. From October to December it was decreased while January to March it was increased during second year of study. Both years during September the Calcium was recorded more (Fig 5.120).

5.1.1.9.12 Chloride The chloride level showed the same during the months of January and February of first year. Which was the highest, lowest level was recorded during the month of August in first year of study and March in second year of study (Fig 5.121).

5.1.1.10 Evaluation of the influence of year, month and regions of the lake on the water quality parameters. The three-way ANOVA of the water quality parameters evaluate the effect of year, month and area (region) of the lake has been given in Table 5.22. The year wise variations were significant (P<0.05) with regard to Water depth, Surface water temperature, Dissolved Oxygen, Silicate, Nitrite, Nitrate level and remaining water quality parameters were not significant (P>0.05). All water quality parameters were had significant influence in month wise variable. Area (regions) of the lake didn‟t have significant influence (P>0.05) on Surface water temperature, pH, Dissolved Oxygen, Salinity, Nitrite, Sulphate, Calcium and Chloride.

The two variable of interaction between three variables of year, month and area were not significant on pH. The interaction between year and area was not significant with regard to Surface water temperature, Nitrite, Sulphate and Chloride. Year and month with regard to Phosphate. Three-way interaction between year, month and area (regions) was not significant (P>0.05) for pH (Table 5.22).

5.1.1.11 Variations in the bottom soil parameters of the Karaivetti Lake Variations in the bottom soil parameters of the Karaivetti Lake during different months and season of the study period has been given in table 5.23 to 5.28

OBSERVATIONS AND RESULTS

and comparisons between the first year and second year of study with regard to different variables have been described in figures 5.122 to 5.127.

5.1.1.11.1 Soil texture analysis Soil texture analysis revealed that region „A‟ and „C‟ had clayey loam and region „B‟ sandy loam during the study period.

5.1.1.11.2 Monsoon I (October, November and December 2010) 5.1.1.11.2.1 Soil depth Overall mean soil depth of the lake during monsoon was 128.13 ± 42.51 cm with November 2010 recording higher depth (137.42 ± 35.36 cm) than October 2010 ( 101.2 ± 29.73 cm ) and December 2010 (132.33 ± 51.0 cm) All the Region of „B‟ had the highest mean soil depth in this season (Table 5.23).

5.1.1.11.2.2 Electrical conductivity Soil in all the lake recorded higher electrical conductivity during December 2010 than October 2010 and November 2010 Correspondingly the overall mean electrical conductivity of the soil of the lake was 0.41 ± 0.22 m.mho/cm during December, 0.53 ± 0.22 m.mho/cm during October 2010 and during November 2010 (Table 5.23).

5.1.1.11.2.3 Soil pH The pH values of the lake soil were little fluctuated in all the region of the lake during all month of this season. The overall mean pH of the soil of the lake was 7.55 ± 00 (Table 5.23).

5.1.1.11.2.4 Nitrogen Overall mean soil nitrogen level of the lake was 51.49 ± 12.38 kg/ ha during October 2010, 61.08 ± 24.91 kg/ha during November 2010 and 48.77 ± 20.35 kg/ha during December 2010. All the regions of the lake had decreased mean soil nitrogen in this season of the lake where as regions „C‟ had more soil nitrogen than the two regions in October of this season (Table 5.23).

OBSERVATIONS AND RESULTS

5.1.1.11.2.5 Phosphorus The mean soil phosphorus level was which was 60.6 ± 22.75 kg/ha during November 2010 got decreased to 11.25 ± 5.07 kg/ha during October 2010 and 30.74 ± 20.88 kg /ha during December 2010 (Table 5.23).

5.1.1.11.2.6 Potassium During this season the mean soil potassium level was highest during December 2010 (220.05 ± 20.59 kg/ha) and least during November 2010 (135.21 ± 52.05 kg/ha) (Table 5.23).

5.1.1.11.3 Post - Monsoon I (January, February and March 2011) 5.1.1.11.3.1 Soil depth Overall mean soil depth of the lake during post monsoon I was 81.58 ± 51.75 cm with January 2011 recorded higher soil depth (128.5 ± 54.29 cm) than February 2011 (75.5 ± 28.2 cm) and March 2011 (33.5 ± 23.76 cm).

5.1.1.11.3.2 Electrical conductivity The mean soil electrical conductivity of the lake was 0.45 ± 0.31 m.mho/cm during of January 2011 with region „C‟ having higher values than the other regions of the lake (Table 5.24) where during February 2011 was 7.57 ± 0.18 m.mho/cm and March 2011 was 0.53 ±0.68 m.mho/cm.

5.1.1.11.3.3 Soil pH The overall mean of the soil pH value in the lake during this season was 7.14 ± 1.76 and in February 2011 slightly higher value was recorded than other months of this season (Table 5.24).

5.1.1.11.3.4 Nitrogen The soil nitrogen level in the lake were 48.18 ± 10.1 kg/ha during January 2011, 70.19 ± 12.2 in February 2011 and 55.55 ± 30.78 in March 2011 (Table 5.24).

OBSERVATIONS AND RESULTS

5.1.1.11.3.5 Phosphorus The soil phosphorus level in the lake showed in decreasing trend across the months of this season on the overall mean value (65.68 ± 39.02 kg/ha) during January 2011 got increased to 37.26 ± 18.01 kg/ha during February 2011 and to 31.49 ± 2.19 kg/ha during March 2011. The region „B‟ of the lake recorded the highest soil phosphorus level when compared to other regions in all the months of this season (Table 5.24).

5.1.1.11.3.6 Potassium The soil nitrogen content of the lake showed an increasing trend across the months of the season as it was 291.94 ± 111.52 kg/ha, 94.24 ± 15.55 kg/ha and 88.39 ± 47.95 kg/ha during January, February and March 2011 of this season, respectively (Table 5.24).

5.1.1.11.4 Pre - monsoon I (August and September 2011) 5.1.1.11.4.1 Soil depth The region „A‟ of the lake was not recorded during the month of August 2011. Overall mean soil depth 52.38 ± 14.62 cm recorded as the highest mean depth (55.67 ± 19.99 cm) among the three months of this season (Table 5.25).

5.1.1.11.4.2 Electrical conductivity The mean soil electrical conductivity of the lake at the start of this season i.e., August 2011 was 1.95 ± 0.90 m.mho/cm(Table 5.25). It decreased to (0.86 ± 0.37 m.mho/cm) during September 2011. The soil electrical conductivity value didn‟t record in the region of „A‟ during August 2011(Table 5.25).

5.1.1.11.4.3 Soil pH The overall mean soil pH value in the lake was 7.73 ± 0.16 during this season September 2011 was noted slightly higher recorded than the mean of August 2011 ( 7.71 ± 0.18 ) (Table 5.25).

OBSERVATIONS AND RESULTS

5.1.1.11.4.4 Nitrogen The soil nitrogen content of the lake showed an increasing trend across the months of this season as it was 50.57 ± 24.51 kg/ha, 62.50 ± 27.13 kg/ha during August 2011 and September 2011 of this season respectively (Table 5.25).

5.1.1.11.4.5 Phosphorus The overall mean phosphorus value of lake was 103.31 ± 195.58 kg/ha during this season with September 2011 recorded the highest mean value 149.20 ± 240.60 kg/ha than the other months of this season (Table 5.25).

5.1.1.11.4.6 Potassium The overall mean potassium value of lake was 243.70 ± 148.61 kg/ha during this season with August 2011 recorded the highest mean value 343.09 ± 153.39 kg/ha than the other months of this season (Table 5.25).

5.1.1.11.5 Monsoon II (October, November and December 2011) 5.1.1.11.5.1 Soil depth The overall mean soil depth during this season was 124.5 ± 46.68 cm with October 2011 recording the highest mean depth (125.33 ± 46.8 cm) among the three months of this season (Table 5.26).

5.1.1.11.5.2 Electrical conductivity The mean soil electrical conductivity of the lake at the start of this season i.e., October 2011 was 0.28 ± 0.11 m.mho/cm (Table 5.26). Then the same mean value was November 2011 and December 2011 (0.66 ± 0.14 m.mho/cm).

5.1.1.11.5.3 Soil pH The overall mean soil pH value of lake was 7.49 ± 0.2 during this season with December 2011 recording a higher mean pH value (7.54 ± 0.2) than the other months of this season (Table .5.26).

OBSERVATIONS AND RESULTS

5.1.1.11.5.4 Nitrogen The soil nitrogen content of the lake showed on increasing trend across the months of the season as it was 60.32 ± 22.38 kg/ha, 70.73 ± 22.95 kg/ha and 78.4 ± 4.16 kg/ha during October, November and December 2011 of this season respectively (Table 5.26).

5.1.1.11.5.5 Phosphorus The overall mean phosphorus level of the during this season was 27.0 ± 17.25 kg/ha with November 2011 recording a slightly higher mean value of 36.6 ± 22.04 kg/ha than the other months of this season (Table 5.26).

5.1.1.11.5.6 Potassium The mean potassium level recorded in the lake was higher during October 2011 (155.31 ± 29.08 kg/ha) than November 2011 (82.66 ± 59.64 kg/ha) and December (16.42 ± 2.05 kg/ha). Region „A‟ recorded the highest potassium levels than the other regions during all the months of this season (Table 5.26).

5.1.1.11.6 Post - Monsoon II (January, February and March 2012) 5.1.1.11.6.1 Soil depth The overall mean soil depth of the lake during post-monsoon was 84.19 ± 47.09 cm with January 2012 recording higher depth 119.42 ± 49.32 cm than February 2012 (71.42 ± 37.16 cm) and March 2012 (50.50 ± 11.16 cm) (Table 5.27).

5.1.1.11.6.2 Electrical conductivity The mean soil electrical conductivity of the lake was 0.38 ± 0.22 m.mho/cm during January 2012. It was increased to 0.4 ± 0.27 m.mho/cm during February 2012 and 0.61 ± 0.11 m.mho/cm during March 2012 (Table 5.27).

