FISH HABITATS AND SPECIES ASSEMBLAGEI IN THE SELECTED RIVERS OF KERALA AND INVESTIGATION ON LIFE HISTORY TRAITS OF PUNTIUS CARNA TICUS (JERDON, 1849}
‘17{"E.S'I.S' S‘U DOC TO R O F PH I LOSO PH Y (BY mMANOJKUMAR man T.G. COCHIN UNIVERSITY OF SCIENCE AND TECHNOLOGY KOCHI-682016 2006 Qecficatezf to my fiefiruezf parents DECLARATION I,Manojkumar T.G., do hereby declare that the thesis entitled “Fish habitats and species assemblage in the selected rivers of Kerala and investigation on life history traits of Puntius carnaticus(Jerd0n,1849)” is a genuine record of research work carried out by me under the guidance of Dr.B.Madhus00dana Kurup, Professor, School of Industrial Fisheries,Cochin University of Science and Technology ,Kochi -l6 and no part of the work has previously formed the basis for the award of any Degree, Associateship and Fellowship or any other similar title or recognition of any University or institution. Kochi -682016 .i . 22"“ March 2006 Manojkumar T.G./ CERTIFICATE This is to certify that the thesis entitled “Fish habitats and species assemblage in the selected rivers of Kerala and investigation on life history traits of Puntius carnaticus(Jerdon,I849)” is an authentic record of research work carried out by Sri.Manojkumar T.G. under my guidance and supervision in the School of Industrial Fisheries, Cochin University of Science and Technology in partial fulfillment of the requirements for the degree of Doctor of Philosophy and no pan thereof has been submitted for any other degree. _ ._3 Kochi — 682016 Dr.B.Madhusoodana‘ Kurup 22"“ March 2006 (Supervising Guide) Professor School of Industrial Fisheries Cochin University of Science and Technology, Kochi — I6 flclinowfedgements I wish to express my sincere thanks and deepest sense of gratitude to my guide Dr. B. Madhusoodana Kurup, Professor, School of Industrial Fisheries, Cochin University of Science and Technology, for his unfailing guidance, intellectual inputs, invaluable suggestions, critical assessment and constant encouragement throughout the tenure of my research work. I am also gratefill to Prof. (Dr.) Saleena Mathew, Director, School of Industrial Fisheries, Prof. (Dr.) Ramakrishnan Korakkandy and Prof. (Dr.) C. Hridayanathan, Former Directors, School of Industrial Fisheries, for providing necessary facilities to carry out this work successfully. l am happy to record my sincere gratitude to Dr.K.Ravindran,UGC Visiting Professor of this school for his valuable advices and friendly support during the period of my research work at this school. I am deeply indebted to Prof.T. M. Sankaran (Retd), College of Fisheries, Panangad and Dr. M. Hariknshnan, Lecturer, St. Alberts college, Ernakularn for their generous help in the statistical analysis of the data and invaluable help extended to work on various software packages of fish population dynamics. The timely advices given by Dr. Philip Thalamage Scientist, U.S.Geological Survey and Dr. Sanjeevkumar Sreevastava, Scientist, National Bureau of Fish Genetic Resources,Lucknow in standardising the methodology of the Habitat inventory part of this work is deeply acknowledged. I am grateful to Sri G. Mohan Kumar, IAS, Chairman, MPEDA for encouragement in completing this work after my placement at Rajiv Gandhi Centre for Aquaculture I am highly thankful to Sri.Y.C.Thampy Samraj, Project Director, RGCA, Dr.P. J ayagopal, Project Manager and all other my colleagues in RGCA — DTS project for rendering their constant motivation and support for completing this work. The encouragement and assistance extended by my teachers, other faculty members of the office staff and my fellow researchers at the School of Industrial Fisheries are greatly acknowledged. I would like to place on records my immense gratitude and appreciation to Mr.Radhakrishnan K.V., Mr.Eapen Jacob, Dr.Euphrasia C.J., Mr.Venu S., Dr.Joice V. Thomas, Mr.Johny T. Varghese, Mr. Ronald W,. Ms. Subhasree Shankar, Mrs.Sreedevi.C. and Mr.Paul Thampy for their valuable help and support rendered for the sumptuous fulfilment of this research work. My sincere thanks are also due to Ms.Neethu K.G.,Data Entry Operator of the NAT—ICAR Project. Sincere thanks are also due to Mr. M. D. Mahesan, V.J. Johny and Mr. Biju for their invaluable support and help rendered in carrying out the habitat inventory surveys in different river systems of Kerala. Last, but not the least, I wish to express my sincere thanks to National Bureau of Fish Genetic Resources, Lucknow for giving me an opportunity to work as a Senior Research Fellow in the NAT-ICAR project on ‘Germplasm Inventory Evaluation and Genebanking of Freshwater Fishes’. Manoj kumar T.G. Contents Section I Fish habitat and species assemblage in the selected rivers of Kerala Page Chapter 2.Materials l.General Introductionand methods 241 Chapter 3.Habitat quality and index of biotic integrity 34 in six major river systems of Kerala Chapter 4.Fish diversity vis-£1-vis altitude in the major 58 River basins of Kerala Chapter 5.0n the extent of degradation of fish habitats 75 In the major river systems of Kerala and Management plans for fish germplasm conservation Chapter 6.Habitat Suitability lndex(HSI) models of selected 96 endangered and endemic fish species of Kerala Section II Life history traits and resource characteristics of Puntius carnaticus(Jerdon,1849) Chapter 7. Systematics 8. Food of Puntius and camaticus(Jerdon,1849) Feeding 132 127 Chapter 9. Maturation and Spawning 148 Chapter 10. Length- ll.Age Weight relationship and andGrowth Condition factor 187 1.76 Chapter l2.Population Dynamics 199 PublicationsReferencesChapter 13.Summary and Recommendations 234293 216 Section I Fish habitat and species assemblage in the selected rivers of Kerala Chapter 1 General Introduction 1.1. Introduction Ecology is a new and exceedingly complex field of study, even though its concept was recognized by the Apostles in their use of the phrase ‘all flesh is grass’. Basically it is a quantitative science and is defined as the study of interrelationships among organisms and the interrelationships of organisms with their non-living enviromnents. The environment includes all physical and biological variables affecting a population, including interactions between the individuals of a population and between individuals of different species. Ecology is usually considering as a branch of biology due to its complex relationship with physiology, population genetics, evolutionary biology but it is also an integration of the biological sciences with the earth sciences such as Oceanography and Geology and is a unifying concept of how life exists on our planet (Poole, 1974). Aquatic ecology is a multidisciplinary science with no clear boundaries among the many contributing sciences. And it is, in some ways, more complex than terrestrial ecology, because most other systems that have well-defined boundaries, within which community-ecosystem interactions occur while stream and rivers are highly integrated with the adjacent landscape and are influenced by processes within the riparian corridor and the basin as a whole (Cowx and Welcomme, 1998). Moreover, in aquatic ecosystem both communities and enviromnental units tend to be in a permanent state of turbulent flux (Poole, I974). Comprehensive assessment of aquatic ecosystems starts with an evaluation of habitat quality (Plaflcin et al. 1989). In its broadest sense, the term habitat defines where a species lives without specifying resource availability or use (Cowx and Welcomme, 1998). Habitat diversity is a more useful term than that of ecosystem diversity since habitats are easy to envisage. Furthermore, habitats ofien l have clear boundaries. So habitats have been termed as “template for ecology”(Southwood, 1977). Well over a decades ago, the fishery and natural resource agencies began adopting a habitat —based approach to impact assessment and resource inventory, and habitat now forms the basis of species conservation and management, mitigation, planning and environmental regulation. In comparison to population —based management, habitat has the advantages of being relatively stable through time and habitat is easily defined in intuitive physical terms and provide a tangle resource for negotiations and decision making. However, the validity of habitat-based management rests on a precise definition of what constitutes a species habitat, and accurate quantification of habitat quality (Bain and Hughes, 1996). Physical habitat or abiotic variables are believed to influence both the occurrence and biomass of fishes in stream systems, but these relations are not well understood for most species (Hubert and Rahel, 1989). The physical enviromnent selected by fish depends mainly on geological, morphological and hydrological processes that influence riparian vegetation and form a mosaic of stream channel and floodplain habitats (Keim and Skaugset, 2002). The potential capacity of a stream reach or stream segment to support a rich fish community depends on the habitat complexity. Fish species composition, abundance and age class structure of a specific population are determined by the organization, diversity and structure of the physical stream habitat (Cowx and Welcomme, I998). The biotic diversity and natural