Impact of Anthropogenic Stressors on Marine Benthos

CONTENTS

GENERAL INTRODUCTION

Chapter I STUDY AREA AND SAMPLING DESIGN
1.1 Study sites
1.2 Duration of the study
1.3 Sampling Design

Chapter II HYDROLOGY
2.1 Introduction
2.2 Review of Literature
2.3 Materials and Methods
2.4 Statistical Analysis
2.5 Results
2.6 Discussion

Chapter III SEDIMENTOLOGY
3.1 Introduction
3.2 Review of Literature
3.3 Material and Methods
3.4 Statistical Analysis
3.5 Results

Chapter IV HEAVY METALS
4.1 Introduction
4.2 Review of Literature
4.3 Material and Methods
4.4 Statistical Analysis
4.5 Results
4.6 Discussion

Chapter V POLYAROMATIC HYDROCARBONS(PAHs) 237-277
5.1 Introduction
5.2 Review of Literature
5.3 Materials and Methods
5.4 Statistical Analysis
5.5 Results
5.6 Discussion

Chapter VI MACROBENTHIC INVERTEBRATE ASSEMBLAGES 278-443
6.1 Introduction
6.2 Review of Literature
6.3 Materials and Methods
6.4 Statistical Analysis
6.5 Results

LIST OF TABLES

1.1 Locations, Latitudes & Longitudes of study Sites

2.1 Descriptive statistics for hydrological parameters (SW) along Site 1 during 2013­14

2.2 Descriptive statistics for hydrological parameters(SW) along Site 2 during 2013­14

2.3 Descriptive statistics for hydrological parameters(SW) along Site 3 during 2013­14

2.4 Descriptive statistics for hydrological parameters(SW) along Site 4 during 2013­14

2.5 Descriptive statistics for hydrological parameters(SW) along Site 1 during 2014 -

2.6 Descriptive statistics for hydrological parameters(SW) along Site 2 during 2014 -

2.7 Descriptive statistics for hydrological parameters (SW) along Site 3 during 2014­15

2.8 Descriptive statistics for hydrological parameters (SW) along Site 4 during 2014 -

2.9 Descriptive statistics for hydrological parameters(BW) along Site 1 during 2013 -

2.10 Descriptive statistics for hydrological parameters(BW) along Site 2 during 2013 -

2.11 Descriptive statistics for hydrological parameters(BW) along Site 3 during 2013 -

2.12 Descriptive statistics for hydrological parameters(BW) along Site 4 during 2013 -

2.13 Descriptive statistics for hydrological parameters(BW) along Site 1 during 2014 -

2.14 Descriptive statistics for hydrological parameters(BW) along Site 2 during 2014 -

2.15 Descriptive statistics for hydrological parameters(BW) along Site 3 during 2014 -

2.16 Descriptive statistics for bottom water hydrological parameters along site 4 during 2014 -15

2.17 Comparison between seasonal and site wise variations on hydrological parameters during 2013-14

2.18 Comparison between seasonal and site wise variations on hydrological parameters during 2014-15

2.19 Multivariate tests for seasonal and site wise variations in hydrological parameters during 2013-14

2.20 Multivariate tests for seasonal and site wise variations in hydrological parameters during 2014-15

2.21 Multivariate tests for comparison of variations in seasons, sites and years on hydrological parameters during 2013-15

2.22 Correlation matrix between hydrological parameters along Site 1 during 2013-14

2.23 Correlation matrix between hydrological parameters along Site 2 during 2013-14

2.24 Correlation matrix between hydrological parameters along Site 3 during 2013-14

2.25 Correlation matrix between hydrological parameters along Site 4 during 2013-14

2.26 Correlation matrix between hydrological parameters along Site 1 during 2014-15

2.27 Correlation matrix between hydrological parameters along Site 2 during 2014-15

2.28 Correlation matrix between hydrological parameters along Site 3 during 2014-15

2.29 Correlation matrix between hydrological parameters along Site 4 during 2014-15

3.1 Descriptive statistics for sedimentological parameters along study sites during 2013 -

3.2 Comparison between seasonal and sitewise 163 variations on Sedimentological parameters along study sites during 2013-14