5.1.1.11.6.3 Soil pH The overall mean soil pH value in the lake during this season was 7.57 ± 0.26 with January 2012 recording slightly higher values than other months of seasons 2012 (Table 5.27).

OBSERVATIONS AND RESULTS

5.1.1.11.6.4 Nitrogen The mean soil nitrogen level in the lake was 75.74 ± 8.41 kg/ha during January 2012, 68.34 ± 15.59 kg/ha during February 2012 and 80.28 ± 23.76 kg/ha during March 2012 with a overall mean value of 74.10 ± 16.20 kg/ha for the entire season (Table 5.27).

5.1.1.11.6.5 Phosphorus The mean soil phosphorus level of the lake was 21.22 ± 17.85 kg/ha, 41.82 ± 21.37 kg/ha and 30.13 ± 23.22 kg/ha during January 2012, February 2012 and March 2012 respectively (Table 5.27).

5.1.1.11.6.6 Potassium The overall mean soil potassium content of the lake during this season was 69.63 ± 34.23 kg/ha with February 2012 recording higher values (78.74 ± 32.75 kg/ha) than other months of season 2012 (Table 5.27).

5.1.1.11.7 Pre - monsoon II (August and September 2012) 5.1.1.11.7.1 Soil depth The soil depth of the lake showed as decreasing trend across the months of the season as it was 140.11 ± 31.42 cm and 128.08 ± 47.23 cm during August 2012 and September 2012 of this season respectively (Table 5.28).

5.1.1.11.7.2 Electrical conductivity The mean soil electrical conductivity of the lake of this season i.e., August 2012 was 0.79 ± 0.22 m.mho/cm (Table 5.28). It was increased to 0.73 ± 0.29 m.mho/cm during August 2012 and 0.82 ± 0.14 m.mho/cm.

5.1.1.11.7.3 Soil pH The overall mean soil pH value of lake was 7.58 ± 0.23 during this season with September 2012 recording a lower mean pH values (7.53 ± 0.20) than the other months of this season (Table 5.28).

OBSERVATIONS AND RESULTS

5.1.1.11.7.4 Nitrogen The mean soil nitrogen level was 75.71 ± 14.17 kg/ha during August 2012. It got decreased to 66.6± 28.15 kg/ha during September 2012 (Table 5.28).

5.1.1.11.7.5 Phosphorus The overall mean soil phosphorus level of the lake during this season was 40.12 ± 41.44 kg/ha, with September 2012 recording a slightly higher mean value of (54.95 ± 49.06 kg/ha) than the other months of this season (Table 5.28).

5.1.1.11.7.6 Potassium The mean potassium level recorded in the soil of the lake was higher during August 2012 (122.34 ± 172.18 kg/ha) (Table 5.28).

5.1.1.12 Month-wise and season-wise comparisons of fluctuation in bottom soil parameters Comparisons of month-wise and season-wise variation in different bottom soil parameters of the lake during the study period have been shown in fig.5.122 to 5.127.

5.1.1.12.1 Soil depth The soil depth was highest during November and lowest during August in first year of study. In second year highest during September and lowest during March (Fig. 5.122).

5.1.1.12.2 Electrical conductivity The electrical conductivity of first year of the study was least recorded except September, when compared with first year of study. The second year gave good result to the electrical conductivity. The month of September was showed highest mark in both years of the study. Pre-monsoon showed higher value in the seasons (Fig. 5.123).

5.1.1.12.3 Soil pH There was very least fluctuation in soil pH except March and August during first year and second year of study while it deference in March (Fig. 5.124).

OBSERVATIONS AND RESULTS

5.1.1.12.4 Nitrogen The soil nitrogen level was highest during February of first year, December and August of second year, more fluctuation was not seen between the season (Fig. 5.125).

5.1.1.12.5 Phosphorus The phosphorus level of the lake soil showed the greatest value during September in both years of study. Pre-monsoon was recorded highest (Fig. 5.126).

5.1.1.12.6 Potassium The Potassium level showed a decreasing trend from October to November followed by an increase during December to January and thereafter a decreasing trend up to March in the first year „A‟ region of August didn‟t recorded, In the second year a decreasing trend was recorded from October to December. In general the highest potassium levels were recorded during pre-monsoon months (Fig. 5.127).

5.1.1.13 Evaluation of the effects of year, month and regions of the lake on Soil Characters. Result of three-way ANOVA performed to evaluate the effects of year month, and area (regions) of lake on various soil parameters during the study period has been given in Table 5.29. Area (regions) of the lake didn‟t have significant influence (P>0.05) on pH, phosphorous, and potassium, month of the lake was not significant influence only on nitrogen. The depth only had significant variations in soil parameters. The interaction between year and month was significant (P<0.005) with regard to soil depth, year and area (regions) was significant (P<0.005) to the depth. Nitrogen and Potassium of soil parameters month and area was not significant (P>0.005) to soil pH, nitrogen, phosphorus and potassium. Three way interactions between year, month and area (regions) was not significant (P>0.005) for soil pH, and phosphorus (Table 5.29).

5.1.1.14 Variation in biological parameters of the Karaivetti lake Variations in biological parameters of the Karaivetti Lake during different months and seasons of the study period has been given in the table 5.30 to 5.35 and

OBSERVATIONS AND RESULTS

comparison between the first year and second year of study with regard to different variables have been depicted in figures 5.128 to 5.130.

5.1.1.14.1 Monsoon I (October, November and December 2010) 5.1.1.14.1.1 Plankton volume The overall mean plankton volume of the lake was 0.63 ± 0.23 ml/10l. The highest values for plankton volume were recorded in the months of December 2010 (Table 5.30).

5.1.1.14.1.2 Biomass of benthic annelid worms Overall mean biomass of annelid worms in the benthos of the lake was higher in December 2010 (2034.4 ± 1324.0 mg/1kg of soil) and November 2010 (358.0 ± 166.0 mg/1kg of soil) (Table 5.30).

5.1.1.14.1.3 Biomass of benthic molluscs The mean biomass benthic molluscs was higher during November 2010 (3693.0 ± 1342.35 mg/1kg of soil) with the highest values in region „C‟ during (3514.8 ± 2156.0) October 2010 (Table 5.30).

5.1.1.14.2 Post - Monsoon I (January, February and March 2011) 5.1.1.14.2.1 Plankton volume The overall mean plankton volume value was 0.47 ± 0.22 ml/10l, during this season with monthly mean values of 0.58 ± 0.19 ml/10l, 0.51 ± 0.18 ml/10l and 0.32 ± 0.22 ml/10l for January, February and March 2011 respectively (Table 5.31).

5.1.1.14.2.2 Biomass of benthic annelid worms The mean biomass of the benthic annelid worms of the lake was the highest during January 2011 (603.2 ± 585.5 mg/1kg of soil) and „lower‟ during March 2011 135.71 ± 101.6 mg/1kg of soil of this season (Table 5.31).

5.1.1.14.2.3 Biomass of benthic molluscs The overall biomass mean value was recorded to be 3082.1 ± 133.1 mg/1kg of soil during this season (Table 5.31).

OBSERVATIONS AND RESULTS

5.1.1.14.3 Pre - monsoon I (August and September 2011) 5.1.1.14.3.1 Plankton volume The overall mean plankton volume was 0.42 ± 0.16 ml/10l of soil during this season (Table 5.32) with the higher values being recorded during September 2011 (0.44 ± 0.16 ml/10l).

5.1.1.14.3.2 Biomass of benthic annelid worms The mean biomass of benthic annelid worms was 0.38 ± 0.15 mg/1kg of soil during August 2011 and 512.30 ± 170.21 mg/1kg of soil during September 2011. Region „A‟ recording „Nil‟ values in the month of August 2011(Table 5.32).

5.1.1.14.3.3 Biomass of benthic molluscs With regard to the benthic molluscs biomass there was a decreasing trend from the month of August 2011 (3890.0 ± 1485.52 mg/1kg of soil) to September 2011 (3423.0 ± 1277.95 mg/1kg of soil (Table 5.32).

5.1.1.14.4 Monsoon II (October, November and December 2011) 5.1.1.14.4.1 Plankton volume The overall mean plankton volume of the lake was recorded to the 0.47 ± 0.16 ml/10l during this season then the same volume was recorded during October 2011 and December 2011 (0.5 ± 0.17 ml/10l) (Table 5.33).

5.1.1.14.4.2 Biomass of benthic annelid worms The mean biomass of benthic annelid worms was 695 ± 445.52 mg/1kg of soil during October 2011 and 663.42 ± 327.41 mg/1kg of soil during November 2011, with December 2011 was recording higher values (884.2 ± 580.35 mg/1kg of soil) than the other regions of the lake in this season (Table 5.33).

5.1.1.14.4.3 Biomass of benthic molluscs There was decreasing trend in the mean biomass of benthic annelid worms from, October 2011 (3981.5 ± 2029.03mg/1kg) to December 2011 (1201.8 ± 644.61 mg/1kg) (Table 5.33).

OBSERVATIONS AND RESULTS

5.1.1.14.5 Post - Monsoon II (January, February and March 2012) 5.1.1.14.5.1 Plankton volume The overall mean plankton volume was 0.41 ± 0.12 ml/10l during this season with higher values recorded during January 2012 (0.5 ± 0.11 ml/10l) than the other two months of this season (Table 5.34).

5.1.1.14.5.2 Biomass of benthic annelid worms The mean biomass of benthic annelid worms was 742.0 ± 409.29 mg/1kg of soil during January 2012, 525.17 ± 282.1 mg/1kg of soil during February 2012 and 429.88 ± 185.93 mg/1kg of soil during March. Region „A‟ of the lake recorded the maximum biomass of benthic annelid worms during January 2012 (Table 5.34).

5.1.1.14.5.3 Biomass of benthic molluscs The mean biomass of benthic molluscs was 528.4 ± 253.69 mg/1kg of soil during January 2012 than the months of February 2012 was increased to 3773.3 ± 2437.44 mg/1kg of soil and the month of March 2012 was decreased to 3466.4 ± 1806.55 mg/1kg of soil (Table 5.34).