characteristic of fish communities are directly related to the variety and extent of natural habitats within a river basin. Consequently, a stream ecosystem has to have a complex habitat structure to maintain a healthy and diverse fish community (Cowx and Welcomme, 1998). Habitat is the principal determinant of biological potential of a stream and, as such, can be used to predict 2 biological conditions, particularly the presence and abundance of fish (Gorman and Kart 1978; Plaflcin et al. 1989; Rankin 1989). On this basis the Conservation International (CI) developed the Rapid Assessment Programme (RAP) to provide information necessary to develop a rational conservation management strategy for a particular area. In a review by WWF, IUCN and UNEP on ways of conserving genetic diversity of fieshwater fish it was recommended that the best way to conserve species diversity is to conserve habitats (Naiman, 1991). The convention on Biological Diversity was negotiated before the United Nations Conference on Environment and Development (UNCED) held in Rio de J aneiro in l992.0ver 175 cotmtries are now part of this convention which aims at to conserve biodiversity through its sustainable and equitable use. Signatory countries have indicated that they are aware of the general lack of information regarding biological diversity and have agreed to enhance scientific and technological studies to provide the basic knowledge required to implement biodiversity conservation strategies. On the basis of habitat the biodiversity measures have been divided into alpha diversity (within-habitat), beta diversity (between -habitat) and gamma diversity (Landscape diversity). Alpha diversity deals with the species interaction within a habitat (Whittaker, 1960,1967) while beta diversity deals with the species interactions between habitat or community (Whittaker, 1960). Gamma diversity or landscape diversity is the most complex type of diversity measure and was defined as the mosaic of habitats over larger scales ofien hundreds of km (Whittaker, 1960; Cody 1986). There are many reasons why humans should be concemed with biodiversity conservation. Organisms provide a wealth of resources and ecological services that benefit humans. Biotic resources include food, building, materials, firewood and medicines. Many organisms bring significant pleasure and humans also have a moral 3 and ethical responsibility to care for the environment and the variety of life it supports (Osborne, 2000). An estimation of the socio-economic benefits accruing from biological diversity at United States revealed that about 4.5% of the GDP of the nation(approximately 87 billion US dollar per year) originates from the collection and catching of wild species(Keating, I993). Even if this is the condition in U.S.A what will be the benefit of biodiversity conservation accrued in a biodiversity hotspot like India? Scientists estimate that over the next 25 years more than a million species of plants and animals will become extinct (Wilson, l988;Ehrlich and Wilson, 199l;Sou1e, 199]). The ever-increasing demand for resources in terms of land area (agriculture, urbanization, industry, Leisure) materials (food, construction materials) and energy from an ever-increasing population and the attendant array of harmful effects (pollution, degradation, fragmentation and disappearance of habitats) constitute the greatest threats to the integrity of ecosystems and, consequently, to biodiversity. National Research Council outlined the five important and widespread human impacts on biodiversity and placed habitat loss and degradation as the prime factors responsible for biodiversity decline. On this basis Solbrig(l99l) opined that in order to ensure the maximum quantity and quality of renewable resources for ourselves and our descendants ,we must leam to use resources sustainably. Habitat based approach has following applications in wet land ecosystem studies (1) for the proper understanding and management of human impact on fish diversity (2) to study the relationship between habitat variables and species assemblage structure (3) to quantify the extent of ecosystem degradation (4) to develop the Habitat Suitability Index (HSI) models of individual species (5) to classify the river reaches 4 based on their physical conditions and instream habitat features (6) to study the habitat quality and biotic integrityof the ecosystems. l.lHabitat concept Fish in rivers depend on undamaged interactive pathways along four dimensions, i.e. longitudinal, lateral, vertical and temporal. The longitudinal pathway refers to the migration of fishes that are very essential for reproduction and rearing of larvae and young fish. The presence of barriers will definitely affect the species composition of fish populations both above and below. This barrier - effect view of the way in which fish communities are distributed in river ecosystems relates to the effect of longitudinal pathways and is connected to the habitat-centered view. The lateral dimension suggests that the interactions between riparian vegetation and the river channel provide suitable habitats such as inshore zones, comected backwaters and the various types of stagnant water bodies. These habitats serve not only as preferred feeding and refuge areas but also as spawning areas, depending on the fish species. The vertical dimension refers to riverine groundwater interactions and concems mainly fish species that bury their eggs in gravel depressions. Habitat requirements of eggs and embryos during incubation in substrate interstices are different from those of fish living in the open water. To ensure the development of the embryo, sufficient water must flow at sufficient depth through the gravel as to supply the eggs and embryo with oxygen and carry away metabolic wastes. Hydrological processes in the groundwater-river exchange play an important role for successful reproduction of lithophilic fish. In addition to the above three pathways of interactions, the fish community structure is also significantly influenced by the local habitat conditions itself. Fish species 5 composition, abundance and age class structure of a specific population are determined by the diversity and structure of the physical stream habitat which is contributed by the channel geomorphology, substrate, instream cover and riparian zone conditions. 1.1.1. Channel geomorphology Based on the landscape, the valley through which the river passing was classified into the following types Colluvial: Landslides from adjacent hill slopes deliver sediment and organic matter and usually the riverbank is ‘V’ shaped Alluvial: The sediment is transported only by stream flow and usually the bank is an overhanging type. Bedrock type: The bedrock valley has little soil and the river bank is mainly formed of bedrock. A charmel reach is a channel segment with relatively repetitions and homogenous sequence of physical processes and habitat types (eg. Homogenous slope, habitat, channel type and riparian features). A river system can be divided into three zones (l) Erosion zone (2) sediment transfer zone and (3) deposition zone. In erosion zone channel slope is relatively steep and deposition of sediment, if it occurs is localized. The eroding nature of the charmel ensures that the substrate particle size is large (cobbles and boulders) and, occasionally the river may be eroded to the bedrock. The steep channel slope and coarse substrate may produce turbulent flow, in which the river reaches may be bedrock, cascade, step pool or pool-riffle type. The sediment transfer zone is a region in which river gradient is reduced so that water and sediment are transported with little net loss or gain. Substrate particle size is dominated by sand and gravel and flow is relatively smooth and unbroken. Usually 6 the charmel reaches in the sediment transfer zone is either pool-riffle, braided, plane bed type or regime type. The deposition zone is where the river deposits its sediment load, typically as it approaches the sea and develops a delta or an estuary. The substrate is dominated by fine silt and the reach is usually a regime type. Based on the physical parameters such as channel pattern, charmel confinement, gradient, streambed and bank materials the stream reaches may be classified into following categories (Anon, 2000). Cascade reach Cascade reach is characteristic of steepest alluvial channel. A few small pools may be present but majority of flowing water tumble over and around boulders and large woody debris. Pool-riffle reach The reach characterized by the alternative iiffles and pools and is very prevalent type of reach in alluvial valley of low to moderate gradient. The reach is most commonly associated with low to midsize streams. Braided reach This reach is characterized by numerous grave and sand bars scattered throughout the channel. This habitat is a sign of water scarcity and degradation. No fish species like to stay in this habitat. Regime reach This reach is very cormnon in low gradient meandering channels (downstreams) with predominantly sandy substrata. The reach is characterized by deeper areas with very low or negligible flow rates. Step-pool reach 7 Step-pool reach is rare and found only in the upstream reaches. This habitat is formed due to the accumulation of boulders and logs that forms a series of steps alternating with pools containing finer substrata Plane bed reach This reach is characterized by long relatively straight channels of uniform depth. Due to the low diversity of channel geographical units no common fish species is available from this reach. Bedrock reach This reach exhibits little or no alluvial bed material or valley fill and are generally confined by valley walls and lack flood plains. Plate l.l.depicts the 7 different types of channel reaches in riverine ecosystems,while the common fish species available in various channel reaches of Kerala rivers are shown in Plate 1.2 to 1.6. All the 7 types of channel reaches were formed of numerous channel geographical units (CGU) or microhabitats and the percentage occurrence of each type of microhabitat have significant influence on the distribution and abundance of fishes in the respective reaches (Lachavarme and Juge,l997). The microhabitat for an individual fish is the site where the fish is located at any point in time. The chamiel geographical units are of the following types. 