3.3 Descriptive statistics for Sedimentological 165

parameters along study sites during 2014 -

3.4 Comparison between seasonal and sitewise variations on Sedimentological parameters along study sites during 2014-15

4.1 Descriptive statistics for heavy metals (SW&BW) along Site 1 during 2013-14

4.2 Descriptive statistics for heavy metals (SW&BW) along Site 2 during 2013-14

4.3 Descriptive statistics for heavy metals (SW&BW) along Site 3 during 2013-14

4.4 Descriptive statistics for heavy metals 194 (SW&BW) along Site 4 during 2013-14

4.5 Comparison between seasonal and sitewise variations on heavy metals (SW&BW) during 2013-14

4.6 Descriptive statistics for heavy metals (SW&BW) along Site 1 during 2014-15

4.7 Descriptive statistics for heavy metals (SW&BW) along Site 2 during 2014-15

4.8 Descriptive statistics for heavy metals (SW&BW) along Site 3 during 2014-15

4.9 Descriptive statistics for heavy metals (SW&BW) along Site 4 during 2014-15

4.10 Comparison between seasonal and sitewise variations on heavy metals (SW&BW) during 2014-15

4.11 Descriptive statistics for heavy metals in sediment along study sites during 2013-14

4.12 Comparison between seasonal and site wise variations on sediment heavy metals along study sites during 2013-14

4.13 Descriptive statistics for heavy metals in sediment along study sites during 2014-15

4.14 Comparison between seasonal and site wise variations on sediment heavy metals along study sites during 2014-15

4.15 Maximum Permissible Limit (MPL) of heavy metals according to International standards

5.1 Toxicity equivalency Factors (TEFs) for minimum required carcinogenic PAHs (cPAHs)

5.2 Descriptive statistics for PAH (SW&BW) along Site 1 during 2013-14

5.3 Descriptive statistics for PAH (SW&BW) along Site 2 during 2013-14

5.4 Descriptive statistics for PAH (SW&BW) along Site 3 during 2013-14

5.5 Descriptive statistics for PAH (SW&BW) along Site 4 during 2013-14

5.6 Comparison between seasonal and site wise variations on PAHs during 2013-14

5.7 Descriptive statistics for PAH (SW&BW) along Site 1 during 2014-15

5.8 Descriptive statistics for PAH (SW&BW) along Site 2 during 2014-15

5.9 Descriptive statistics for PAH (SW&BW) along Site 3 during 2014-15

5.10 Descriptive statistics for PAH (SW&BW) along Site 4 during 2014-15

5.11 Comparison between seasonal and site wise variations on PAHs along study sites during 2014-15

5.12 Descriptive statistics for sediment PAH along study sites during 2013-14

5.13 Comparison between seasonal and site wise variations on sediment PAH during 2013­14

5.14 Descriptive statistics for sediment PAH along study sites during 2014-15

5.15 Comparison between seasonal and site wise variations on sediment PAH during 2014­15

5.16 USA EPA Priority List of PAHs

5.17 Seasonal Variation of 16 PAHs (ng/L) of SW from the study sites

5.18 Seasonal Variation of 16 PAHs (ng/L) of BW from the study sites

5.19 Seasonal Variation of 16 PAHs (ng/g) of sediment from the study sites

5.20 Toxicity Equivalency Factors (TEFs) and toxic benzo [a] pyrene equivalent (TEQ)for PAHs at Site 1 (SW, BW and Sediment)

5.21 Toxicity equivalency Factors(TEFs) and toxic benzo[a]pyrene equivalent (TEQ)for PAHs at Site 2(SW, BW and Sediment)

5.22 Toxicity equivalency Factors(TEFs) and toxic benzo[a]pyrene equivalent (TEQ)forPAHs at Site 3 (SW, BW and Sediment)

5.23 Toxicity equivalency Factors(TEFs) and toxic benzo[a]pyrene equivalent (TEQ)for PAHs at Site 4 (SW, BW and Sediment)

5.24 PAHs ratio along study sites (SW, BW and Sediment)

5.25 Sediment PAH concentrations compared with ERL and ERM values

6.1 Multivariate Tests: Spatio-temporal variations on Macrofaunal density during 2013-14

6.2 Multivariate Tests: Spatio-temporal variations on Macrofaunal density during 2014-15

6.3 Multivariate Tests: Spatio-temporal variations on Macrobenthic Biomass during 2013-14

6.4 Multivariate Tests: Spatio-temporal variations on Macrofaunal Biomass during 2014-15

6.5 Post Hoc Tests: Sitewise Variation on Macrobenthic invertebrate density during 2013 -14

6.6 Multiple comparisons: Sitewise Variation Macrobenthic invertebrate Biomass during 2013 -14

6.7 Post Hoc Tests: Sitewise Variation on Macrobenthic invertebrateDensity during 2014 -15

6.8 Post Hoc Tests: Sitewise Comparison on Macrobenthic Biomass during 2014 -15

6.9 Multivariate Testsa: Year wise Comparison of Diversity Indices

6.10 Spatio-temporal variation in Diversity indices during 2013-14

6.11 Spatio-temporal variation in Diversity indices during 2014-15

6.12 Spatio-temporal variation in Diversity indices of Gastropods during 2013-14

6.13 Spatio-temporal variation in Diversity indices of Gastropods during 2014-15

6.14 Spatio-temporal variation in Diversity indices of Bivalves during 2013-14

6.15 Spatio-temporal variation in Diversity indices of Bivalves during 2014-15

6.16 Spatio-temporal variation in Diversity indices of Crustaceans during 2013-14

6.17 Spatio-temporal variation in Diversity indices of Crustaceans during 2014 -15

6.18 Spatio-temporal variation in Diversity indices of Polychaetes during 2013-14

6.19 Spatio-temporal variation in Diversity indices of Polychaetes during 2014-15

6.20 Spatio-temporal variation in Diversity Indices of Scaphopods during 2013-14

6.21 Spatio-temporal variation in Diversity indices of Scaphopods during 2014-15

6.22 Spatio-temporal variation in Diversity indices of Echinoderms during 2013-14

6.23 Classification of sites based on BOPA index

6.24 Principal Component Analysis (PCA) along site 1 during 2013-14

6.25 Principal Component Analysis (PCA) along site 2 during 2013-14

6.26 Principal Component Analysis (PCA) along site 3 during 2013-14

6.27 Principal Component Analysis (PCA) along site 4 during 2013-14

6.28 Principal Component Analysis (PCA) at site 1 during 2014-15

6.29 Principal Component Analysis (PCA) at site 2 during 2014-15

6.30 Principal Component Analysis (PCA) at site 3 during 2014-15

6.31 Principal Component Analysis (PCA) at site 4 during 2014-15

6.32 CCA variable Scores for site 1 during 2013­14

6.33 CCA eigen values for site 1 during 2013-14

6.34 CCA variable scores for site 2 during 2013­14

6.35 CCA eigen values for site 2 during 2013-14

6.36 CCA variable scores for site 3 during 2013­14

6.37 CCA eigen values for site 3 during 2013-14

6.38 CCA variable scores for site 4 during 2013­14

6.39 CCA eigen values for site 4 during 2013-14

6.40 CCA variable scores for site 1 during 2014­15

6.41 CCA eigen values for site 1 during 2014-15

6.42 CCA variable scores for site 2 during 2014­15

6.43 CCA eigen values for site 2 during 2014-15

6.44 CCA variable scores for site 3 during 2014­15

6.45 CCA eigen values for site 3 during 2014-15

6.46 CCA variable scores for site 4 during 2014­15

6.47 CCA eigen values for site 4 during 2014-15

6.48 List and percentage variation of macrobenthic invertebrate assemblages 2013-14

6.49 List and percentage variation of macrobenthic invertebrate assemblages 2014-15

LIST OF FIGURES

1.1 Map of Kerala showing the study sites

1.2 Varkala Tourist Influx

1.3 Massive foot traffic and sewage flow

1.4 A portion of the cliff at Varkala overlooking the Arabian sea

1.5 Neendakara harbour

1.6 Eutrophication in Neendakara

1.7 Oil pollution in Neendakara

1.8 Mineral Separation Plant (MS Plant)

1.9 Panmana acid fields

1.10 Effluents directly flow into near water bodies

1.11 The spreading of effluents to the sea

1.12 Alappad

2.1 Spatio-temporal variations of SW temperature (°C) during 2013 -15

2.2 Spatio-temporal variations of SW DO (mg/L) during 2013 -15

2.3 Spatio-temporal variations of SW pH during 70 2013 -15

2.4 Spatio-temporal variations of SW salinity (ppt) 71 during 2013-15

2.5 Spatio-temporal variations of SW TDS (ppt) 72

2.6 Spatio-temporal variations of SW NO2 (^g/L) 73 during 2013-15

2.7 Spatio-temporal variations of SW NO3 (^g/L) 74 during 2013-15

2.8 Spatio-temporal variations of SW PO4 (^g/L) 75 during 2013-15

2.9 Spatio-temporal variations of SW SiO3 (^g/L) 76 during 2013-15

2.10 Spatio-temporal variation of SW chlorophyll a 77 (mg/m³ ) during 2013-15

2.11 Spatio-temporal variations of BW temperature 92 (°C) during 2013-15

2.12 Spatio-temporal variations of BW pH during 93 2013.15 2.13 Spatial and Temporal variations of BW DO 94 (mg/L) during 2013-15