5.1.1.14.6 Pre - monsoon II (August and September 2012) 5.1.1.14.6.1 Plankton volume The overall mean plankton volume of the lake was 0.44 ± 0.16 ml/10l. Highest values for plankton volume were recorded in the month of September 2012 (0.47 ± 0.17 ml/10l) (Table 5.35).

5.1.1.14.6.2 Biomass of benthic annelid worms Overall mean biomass of annelid worms in the benthos of the lake was higher in September 2012 (529.7 ± 168.97 mg/1kg of soil than August 2012 (177.44 ± 70.84mg/1kg of soil) during this season (Table 5.35).

5.1.1.14.6.3 Biomass of benthic molluscs The mean biomass of benthic molluscs was higher during August 2012 (4019.56 ± 1345.44 mg/1kg of soil) than September 2012 (3436.37 ± 1148.97 mg/1kg

OBSERVATIONS AND RESULTS

of soil) with the highest values in region „B‟ during both months of this season 2012 (Table 5.35).

5.1.1.15 Month-wise and season-wise comparisons of fluctuation in biological parameters . Comparisons of month-wise and season-wise variations in different biological parameters of the lake during the study period had been showed in figures 5.128 to 5.130.

5.1.1.15.1 Plankton volume The plankton volume was increased during October to December in first year of study, thereafter during January to March the plankton volume decreased in both years of study. Region „A‟ of August was not recorded. All regions were recorded during the month of September in first year of study. In second year of study November had relatively lower in plankton volume. When compared with August, September had highest value (Fig 5.128).

5.1.1.15.2 Biomass of benthic annelid worms The biomass of benthic annelid worms was the highest during December in both years of study while the least was recorded during August in the first year of study and March in the second year of study. The biomass of benthic annelid worms was higher in the monsoon season than the other seasons of the study period (Fig 5.129).

5.1.1.15.3 Biomass of benthic molluscs The highest biomass of benthic molluscs was recorded during November in the first year of study and August in the second year of study where as the lowest biomass of benthic molluscs was recorded during August in first year of study and March in second year. Over all the biomass of benthic molluscs was higher during pre-monsoon season when compared with other seasons of the study period (Fig 5.130).

OBSERVATIONS AND RESULTS

5.1.1.16 Evaluation of the effects of year, month and regions of the lake on biological variables. Results of three ways ANOVA performed to evaluate the effects of year, and area of the lakes on the various biological parameters during the study period have been given in Table 5.36. The year and area wise variations were not significant (P>0.05) with regard to all biological biomass. The month (regions) of the lake had significant effects (P>0.05) on plankton volume. Two way interactions between three variations of year, month and area were not significant with regard to plankton and mollusks, except Annelid worms Three way interactions between year, month and area (regions) were not significant (P<0.05) for plankton biomass only (Table 5.36).

5.1.1.17 Relationship of water quality parameters, soil parameters and biological variables with waterbirds population characteristics. Effect of water quality parameters, soil parameters and biological parameters on the population characteristics features of waterbirds and ecological group-wise water bird population characteristics were investigated using multiple regression models derived and the models derived were given in the table 5.37 to 5.54.

5.1.1.17.1 Density of Waterbirds Results of multiple regression equations developed on the relative influence of various factors on the density of grand total waterbirds like diving birds, swimming birds, large waders, small waders and aerial foragers in the Karaivetti Lake have been given in tables 5.37 to 5.42.

5.1.1.17.1.1 Density of grand total waterbirds Variations in water depth, Surface water temperature, salinity, sulphate, electrical conductivity and soil pH entered in to the multiple regressions models to predict the density of total waterbirds in the Karaivetti Lake (Table 5.37). This model was significant (P<0.001) and explained 22.6% of total variance in the density of total water birds in the Karaivetti Lake during the study period. Among the variables entered into the predictor equation soil pH only had a positive relationship with density of total waterbirds (Table 5.37).

OBSERVATIONS AND RESULTS

5.1.1.17.1.2 Density of total diving birds Results of multiple regression analyses performed to evaluate the influence of various seasonal, physico-chemical and biological factors on the density of total diving birds of Karaivetti Lake have been given in the (Table 5.38). Among the water quality parameters that entered into this regression equation soil depth influenced the density of total diving birds positively and linearly (Table 5.38).

5.1.1.17.1.3 Density of total swimming birds The results showed that multiple regression analysis performed to evaluate the influence of various factors of physico-chemical and biological factors on the density of total swimming birds have been shown in the (Table 5.39) Among the water quality parameters that entered into this regression equation water pH, chloride, soil depth and electrical conductivity influenced the density of total swimming birds positively and linearly (Table 5.39).

5.1.1.17.1.4 Density of total large waders Among the water quality parameters that entered into this regression equation. Dissolved oxygen, sulphate, soil depth and electrical conductivity influenced the density of total large waders positively, plankton volume influenced the density of total large waders linearly and positively (Table 5.40).

5.1.1.17.1.5 Density of total small waders The multiple regression of density of total small waders positively influenced in variables of water pH, dissolved oxygen, chloride and soil depth (Table 5.41).

5.1.1.17.1.6 Density of total Aerial foragers Results of multiple regression analyses performed to evaluate the influence of various seasonal physico-chemical and biological factors on the density of total aerial foragers of Karaivetti Lake have been given in the (Table 5.42). Among the water quality parameters that entered into this regression equation, water pH, Nitrate, soil depth, potassium and biological variable of Annelid worms linearly and Dositrely (Table 5.42).

OBSERVATIONS AND RESULTS

5.1.1.17.2 Diversity of total waterbirds The multiple regression equation influenced on various factors on the diversity of grand total waterbirds, diving birds, swimming birds, large waders, small waders and aerial foragers in the Karaivetti Lake have been seen in tables 5.43 to 5.48.

5.1.1.17.2.1 Diversity of grand total water birds Variation in water depth, Surface water temperature, dissolved oxygen, salinity, Nitrate, calcium, soil depth and potassium involved in the multiple regression models to foretell the diversity of grand total waterbirds in Karaivetti Lake (Table 5.43). This mode had significant (P<0.001) and explained 33% of total variance in the diversity of total waterbirds in the Karaivetti Lake during the study periods. Among the variable water depth, temperature, salinity, calcium and potassium had a positive relationship with diversity of total waterbirds (Table 5.43).

5.1.1.17.2.2 Diversity of total diving birds Among the total variables of water pH, salinity, nitrate, phosphate, calcium, soil depth, potassium, plankton and annelid worms in the diversity of total diving birds except that the nitrate and soil depth all of them were positively and linearly related with diversity of diving birds (Table 5.44).

5.1.1.17.2.3 Diversity of total Swimming birds The diversity of swimming birds showed the results in the multiple regression analysis soil pH only had a positive regression with diversity of total swimming birds (Table 5.45).

5.1.1.17.2.4 Diversity of total large waders Results of step-wise multiple regression analyses performed to evaluate the influence of various physico-chemical and biological factors on diversity of large waders (Table 5.46). Among the water quality parameters that entered into this regression equation, water depth, temperature, calcium and biological variable of molluscs influenced the species diversity of total waterbirds positively and linearly (Table 5.46).

OBSERVATIONS AND RESULTS

5.1.1.17.2.5 Diversity of total small waders Among the various water quality parameters that had got positively variables of influence of water pH, salinity and chloride (Table 5.47).

5.1.1.18.2.6 Diversity of total aerial foragers In water quality parameters of total diversity of aerial foragers except nitrate and chloride remaining parameters were had positive and linear regression (Table 5.48).

5.1.1.17.3 Species richness of water birds Results of step-wise multiple regression analyses performed to evaluate the influence of various physico-chemical and biological factors on the species richness of grand total waterbirds, diving birds, swimming birds, large waders, small waders and aerial foragers of Karaivetti Lake have been given in the table 5.49 to 5.54.

5.1.1.17.3.1 Species richness of grand total water birds Among the water quality parameters that entered into this regression equation water pH, dissolved oxygen, salinity, nitrate, plankton and Annelid worms influenced the species richness of total waterbirds positively and linearly. This model was highly significant (P<0.001) and explained 60.4% of the total variance in the density of total waterbirds in the Karaivetti Lake during study period (Table 5.49).

5.1.1.17.3.2 Species richness of total diving birds Among the water quality parameters that entered into this regression equation. Water pH, dissolved oxygen, salinity, soil depth, plankton and annelid worms influenced the species richness of total waterbirds positively and linearly (Table 5.50).

5.1.1.17.3.3 Species richness of total swimming birds Results of multiple regression analyses performed to evaluate the influence of water quality parameters of water pH, dissolved oxygen; nitrate and soil depth influenced the species richness of total waterbirds positively and linearly. Plankton

OBSERVATIONS AND RESULTS

and Annelid worms influenced the species richness of total waterbirds linearly and positively (Table 5.51).

5.1.1.17.3.4 Species richness of total large waders Variations in silicate, nitrate, sulphate, calcium, chloride, electrical conductivity, solid pH, nitrogen, phosphorus, potassium, and plankton and Annelid worms entered into the multiple regression models to predict the richness of total waterbirds positively and linear variables in Surface water temperature, nitrate, chloride, nitrogen, phosphorus, plankton and Annelid worms (Table 5.52).

5.1.1.17.3.5 Species richness of total small waders Among the water quality parameters that entered into this regression equation, water pH, dissolved oxygen, salinity, nitrate and annelid worms influenced the species richness of total waterbirds positively and linearly (Table 5.53).

5.1.1.17.3.6 Species richness of total aerial foragers Among the variations of water quality parameters, soil parameters and biological population, The nitrate, chloride, soil depth and nitrogen had positive relationship and it was significant (P<0.001) and explained 72.8 % of the total variance in the richness of total waterbirds in Karaivetti Lake during the study period (Table 5.54).

5.1.1.18 Relationships of water quality feature, soil parameters and biological variables with density of total waterbirds. Effects of water quality feature, soil parameters and biological parameters on the density of total waterbirds were investigated using Pearson correlation models and the models derived were given in the table 5.55 to 5.57.