1. Fast water 1.1. Turbulant 1.1.1. Falls 1.1.2. Cascade 1.1.3. Rapids 1.1.4. Riffle R 1.1.5. Chute 1.2. Non turbulent 1.2.1. Sheet 1.2.2. Run 2. Slow water 2.1. Scour pools 2.1.1. Eddy pools 2.1.2. Trench pools 2.1.3. Mid-channel pools 2.1 .4. Cinvergence 2.1.5. Lateral pools 2.1.6. Plunge pools 2.2. Dammed pools 2.2.1. Debris 2.2.2. Landslide 2.2.3. Backwater 2.2.4. Abandoned channel Instream cover Cover is defined as the structured material (Boulders, logs or stump), channel features (ledges, vegetation) and water features (turbulence or depth) in the wetted channel or within lm above the water surface that provides hiding, resting or feeding places for fish. The various cover types are of the following. 1. Turbulance; It is defined as cover when the water velocity in a stream at a given point varies erratically in magnitude and direction and disrupts reaches with laminar flow. 9 2. Woody log: All the woody debris more than I cm of diameter must be recorded along with its length. The woody logs/debris less than 10cm is classified as small woody debris while the woody logs larger than 10cm are classified as large woody debris. 3. Vegetation: The vegetation seen in the stream and also overhanging the stream may be calculated and the dominant species may be noted. The vegetation may be classified as emergent, floating, submerged and overhanging. 4. Depth: Depending on water transparency provides surface concealment for fish 5. Boulder: Stream substrate particles with diameter more than 256mm provides cover when they create a turbulent white water surface layer, scour out pool or overhang the stream. 6. Undercut bank: Stream bank where the base is cut away by the water and overhangs the part of the stream. Substrate Substrate refers to the bottom material of the water body and it is almost always documented in habitat studies because of the following reasons 1. The substrate determines the roughness of the stream which influences channel hydraulics 2. Substrate provides micro conditions needed by many fish species (foe spawning) 3. Substrate provides clue to local and water shed influences on stream habitat quality. Based on the particle size the substrate may be classified into 6 types which are illustrated in Table l.l. Quality of substrate IO The quality of the substrate is determined by delineating the embedness of the substrate. Embedness is a substrate attribute reflecting the degree to which larger particles (boulders cobble and gravels) are covered by fines (sand, silt and clay). Table l.2.shows the criteria to detennine quality of substrate based on the embedness level. Riparian zone: The vegetation on land surface on land adjacent to the normal high waterline of the stream, extending to the portion of land that influenced by the presence of adjacent ponded or channeled water. Based on the water retention capacity the riparian zone was classified into Hydroriparian: The soil/substrate is rarely/briefly dry and wet riparian plant dominate vegetation Mesoriparian: The soil/ substrate is dry seasonally Xeroriaprian: The soil/substrate is wet less than one month a year 1.2. Stream classification A classification of river is an organization of data on stream features into discreet combinations. It has long been a goal of individuals working with rivers to define and understand the processes that influence the pattem and character of river systems. The differences in river systems, as well as their similarities under diverse settings, pose a real challenge for study. One axiom associated with rivers is that what initially appears complex is even more so upon further investigation. Underlying these complexities is an assortment of interrelated variables that determines the dimension, pattem and profile of the river system. Stream pattern morphology is directly influenced by eight major variables including channel width, depth, velocity, discharge, channel slope, roughness of the channel materials, sediment load and sediment size (Leopold et al. 1964). Because stream morphology is the product of this ll integrative process, the variables that are measurable should be used as stream classification criteria. Obiviously a classification scheme risks oversimplification of a very complex system. While the classification of river systems based on channel morphology is essential to Iihieve the following objectives 1." Predict a river’s behavior from its appearance Develop specific hydraulic and sediment relations for a given morphological dlllllnel type and state 3.jPIoVide a mechanism to extrapolate site-specific data collected on a given stream Inch to those of similar character a consistent and reproducible frame of reference of communication for with river systems in a variety of professional disciplines streams is not new. Davis (1899) first divided streams into three on relative stage of adjustment: youthfill, mature and old age. systems based on qualitative and descriptive ifsubsequently ..-I‘: developed by Melton (1936) and Matthews (1956). 3' 3*‘-.| i '='--\..| -- - - -. i=2 §3| wormed (1951) divided the streams into straight, meandering and typu. Schumm( 1963) classified the river stretches based on channel sl'abiIity(stable, eroding or depositing)and mode of sediment transport(mixed load, qlapended load and bedload). Culbertson et al. (1967) utilized depositional features, vegetation, braiding patterns, sinuosity, meander scrolls, bank heights, levee formation and flood plain types. Thombury(l969)classified the river stretches as antecedent, superposed, consequent and subsequent based on valley types. Khan (I971) developed a quantitative classification for sand-bed streams based on sinuosity, slope and charmel pattern. To cover a wide range of stream morphologies, a 12 Ill. (1972, 1976), Galay et aI.(l973) and Mollrd(l973). Schumm (1977) developed a based on sediment transport, channel stability and some physical river. stretches. Based on the physical properties of the river stretches ~%\§iBlo$tt(l978)described four channel types such as braided , braided point ‘point bar and equi width point bar. Church and Rood (1983) classification,. system for alluvial river channels. Rosgen(1994) developed .'~.5l;t . system based on sinuosity, entrenchment ratio, w/d ratio, slope and typeof dominant substratlmi in the river reaches after field observation of hundreds of of various sizes in all the climatic regions of North America. Although fish community analyses have used numerous approaches, analytical procedures for habitat data are still relatively new. Approaches to habitat analysis have involved using habitat indices (Fajen and Wehnes l982;Plafl Rlnkin l989;Petersen l992;Wang et a1.l998; Goldstein et al.l999), Habitat quantification models (Terrel et al. 1982, Nestler et al. 1989; Baker and Coon 1997), examination of habitat gradients (Schlosser 1982) or analysis of habitat preference (Rosenzweig 1981; Nelson et al.l992). All these analysis are composed of various measures called metrics that are designed to rate the streams physical environment. The metrics rate the various aspects of the enviromnent in several categories; channel geomorphology, Riparian zone, substrate, instream cover and biology (Stauffer and Goldstein, 1997) 1.3. Habitat indices Indices that characterize habitat are important for proper interpretation of biological smvey results (Plafldn et al. 1989) by providing an enviromnental context. Moreover, the habitat indices can serve as tools for rapid appraisals of habitat quality before an 13 dacriptive classification scheme was developed for Canadian rivers by Kellerhals et Ill. (1972, 1976), Galay et aI.(l973) and Mollrd(l973). Schumm (1977) developed a based on sediment transport, channel stability and some physical river. stretches. Based on the physical properties of the river stretches ~%\§iBlo$tt(l978)described four channel types such as braided , braided point ‘point bar and equi width point bar. Church and Rood (1983) classification,. system for alluvial river channels. Rosgen(1994) developed .'