2.14 Spatio-temporal variations of BW salinity (ppt) during 2013-15

2.15 Spatio-temporal variations of BW TDS (ppt)

2.16 Spatial and Temporal variations of BW NO2 (|ig/L) during 2013-15

2.17 Spatial and Temporal variations of BW NO3 (|ig\L) during 2013-15

2.18 Spatio-temporal variation of BW PO4 (^g/L) during 2013-15

2.19 Spatio-temporal variation of BW SiO3 (^g/L) during 2013-15

2.20 Spatio-temporal variations of BW chlorophyll a (mg/m³ ) during 2013-15

3.1 Spatio-temporal variations of sediment temperature (°C)

3.2 Spatio-temporal variations of sediment OC (%) 2013-14

3.3 Spatio-temporal variations of sediment OM (%)2013-14

3.4 Spatio-temporal variations of sediment OC (%) 2014-15

3.5 Spatio-temporal variations of sediment OM (%)2014-15

3.6(a) Schematic plot showing textural classes according to Sheppard’s Classification

3.7(b-e) Ternary plots for (b) Site 1 (c) Site 2 (d) Site 3 and (e) Site 4 during 2013 - 14.

3.8(a-d) Ternary plots for: (a) Site 1 (b) Site 2 (c) Site 3 (d) Site 4 during 2014 - 15