5.1.1.18.1. Pearson correlation model to predict the density of total waterbird in the Karaivetti Lake in response to variation due to water quality feature of the lake. Among the water quality feature analyzed using Pearson correlation to find the significance against the density of total waterbirds, the influence of Depth on the

OBSERVATIONS AND RESULTS

density of total waterbirds was more positive and linear (P>0.117) and almost all the waterbirds except Spotted –billed pelican, Northern Shoveller and Grey Heron. (Table 5.55).

5.1.1.18.2 Pearson correlation model to predict the density of total waterbirds in the Karaivetti Lake in response to variation due to bottom soil parameters of lake. The influence of pH on the density of bottom soil parameters was positive and linear (P>0.117) in almost all the waterbirds expect Darter, Bar-headed goose, and Painted stork (Table 5.56) than the variations in the bottom soil phosphorus influenced (P>0.117) the variations in the density of majority of waterbirds whereas Spot-billed duck, Garganey, Common moorhen, White-breasted waterhen and Wood sandpiper were not significant (Table 5.56).

5.1.1.18.3 Pearson correlation model to predict the density of total waterbirds in the Karaivetti Lake in response to variation due to biological characters of lake. The variations in the biological parameters viz, plankton, annelid worms and molluscs (p>0.117) the variations in the density of Little Grebe, Little Cormorant, Bar-headed Goose, Garganey, Cattle Egret, Blank-crowned Night-Heron, Indian Pond-Heron, Eurasian Spoonbill, Black-winged Stilt, Whiskered Tern, and Small Blue Kingfisher were significant, where as remaining birds were not significant (Table 5.57).

5.1.1.19 Socio-economic survey around the lake The results of the socio-economic surveys had been given in table 5.58 and 5.59.Totally 4 villages surrounding the lake with a total human population of 16,099. Agriculture is the major profession in all these villages. Majority of the people belonged to backward communities and schedule caste (Table 5.58).

5.1.1.20 Anthropogenic pressure Various kinds of use of the lake by the local people and the anthropogenic pressures are given in table 5.59. The local people use this lake for fishing, irrigation,

OBSERVATIONS AND RESULTS

fuel wood collection, grazing and medicinal plants collection, besides encroaching the lake area for agriculture as well, cattle washing, washing of clothes (detergent pollution) and soiling (defecation) of the lake bund are also common (Table 5.59).

5.1.1.21 Agricultural pollution A survey of agricultural pollution revealed that urea, DAP (Di Ammonium phosphate), potash and complex (mixture of fertilizers) were the common fertilizers applied in the catchment areas of the lake. The pesticides used include the Organo Chlorine and Organo phosphorous chemicals such as Monochrotophos, Dimecron, Karattea, Agent Plus, Piendal, Piorpaan Papas, Metacid, Melathion, Karatae, Luied power and BHC (Table 5.59).

DISCUSSION

6. DISCUSSION

6.1 Waterbirds and Karaivetti Lake Forty three species of waterbirds belonging to 14 families and 7 orders were recorded in the Karaivetti Lake during the study period (Table 5.1). Among them were the “Near threatened” birds viz. the Spotted Billed Pelican (Pelecanus philippensis), Darter (Anhinga rufa), Painted Stork (Mycteria leucocephala) and White Ibis (Threskiornis aethiopica). Further rare species viz. Bar-headed Goose (Anser indicus), Northern Pintail (Anas acuta) and Northern Shoveller (Anas clypeata), was also among the winged visitors to this Lake. This showed the great significance of this Lake in the migratory bird life in this area. This region viz. the Cauvery delta, in which this Lake is situated is known for a variety of waterbirds habitats such as the swamps of Point Calimere (which is a Ramsar Site), the Udhayamarthandapuram Wildlife Sanctuary, Karaivetti Lake and Vaduvoor Lake, which are major attractions of migratory waterbirds every year (Sampath and Krishnamoorthy, 1989a, 1989b; Balamurali, 1995; Meganathan, 2002; Sridharan, 2003; Ramesh, 2008; Vachanth, 2008; Thavakumar, 2008; Balamurugan, 2009; Arunkumar, 2009; Gokula 2013; Vachanth, 2013). This present study clearly established that Karaivetti Lake as bird sanctuary in 1999 by the forest department is also equally important for waterbirds. The migratory birds require a mosaic of habitats to fulfill their requirements and often they select an area from the landscape point of view. Such water bodies are often regarded as stop over sites to migratory birds to replenish their energy during their long migratory routes (Valasquez and Hockey, 1991). Thus the entire mosaic of wetlands, including coastal and inland, of this area may be taken as one landscape of attraction for waterbirds in which the Karaivetti Lake is a key component.

6.2 Phenology of individual bird visitations Little Grebe, Spotted-billed Pelican, Little Cormorant, Darter, Little Egret, Large Egret, Median Egret, Cattle Egret, Gray Heron, Purple Heron, Black-crowned Night Heron, Indian pond-Heron, Painted Stork, Asian Open bill-stork, Oriental White Ibis, Black Ibis, Glossy Ibis, Eurasian Spoonbill, Gad wall, Northern Pintail,

DISCUSSION

Common Teal, White-breasted Waterhen, Purple Moorhen, Common Coot, Little Ringed Plover, Red-wattled Lapwing, Yellow-Wattled Lapwing, Wood Sandpiper, Common Sandpiper, Whiskered Tern, Little Tern, Small Blue Kingfisher, Lesser Pied Kingfisher, White-breasted Kingfisher, were observed in all the season of both years of study and so they might be regarded as residents of this Lake.

Bar-headed Goose, Spot-billed Duck, Northern Shoveller, Garganey, Common Moorhen, Black-Winged Stilt and Little Stint were not found in the pre-monsoon months of both years. Very low water levels in the Lake characterize in the post- monsoon months, that the birds require very deep water their absence in the post- monsoon might be due to lower water depth (Table. 5.3).

The Indian shag was not found in the pre-monsoon months during the first year of study but extended its stay to the pre-monsoon months during the second year of study. The Indian shag doesn’t require very deep water. This might be the reason for the presence of Indian shag in the pre-monsoon season of the second year.

There were variations in the population peaks the diving birds as the peaks of were observed during January in Little Grebe, Indian shag, and Darter in the first year and during December in Little Grebe, Little Cormorant, Darter and Common Coot in the second year (Vide Fig. 5.49 - 5.53) this might also be due to the difference in the water inflow to the Lake and the monsoon rainfall in the both years (Fig. 3.16).

A few water bird species had definite Phenology in their visitations, the Little Grebe, Little Cormorant, Indian Shag and Common Coot were observed in the monsoon and pre-monsoon months of first year and swimming birds of Gadwall, Bar- headed Goose essentially in the post-monsoon and pre-monsoon season the Bar- headed Goose, Spot-billed Duck, Northern shoveller, Garganey and large wader Common Moorhen in the monsoon and post-monsoon of the both year.

In Black-Winged Stilt and Little Stint were available in the monsoon and post- monsoon of both years, majority of large wader species had the population peaks

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DISCUSSION

during the monsoon. The population density of aerial foragers like Whiskered Tern, Little Tern, Small Blue Kingfisher, Lesser Pied Kingfisher and White-breasted Kingfisher showed an increase during October, November and December, when usefully the water level is high and decrease during August and September, when the water level is receding (Table 5.97).

Thus it is show that monsoon season was the most preferred season for the all water birds. This might be a corollary of higher water depth during monsoon which is important for water birds, and lower water level during the pre monsoon which in usually preferred by the swimming birds like Spotted-billed Pelican, Significance of water level in wetlands is influencing waterbird visitations had also been brought out by earlier reports (Summerleft 1971, Nilsson 1972, leperle 1974, Rundle and Fredrickson 1981, Sayre and Rundle 1984, Muekin and Kadlec 1986, Poysa 1989, Sampath and Krishnamoorthy 1989a, Breininger and Smith 1990, Rostogi and Pathak 1990, Vijayan et al.1990, Nagarajan and Thiyagesan 1996,). However, the role of water depth on waterbird populations in the Lake must be viewed along with the water quality factors discussed in latter section of this text.

6.3 Influence of water quality factors on waterbirds population characteristics All the water quality factors studied were found to significantly influence one or more waterbirds population characteristics (Tables. 5.37 to 5.54). The Literature abounds with reports on the effect of water quality factors on waterbirds in a wetland (Hutchinson, 1957; McMohan, 1967, 1968; Stewart and Kantrud, 1971; Wetzel, 1975; Patterson, 1976; Nilsson and Nilsson, 1978; Swanson et al., 1978; Murphy et al., 1984; Compere and Symoens, 1987; Mephan, 1987; Mittal et al., 1990 and Sampath and Krishnamoorthy, 1990; Sridharan, 2003).

6.3.1 Water Depth Water depth was found to be influenced the density of large waders, small waders and aerial forgers (Table 5.40, 5.41, 5.42). Water depth was found to be an important factor in influencing habit use by migrant Soras and Virginia rails at the Mingo National Wildlife Refuge in Southern Missouri U.S.A (Sayre and Rundle

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DISCUSSION

1984). The dynamics of foraging habitat use by long-legged wading birds was found to vary with respect to water level fluctuation patterns in the Florida Bay (Powell 1987). Importance of water depth in the wetland use had also been documented for Teals by Poysa (1989) and for Cormorants and coots by Rostogi and Pathak (1990). A relationship between the waterbirds habitat use and water level had been reported in the Great Vedaranyam Salt swamps (Sampath and Krishnamoorthy 1989 a) and in the Pichavaram wetlands (Nagarajan and Thiyagesan 1996) as well. Anand (1999) found the water level at the Veeranam Lake, Tamilnadu, southern India was crucial in determining the type of waterbirds that use it, as during the pre-monsoon season when the water level is very low, the Lake was predominantly occupied by the waders while during the monsoon season (when the water level is high) swimming birds becomes the major constituent of the waterbirds population.