~.5l;t . system based on sinuosity, entrenchment ratio, w/d ratio, slope and typeof dominant substratlmi in the river reaches after field observation of hundreds of of various sizes in all the climatic regions of North America. Although fish community analyses have used numerous approaches, analytical procedures for habitat data are still relatively new. Approaches to habitat analysis have involved using habitat indices (Fajen and Wehnes l982;Plafl Rlnkin l989;Petersen l992;Wang et a1.l998; Goldstein et al.l999), Habitat quantification models (Terrel et al. 1982, Nestler et al. 1989; Baker and Coon 1997), examination of habitat gradients (Schlosser 1982) or analysis of habitat preference (Rosenzweig 1981; Nelson et al.l992). All these analysis are composed of various measures called metrics that are designed to rate the streams physical environment. The metrics rate the various aspects of the enviromnent in several categories; channel geomorphology, Riparian zone, substrate, instream cover and biology (Stauffer and Goldstein, 1997) 1.3. Habitat indices Indices that characterize habitat are important for proper interpretation of biological smvey results (Plafldn et al. 1989) by providing an enviromnental context. Moreover, the habitat indices can serve as tools for rapid appraisals of habitat quality before an 13 extensive biological survey is undertaken and the use of habitat indices allows sampling of sites that have comparable habitat quality (Stauffer and Goldstein, 1997). 1.3.1. Habitat quality (HQ) scoring Habitat quality scoring are composed of various measures called metrics that are dwigned to rate the stream’s physical environment.The metrics rate the various Ipeets of the environment in several categories; channel geomorphology, riparian mne, substrate and instream cover and biology. The sum of the ratings of all the IIlI:tl'ics produces the total index score. The correlation of habitat index score with fish immunity statistics is a means of evaluating the effectiveness of the habitat indices in particular sites or geographic areas because the relative composition of a fish is a sensitive indicator of direct and indirect stresses on the entire aquatic leosystem(Fausch et al.1990;Karr l99l).Gorman and Karr(l978)correlated stream | /-.> F.-~ . r Ulitat diversity with fish species diversity in selected streams in Indiana and Panama 1 . -'1 ix Md suggested that fish community characteristics for a particular segment of a stream Q13\. . .‘. determined by the complexity of habitats present in the area. v I 1.3.2. Biotic integrity .5 _ x F}-ii"-I The physical, chemical and biological integrity of nation’s water resources can best be med by evaluating the degree to which waters provide the beneficial uses. Important uses as defined by society may include water supply, recreational and other uses as well as the preservation of future options for the use of the resource. Pollution may induce alteration in the chemical, physical, biological and radiological integrity of water. The environmental quality monitoring in the streams based on the development of thresholds and criteria levels for specific contaminants have the l ? . following drawbacks: !A It is not accounting the naturally occurring geographic variation of contaminants 14 -'~ ww _-_~,_-¢‘. ,v; j0 2. Not considering the suble effect or how it affects the aquatic fauna and flora (eg. reproduction, growth) 3. It misses many of the man induced perturbations such as flow alterations,habitat degradation, heated effluents and uses of power generation, etc. In short, criteria that emphasize chemical attributes of water are unsuccessful as surrogates for measuring biotic integrity (Kan and Dudley, 1981). Since an ability to sustain a balanced biotic community is one of the best indicators of the potential for beneficial use. Biological communities reflect water shed conditions since they are sensitive to changes in a wide array of enviromnental factors. Many groups of organisms have been proposed as indicators of enviromnental quality. Wisconsin natural resource department of United States pioneered the development of bioassessment and biomonitoring techniques based on benthic micro invertebrate community data during l9'70’s (Hilsenhoff 1977). Micro invertebrates and diatoms have been widely used in monitoring because of the availability of a theoretical substructure that allows an integrated ecological approach (Cummins 1974; Vamiote et al.l980). However, use of diatoms or invertebrates as monitoring targets has the following major deficiencies. l. They require specialized taxonomic expertise 2. It is difficult and time consuming to sample, sort and identify micro invertebrates and diatoms 3. Back ground life history information is often lacking for many species of microinvertebrates and diatoms 4. The results obtained by using diatoms and invertebrates are difficult to translate into values meaningful to the general public. 15 The procedure to use fish populations in bioassessment programme were first described by Dr. James Karr during I980 to assess biotic integrity and environmental quality in small streams in Indiana and Ilinois (Karr 1981, Karr et al. 1986). Fishes, have numerous advantages as indicator organisms for biological monitoring programs. These advantages include l. Life history information is extensive for most fish species 2. Fish communities generally include a range of species that represent a variety of trophic levels (omnivores, herbivores, insectivores, planktivores, piscivores) and include foods of both aquatic and terrestrial origin. Their position at the top of the aquatic food web in relation to diatoms and invertebrates also helps provide an integrative view of the watershed environment. 3. Fish are relatively easy to identify. Technicians require relatively little training. Indeed, most samples can be sorted and identified at the field site itself, with release of study organisms after processing 4. The general public can relate to statements about conditions of the fish community. 5. Both acute toxicity (missing taxa) and stress effects (depressed growth and reproductive success) can be evaluated. Careful examination of the recruitment and growth dynamics among years can help to pinpoint periods of unusual stress. 6. Fish are typically present, even in the smallest streams and in all but the most polluted waters. l6 1.3.2.1. Index of Biotic Integrity (IBI) scoring Index of Biotic integrity is a biological criterion. But its integration with the habitat indices are very essential to understand the community structure prevailing at different reaches of the river system. Karr and Dudley (1981) defined biotic integrity as ‘a balanced, integrated adaptive community of organisms having a species composition, diversity and functional organization natural habitats of that region. Although the specific attributes and expectations of the original version of IBI apply only to Indiana and Ilinois , the general principles underlying the IBI concept applied to many streams throughout the North America. Biologists and managers in other states of U.S.A and Canadian provinces found the IBI to be a useful assessment and evaluation tool and modified the IBI to fit the physical and biological characteristics of streams in their areas (Miller et al. 1988, Fausch et al. 1990). One of the most thorough modifications of the IBI has been done by the Division of Water quality and Monitoring and Assessment of the Ohio Environmental Protection Agency (Ohio EPA, 1988). The Ohio EPA developed several versions of the IBI based on hundreds of fish community, habitat and water quality samples from a wide variety of Ohio streams and rivers. The Ohio Environmental Protection Agency uses the IBI extensively and IBI scores have been incorporated in to Ohio water quality standards. In the present study, a pioneer attempt had been done to introduce the concept of Index of Biotic Integrity (IBI) scores to six major river systems of Kerala. The criteria used for IBI scoring mainly derived from the Wisconsin version of the Ohio EPA (Lyons, 1992) with suitable modifications compatible to the ecological conditions prevailing in the river systems of Kerala. 17 1.3.2.1. Index of Biotic Integrity (IBI) scoring Index of Biotic integrity is a biological criterion. But its integration with the habitat indices are very essential to understand the community structure prevailing at different reaches of the river system. Karr and Dudley (1981) defined biotic integrity as ‘a balanced, integrated adaptive community of organisms having a species composition, diversity and functional organization natural habitats of that region. Although the specific attributes and expectations of the original version of IBI apply only to Indiana and Ilinois , the general principles underlying the IBI concept applied to many streams throughout the North America. Biologists and managers in other states of U.S.A and Canadian provinces found the IBI to be a useful assessment and evaluation tool and modified the IBI to fit the physical and biological characteristics of streams in their areas (Miller et al. 1988, Fausch et al. 1990). One of the most thorough modifications of the IBI has been done by the Division of Water quality and Monitoring and Assessment of the Ohio Environmental Protection Agency (Ohio EPA, 1988). The Ohio EPA developed several versions of the IBI based on hundreds of fish community, habitat and water quality samples from a wide variety of Ohio streams and rivers. The Ohio Environmental Protection Agency uses the IBI extensively and IBI scores have been incorporated in to Ohio water quality standards. In the present study, a pioneer attempt had been done to introduce the concept of Index of Biotic Integrity (IBI) scores to six major river systems of Kerala. The criteria used for IBI scoring mainly derived from the Wisconsin version of the Ohio EPA (Lyons, 1992) with suitable modifications compatible to the ecological conditions prevailing in the river systems of Kerala. 