4.1 Spatio-temporal variations of SW Fe (^g/L)

4.2 Spatio-temporal variations of BW Fe (^g/L)

4.3 Spatio-temporal variations of SW Pb (^g/L)

4.4 Spatio-temporal variations of BW Pb (^g/L)

4.5 Spatio-temporal variations of SW Cd (^g/L)

4.6 Spatio-temporal variations of BW Cd (^g/L)

4.7 Spatio-temporal variations of SW Cr (^g/L)

4.8 Spatio-temporal variations of BW Cr (^g/L)

4.9 Spatio-temporal variations of SW Ni (^g/L)

4.10 Spatio-temporal variations of BW Ni (^g/L)

4.11 Spatio-temporal variations of SW Zn (^g/L)

4.12 Spatio-temporal variations of BW Zn (^g/L)

4.13 Spatio-temporal variations of SW Hg (^g/L)

4.14 Spatio-temporal variations of BW Hg (^g/L)

4.15 Spatio-temporal variations of Fe in sediment (^g/g)

4.16 Spatio-temporal variations of Pb in sediment (^g/g)

4.17 Spatio-temporal variations of Cd in sediment (^g/g)

4.18 Spatio-temporal variations of Cr in sediment (^g/g)

4.19 Spatio-temporal variations of Ni in sediment (^g/g)

4.20 Spatio-temporal variations of Zn in sediment (^g/g)

4.21 Spatio-temporal variations of Hg in sediment (^g/g)

5.1 Structure of PAHs with multiple aromatic rings

5.2 Chemical structure of the EPA selected PAHs

5.3 Spatio-temporal variations of SW PAH (ng/L)

5.4 Spatio-temporal variations BW PAH (ng/L)

5.5 Spatio-temporal variations of PAHs in sediment (ng/g)

5.6 Seasonal-mean variation of E16 PAHs in SW(ng/L)

5.7 Seasonal-mean variation of E16 PAHs in BW(ng/L)

5.8 Seasonal-mean variation of E16 PAHs in sediment (ng/g)

5.9 PAH profiles and TEQ (ng /L) in SW at Varkala

5.10 PAH profiles and TEQ (ng /L) in BW at Varkala

5.11 PAH profiles and TEQ (ng/g) in sediment at Varkala

5.12 PAH profiles and TEQ (ng /L) in SW at Neendakara

5.13 PAH profiles and TEQ (ng /L) in BW at Neendakara

5.14 PAH profiles and TEQ(ng/g) in sediment at Neendakara

5.15 PAH profiles and TEQ (ng /L) in SW at Chavara-Titanium

5.16 PAH profiles and TEQ (ng /L) in BW at Chavara-Titanium

5.17 PAH profiles and TEQ (ng/g) in sediment at Chavara-Titanium

5.18 PAH profiles and TEQ (ng /L) in SW at Alappad

5.19 PAH profiles and TEQ (ng /L) in BW at Alappad

5.20 PAH profiles and TEQ (ng/g) in sediment at Alappad

6.1 Benthic Assemblages during 2013- 15

6.2 Numerical abundance of benthic assemblages during 2013-14

6.3 Numerical abundance of benthic assemblages during 2014-15

6.4 Macrobenthic biomass during 2013-15

6.5 Average biomass of macrofauna during 2013-14

6.6 Average biomass of macrofauna during 2014-15

6.7 Seasonal variations in macrobenthic assemblages along site 1 during 2013-14

6.8 Seasonal variations in macro benthic assemblages along site 1 during 2014-15

6.9 Seasonal variations in benthic assemblages along site 2 during 2013-14

6.10 Seasonal variations in benthic assemblages along site 2 during 2014-15

6.11 Seasonal variations in benthic assemblages along site 3 during 2013-14

6.12 Seasonal variations in benthic assemblages along site 3 during 2014-15

6.13 Seasonal variations in benthic assemblages along site 4 during 2013-14

6.14 Seasonal variations in benthic assemblages along site 4 during 2014-15

6.15 Spatio-temporal variations in diversity indices during 2013 - 14

6.16 Spatio-temporal variations in diversity indices during 2014 - 15

6.17 Spatio-temporal variations in diversity indices of gastropods during 2013-14

6.18 Spatio-temporal variations in diversity indices of gastropods during 2014 - 15

6.19 Spatio-temporal variations in diversity indices of bivalves during 2013-14

6.20 Spatio-temporal variations in diversity indices of bivalves during 2014-15

6.21 Spatio-temporal variations in diversity indices 363 of crustaceans during 2013-14

6.22 Spatio-temporal variations in diversity indices of crustaceans during 2014-15

6.23 Spatio-temporal variation in diversity indices of polychaetes during 2013-14

6.24 Spatio-temporal variations in diversity indices of polychaetes during 2014-15

6.25 Spatio-temporal variations in diversity indices of scaphopods during 2013-14

6.26 Spatio-temporal variations in diversity indices of scaphopods during 2014-15

6.27 Spatio-temporal variations in diversity indices of echinoderms during 2013-14

6.28 Dendrogram showing spatio-temporal similarities of faunal groups during 2013-14

6.29 Dendrogram showing spatio-temporal similarities of faunal groups during 2014-15

6.30 nMDS plot for macrobenthic invertebrate groups of seasonal basis during 2013-14

6.31 nMDS plot for macrobenthic invertebrate groups of seasonal basis during 2014-15

6.32 nMDS plot for macrobenthic abundance during 2013-14

6.33 nMDS plot for macrobenthic abundance during 2014-15

6.34 ABC curves for site 1 during 2013-14

6.35 ABC curves for site 2 during 2013-14

6.36 ABC curves for site 3 during 2013-14

6.37 ABC curves for site 4 during 2013-14

6.38 ABC curves for site 1 during 2014-15

6.39 ABC curves for site 2 during 2014-15

6.40 ABC curves for site 3 during 2014-15

6.41 ABC curves for site 4 during 2014-15

6.42 AMBI value and relative abundance of 382 ecological groups at site 1

6.43 AMBI value and relative abundance of 382 ecological groups at site 2

6.44 AMBI value and relative abundance of 383 ecological groups at site 3

6.45 AMBI value and relative abundance of 384 ecological groups at site 4

6.46 PCA ordination plot for Hydrological variables 386 along site 1 during 13-14

6.47 PCA ordination plot for Hydrological variables 387 along site 2 during 2013-14

6.48 PCA ordination plot for Hydrological variables 388 along site 3 during 2013-14

6.49 PCA ordination plot for Hydrological variables 389 along site 4 during 2013-14

6.50 PCA ordination plot for Hydrological variables 390 along site 1 during 2014-15

6.51 PCA ordination plot for Hydrological variables 391 along site 2 during 2014-15

6.52 PCA ordination plot for Hydrological variables 392 along site 3 during 2014-15

6.53 PCA ordination plot for Hydrological variables along site 4 during 2014-15

6.54 CCA Bi-Plot for site 1 during 2013-14

6.55 CCA Bi-Plot for site 2 during 2013-14

6.56 CCA Bi-Plot for site 3 during 2013-14

6.57 CCA Bi-Plot for site 4 during 2013-14

6.58 CCA Bi-Plot for site 1 during 2014-15

6.59 CCA Bi-Plot for site 2 during 2014-15

6.60 CCA Bi-Plot for site 3 during 2014-15

6.61 CCA Bi-Plot for site 4 during 2014-15

LIST OF PLATES

Sl No Plates

I Sample Collection

II Laboratory Analysis

III-V Macro benthic invertebrate assemblages 429

GENERAL INTRODUCTION

MARINE REALM

The earth's surface is covered by approximately 71% of oceans, and the water depth averages 3.8 km, giving a volume of 1370 x 10⁶ km³. The oceans are among our biggest resource for life on earth and are obviously the substantial domicile of living organisms, and are fringed with coastlines that run for nearly 380,000 km. Since life exists throughout this immense ocean it constitutes the single largest repository of organisms on the planet. These organisms include representatives of virtually all phyla and are tremendously varied. All of them, however, are subjected to the properties of the seawater that surrounds them, and many features common to these plants and animals are the results of adaptations to the watery medium and its movements (Prasad, 2010).

All major oceans around the world differ with the extent of landmass, circulation patterns, and physicochemical properties. Rest of the major water bodies of the open-ocean and deep-sea environments are referred to as seas. A sea can be termed as a water body, smaller than an ocean with its own unique characteristics defined by basin morphology. Due to their circulation patterns and geomorphology, seas are highly influenced by continental land mass and island chain structures than oceanic environments (ME,2002).

Coastal and nearshore marine ecosystems are considered as environments bound by coastal land margins (seashore) and its continental shelf (100­200 m) situated below sea level, strongly influenced by its oceanographic and physical processes. Ecologically, the nearshore and coastal zone grading from shallow water depths are influenced by adjacent landmass and the input derived from coastal rivers and estuaries till the continental shelf break, where all oceanic processes predominate (FGDC,2012).

Continental shelves team up with life in the presence of sunlight available in shallow waters, in contrast to the biotic desert of oceans' abyssal plain. The pelagic (water column) environment of the continental shelf constitutes the neritic zone and the benthic (sea floor) zone of the shelf known as the sublittoral zone. Though these shelves are usually fertile, during sedimentation anoxic conditions may prevail, with deposits over geologic time as sources of fossil fuels. More variability is found in the waters of the continental shelf, in environmental conditions, than do either the epipelagic of the deep sea or the open ocean. Both continental shelf and slope are parts of the continental margin. Terrigenous sediments cover the continental shelves; derived from erosion of the nearby continents, with little of sediments derived from current rivers. Around 60-70% of the world’s

sediment are relict, deposited during last ice age; when sea level was 100 - 120 m lower than now (Peter,2012).

INDIAN OCEAN

The Indian Ocean, third largest of the world's oceans, makes up about 20% of Earth's water. It boasts of an area approximately 28,360,000 square miles (73,440,000 sq. km) and is also the youngest of world's major oceans with its hydrological characteristics derived from interaction of atmospheric conditions (rain, wind and solar energy) within the surface, sources of water and deep (thermohaline) circulation, all of which combine to form generally horizontal layers of water. Temperature and salinity in different combinations constitute each layer forming discrete water masses of varying densities, with lighter overlying denser water. In surface-water temperature, seasonal variations are observed. The surface circulation of the oceans is found to be wind-driven. Surface circulation in the monsoon zone reverses every half year, featuring two opposing gyres separated by the Indian sub­continent (Friedrich et al., 2009).