Extremely shallow water and adjacent exposed salt water mud were found to be highly attractive to shore birds in manmade impoundments of South Eastern Missouri (Rundle and Fredrickson 1981). Wading bird densities were observed to increase with declining water levels in the coastal impoundments in East - Central Florida. (Breininger and Smith 1990). Conversely deep water has been reported to reduce the availability and accessibility of invertebrate to feeding water flow (Nisson 1972, Leperle 1974, Murkin and Kadlec 1986). Thus the water depth variations are an important factor to reckon with in analyzing waterbirds habitat utilization patterns.

Different regions of Karaivetti Lake viz. A, B and C are of different depths and each region has shown different diversities and densities of various water species / groups (Tables 5.16 to 5.21). This was because there were variations in water depths in different months / seasons (Tables 5.16 to 5.21) offering a variety of water depths. Consequently food (prey) availability and accessibility to different kinds of waterbirds species / groups also might have varied widely and might have acted differently for different waterbirds species / groups. Thus it inferred that the water depth is a crucial factor in the waterbirds visitations and use of the Karaivetti Lake, Instead of desilting to uniform depth throughout the Lake, differential desilting at different parts of the Lake so as to provide a variety of water depth, is to be done. According to Safran et al. (1997) a broad range of water depth used by water flow and relatively restricted

102

DISCUSSION

depth used by waders indicate that water depth can be manipulated to benefit a multitude of waterbirds species. Further, the Lake should not be totally drained for agricultural purposes and at least 2 feet water level is to be maintained in order to support the biodiversity in this sanctuary.

6.3.2 Surface water temperature In the present study shown water temperature influenced positively the density of total waterbirds, diversity of total waterbirds, diversity and richness of large waders (Table 5.37, 5.43, 5.46, 5.52) then the diversity of aerial foragers negatively influenced (Table 5.48), (Sridharan, 2003; Vachanth, 2013) gave result as water temperature influenced negatively the density of total waterbirds. According to Sathe et al., (2001), a large number of ecological processes in the fresh water bodies are influenced by temperature. Graham et al., (1982) has shown that water temperature to regulate photosynthesis in the aquatic ecosystems. Water temperature had been regarded as a limiting factor in the development of zooplankton (Moore, 1978) and to play an important role in controlling the occurrence and abundance of algal diversity (Nazneen, 1980). Sridharan, (2003) found water temperature influenced negatively the density of total waterbirds, swimming birds and small waders and positively the diving birds and large waders. Hoff and Ibara, (1977) reported a close correlation between water temperature and fish abundance and diversity in the Solcum River Estuary, South Eastern, New England. So, it may be inferred that the effect of water temperature and waterbirds might be via its effect on productivity in the wetland concerned. In fact, Blair, (1992) could predict the loon use of aquatic habitats on the basis of surface water temperature. Water and mud temperature entered as significant factors in multiple regression models to predict wader populations in the Pichavaram wetlands (Nirmaladevi, 1994). Since, water temperature is essentially a corollary of atmospheric temperature; the effect of water temperature could also be a reflection of birds response to atmospheric temperature changes. For e.g., cold weather had caused many wild fowls to leave UK during September to March 1980 – 87 (Salmon, 1988). So, a combined effect of both the ambient air temperature (seasonal effects) and surface water temperature might have caused the above relationship between surface water temperature and waterbirds populations found in the Karaivetti Lake.

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DISCUSSION

6.3.3 Water pH Water pH negatively influenced the density, diversity and richness of all waterbirds (Tables 5.39, 5.41, 5.42, 5.44, 5.46, 5.49, 5.50, 5.51 and 5.53) but pH of wetland as an important factor in waterbirds distribution had also been reported earlier (Gibbs et al 1991, Vickery 1991, McNicol and Wayland 1992). According to Odum (1971), pH directly or indirectly affects the production of aquatic organisms. Water acidity was found to influence the broods in unmanaged fresh water wetlands in southern New Brunswick (Petrie and Rogers 1997). According to Bendell and McNicol (1995) pH levels could alter the invertebrate and other prey types and thereby the feeding habits and food selection of waterbirds. Elmberg et al. (1992) found pH and the relative abundances of Gaviidae and podicipedidae were correlated. Acidification in aquatic habitats was found to reduce the piscivorous and non- piscivorous birds mainly by reducing their food supply (Graveland 1990). Muniz (1990) stated that the distribution of fish-eating birds may be influenced by the effects of acidification on the performance of their prey as the distribution of Dipper, a riverine bird, as well as its breeding success, had been restricted due to acidification which had decreased the availability of its macro invertebrate prey. According to Gibbs et al. (1991) low pH typified wetlands used by large bodied piscivores and other waterbirds were associated with more densely vegetated, chemically buffered wetlands. A significance relationship between waterbirds use of wetlands and their pH was also reported by McNicol and Wayland (1992) in the Central and Eastern Maine, U.S.A and in the coastal wetlands of Tamilnadu, Southern India by Nagarajan and Thiyagesan (1996) and Divakaran (2000).

6.3.4 Dissolved Oxygen The dissolved oxygen level was negatively influenced the density, diversity, and species richness of all waterbirds (Table. 5.40, 5.41, 5.43, 5.45, 5.46, 5.49. 5.50, 5.51 and 5.53), (Sridharan, 2003; Vachanth, 2013). According to Wetzel and Likens, (1979), among all the abiotic factors, dissolved oxygen is the most important factor in the fresh water life as it provided valuable information about the biological and biochemical reactions going on in water. Sathe et al., (2001) stated that dissolved oxygen is of great limnological significance as it regulated metabolic processes of

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DISCUSSION

aquatic organisms and indicates the status of water body. According to Wetzel, (1975) dissolved oxygen is very essential for metabolism of all aquatic organisms that process aerobic respiratory biochemistry. Relationship between the variations in the waterbirds population and the dissolved oxygen levels had been reported previously as well (Murphy et al., 1984; Lelek, 1988 and Sampath and Krishnamoorthy, 1990).

6.3.5 Salinity In the present study Salinity negatively influences the density, diversity, and species richness of all waterbirds (Table. 5.37, 5.39, 5.42, 5.43, 5.47, 5.49, 5.50, 5.53, and 5.54). Salinity had been reported to influence to a large extent the succession and dominance of various aquatic organisms (Ramamurthy, 1965). Sridharan, (2003) showed that the salinity influenced the density of diving birds, swimming birds and large water and richness of diving birds and swimming birds. Higher salinities were reported to cause reduction in the prawn and fish diversity and abundances (Ramachandran et al., 1965). An inverse relationship between the wader population density, richness, diversity and salinity was observed in the Pichavaram wetlands by Nagarajan, (1990). The author opined that this might be due to the negative impact of salinity in the food resources of the waders viz. invertebrates and fish populations. In the reclaimed saltpans at the Berg river estuary, South Africa, Velasquez, (1992) observed the quality of such artificial wetlands as foraging sites for shore birds and wading birds depend largely on the abundance of benthic macrofauna which in turn was determined by salinity. Velasquez, (1992) found that the highest foraging densities of waterbirds occurred with salinities of 25-70 and 170-220 ppt at the Berg River estuary, South Africa. Warnoock et al., (2002) reported that the highest numbers and species richness of waterbirds occur with salinities around 140 and 126 ppt, respectively, at San Francisco Bay, USA. Takekawa et al., (2006) also indicated that most waterbirds forage in mid salinity (81-150 ppt) at San Francisco Bay, USA.

6.3.6 Silicates Silicates influenced the diversity and richness of large waders in Karavetti Lake (vide tables 5.46, 5.52). According to Ramachandran et al. (1965) the concentration of silicates along with salinity could influence the composition,

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DISCUSSION

successive and dominance of various aquatic organisms. Waders population diversity measures were reported to be influenced negatively by levels of silicates by Nagarajan (1990) in the Pichavaram wetlands. The author opined that the silicate’s influence on the wader population might be indirect via their impacts on aquatic micro and macro faunal availability and diversity, which are dependent on the productivity of the wetland in which silicates play a crucial role.

6.3.7 Nitrite and Nitrate Nitrite negatively influenced the density, diversity and richness of all water birds, (Table 5.42, 5.48, 5.51, and 5.54). In the present study, Nitrates influenced the density of aerial foragers, diversity of diving birds as well as diversity of aerial foragers, richness of total water birds, swimming birds were positive influenced (Table 5.42, 5.44, 5.48, 5.49, and 5.51). Nitrate and other nutrients are regarded as important limiting factors for various aquatic organisms (Odum 1971, Wetzel and Likens 1979). Nitrate is an important factors for controlling the occurrence and abundance of phytoplankton (Dwivedi and Pandey 2002), as it is an important source of nitrogen for phytoplankton ( Srivastava and Vidyarthi 2002). Anjaneyalu and Vasanthi (1989) observed the phytoplankton abundance in the Peguin fish farm in the periphery of the kolleru, Andhra Pradesh, Indian to be correlated with nitrites and nitrates.

6.3.8 Phosphate The phosphate positively influenced only the richness of aerial foragers (Table 5.54). Density of large waders small waders aerial foragers diversity of water birds swimming birds, large waders (Table 5.39, 5.40, 5.41, 5.42, 5.43 and 5.46).Anjaneyalu and Vasanthi, (1989) observed the phytoplankton abundance in the Penguin fish farm in the periphery of the Lake Kolleru, Andhra Pradesh, India to be correlated with nitrites, nitrates and phosphates. According to Dave et al., (1999) phosphorus was recognized as critical single factor for maintaining fertility of benthic habitat. Phosphorus had been regarded as the major limiting nutrient of water body by Heilman, (1968); Klopaters, (1978) and Brown, (1981). According to (Sridharan, 2003) Phosphate influenced the density of large waders and aerial foragers, diversity

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of small waders and richness of all the waterbirds groups except diving birds. Further phosphate was considered to be the important nutrient limiting the growth of phytoplankton (Welch et al., 1978). A positive correlation between phosphates and algae had been reported by Kramer et al., (1979) and Sarkar et al., (1985). A study of waterbirds habitat relationship on Lake in Sweden by Nilsson and Nilsson, (1978) yielded the total phosphorus as the best predictor waterbirds density and the authors concluded the waterbirds density was directly related to the Lake productivity as mediated by phosphate level. At the Scottie-Despair Creek Wetlands, U.S.A. Murphy et al., (1984) had also found the nitrites and phosphates to influence the water flow populations. Merendino et al., (1992, 1993) found the wetland fertility to apparently influence the abundance and distribution of Mallards and Black Ducks in central Ontario.