17 1.3.3. Habitat Suitability Index models Most habitat models are based on co -variation between environmental variables and habitat use in the wild (Rosenfeld, 2003). Stream habitats are strongly hierarchical and habitat associations can be modeled at a variety of spatial scales. Usually three fundamental types of predictive models can be used to define habitat requirements from correlative data; distributional or macro habitat models, which predict the presence or absence of species at large spatial scales (eg., within different drainage basins);capacity models(multiple regression), which predict density or population size when a taxon is present (usually at the reach or channel unit scale) and microhabitat models, which predict habitat associations at a fine spatial scale.(eg. water velocities and depths selected by different species). Bioenergetic habitat models for stream fishes have recently been emerged as an additional class of habitat model. These models differ fundamentally from other model types in that they are inherently mechanistic (ie., their predictions are based on explicit biological mechanisms rather than observational data). Habitat suitability index models have a wide range of applications. To conserve the extreme fish germplasm resources and endemism, declaration of aquatic sanctuaries and mitigating anthropogenic activities, development of habitat suitability index (HSI) models are very essential. With the help of this infonnation, the species can be conserved in their natural habitats by way of maintaining the critical habitat parameters at threshold levels. These models are also vital in deciding the factors governing endemism. Habitat Suitability Index models are widely employed as an efficient tool for the conservation and management of the stock of indigenous fishes (Hubert and Rahel, 1989). These models are also useful either in simulating the required habitat in other regions of the same river or demarcating identical habitats 18 where the species can be transplanted. Habitat Suitability Index (HSI) models will give some technical guidelines for stream restoration and management activities. The monitoring and maintenance of the critical parameters deciding the distribution and abundance of endangered species will helps to maintain the physical, chemical and biological integrity of the river system and in effect reduce the ecosystem degradation. With this view the U.S Fish and wildlife service has developed a series of Habitat suitability index (HSI) models to describe and quantify habitat influences on the abundance of particular species (Terrell, 1984), which found its immense application for fish species conservation pro grammes. A combined analysis of diversity indices (Shanon-Weiner diversity index,Simpson index,Pieoleou’s evenness index, Margalef‘ s index) and Index of Biotic Integrity(IBI) scoring with habitat variables will unfold the extent of ecosystem degradation lmdergone in a water body. The diversity indices and the index of biotic integrity(IBI) scores so arrived at will give a summary picture of the biological potential of an area which is the net product of physico-chemical and biological conditions prevailing in the study area. According to Plafflrin er al. (1989) habitat is a principal determinant of biological potential and can be used as a general predictor of biological conditions or there are links between the diversity of species (biological diversity) and the way ecosystem functions (Osbome, 2000). According to Mac Aurthur(l972) and Cody(l975),diversity of habitat is the major factor determining the pattern of species diversity in an area, which is supported by the Krebs postulations. Krebs (1985) revealed that the more heterogeneous and complex the physical environment, the more complex the plant and animal communities and in a healthy ecosystem where the interaction between habitat variables and species diversity are more the abundance of each species is the product of same integer while overcrowding or degeneration of 19 any of the species occurs due to some habitat alterations. Portt et al.(l986) experimentally proved that reduction of the complexity of aquatic ecosystem drastically reduces establishment of large specimens.Schliosser (1982) and Lachvarme and Juge(l997) opined that habitat degradation may leads to the modification of trophic structure, reduction in the reproductive potential of the population leading to greater variability and smaller number of specimens in a population. S0 quantification of the extent of relationship between habitat variables and fish species descriptions such as diversity indices, fish abundance and index of biotic integrity (IBI) scoring are the ideal methods to quantify the ecosystem degradation brought about in a river system. Studies on community level is rather very common in temperate systems (Ross, I986), while tropical fish communities especially of the South Asia, are thoroughly under investigated (Wikramanayake and Moyle, 1989). Due to its immense applications in natural resource conservation in western countries like U.S.A., Canada and many European countries, habitat ecology had become the major component of biological research. But investigations on the fishes of the fluvial systems in Kerala or India are mostly limited to mere descriptions on taxonomy or distributions and in few cases, their biology, if the species are commercially important (Anm, 1997). The next level of understanding of fishes, ie, from species level to community/ assemblage level, sheds ample insight in to the structure and ftmctioning of fish communities in natural systems. The present study is a pioneer attempt in this line to assess the impact of human intervention in the habitat and biotic integrity of six major river systems of Kerala, which would be usefial in impressing upon the seriousness of habitat degradation and biotic devastation thus enabling the concerned to adopt relevant conservation and management steps to conserve the resources. An attempt was also 20 made to study the biology of an endemic fish species Puntius carnaticus (Jerdon, 1849), which would be a better substitute for grass carp in aquaculture basket of our country. So it is hoped that the results of the present study will open new vistas for the conservation of threatened freshwater fishes, demarcation and declaration of aquatic sanctuaries, and overall, for developing better management and restoration measures for the lotic ecosystems of the country. Against this background the present study was undertaken with the following objectives l. To study the physical (channel geomorphology and riparian zone) and chemical conditions and instream habitat (instream cover and substrates) in six major river systems of Kerala 2. Based on some physical ratios (sinuosity, entrenchment ratio, w/d ratio, slope) and dominant substrates classify the river stretches up to Rosgen’s II level. 3. To study the biotic integrity and habitat quality (HQ) in six major river systems of Kerala 4. To study the biodiversity status of six major river systems in Kerala 5. To quantify the extent of ecosystem degradation due to increased human intervention and suggest mitigation measures 6. To develop the Habitat Suitability Index (HSI) models of 10 endemic and endangered freshwater fishes endemic to the streams of Westem Ghats 7. To study the food and feeding, reproductive Biology, length-weight relationship and condition factor, age and growth and population dynamics of P. carnaticus for evaluating the suitability of the species for aquaculture. The results of the present study are organized under 2 sections comprising a total of 13 chapters. The first section consists of 6 chapters, dealing with the habitat 21 structure and habitat-species relationships in six major river systems of Kerala. While the results of life history traits of P. carnaticus are presented under section 2. The first chapter under section l is the general introduction and review of literature wherein a general outline on the necessity of habitat inventory, rationale and the present scenario of habitat ecology are clearly illustrated. Materials and methods employed to comply the objective of the study are adequately explained in chapter 2.Location wise instream habitat and physico-chemical conditions at selected reaches in six major river systems of Kerala are presented in chapter 3.Besides, the charmel classification, habitat quality (HQ) scoring and Index of Biotic Integrity (IBI) scoring of the selected