During northeast monsoon, a weak counterclockwise gyre is found to develop in the Arabian Sea and a strong clockwise gyre in the Bay of Bengal. During the southwest monsoon, the reverse current flow is observed in both the seas, forming warm and cold-core eddies in the Arabian Sea. An immense load of suspended sediments from rivers are found emptying into the Indian Ocean, which is highest of the three oceans; nearly half of it flowing from the Indian subcontinent alone. The terrigenous sediments that occur mostly in the continental shelves, rise in the slopes and merge into abyssal plains (Schott and McCreary, 2001).

India is reported to have approximately a coastline of about 7,500 km (Chandramohan et al., 2001), with 250 million residing at 50 km distance from the coast (Areti, 2007) and is estimated to be a major industrialized country in the world and with industrialized towns or cities located mainly near the coastal areas, and almost 70% of the coastal waters are found to be polluted, mainly by industrial effluents and sewage. These pollutants are disposed into the marine environment, both directly and indirectly, estimated to generate around 18,240 million liters per day (MLD) of wastewater into the coastal waters (Sampath, 2003).

ARABIAN SEA

The Arabian Sea which is located in the northern Indian Ocean covering about 1% of the world's ocean surface, accounts for 5% of global marine production due to its overwhelming upwelling. During the southwest monsoon, reversed circulation and mixed layer deepening is found compared to northeast monsoon (Qasim 1977 and 1982). The seasonal upwelling creates intense surface productivity and high export particle flux at the euphotic zone, with reversal of bi-annual current in the winter and influx of cold nutrient- rich waters at its surface during summer. These phenomena during south-west monsoons, thus, promote high plankton productivity.

The Arabian Sea has a monsoon climate with a minimum air temperature of about 75 to 77 °F (24 to 25 °C) in the central Arabian Sea during January and February with temperatures rising higher than 82 °F (28 °C) in both June and November. During the rainy season, southwest monsoon winds blow (April to November) and salinity less than 35ppt is recorded. In the euphotic zone, an attributable part is the coastal upwelling, thus circulating settled nutrients to the seafloor. This periodic occurrence in the Arabian Sea, however, leads to the mass mortality of fish and the phenomenon is attributed to a subsurface layer of water of tropical origin which is oxygen deficient, but phosphate-rich. Under certain circumstances, this subsurface layer rises to the surface due to strong upwelling resulting in the death of fish, due to lack of oxygen. This Oxygen Minimum Zone (OMZ) is located at the Arabian Sea in depths of 100 to 1300m (Qasim 1982; Hughes and Goodall, 1992; Helly and Levin 2004); and these regions when in contact with sediments of continental margin have been found to have a profound impact on distribution and biomass of the bottom-living organisms.

While considering vertical fluxes and processes of the benthic boundary layer and within surface sediments, continental margins of the Arabian Sea and its surface level, their sediments have a great importance (Walsh 1991; Naqvi et al., 2000, 2006 and Cowie, 2005). Very high mean and annual particulate organic carbon fluxes are found to move into the deep ocean in the northern and western Arabian Sea (Wanink and Witte, 2000). Additionally, vertical particulate, organic carbon fluxes are largely recorded in the open ocean during seasonal variations (Ittekkot et al., 1996).

High organic production, with sources of water in limited quantities, results in replacement of rapid utilization of oxygen and development of unusually intense deep oxygen minimum layer (Haake et al., 1993 and Cowie 2005). This enhanced flux of labile organic material is then delivered into the deep-sea benthic boundary. Turbulence or wave action is one of the most important physiological factors that act on the bottom communities. In the shallower waters, the interaction of all waves, currents, and upwelling act to create a turbulence, keeping inshore waters becoming thermally stratified for brief periods, at least in the temperate zone. Thus, nutrients are rarely limiting or locked up in a bottom reservoir.

Productivity is generally high in offshore waters due to their nutrient abundance, both from land run-off and recycling. Wave action is also found to be an important factor since ocean swell for longer periods and storm waves tend to have an effect, extending to the bottom of these shallow waters. In soft bottoms, the passage of such waves may cause large surging motions in the bottom water, which greatly affect the stability of the substrate. The substrate particles may be moved around and resuspended. They were found to have a profound effect on the benthic fauna of the substrate. Heavy wave action is found to remove fine particles by keeping them in suspension, leaving mainly sand and thus, making fine silt sediments, occurring only in areas with low wave action or too deep to be affected by wave action. The salinity of this region is more variable compared to the open or deep ocean, except in areas where large rivers which discharge massive amounts of fresh water, not affecting the \salinity enough to be of ecological significance (Bhat et al., 2001).

Biological communities, as well as the physical and chemical aspects of the marine ecosystems, have changed continually and naturally over time. Oceans and its resources have been used by humans in many creative and useful ways. In recent times, such beneficial human activities face various threats. Urban centers and industrial areas are prime targets of pollution by untreated sewage and industrial wastes since they are densely populated. Microbial pollution is found only along nearshore waters, while dumped/disposed of chemicals are found even in off-shore waters. Increasing global population and industrialization is a major source of marine pollution, due to emerging wastes from urban and municipal run­off, contributing to an increase in pollution level (Subramanian, 1999). Human perturbations lead to the flow of energy patterns bringing fundamental alterations in the present ecosystem’s structure and function.

BENTHIC INVERTEBRATES

Benthic macroinvertebrates or benthos (benthic = bottom, macro = large, invertebrate = organisms without a backbone) are animals that live on the bottom of rivers and seas. It was first emphasized by Haeckel (1891) and derived from the Greek word for ‘depths of the sea' which refers to all organisms living in, on or near a water environment.

Benthos comprises an enormous group of organisms, starting from microorganisms to huge cellular megafauna; which are additionally countless in subculture and feeding modes (Cowie and Levin, 2009). Benthos are ordinarily arranged into three categories - infauna, epifauna, and hyperbenthos i.e. organisms occupying within the substratum, on the surface and above it respectively (Pohle and Thomas, 2001).