6.3.9 Sulphate The sulphate influenced only the diversity of swimming birds (Table 5.45) and negatively of diving bird, large waders aerial foragers, diversity of diving birds, (Table 5.44) small waders, aerial forgers, richness of diving birds, swimming birds, large waders and small waders, (Table 5.38, 5.40, 5.42, 5.44, 5.47, 5.48, 5.50, 5.51, 5.52, and 5.53). According to Zulfiqar Ali, (2005) sulphates are found appreciably in all natural water, particularly those with high salt content. Besides pollution from domestic sewage, biological oxidation of reduced sulphur species also adds to sulphate content. Soluble in water, it imparts hardness with other cations.

6.3.10 Calcium Calcium of the Lake water negatively influences the density of diving birds, (Table 5,.38), swimming birds (Table 5.39), density of aerial forgers (Table 5.42) diversity of waterbirds (Table 5.43) and diving birds (Table 5.44) and positively influenced the density of large waders (Table 5.40) small waders (Table 5.41) diversity of small waders (Table 5.47), species richness of waterbirds, swimming birds (Table 5,51), large waders (Table 5.52), small waders, (Table 5.53). All the ions dissolved in the Lakes water are vital to the health of the living organisms in the Lake. For example, calcium is essential for all the cell processes of plants and animals and

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serves as a structural component for the shells of invertebrate animals like molluscs. The geology of the watershed and the chemical composition of the precipitation are extremely important. On its way to the Lake, water is modified mainly by rock weathering. This leads to an enrichment of bivalent cations, especially calcium. The increased content of calcium permits uptake of carbon dioxide from the atmosphere.

6.3.11 Chloride In the present study chloride of the Lake water negatively influence the density of swimming birds, small waders, diversity of swimming birds, small waders aerial forgers, richness of Diving bird, large waders, aerial forgers (Table 5.39, 5.41, 5.45, 5.47, 5.48, 5.50, 5.52, 5.54). Zulfiqar Ali, (2005) states that the presence of chlorides in natural water can mainly be attributed to dissolution salt deposits in the form of ions (Cl-). Otherwise, high concentrations may indicate pollution by sewage. It is the major form of inorganic anions in water for aquatic life. High chloride content has a deleterious effect on agricultural plants.

6.4 Influence of bottom mud factors on waterbirds population parameters In the present study, Soil depth positively influences the density of swimming birds, large waders, small waders, aerial forgers, diversity of waterbirds, diversity of swimming bird and large waders, (Tables 5.39, 5.40, 5.41, 5.42, 5.43, and 5.46). Soil pH positively influenced only in richness of large waders (Table 5.52) soil nitrogen influenced negatively the density of aerial forgers (Table 5.42) diversity of swimming birds (Table 5.45) richness of large waders (Table 5.52) aerial forgers (Table 5.54). The soil phosphorus negatively influenced in the richness of waterbirds, large waders small waders only (Table 5.45, 5.45). Similarly, wader density measures in the Pichavaram wetlands viz. density, diversity and richness were found to have significant correlations with mud pH, nitrogen, phosphorus and electrical conductivity, the factors other than electrical conductivity being positive in influence (Nagarajan, 1990).

According to Odum, (1971), the nutrients, nitrogen and phosphorus are the major limiting factors of life. Murphy et al,. (1984) had also found the levels of

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nitrites and phosphorus of bottom sediments to influence the water flow population. Nagarajan, (1990) also found a positive correlation between mud nitrogen and phosphorus levels and wader population richness and diversity and opined that these factors play a vital role in delineating animal distribution and abundance.

Some invertebrate groups such as snails (Gastropod) clams (Pelecypod) leeches (Hirudinea) and may flies (Ephemeroptera) were reported to be highly sensitive to mud pH changes (Bell, 1971; (Okland, 1980; Raddum, 1980 and Eilers et al., 1984). Standing crop and diversity of zoobenthos had been reported to be reduced in the streams along with bottom sediment pH (Hall and Licknes, 1980 and Hall et al., 1980). Haines, (1981) also reported the benthic invertebrates to be influenced by bottom soil pH changes. Species richness of macro invertebrate declined in Norweigian Lakes as the soil pH declined (Okland and Okland, 1980). Hendrey et al., (1976) regarded the benthic invertebrates could be less diverse in acidified wetlands, reducing the variety and abundance of prey available to water flows.

Different regions of the Karaivetti Lake had different soil textures (vide section). This was supported by the result obtained by Sridharan, (2003). According to Gupta, (1996) bottom sediment nature could influence its macro-invertebrate population. So, the variations in waterbirds populations with regard to different regions of the Lake might also be due to the impact of the differences in bottom sediment characteristics in different areas of the Lake on the benthic invertebrate populations and their distribution. The fact that the benthic invertebrates are the staple food items of many wader species such as Egrets, Herons, Storks, Plovers, Sandpipers etc. had been well documented (Ali and Ripely, 1968, 1980; King et al., 1978 and Sivakumar, 1990), and so the effect of soil factors on waterbirds might be indirect via their influence on the availability and abundance of benthic macroinvertebrates which are important food items for waterbirds that inhabit a wetland. This is further elucidated in the following section.

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6.5 Influence of Biological factors in waterbirds population parameters Positive plankton availability in the bottom and positive influenced only the richness of aerial foragers of waterbirds (Table 5.54) (Vachanth, 2013) noted that the plankton availability positively influenced the species richness and diversity of total waterbirds (Sridharan, 2003). Observed that plankton availability influenced the density of all water flow groups except aerial foragers and diversity of swimming birds. Relationship between plankton abundance and waterbirds distribution and abundance had been reported by Jesperson (1929). Murphy, (1936) and Kullenberg, (1946). Pillai, (1968) observed the abundance of plankton indirectly influence the fisheries and the Bombay Duck Herpodon neterus in the Bombay coastal water and had stated the “the amount of plankton available may not have a direct and immediate effect on the fisheries but it undoubtedly influence indirectly the fish abundance, the larvae, post larvae and juveniles of the demersal fishes depend upon the planktonic organisms for their nourishment”. Report of Bapat and Bal, (1950, 52) also corroborated the relationship between fish abundance and plankton availability. Thus it can be reasonably concluded that the influence of plankton availability on the waterbirds density could also be indirect via their influence on fish availability.

The benefit molluscan biomass of the Lake soil negatively influenced the density (Table 5.40), diversity (Tables 5.45, 5.46) and species richness (Tables 5.49, 5.51) of total waterbirds (Vachanth, 2013) recorded in their result Benthic molluscan biomass of the Lake soil negatively influenced the density, diversity and species richness of total waterbirds. Availability of worms in the bottom and influenced negatively in the density, diversity and species richness of total waterbirds (Table 5.42, 5.42, 5.44, 5.45, 5.48, 5.49, 5.50, 5.51, 5.52, 5.53). The role of food abundance in waterbirds densities had been well established (McKnight and Low, 1969; Schroeder, 1973; Swanson and Mayer, 1973; Hoffman et al., 1981; Kaminski and Prince, 1984; Murkin et al., 1982; Hafner et al., 1982; Hafner et al., 1986 and Parker et al., 1992). Influence of invertebrate prey taxa on water flow was brought out by McNicol and Wayland, (1992) as well. According to Parker et al., (1992) abundances of aquatic invertebrates was most important in influencing the use of wetlands by water flowl. According to Peterson and Exo, (1999) evaluation of the importance of

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invertebrate communities at feeding sites of waders and water flows is not only fundamental in understanding their feeding ecology, but also enables the evaluation of their habitat use. Hanson and Butler, (1994) also found the population of migratory diving ducks to change owing to changes in macro invertebrates. Safran et al., (1997) had stated that the ecologies of waterbirds are closely related to the distribution and abundance of food resources and for many species of water flows and shore birds, benthic invertebrates are an important dietary component that influences the habitat selection in smaller bodied waterbirds such as Dowitchers, Dunlin, Sandpipers, Northern Shoveller and American Green Winged Teal.

6.6 Other factors that influence waterbirds population parameters Thus, from the foregoing discussion, it can be concluded that the variation in the water and bottom sediment quality and the availability of different prey determine the distribution, abundance and diversity of waterbirds in the Karaivetti Lake during the study period. This was in accordance with the report of McNicol and Wayland, (1992) who found the distribution of water flow broods in Sudbury area Lakes in Ontario to be related to fish, macro invertebrates and water chemistry. However, the actual habitat use by birds, in addition to responding to cues including vegetation structure and invertebrate numbers, can also be affected by various other factors such as population density, number and density of potential competitors and the occurrence of predators (Fretwell and Lucas, 1970; Wiens, 1989 a, b and Nummi et al., 1994). Further birds like dabbling ducks form a well defined grid (Poysa, 1983a) and hence patterns amongst such assemblages may arise from competitive interactions (Wiens, 1989a) as well. According to Nummi et al., (1994) the relative importance of competition versus habitat suitability in determining the distribution of waterbirds needed to be studied in detail. They found the waterbirds density was correlated with the amount of food, density of congenerics and number of congenerics. Hoyer and Canfield, (1994) used data from 46 Florida Lakes to determine the relationships between bird abundance (numbers and biomass) and species richness and Lake trophic status, Lake morphology and aquatic macrophytic abundance. They found Lake trophic status was the major factor influencing waterbirds abundance and species richness in these Lakes and bird abundance remained relatively stable as

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macrophyte abundance increased; but birds that use open-water habitats (e.g. Double Crested Cormorants Phalacrocorax auritus) were replaced by species that use macrophyte communities (e.g. Ring-necked Duck Aythya collaris). According to Goutner and Furness, (1998) waterbirds population changed in different wetlands of Euros Delta, Greece depending on water level, habitat disturbance and poaching pressure in adjacent wetlands. So, an evaluation of these factors on the waterbirds population in the Karaivetti Lake should be taken as a future line of research.