locations are also given in this chapter. The fish diversity of six major river systems based on the diversity indices such as Shamion-Weiner diversity index, Simpson index, Pieolou’s evenness index and Margalef’ s index are summarized in Chapter 4.While Chapter 5 embodies the results of quantification of extent of ecosystem degradation undergone in six major river systems of Kerala.The results of Habitat Suitability Index(HSl) models developed for I0 threatened and endemic freshwater fishes of Kerala are presented in chapter 6.The salient features of Rcarnaticus along with its systematic position are described in chapter 7 under section 2.The results of qualitative and quantitative aspects of food composition in relation to sex, size and season, seasonal variation in feeding intensity as well as gastro-somatic index are presented in chapter VIII. In chapter IX, an attempt is made to investigate the maturation and spawning of P. carnaticus using different methods. Length-weight relationship of males, females and indeterminates was established by the general linear equation and are presented in chapter X. While chapter XI deals with the age and growth studies in P. carnaticus. Population dynamics of P.carnaticus are '7') presented in chapter XII. Chapter XIII gives a summary of the thesis together with relevant recommendations on the basis of the results of the present study which would be useful for the conservation of the unique fish diversity richness in the river systems of Kerala.This chapter is followed by a list of references cited and appendices. 23 Plate 1.1 Seven different types of channel reaches in riverine ecosysystems Step-pool reach Plane bed reach Bedrock reach Braided reach Cascade reach Plate 1.2 Common fishes seen in Cascade reaches of Kerala rivers Tor pUlilora (Hamilton - Buchanan,1822) Plate 1.3 Common fishes seen in Pool-rime reaches of Kerala rivers Osteocheilichthys nashi (Day,1868) Chela dadidurjori(Menon,1952) Gonoproktopterus dubius (Day, 1867) Pun/ius conchonius (Ham-Buch) Neolissochilus wynaadensis (Day, 1873) Plate 1.4 Common fishes seen in Regime reaches of Kerala rivers Gonoproktopterlls eUrmuea (Ham-Buch, 1807) Pristoiepis marginata Jerdon,1848 Channa micropeiles (Cuvier, 1831) Allabas testlldinells (Bloch,1795) Horabagrus braehysoma(Gunther, 1864) Plate I.S Common fishes seen in Step-pool reaches of Kerala rivers Basrilius galensis (Valenciennes,1844) Bhavania auslralis (Jerdon, 1849) Plate 1.6 Common fishes seen in bedrock reaches of Kerala rivers Gonoprokloplerus micropogon periyarensis Raj 1941 a L..:":'~::~::: /ongidorsalis Petiyagoda & Kottlet,1 Chapter 2 Materials and methods 2.1. Description of the study area Detailed habitat inventory and species assemblage studies were conducted during January 2001 to January 2004 at a total of 91 locations of six river systems viz.Periyar ,Chalakudy,Kabbini,Kallada,Pamba and Bharathapuzha river systems giving due representation to all the seven types of channel reaches. The itirinary of river systems where detailed habitat and species inventory were conducted are given in Table 2.1. Kabbini river passes through the neighbouring Kamataka state and drains into Bay of Bengal. 15 locations encompassing between 721-946m MSL were investigated. In Kabbini river system, the sampling stations were located between I10 30’ 59N in the downstream and 76°02’06 E in the upstream, which also accommodates I, II and III order streams. In Bharathapuzha river system, 27 locations were studied including the main stretch, tributaries such as Gayathripuzha, Kunthipuzha, Kanjirapuzha and Chitturpuzha and some I order streams above Malampuzha, Mangalam dam and Meen vallam region. All the locations were embarked between 18.4-1001m MSL. In the main river stretch II, III and IV“ order streams between 10°45’00N and 76038’85E in the upstream and 10°45’ 1 IN and 76°I6’49E in the dOWn stream were studied. In Gaythripuzha the 11 order river stretch between 10°35’2lN and 76°30’22E in the upstream and 10°82’46N and 76°39’25E in the downstream were investigated. In Kunthipuzha I and II order streams in between l1°08’37N and 76°26’35E in the upstream and l0°59’23N and 76°l6’49E in the downstream were surveyed. In Kanjirapuzha I order stream between l0°58’09N and 76°32’59E in the upstream and l0°58’27N and 76°29’54E in the dOWn stream were 24 studied. In chitturpuzha III order river stretch between l0O4l’28N and 76044’33E in the upstream and l0°43’2lN and 76034’ 16E in the downstream were surveyed. In Kallada river system a total of ll locations were studied including the main stretch, tributaries such as Kulathupuzha, Kazhuthuruty Ar and Chenturuny Ar. All the locations were between 20.3 to 641m MSL. In the main river stretch III order streams between 8°56’02’ and 77005’53E in the upstream and 8059’ l2N and 77001’ l4E in the downstream were studied. In Kulathupuzha I and II order streams between 8°8048’29N and 7707’ 18E in the upstream and 8056’llN and 77004’l1E in the down stream were surveyed. In Kazhuthuruty river I and II order streams in between 8058’58N and 77009’l8 E in the upstream and 8057’54 N and 77005’26 E in the downstream were surveyed. Only a single location (8048’29N and 77007’ 18E) were studied in Chenturuny river, which is, a I order tributary of Kallada river system. In Pamba river system a total of l5 locations were surveyed including the main river stretch, tributaries such as Kakkiyar, Kochupamba and Azhutha. In the main river stretch HI and 1v'*' order streams between 9°24’-491\1 and 76°52’33E in the upstream and 9°l9’53N and 76040’35E in the downstream were investigated. In Kakkiyar I and II order streams between 9°l6’22N and 770091 IE in the upstream and 9°20’25 N and 76°56*30 E in the downstream were studied. In Pamba II order streams between 9024’50N and 77°04’l8E in the upstream and 9°24’31N and 7700l’28E in the downstream were observed. In Azhutha II order streams between 9025’54N and 76056’23 E in the downstream were stuveyed. 25 Chalakudy river flows in the Western direction and drains into the Arabian sea at the northem end of the Cochin Backwaters. A total of 20 locations encompassing between 40- 996.4m. MSL were studied which include the main river stretch and major tributaries S11Ch as Sholayar, Parambikulam and Karrapara. In the main n'ver stretch locations between l0°22’45N and 7t>°40*01-5 m the upstream and 10°17’32N and 76°34’66N in the down stream having only third order streams were studied. In the Karappara tributary I and 11 order streams between 10°26’ l3N and 76°35’ 19E in the upstream aha l0°23’46N and 76°43’0 E in the down stream were surveyed. In Sholayar, locations between l0°l8’62N and 76°52’20E m the upstream and l0°23’l0N and 76°39’43E m the down stream having both I and II order streams were investigated. In Parambikulam, tributary locations in the I and II order streams between l0027’27N and 76°39’43E in the upstream and 10023’ ION and 76039’43E in the downstream were surveyed. Periyar river system is flowing in the Westem direction and drains into the Arabian sea through Cochin Backwaters. Habitat inventory and species assemblage studies in this river system were conducted at 29 selected locations in the middle and high plains located between 20 - l540m.MSL. Sampling sites were located in the main river stretch and also in two tributaries such as Neriyamangalampuzha and Pooyamkuttypuzha. The main river stretch located between 9°l8’40N and 77°17 ’22E in the upstream and 10°2’5lN and 76°4s’15 E m the downstream which embark 1, 11.111 and Iv“ order streams were investigated. In Pooyamkuttypuzha II and III order streams betweenl0°07’30N and 76050’lOE in the upstream and 9°58’39N and 77°03’28E in the downstream were surveyed. In Neriyamangalampuzha the II order river stretch between 26 10°05”/N and 77°03’42E in the upstream and l0002’5lN and 76°48’l5E in the downstream were investigated. 2.2. instream habitat and physical conditions The site selection for habitat inventory was based on physical features such as channel pattern, channel confinement, gradient, streambed and bank bed materials (Anon, 2000). Maximum length of each reach was 10 times the average channel width. For habitat analysis, each site was divided into six equally spaced transect with 4 equally spaced sampling points on each transect (Hubert and Rahel, 1989). These procedures yielded at each site 24 measurements on nature of microhabitats, instream cover, substrate, flow velocity and lux, 12 measurements for riparian and bank features, 6 measurements for w/d ratio, entrenchment ratio and slope and one measurement each for sinuosity, dissolved oxygen, pH, TDS, conductivity and hardness. The physical and chemical parameters of the river at each sampling point, reach descriptions such as sinuosity, entrenchment ratio, width/depth ratio, mean channel width, mean channel depth, slope, nature of riparian zone, substrate, instream cover and nature of microhabitats were studied based on Hubert and Rahel(1989),Edds(l998)and Anon(2000). Geographical Position of the selected zones was recorded using hand held GPS while altitude was measured using electronic altimeter. The dissolved oxygen and pH were measured using Eutech cyberscan D0100 dissolved oxygen meter and pH meter respectively. Light intensity on the surface water was measured from all the four sampling points on each transect using TES 1332 digital lux meter. Flow velocity was measured with a water current meter at 0.5m of the water depth at three equally spaced 2'7 points across each transect.Temperature was measured using thermometer while total hardness and alkalinity were estimated following APHA (1992). 