Benthic animals are further classified according to their structure into the following: micro (<0.063 mm), meio [0.063-1.0 (or 0.5) mm], macro [>1.0 (or 0.5) mm] (Mare, 1942) and mega (> 10.0 mm) benthos (Tagliapietra and Sigovini, 2010). Benthic fauna forms the largest constituent of marine food chains (Holme and McIntyre, 1971) as they are most affected due to recycling of minerals, carbon, nitrogen, and sulfur (Schweitzer 1974, Giblin et al., 1995 and Heip et al., 2001). Organisms retained within the sieve (between 0.5 and 1mm) are classified as macrobenthos which is popular nowadays. The fundamental taxonomic classes represented are the annelids, crustaceans, and mollusks together with echinoderms and sipunculids. Sensible classifications within sampling methods adopted have ended in the differentiation of benthos into two, viz; soft bottom benthos and hard bottom benthos. In their habitats, they are supreme creatures as they are well adapted to deep-water pressure and unable to exist in the upper areas of the water column (around 1 atmosphere/10 m of water depth).

As light is unable to reach deep into the ocean, benthic ecosystem often derives energy from organic matter found in the water column, which drifts down to the depths. This dead and decaying matter supports the benthic food chain. Hence, most of the organisms are scavengers or detritivores, while rest of the microorganisms use chemosynthesis for producing biomass.

Benthic invertebrates, harvested commercially or recreationally, can mediate threats to public health by bio-accumulating toxic substances (metals, DDT and PCBs) that are deposited in the sediments. A threat in public health may arise due to the consumption of contaminated fishes and large epibenthic invertebrates that prey on chemically contaminated benthic infauna (O'Connor and Rachlin, 1982; Dillon, 1984 and Kay, 1984).

Benthic infauna is superior to all other monitored

biological organisms (plankton, fishes and marine birds) since they are bottom dwellers and are forced to adapt to environmental stress. These responses to contamination of sediments define the spatial definition of impacts (Gray, 1980; Hartley, 1982; Phillips and Segar, 1986). They are also effective indicators of impact at higher levels (community level) due to their importance to the ecosystem structure (food web). The abundance of macrobenthic invertebrates in aquatic ecosystem indicates the biological condition of the waterbody. Healthy biological conditions of water bodies facilitate a large variety and an enormous number of macroinvertebrate taxa, most of them intolerant of pollution.

Pollution-tolerant species with very little diversity or abundance may indicate an unhealthy waterbody which is the most comprehensive indicator of health in an ecosystem. The biology of each waterbody is healthy when its chemical and physical components are in good condition (US EPA,2016). Rosenberg and Resh (1993) suggested that anthropogenic disturbances strongly affect species richness in aquatic invertebrates.

Macrobenthic fauna tends to remain in their original habitats due to their great adapting capability. Any changes in water quality and high loads of pollution can be tolerated by them. When under pollution, the community structure simplifies in favor of the tolerant species, leading to an abundance of certain species in the ecosystem decreasing diversity and species richness. Belal et al., (2016) found that an assessment of diversity and indicator species helps water quality evaluation. Stringent benthic biomonitoring helps to detect precise changes and serves as early indicators before drastic environmental changes occur. Significance in the study of macrobenthos has received considerable attention in the recent years as biological indicators of environmental change in aquatic ecosystems and also as reliable sources of food for organisms.

The abundance of benthic animals in the closely related area can be regarded as an indicator organism, denoting the nature of an ecological niche due to their limited mobility and intolerance in adverse conditions. They survive in sediments with chemical contaminants and low dissolved oxygen levels. Environmental stressors affect the lifespan of benthos since they are sedentary in nature to react to multiple stressors.

Disturbances in structural changes of benthic communities differ and are predictable, hence are used to analyze overall health of oceans and estuaries (Frouin, 2000). The disturbances in benthic community structures are commonly used in pollution assessment studies (Warwick and Clarke, 1993). Information on the composition of standing bottom communities is related to stresses undergone by preceding communities found in adjacent areas. This concept is of great importance in biological monitoring of benthic invertebrates as useful tools due to their narrow and specific environmental tolerances. An organism cannot survive in an environment which does not provide its physical, chemical and nutritional requirements.

Long-term assessments on benthic communities provide information on environmental changes, dredged material, organic enrichment, aggregate extraction and climate changes (Rees et al., 2006; Foden et al., 2009 and Birchenough et al., 2010). Another important functional role of macrobenthos lies in their reworking of sediments (i.e. bio­perturbation and bio-irrigation) providing food to higher trophic groups by creating favorable environments through habitat-engineering species (Hendrick and Smith, 2006; Hoey et al., 2008). This need for assessing and monitoring benthic changes (including climate changes) has prompted researchers to collect information over a long time­scale.

MARINE POLLUTION

The primary cause of alterations in marine biodiversity are direct and indirect human activities. Anthropogenic stressors are changing conditions of coastal areas and impacting its habitats. But, when multiple stressors act simultaneously, their effects on the prevailing ecosystems become more difficult to predict.

Several chemical substances like Poly Aromatic Hydrocarbons (PAHs), Heavy Metals (HM), pesticides, herbicides, plastic compounds and nutrients found in the environment are either natural or of human origin. Concentrated pollutants tend to be found in three parts of the ocean. First, is that they gather at the sea bottom by being chemically attached to sediment particles (silt and clay) or by settling directly as solids onto the seafloor. Burrowing benthic organisms, mix these materials with the sediment. Secondly, concentrated pollutants separate at varying densities in the water masses which commonly occur in estuaries, where a wedge of saltwater comes in contact with fresh or slightly saline water. Thirdly, solid and dissolved wastes collecting at the interface between sea and air, cause a very thin (0.1 to 10 mm) surface microlayer (neuston layer). Mining wastes, fuel ash, and radioactive materials are among the many primary marine pollutants (Hughes and Goodall, 1992). Chemicals and solids including pollutants, combine and effect planktons of all kind, including embryonic forms of invertebrates and fishes that dwell temporarily in surface water as a habitat. Once these pollutants invade the environment, they are degraded or broken down by various biological and oceanographic activities (Pinet, 2009).

SEASONAL INFLUENCE ALONG THE SOUTHERN COAST OF KERALA

The main characteristics of the Kerala coastal waters are the influence of south-west monsoon from the Arabian Sea, which is found to create an impact on its hydrological conditions. Based on this influence, monsoon precipitation and its associated environmental conditions, the annual pattern can be cleaved into three seasons, having significant hydrological characteristics. The pre­monsoon (February-May) is characterized by very little rainfall and fairly uniform high salinity and temperature. The monsoon (June-September) is characterized by heavy rainfall and high inflow of river waters into the coastal waters, causing considerable lowering of salinity. The post­monsoon (October-January) is characterized by an increase in salinity and temperature (Vivekanandan et al.,2003).