6.7 Threats and conservation issues Four villages with a total human populations of 16,099 surround the Lake. The socio-economic surveys revealed that the Lake is playing a vital role in the livelihood of the human population of these villages. Agriculture is the main occupation of the people of these villages and they greatly depend on the Lake for irrigation, cattle washing etc. Thus there exists a conflict between wildlife and people in and around this Lake.

Various kinds of threats such as excessive fishing, poaching of birds, cattle grazing, fuel wood collection, encroachment, siltation, weed invasion and pollution were identified for the Lake during the study period. Earlier Wolstencroft et al., (1989) reported that these were the major threats around Asia in various wetlands. Thiyagesan and Nagarajan, (1995) listed similar threats as a result of various developmental projects to the coastal wetlands of Tamilnadu, Southern India. Divakaran, (2000) also noticed majority of these threats in different islands of Gulf of Mannar, Southern India, causing great havoc on bird life there as well as same (Sridharan, 2003) and (Vachanth, 2013) observed the same threats in Vaduvoor and Kallaperambur respectively.

6.7.1 Conflicts with irrigation The Lake is used for irrigation purposed by the surrounding villagers. The farmers raise three crops (Samba, Kuruvai and Thaladi) of paddy every year in Karaivetti Lake ayacut area. In the ayacut area the maintenance of channels was very poor, which causes loss of water. This injudicious and callous use of the Lake’s water

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for irrigation reduces the water level of the Lake often to levels detrimental to the waterbirds. The water use for irrigation from this Lake is without any planning and quite unmindful of bird life. Such an action results in conflicts of interests between local agriculturalists and forest department officials and conservationists. Further, in standing water subject to rapid fluctuation in water level, the shore line experiences similar changes to that of abstracted rivers i.e., there is a great reduction in macrophyte vegetation and in invertebrates which cannot withstand desiccation. Consequently the shallow littoral areas of abstracted Lakes, normally the riches zones, have poor production and their community changes (Maitland, 1990). However, Nagarajan and Thiyagesan, (1996) noticed that the agricultural lands adjacent to the wetlands (such as Lakes and mangroves) acted as potential foraging ground for wide variety of waterbirds. So, a compromising formula that caters to the needs of both the farmers and the birds needs be the devised by organizing awareness campaigns and workshops in this regard.

6.7.2 Water quality The water quality of the Lake is not good for drinking because of having high guano deposition .So the usefulness of the Lake for drinking water is highly reduced. A negative impact of guano deposition on water quality was also described earlier by Balamurali, (1995) for the Udhayamarthandapuram Lake, Southern India. Dredging the Lake is urgently required to improve the water quality.

6.7.3 Fishing The Lake is a very good fishery resource. Professional fishing people are living around this Lake. They fix their fishing nets during night hours and collect the trapped fishes during the early morning hours. During the rainy season the fishermen use fish baits like paddy husk, rice and cow dung with oil cakes etc. to attract and catch fishes. They catch all sizes of fish (juveniles, fingerlings, sub adults and adult fishes) in all seasons. Earlier Charkrabarthi, (1978) also reported this problem in the swamps of Sunderbans. The larger fishes are consumed or sold immediately, but the smaller ones are dried and stored for future sale. Thiyagesan and Nagarajan, (1995) reported the negative impacts of the over Exploitation of aquaculture and fisheries

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resources in inland and coastal wetlands of the East coast of India on their bird life. So, the over exploitation of the fishers resources of this Lake should be prevented. The Fisheries Department should initiate immediate steps for the sustainable use of this Lake in this regarded. In Pakistan, fisheries department without the consent of wildlife department auction the right of fishing in Lakes. Many wetlands sanctuaries are also auctioned, which leads to a heavy mortality of water flow during the migratory season (Khurshid, 1991, Sridharan, 2003 and Vachanth, 2013).

6.7.4 Siltation During the rainy season the eroded soil from catchments get dumped into the Lake area. This is because of the mismanagement of the inlet of the Lake. This siltation reduces the water holding capacity of the Lake. Siltation, a serious problem, results in low water depth and thereby facilitating the invasion of weed patches. So the Lake must be desilted immediately and the weeds should be cleared either manually or by application of weedicide. Such a step will increase the irrigation potential of the Lake and improve the condition for the wild life, especially waterbirds. Further these Lakes have immense potentials for fisheries development and when they are dredged and the water quality is properly maintained, a higher fish production is ensured. Studies by Anand, (1999) in the Veeranam Lake, Southern India have also proved that desiltation was not only useful in terms of improvement of irrigation and fisheries potential, but also in increase of wildlife diversity and use.

Very high amounts of nutrient loading due to heavy bird use also increases with decrease in water level. When we also take into account the lower water depths due to siltation in the Lake, the situation becomes graver. According to Vallenweider, (1968) water bodies with less water depths would be more affected by these eutrophication problems. Balamurali, (1995) also suggested the removal of nutrient laden sediment by dredging in the Udhayamarthandapuram Lake, to improve the habitat for birds. However, according to Sager, (1976), for the dredging to produce lasting effects on water quality, other factors such as extent of nitrogen and phosphate loading, basin morphometry, retention rate and flushing rate should also be

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considered. So, data on these aspects should be collected and used in planning the desilting operations.

6.7.5. Weed invasion Ipomoea (weed) invasion was very high in the Lake. Anand, (1999) observed that the Ipomoea invasion changed the water quality and reduced the primary production and nutrient cycle in the Veeranam Lake, Southern India. So, it should be removed totally from the Karaivetti Lake.

6.7.6. Encroachment The neighbouring land owners of the Lake area were found to have encroached the Lake for farming. This is a severe threat to the Lake and shoned be prevented. Encroachment of the Lake area by conversion into paddy fields is to be sorted out by an integrated approach by the Government Departments viz. Forest Department, Revenue Department and Public Works Department etc. and by involving local panchayats by convincing the people about the environmental significance of the Lake.

6.7.7. Poaching of birds Poaching of birds by the surrounding villagers were by many methods viz. shooting, using nylon noose etc. for these nylon noose captures, they use food baits; like molluscs, fishes and frogs for aquatic carnivorous birds and fruits and grains for terrestrial frugivorous and gramniovorous birds. The fishing nets also trapped the birds some times, which were collected by the villagers and sold in the market. Apart from the meat they sell their feathers also for ornamental purposes. Duck varieties (Garganey, Cotton teal, Northern Shoveller, Pochard, Common teal) diving birds (Cormorant, Coot, Grebe) and all large waders (Egrets, Herons, Storks) were the major birds poached. Wolstencroft et al., (1989) also reported that the poaching was major threat in the wetlands of Indian sub continent. Lampio, (1982) stated that water flow have been hunted in many countries for thousands of years, and the customs and traditions that have grown up during this period differ greatly, sometimes because of varying circumstances but sometimes for no obvious reason. Lampio, (1982) also

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quotes that, it has often been said that the disturbance caused by hunting is more harmful than direct killing. Appointment of more staff and constant vigil by the Forest Department is urgently needed to stop this menance.

6.7.8. Cattle grazing The Lake area is used by surrounding villagers for grazing their domestic live stocks especially during summer. This intensive cattle grazing could result in breaking the nutrient cycle of the Lake. Further, the trampling of cattle could harden the soil surface and reduce the aeration of the Lake. Earlier Meganathan, (2002) also expressed similar apprehensions for the fresh water Lakes of Tamilnadu, Southern India. The local people must be educated in this aspect.

6.7.9. Cattle washing The surrounding village people are using the Lake for washing their live stocks. The live stocks are allowed freely to drink and bathe in this Lake. This cattle washing pollutes the water and acts as a detergent for waterbirds as described in the earlier section (5.4). So, cattle washing should be prohibited in the Lake.

6.7.10. Fuel wood collection Another threat is wood collection for fuel by the local villagers from the Lake and its immediate surroundings. Acacia, Zizypus and Prosophis were the plants cur for fuel wood. They are the roosting and nesting places for birds like Openbill Storks and Night Herons. Dickson et al., (1995) regarded that protection of vegetation along the sides of the wetlands are important to retain water quality and accommodate wildlife including breeding birds, in eastern Texas, U.S.A. So, these vegetation, especially at the northern region of the Lake must be given full attention and protection to prevent human disturbances and poaching.

6.7.11. Pollution Pollution from the agricultural runoff from the nearby villages and agricultural practices is another major threat to the faunal diversity in the Lake as approximately 2750 tons of fertilizers and 3200 liters of pesticides are used annually for agricultural

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purposes in the catchment area of the Lake (vide tables). Dumping of unwanted bottles, plastic covers and domestic sewage into the Lake was also noticed during the study period. Austin, (1985), Schnick et al., (1986) and Maitland, (1989, 1990), Kjetil Bevanger, 1998., highlighted that such environmental pollution could cause severe damages to the water quality and thereby to the wetland’s biodiversity. So, the Agriculture Department should take necessary steps to reduce the use of pesticides and educate the farmers on the importance of organic farming. Government and NGO’s must undertake awareness campaigns about the proper methods of solid waste disposal.