2.3. Fish sampling regime For analyzing the species assemblage structure, sampling of fishes was at all stations selected for habitat inventory. Samples were collected during 8:00-18:00 h and 20:00 06:00 h. using monofilament and multifilament gillnets of different mesh sizes (32,34,64,78 and l00mm), cast net (mesh size: 16 and 22mm) and hand/scoop nets (mesh size: 6and 8mm). The fishing effort was made uniform at all the sampling locations. The fishes were identified following Day (1878; 1889), Jayaram (1981) and Talwar and Jhingran (1991). Required specimens for laboratory examination were preserved in 10% fonnalin while the rest of the fishes were released back into the system without any damage. 2.4. Stream classification The river reaches identified for habitat study were classified upto Rosgen’ II level following Rosgen(l994)(Table 2.2& 2.3). 2.5. Habitat quality scoring The habitat quality scoring of the selected locations in Periyar river was done based on Lyons (1992). But to suite with the environmental conditions prevailing in Westem Ghats streams, the fifth rating item such as BB ratio in the original habitat quality scoring system was replaced by sinuosity and w/d ratio. Appropriate changes were also incorporated in the qualitative evaluation of the habitat quality scoring. The metrics used for habitat quality scoring and scoring criteria were shown in Table 2.4.The qualitative evaluation of habitat quality scoring is shown in Table 2.5. 28 2.6. Index of Biotic Integrity scoring Species richness This metric is a common measure of biological diversity that generally decline with environmental degradation (Karr, 1981). The original metric of Karr (1981), total number of species was modified to number of native species in the Wisconsin version (Lyons, 1992). The number of native species used is a measure of biological diversity that typically decreases with increased degradation (N oss, 1990). Species composition In the present study the three metrics, number of darter species and number of sunfish species were replaced by number of loach species, sucker species and number of water coloumn species. Lyons (1992) suggested these substitutes and they are common substitutes when IBI is modified for using outside the United States (Hughes and Oberdorff, 1999), Ganasan and Hughes (1998) also used the modification for central Indian rivers and included both large and small benthic species in this metric, for accommodating both darter and sucker substitute metrics. Both these two metrics are strongly responsive to change in water quality and habitat structure like siltation, turbidity, reduced oxygen content and toxic chemical (Oberdorff and Hughes, 1992). Water column species are medium sized, midwater species, which tend to occur in pools or other areas of slow moving water. They are active swimmers that typically feed on a variety of invertebrates or other fishes (Lyons, 1992; Ganasan and Hughes, 1998). The metrics such as percent sucker, percent intolerant species and percent tolerant individuals were retained as such. Suckers are large bentic species that generally live in pools or runs, although a few species are common in riffles. Some species are intolerant of 29 enviromnental degradation, whereas others are tolerant (Lyons, 1992). The metric, number of intolerant species was retained as it declines with environmental degradation (Karr 1981, Lyons, 1992). Trophic composition The three metrics namely percentage omnivore, percentage top carnivore and percentage insectivore were retained as such while percentage of simple lithophilous spawners were replaced by percent herbivore species. This herbivore metric as proposed by Ganasan and Hughes (1998) is significant in tropical and subtropical rivers where such species are vital trophic components, a view supported by Hughes and Oberdorff(l999). Moreover herbivores being sensitive to physical and chemical alteration in habitat are indicative of primary production status in the site. Fish abundance and condition correlation factors The metrics such as number of fishes per 300m sampled (excluding tolerant species) and percent with deformities, eroded fins, lesions, or tumors were retained. Total number of individuals is a gross measure of fish production and is lowest in highly disturbed systems (Lyons, 1992). The metric percent of fish with anomalies has been an important indicator of highly degraded zones in the rivers (Karr et al. 1986; Hughes and Gammon, 1987; Ganasan and Hughes, 1998). The number of individual fish with skeletal or scale deformities, heavily frayed or eroded fins, open skin leis ions, or tumors, that are apparent fi'om an external examination were only considered in the anomaly category. Fish with heavy parasite burdens were not included in this category unless the parasites have caused deformities or lesions. Also fish with anomalies that are only visible after dissection were not included. 30 Calculation of IBI metrics: The scoring criteria was developed (Table 2.6) as per the methods of Lyons (1992). The maximum values obtained for the metric ‘total number of native species, number of loach species, number of sucker species, number of midwater species, number of intolerant species, percent omnivores, percent insectivores, percent top carnivores, percent herbivores and number of individuals per 300ml are indicators of the least disturbed condition. Maximum values for the metric % tolerant, %omnivores and %individuals with anomalies or disease are indicators of highly altered habitat conditions. The qualitative evaluation of the IBI scores (Table 2.7) were done following Lyons (1992) and Karr et al. (1986) with a slight modification based on the ecological conditions prevailing in the Western ghat streams. 2.7. Calculation of Diversity indices: Once the identification is confirmed the number of specimens belonged to each species from each location were enumerated and used for calculating biodiversity indices such as Shanon-Weiner index, Simpson index, Margalef’ s index and Piele0u’s evenness index using the statistical software Primer V5(Plymouth Routines in Multivariate Ecological Research, Clarke and Wa1wick,200l).The diversity indices so calculated for each location were further compared using two way ANOVA (Schender and Cohran, 1967) to confirm whether there is any significant variation in diversity at same altitudes in different river systems and also between different altitudes in same river system. l. Shanon-Weiner (Shanon and Weaver, 1949), diversity index was used to emphasize species richness 31 Calculation of IBI metrics: The scoring criteria was developed (Table 2.6) as per the methods of Lyons (1992). The maximum values obtained for the metric ‘total number of native species, number of loach species, number of sucker species, number of midwater species, number of intolerant species, percent omnivores, percent insectivores, percent top carnivores, percent herbivores and number of individuals per 300ml are indicators of the least disturbed condition. Maximum values for the metric % tolerant, %omnivores and %individuals with anomalies or disease are indicators of highly altered habitat conditions. The qualitative evaluation of the IBI scores (Table 2.7) were done following Lyons (1992) and Karr et al. (1986) with a slight modification based on the ecological conditions prevailing in the Western ghat streams. 2.7. Calculation of Diversity indices: Once the identification is confirmed the number of specimens belonged to each species from each location were enumerated and used for calculating biodiversity indices such as Shanon-Weiner index, Simpson index, Margalef’ s index and Piele0u’s evenness index using the statistical software Primer V5(Plymouth Routines in Multivariate Ecological Research, Clarke and Wa1wick,200l).The diversity indices so calculated for each location were further compared using two way ANOVA (Schender and Cohran, 1967) to confirm whether there is any significant variation in diversity at same altitudes in different river systems and also between different altitudes in same river system. l. Shanon-Weiner (Shanon and Weaver, 1949), diversity index was used to emphasize species richness 31 H’ = -sigma pi loge (pi) where pi is the proportion of the total count arising from the ith species. The natural logaritham is used for biological interpretation. 2. Margalef’ s index was used to measure the number of species present for a given number of individuals. d=(S-l) Log N, where S is the total number of species and N the total number of individuals 2. Simpson index 1-7» is a equitability or evermess index, its largest value correspond to the equal abundance of all the species present in the ecosystem. This index has the natural interpretation as the probability that any two individuals chosen at random, are from the same species. 