During 2013, the monsoon showered over Kerala, led to experience the heaviest rains in nearly two decades. The southwest monsoon is found to set over Kerala on 1st June, with minor fluctuations over the years, advances over entire south Arabian Sea with Maldives-Comorin, Lakshadweep and some parts of central Arabian Sea.

During 2014, compared to 2013, the southwest monsoon exhibited many interesting facts. The monsoon onset over Kerala was delayed by 5 days from the regular date of arrival and also, exhibited strong intra-seasonal variability associated with the Madden and Julian Oscillation (MJO). MJO is a large-scale coupling between atmospheric circulation and deep tropical convection activity and near normal activity of low-pressure systems formed during the season (IMD,2014). A long break in monsoon activity was observed in the middle of August, due to the influence of MJO activity and the deficient rainfall along with strong temporal and spatial variations, creating an adverse impact on productivity.

During 2015, the southwest monsoon was found to advance over the Bay of Bengal, touching the southern parts of Sri Lanka. But in Kerala, the monsoon was found to be stagnated for a week and displayed a sluggish progress due to an anticyclone formation reported in the Arabian Sea. The state of Kerala was found to receive only patchy rains during the period (only 12% of the regular rainfall), when the timely onset of the southwest monsoon was crucial for sowings of Kharif (summer) crops such as paddy and the deficit in rainfall affected the output (Kurian, 2017).

POLLUTION ALONG THE KERALA COAST

The Kerala landscape, situated between the Arabian Sea to the west and Western Ghats to the east is reported to have an area of 38,863 km², which is 1.18% of India's landmass and is 580 km in length and 35 -120 km in width.

Kerala is setting up her approach towards industrialization. Most of her industries and concrete areas are positioned on the coastal areas, with its offshore fields as one of the most engaged supply lanes, making intertidal and offshore regions intriguing for scientific studies. Anthropogenic illness poses multiple hazards, seriously impeding the fragile balance between nature and particular engineering framework of Kerala. Increasing human intervention at coastal belts, leading to a geometric increase of pollution load is alarming. Excessive nutrients (leading to eutrophication), heavy metals, organic compounds, oil spills and microbial increase form a cascading and incessant litany of marine contaminants and pollution sources (Kesavan et al., 2013).

In Kerala, coastal pollution has been increasing tremendously during the past decades by the extensive industrial production and use of chemicals, pesticides and fertilizers, acids, alkalies and toxic metals resulting in undesirable alterations to the water quality of inland and coastal water sources and the coastal environment as a whole. Factors such as waste disposal, coastal erosion, tourism industry, coastal engineering activities and sand-mining are also creating pressure on the coastal ecosystem. Over-exploitation of resources (mangroves, fisheries, sand, and landscape) and growth of tourism area identified as prime factors for exerting stress on the ecosystem. Sand extraction from beaches and wetland reclamation are also rampant. Wetlands, mangroves, mud banks, beaches, estuaries, and cliffs are reported to be in various stages of degradation. Wetlands are being reclaimed, mangroves are mostly destroyed for development of urban space and construction of ports and shrimp farms, damaging the estuarine and backwater ecosystem. The Cochin backwaters and coastal areas of Alappuzha, Kayamkulam, Kollam, Paravoor, and Veli are identified as the hotspots of the state (KSCSTE, 2007).

Several industries located upstream and the harbor activities contribute to pollution. Over the last few years, sediments collected at the mouth of the Cochin backwaters were found with higher levels of cadmium and lead, and the concentration of these metals have been found to be gradually increasing. Bottom trawling is also found to pose a major threat to the marine ecosystem along the coast of Kerala.

The inadvertent removal of some organisms from the ecosystem would impair dynamics of the food chain, affecting the whole ecosystem. Stake net method of fishing is found to remove a wide array of non- target organisms, whose function are unavoidable to the aquatic environment. Also, adverse effects were seen in brackish water bodies of the State, subjected to various types of pollution emerging from industrial effluents, pesticides, chemical fertilizers and sewage.

Higher concentrations of industrial effluents are reported to be discharged into rivers and estuaries of Kerala daily. Heavy metal (Cu, Hg, Zn, and Cd) concentrations above permissible levels were also reported. Presence of ammonia, acids, alkalis, fluorides and radioactive materials in the water body also have resulted in heavy fish mortality (Eloor-Varapuzha region). Fishing with synthetic fibers, modification of fishing gear and craft, indigenization of fishing techniques such as mini trawling and mini purse seining have contributed to overexploitation of fin and shellfishes in the seas. The ubiquity and magnitude of human perturbations are greatly reduced in some areas by eliminated opportunities to study pristine habitats or communities within habitats (KSCSTE,2007).

Natural changes occurring in the oceans, ranging from seasonal climatic events (hurricanes, typhoons and storm tides) leading to the destruction of local habitat results in frequent reversible alterations in biodiversity and get deeply integrated into larger spatio-temporal patterns of the ecosystem. These effects are frequently irreversible, over the normal span of human life.

The present scenario of the coastal waters of Kollam, mainly at Neendakara and Chavara are related to the degradation of water quality by pathogenic bacteria and petroleum hydrocarbons (Qasim and Madhupratap, 1981; Sarthre et al., 2001; D’Cruz and Miranda, 2005; Wilma, 2010). Earlier studies confirmed that Neendakara is more contaminated than Cochin, due to increasing load of sewage. Sand mining areas at Panmana and Chavara region are threatened by industrial effluents from KMML (Kerala Metals and Minerals Ltd), a public-sector unit based at Chavara in Kollam. This industrial enterprise has degraded the environment and is extremely destructive to the flora and fauna of the region (Lekshmi et al., 2012).

HYPOTHESIS

Inventorizing spatio-temporal variability of the macrobenthic invertebrate assemblages along sites subject to varying anthropogenic stress will reveal new indicator species which can be used to predict the nature and load of pollutant.

SIGNIFICANCE OF THE STUDY

In Kerala, no scientific research has been done to assess the impact of multiple anthropogenic stressors which is rampant along the southern coast. This thesis explores the kinetics of macroinvertebrates at three anthropogenically disturbed regions, along the coast of Kerala. A near- pristine site, which is supposed to serve as a control, was also included in the present study. A correlation of the spatio-temporal dispensation of the communities with environmental parameters has been attempted. Inventorizing the benthic invertebrate assemblages at the sites exposed to differing pollution load (both in quantity) has revealed some alarming observations which need to be addressed immediately. The study has also brought about the efficacy of biomonitoring coastal ecosystems using benthic assemblages.