6.8. Management recommendations Overall, ecosystem-based approach is needed in wetland management with various targets, including management with the goal of providing waterbirds habitat. This requires integrated knowledge of the entire wetland ecosystem (including hydrology, geology, agrology, botany, ornithology) with considering multiple spatial scales, temporal variability and the diverse habitat requirements of waterbirds (Parsons, 2002; Anteau and Afton, 2008; Euliss et al., 2008 and King et al., 2009).  Since this Lake has already been declared as a sanctuary encroachment of the Lake must be prevented, this can be effectively and easily achieved with strict enforcement of law and constant vigil.  Water quality and water level of the Lake should be maintained to make the needs of both agriculture and wild life.  Total removal of the weed Ipomea shend is done.  Desiltation of the Lake should be done immediately with adequate care and planning to provide a variety of depth levels.  Advices must be given to reduce pesticide pollution in the agricultural fields of the Lake.  There are major resource for developing this Lake as a good tourist attracting place since the Lake is situated nearer to other areas such as Point Calimere wildlife sanctuary and other cultural heritages nearby (such as Thiruvaiyaru, Thanjavur, Ariyalur and Thiruchirappali). This step would increase the in tervention of income to the local people from ecotourism.

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 Cattle grazing and cattle washing in the Lake should be prohibited.  Steps must be taken by the Forest Department to prevent poaching of birds. Poaching the nomadic must be stopped by effective laws, such as better vigil and weaning of nomadic from wildlife hunting by educating them and providing alternative livelihood.  A campaign must be made useful for the local public to realize the importance of the Lake with their wild life values and need to utilize them judiciously and sustainably for mutual benefit.  Electrocution and collision of birds with high voltage power lines run near the Lake are the existing threats to the avifauna of Karaivetti. A dead Spotted - billed Pelican was recorded on the power line in January 2007 and local people also confirmed the happening of such incidents. So, a combined approach and with social co-operation resulting in the strict use of this fresh water resource forwarding to improved qualities of living surrounding this Lake and increased facilities are recommended.

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7. SUMMARY

Density, richness, diversity and Phenology of visitations of waterbirds in Karaivetti Lake, Tamilnadu, Southern India was studied during October 2010 to September 2012 and the relative importance of water quality and soil factors and the availability of plankton and benthic macro fauna on the waterbirds population parameters were assessed. An assessment of socio-economic importance of the lake and the threats and conservation issue pertaining to the lake were also made.

Forty three species of waterbirds were recorded in the Karaivetti lake during the study period. Among them one species belongs to Poeicipediformes, four species to Pelecaniformes, 14 species to Ciconiiformes, seven species to Anseriformes, four species of Gruiformes, 10 species to Charadriiformes and three species to Coraciiformes, These birds were ecologically classified into five groups namely, Divers (Little Grebe, Tachybaptus ruficollis, Little Cormorant, Phalacrocorax niger, Indian Shag, Phalacrocorax fuscicollis, Darter, Anhinga melanogaster, Common Coot, Fulica atra), Swimming Birds (Spotted - billed Pelican Pelecanus philippensis, Gadwall, Anas strepera, Bar-headed Goose, Anser indicus, Northern Pintail, Anas acuta, Common Teal, Anas crecca, Spot-billed Duck , Anas poecilorhyncha, Northern Shoveller, Anas clypeata, Garganey, Anas querquedula), Large waders (Little Egret, Egretta garzetta, Large Egret, Casmerodius albus, Median Egret, Mesophoyx intermedia, Cattle Egret, Bubulcus ibis, Grey Heron, Ardea cinerea, Purple Heron, Ardea purpurea, Black-crowned Night –Heron, Nycticorax nycticorax, Indian Pond- Heron, Ardeola grayii, Painted Stork, Mycteria leucocephala, Asian Openbill – Stork, Anastomus oscitans, Oriental White Ibis, Threskiornis melanocephalus, Black Ibis, Pseudibis papillosa, Glossy Ibis, Plegadis falcinellus, Eurasian Spoonbill, Platalea leucorodia, Common Moorhen, Gallinula chloropus, Purple Moorhen Porphyrio porphyrio), Small Waders (White - breasted Waterhen, Amaurornis phoenicurus, Pheasant - tailed Jacana, Hydrophasianus chirurgus, Little Ringed Plover, Charadrius dubius, Black -Winged Stilt, Himantopus himanotopus, Red- watt led Lapwing, Vanellus indicus, Yellow -wattled Lapwing, Vanellus malabaricus, Wood Sandpiper, Tringa glareola, Common Sandpiper, Actitis hypoleucos, Little

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Stint, Calidris minuta), and Aerial Foragers (Whiskered Tern, Chlidonias hybridus, Little Tern, Sterna albifrons, Small Blue Kingfisher, Alcedo atthis, Lesser Pied Kingfisher, Ceryle rudis, White-breasted Kingfisher, Halcyon smyrnensis).

Among the birds observed in the lake the Spotted - billed Pelican, Bar-headed Goose, Darter, Painted stork and White ibis are under, “Near threatened” category of the classification by Birdlife International 2001.

Little Grebe, Spotted-billed Pelican, Little Cormorant, Darter, Little Egret, Large Egret, Median Egret, Cattle Egret, Gray Heron, Purple Heron, Black-crowned Night Heron, Indian pond-Heron, Painted Stork, Asian Open bill-stork, Oriental White Ibis, Black Ibis, Glossy Ibis, Eurasian Spoonbill, Gad wall, Northern Pintail, Common Teal, White-breasted Waterhen, Purple Moorhen, Common Coot, Little Ringed Plover, Red-wattled Lapwing, Yellow-Wattled Lapwing, Wood Sandpiper, Common Sandpiper, Whiskered Tern, Little Tern, Small Blue Kingfisher, Lesser Pied Kingfisher, White-breasted Kingfisher, were observed in all the season of both years of study and so they might be regarded as residents of this lake.

The population peaks diving birds were observed during January in Little Grebe, Indian shag, and Darter in the first year and during December in Little Grebe, Little Cormorant, Darter and Common Coot in the second year. A few water bird species had definite Phenology in their visitations, the Little Grebe, Little Cormorant, Indian Shag and Common Coot were observed in the monsoon and pre-monsoon months of first year and swimming birds of Gad wall, Bar-headed Goose essentially in the post-monsoon and pre-monsoon season the Bar-headed Goose, Spot-billed Duck, Northern shoveller, Garganey and large wader Common Moorhen in the monsoon and post-monsoon of the both year. Small waders of Black-Winged Stilt and Little Stint in the monsoon, and post-monsoon of both years, majority of large wader species had the population peaks during the monsoon. The population density of aerial foragers like Whiskered Tern, Little Tern, Small Blue Kingfisher, Lesser Pied Kingfisher and White-breasted Kingfisher showed an increase during October,

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November and December, when usefully the water level is high and decrease during August and September, when the water level is receding.

The water quality factors studied included surface water temperature, pH, dissolved oxygen, salinity, nitrite, nitrate, phosphate, silicate, calcium, chloride and sulphate. The bottom soil parameters studied included mud electrical conductivity, soil pH, nitrogen, phosphorus and potassium. All the water quality and soil quality variable showed month-wise, season-wise, year-wise variations and significantly influenced one or more waterbird population characteristics, as inferred from the multiple regression models developed. Water depth was found to be influenced the density of large waders, small waders and aerial forgers. The water temperature influenced positively the density of total waterbirds, diversity of total waterbirds, diversity and richness of large waders. Water pH negatively influenced the density, diversity and richness of all waterbirds. The dissolved oxygen level was negatively influenced the density, diversity, and species richness of all waterbirds. Salinity negatively influences the density, diversity, and species richness of all waterbirds. Nitrite negatively influenced the density, diversity and richness of all water birds. Nitrates influenced the density of aerial foragers, diversity of diving birds as well as diversity of aerial foragers, richness of total water birds, swimming birds were positively influenced. The phosphate influenced positively only the richness of aerial foragers. The sulphate influenced only the diversity of swimming birds. Calcium influenced positively the density of large waders small waders diversity of small waders, species richness of water birds, swimming birds, large waders, small waders. Chloride of the lake watershed negative influence the density of swimming birds, small waders, diversity of swimming birds, small waders aerial forgers, richness of Diving bird, large waders, aerial forgers.

Soil depth positively influences the density of swimming birds, large waders, small waders, aerial forgers, diversity of water birds, diversity of swimming bird and large waders. The Soil pH positively influenced only in richness of large waders. Soil nitrogen influenced negatively the density of aerial forgers, diversity of swimming birds, richness of large waders and aerial forgers. The soil phosphorus negatively influenced in the richness of waterbirds, large waders small waders only.

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SUMMARY

It was inferred that the physico-chemical features of the lake water and sediment influenced the productivity, availability and accessibility of the prey item and thereby the waterbird population characteristics of the lake. The biological parameters studied included plankton volume, biomass of annelid worms and biomass of benthic molluscs, all of which varied significantly month-wise, season-wise and year-wise. Multiple regression analysis showed that Plankton availability in the bottom mud positive influenced only the richness of aerial foragers of water birds. The availability of worms in the bottom mud and benefit molluscan biomass of the lake soil negatively influenced the density, diversity and species richness of total water birds.

Thus it was concluded that the variations in the water and sediment quality and the availability of different prey items determined the variations in the distribution, abundance and diversity of waterbirds in the Karaivetti lake during the study period. Socio-economic surveys revealed that the lake is playing a vital role in the livelihood of the human population of five villages with 5,700 people that surround the lake. Agriculture is the main occupation of the people of these villages and they greatly depend on the lake for irrigation, cattle washing etc. Thus there exists a conflict between wildlife and human in and around this lake.

Major threats recorded were conflicts with irrigation, water quality, fishing, siltation, weed (Ipomoea) invasion, encroachment, poaching of birds, cattle grazing, cattle washing, fuel wood collection and agricultural pollution. The consequences of these threats on the waterbirds on this lake have been discussed and management suggestions for the conservation and sustainable use of the lake and its resources have been given. The management suggestions include proper maintenance of water quality, desilting, weed removal, prevention of encroachment, cattle grazing and cattle washing, prevention of pesticide pollution and educating the public by awareness campaigns. The lake has high potentials for ecotourism, which should be exploited.

122

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XXXIII

INTRODUCTION

REVIEW OF LITERATURE

STUDY AREA

METHODS

OBSERVATIONS &RESULTS

DISCUSSION

SUMMARY

REFERENCES

APPENDICES

PUBLICATIONS