The study highlights the strong deterministic nature of zoobenthic community and its ability to resist varying anthropogenic disturbances, while identifying new sentinel organisms. Investigating the temporal and spatial parameters of benthic macroinvertebrates and its impacts on trophic levels, determine the fate of energy and nutrient flow into the coastal waters. Estimating secondary production of major taxonomic groups and their value in the food chain, characterizes trophic dynamics within the system.

OBJECTIVES OF THE STUDY

- To Map temporal and spatial variability of macroinvertebrate communities in different polluted habitats and in a near-pristine habitat.
- To Compare differences in the distribution pattern, seasonal occurrence, abundance and composition of macrobenthic communities over a gradient of human disturbances.
- To Identify species or communities which act as a measure of disturbance and also evaluate the faunal relationship to the hydro-geochemical parameters (especially HM and PAHs).

CHAPTER I- STUDY AREA AND SAMPLING DESIGN

1.1 STUDY SITES

The area of study extends from the coastal waters off the Varkala coast in Thiruvananthapuram to the coast of Alappad in Kollam, South Kerala. This stretch of coastal belt is an integral part of the Arabian Sea, incorporating a stretch of 60.5 kms. The sites selected for the study are Varkala, Neendakara, Chavara- Titanium and Alappad (Table 1.1 and figs 1.1).

Table 1.1 Locations, Latitudes & Longitudes

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Figure 1.1 Map of Kerala showing the study sites

1.1.1 SITE 1 -VARKALA

Varkala is the only place in Southern Kerala, where cliffs are visible adjoining the Arabian Sea. The cenozoic sedimentary cliffs are precise, with unique geological features on the flat coast of Kerala, which is famous to geologists as the Varkala Formation. It is also declared as a geological monument by the Geological Survey of India, with several water spas and spouts, discovered along the edges of the cliffs.

In 2015, the Ministry of Mines, an ancillary unit under the Government of India and the Geological Survey of India (GSI) introduced Varkala Cliff as a geo-history site and considered it as a crucial area for the Geology Department of Kerala as it exposes areas belonging to the Cenozoic era, popularly acknowledged as the Warkalli formation.

Another critical highlight of the Varkala seashore is the prevalence of naturally found mineral, Thorium-oxide in the black sand on the beach. Areas of Varkala coast (Papanasam) are also frequented by the locals and peoples from other places scattering ashes of their cremated relatives into the sea. Despite the burial activity, the beach continues to be famous amongst swimmers, native and foreign alike. Additionally, it is a pilgrimage center and a vacationer haven. Quite naturally, a high level of domestic and organic pollutants, attributable to huge pedestrian traffic and direct waste inputs are flowing into the ocean at this site (figs 1.2 & 1.3).

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Figure 1.2 Varkala -Tourist Influx

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Figure 1.3 Massive foot traffic and sewage flow

In the near future, the areas encompassing the geological monument would be declared as a countrywide geopark, with the chosen area being litter- free with no mining or manufacturing activities in the vicinity (fig 1.4). A clearance process from the Union Ministry of Environment and Forests might be required for this, in case of any future activities in the area.

Varkala stands proudly as an opportunity to search out a place within the UNESCO’s international map of geo- historical sites. UNESCO runs a Global Geo park Programme, in which people residing in regions of exceptional geological significance are expected to co­perform with a purpose to keep the cliff and its surroundings clean, since declared as a protected area. Construction hobby and dumping of trash are strictly forbidden in the location (Mahadevan, 2012).

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Figure 1.4 A portion of the cliff at Varkala overlooking the Arabian sea

1.1.2 SITE 2 -NEENDAKARA

The site is a scenic fishing hamlet 09 kms north of Kollam city encased by Ashtamudi Lake in the East and the Arabian Sea in the West. Ashtamudi estuary

opening into the sea at Neendakara is also a Ramsar site. Neendakara harbor is also known as one of the distinguished domestic tourist destinations in Kollam. It was formerly selected by the Indo - Norwegian Foundation (1952) for the inception of fishing- cum- harbor development programme in India. The fishing pastime in this area has obtained an outstanding impetus, ever since in considering the fact. During 1963-67, two breakwaters of length 610m (Seaward) and 380m (Leeward) were constructed on the advice of the Intermediate Port Development Committee by The Government of India (GK,1980).

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Figure 1.5 Neendakara harbour

After its construction, Neendakara had witnessed an amazing boom of mechanized fishing boats. The fishing activities at Neendakara turned ways in 1952, when the Indo-Norwegian foundation for development selected the two fishing villages, Neendakara and Sakthikulangara on both sides of Ashtamudi wetlands (Sanadevan, 1959). It was in 1968, that the Engineering department under the Government of Kerala, recognized the capability and opportunities by selecting the port as a fishing cum cargo harbor (DPGK, 2010) [fig 1.5].

Presently Neendakara harbor has a potential to deal with about 3300 boats from numerous parts of Kerala with facilities like ice and freezing plants, processing centers, exporting centers, diesel and petrol bunks, boat building repairing yards and industrial fishery segments (Anon, 2001). Since, Neendakara is contaminated due to the increasing load of sewage (nitrogenous wastes), it has created eutrophicated conditions (fig 1.6) and oil pollution (oil spills from boat engines) [fig 1.7], has damaged the health of the aquatic system.

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Figure 1.6 Eutrophication in Neendakara

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Figure 1.7 Oil pollution in Neendakara

1.1.3 SITE 3 - CHAVARA-TITANIUM

Chavara -titanium coast came to limelight in the international arena, when a German scientist, Dr. Schomberg accidentally stumbled upon traces of the rare metal ore monazite in the heavy shining particles in coir which was imported from Kerala (of course, the sample was from Chavara-Titanium coast, in Kollam District). The seashores were identified with a wealth of the rarest earth minerals soon became the center of scientific attraction to the outside world.

In the year 1932, a non-public entrepreneur established an enterprise named F. X. Pereira and Sons (Travancore) Pvt. Ltd- a forerunner to the cutting-edge business plant, The KMML (Kerala Minerals and Metals Ltd:). In 1956, it came under the management

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