1- 7L = 1- (epiz) where pi is the proportion of the total count(or biomass) arising from the ith species 3. Evenness of the community was calculated using Pielou’s €V8I1I16SS index(Pielou, 1984) J’ =H’/H’ ma, = H’/log S where H’ma,. is the maximum possible value of Shannon diversity and S is the total number of species 32 2.8. Relationship between habitat variables and species assemblage structure: Shanon-Weiner diversity index, fish abundance and index of biotic integrity were the fish community descriptions used to calculate the relationship between habitat variables and species assemblage structure. In the case of instream habitat and physical conditions Principal Component Analysis (PCA) was used to reduce the number of variables in the data set (Primer V5). For rivers having more number of sampling points the number of PCA axes were fixed to ten while rivers having comparatively less number of representative zones number of PCA axes were reduced to seven. In each axes the parameter showing the highest value was selected for further multiple regression analysis. To find out the extent of relationship between fish population and habitat conditions multiple regression analyses was perfonned between selected instream habitat and physical condition variables with Shanon-Weiner diversity index, fish abundance and index of biotic integrity scores. Regressions were considered significant if the corresponding P-values did not exceed 0.05. 2.9. Habitat Suitability Index models: Physical and instream habitat measurements and population estimates at each site were pooled for statistical analysis using Statistical Package for Social Sciences (SPSS for Windows) software. All the variables having significant (P_<0.05) correlation with the species abundance were further analyzed by simple regression to study the effect of each variable on the occurrence of individual species. Multiple regression models so developed were used in explaining the combined effect of the crucial factors responsible for the endemism of ten critically endangered species studied. 33 Table 2.1.ltinera7|y of river 5 tqns sgrvged for Qablgt a7ngl §__gecl7g7s in7ventory details glamg of 7the |jveL Qumbgr 97f suryelg §eas9ns_ gurgeygq s sjem 7*7 * 7* conghctgd 7 7 7 7 77 7 Bgarat7hapyzha7 777 Si7:g7 77 7 7 Cqvergd a7II7seqson_s7 Kéligdil 7 *7 * Fi\§e 7 7* 7 77 Covgred7aIl7spas7o7ns Pa7mbq* 7* 7 Foui 7* 7* 7 C05/erefl a1l*sgaso7rls Cfhalékugi 7 * 7 * S*ix7 *77 * 77 *77 * €gg€r§q*alIseqs9n§7 knbbnPgriyag 7* 7* 77* 7 §iQhtTgn 7 7* 7 777* 7 Qoveged 7 7* 7 §Covereda|lseasons a7lIse§sc_>_n7s 77 7 7 7 ‘l3ble72.2.Crltgria7for7Ros7Qen'§ level -I §trggm_r7oa7c7h c[ass7ification77 7 77 77 77 Stroimilg 7E*ntr5nclimerTt r;|ii_o WIQ ratjo*7 * 7 7S7!nuqgity7 77 7 S7Iopg 77 Qes A§+7 7 7 7 <17*47 7* 7* 7*7 7 <12 * 7* cjptlgn7* 7 1.0-1.71* 7* 7 7* >*0.1 7 Hea7dwajér7 A *7 7 7 514* 7* 7* 7* %127* 7* 7* 7* 1.07-*1.27* 7** 7* 70.074-07.1 7* fléadgiatgr B *7 *7 I 1-452.27 7* *>127* * 7 7* 7>71.27* 7* 7* 0*-02-76-039 inten*ned7iate7 07 * 7* *7 g*2 7* 7 7* 7* 312 7* 7* $1.47 7* 7* 7* 7 <07.027* 7 M7e§nq§rin* * * ** N*/a7** 7 7* 7* >497 7* 7* 7** 7 ry.-5 7*7* 7*<6.04** 7 B*rai7déd7**7 * * * >4.70 * 7 <30 7* 7* 7* 7* v*éqaB|g* 7**7 <07_0o§* 7* Bréid7ed7 7 *** ** >7§2.27* * 77* 7* é1g* 7* 7* 7* 7 >71.*57* 7* 77*7 *<*0.Q2 7**7Me75nqen‘7q * <1.Z 7 7 7* 7 3127* 7* 7*7* S1.74* 7* 7**7* 7 <0*.og*7* E*ntr7e*nc[1ed77 **7 7**777 *77**1 7<*§17**77**77* 77* 272* 77* 7 **77*77 >7*-27* 77 77*77 *7797-02-0-059 7§U*"L * 77 * 7 7 7 Table 1f.3.(72ritgria jor Rosgen's level-ll streang regcl17clagsificatl2n 7 7 77 7 7 777 7 77 77 7 St?ea|i17t7fl>e*Sl*op7e*ran§e* *7 7 77 7 7Chann*elgfia7l:e*r|_al 77 77 7 7 77 7 77 7 7 ** * ** ** * * * ** Bgflrock 7* 7** 7* E*oql*de[* 7 * 7* 7 Qcizbje 7* §ra7v§l 7* 7 Sg5d7 Sil1or*C[a A**7*7** ** >0.7*1* 7* 7** 7** 7 A?a+7* 7* 7* 7* 77A2§+7** 7* 7* A3g¥7*7 /5451* 7* I*5g+* 77 /76a*+7 ‘ 7* F 7* 0.04¢0.0997*7*7A17 *7*77* f 5 A27 7 *7 i A§aj*7*7§\5* 75 A5*7* A63+7 7 B 7**7*7*7 7 0*-Q47-7 io0*9g* *7* 7 B15 77 * **7*7* 77 7777 7*B257*7*7*7*7*B§a*7* 7 77 7 7 7 Bkia7 7 7*7B§a*7 7 7 7 B6a7 77 7 *7 *7 7* 7 07.702-page 7 7 B17 7 7 7 B2a7 7 7 7* 7 B*37* 7* 78-1&5 * 77* BS 7B§a7 77 * *7 *7 *7 *<*0-0*2 * 7* * Bi<=* *7* 7 7* 7B2<= 7* 7* 7* 7** B37<=*7*7 830* 7**7B§<=*7* B69 13* * * *0.020.39* * * C1b* * * * *C2b* * * C*3b* * C4b* ** *C5b* C6b 7 7 7 70.001770.Q27 7 C17b7 7 7 7 C2 7 77 7 7C§b7 7 C4Q 7 Q5 77 C67 7 7 7*7 7* 7* *€07061*7*7*7*C?g*7*7*77*7*C2q* 7* 7* *7 C*3g:*7*77 C467 *7 *7C§c*7 06?; *7 7 D7***0.0fi1-6.02*** * 7* 7nla 0.6215.39*7 nla7*7 7* *5/a*****n/a*****D3b**D4***D5*7*7**7**7*7 3b *7* D4b *7*7*7 Q*7 *7 *7b *7 *7 D6b*7* D57**7* D6** *7 *7 77*7 7i0.0Q17*7*7*7nla7 7 7 7 7nIa777 77 7n/a777D4c7 7 7D5c7 D6(; 7 Ei\77* 7* 7 <077<*>0§*2639* 7*77*7f 7 *n/7a7*7777‘ 7* 7* 7*77713:» 7* n!a*77* 7* 777* E-ib** 7n/;*77*77* E55*I§67*77 DA4 7 7* DA§*7*0Ae7 *7 E7777 70707.77777Qa777777g/a77777777777777777 <0.0277 77 I1/3777777 7n@777 7 7E377 E47b*7*7 E57*7E6*7*7 b F7777*7* 7* 62-039 75‘ ** * *** 5‘ 177* 7** 7 *7* 47 7 7 *7 677 7777<0.q27777F1777777 7 70-77-777777 7777 71b777777 Fg77777F7377 2b 7 7 F39 Ft17777F5b_7_ F47b77F5g7E677 F77b77 7 97 77 7* 7* 0.702-7g*Is97* 7* 7 *7 0717 7* 7* 7*7*77 627* 77*7 7* 7* G:7;*7* 7*G477*77*_7 G57 *7 Q6*7 *7 7 7 7777 750-Q7277 7 7 7 _G717c7 77 7 7 7 7G72c7 7 77 7 77§3(7:7 77 7§4c7 7 7765077 G§7c7 7 (D Wm DU> Table 2.4.The metrics used and the scoring criteria used for habitat quality scoring at _ _ sele dlocatlonsln Peflar river |Rat1ng item it ‘excellent i !§ood [Fair T Poor j K lExtensive amount No significant bank Limited amount of intermediate amount Zof bank erosion, *erosion,failure.>l-90% bank erosion, failure. 1 of bank erosion, lfailure.,/-50% of of bank protected by 80% of bank failure.60% of bank bank protected by Bank erosion,failure and bank plants of stable rock protected by plants or protected by plants plants or stable i_ stable rock a 101 stable rock 4 l_ rock y 0 y Tprtection 12 l2s-5% of the 100-65% of the bottom 56-45% of the bottom 45-25% of the bottom material Main channel bedrock lmaterial covered by material covered by bottom material covered by lbedrock 25 it ibedrock 15 i coverd bybedrock 8 lbedrock 0 I Tsubstrate(%of area) l 15-0% ’ I I ' cover(turbulance,w oody 100-50% y 49-25% 24-15% debris,vegetati0n, cover(turbulanoe,wood c0ver(turbulance,woo cover(turbulance,woo turbulant white y debris,vegetation, dy debris,vegetation, rdy debris,vegetation, water iturbulant white water turbulant white water turbulant white water boulderspverhangi kboulderspverhanging bou|ders,overhanging boulderspverhangingl ng stream Available cover for adult game stream boulders, stream boulders stream boulders boulders undercut fishlAverage maximumulrundercut Talweg bank) 1 25?1 LundercutbankjL'16 undercut bank) ibankl 0’ A depth(4 deepest deghs) A }>/-10m 25 15-9.9m 16 3-4.9m.4 48 1f3m >1.4 it to 0 l W/DwratioSinuosity _y iy N 1' <1-12 y y 1;6 51348 11.01?-1.2 4 7 19-24 it 2;2 1>/-25 1.2-1 1 _ 0 1 74-soTable100-75 2.5.Qualitative Excellent1 evaluation Good of Habitat Quality_(HQ1 1 scorinL 49-2524-0 7* _l PoorFair if _ Table 2.6.Scoring criteria used for the 10 metrics and 2 correction factors used to calculate the lBl score at selectet W F locations in Periyar river Species richness and it it Scores based on Scores based on Scores based on W comcosition metrics Stream width the number j 1the 10number _V_ 5 the number __ at 0 toTotal to nurnberof 6.2-12.1 native>10 species _ Le-102.5-6.1.W__ W __ >6 <6 6-_6_ <3“? >1-12.2 >14 P19 _.1- 14 <9 ll Number of loach species 7 2.5-6.1 _1.>1 1 g M0 at 6.2-12.1 7 >1 1 0 _ _ 1 >1-12.2 j >1 1 6 O 1 Number of sucker species 2.5-6.1 >1 -9 A lj 6.2-12.1 1 >1 0 _? j + >/-12.2 1 >1 0 Number of miclwater species 2.5-6.1 I 1 0 . 0 7 6.2-12.1 21 11L 0 f _ >/-12.21 __ >2 .L% 1 -2 0 Number of intolerant species 25-6.1 l 1 _ Oi 1 W __ 6.2-12.1 _? >1» -.fl >/-12.2 _ >2 H1 - 2 1 Scores if _ it a_ 10 ,7 -5. it 01 Number of tolerant species 0-19 20 2149 51'-1 00" 11 Trophic metrics 6 7 at . 11 Percent hervivores 6 100-76 15% 74-51 60 __ _ 49-O Percent insectivores i _ at 100-61 606 59-31 - . 1 .6 30 29-0 _ rcent_topcarnivore_s 100-15W 143 1 3-8 7 6-0'1. Percent omnivores _ 0-19 at 20 21:39 -1 40 41-100 I 1 Fish abundance andmcondition correlation fctors Number of individuals per E 1 300m’ lf <50 fish,substract 10 from overall IBI score Percent fishes with anomalies lf>l-4 percent , substract 10 from overall lBl score L _ 1 Table 2.7!Qualitative evaluation of lB_lscore 59-40100-160 i itM 1_H T Excellent Good ' 24-139-25 01_ it 1 FairPoor it <10 _ ?_ 1 Veryugor .-‘L _§ _§ O‘! Q IO D10 Q Chapter 3 Habitat quality and index of biotic integrity in six major river systems of Kerala 3.1. Introduction The most distinctive effect of increasing human activity around the globe is steady reduction of environmental diversity. In the case of fluvial ecosystems, one of the most important factors responsible for the sharp decline in biodiversity has been channelization combined with wetland degradation. Throughout the world, the morphology of river systems has been dramatically altered by human action. The changes have been induced directly by dams and reservoirs and channelization, and indirectly by land-use developments through out the drainage basins. The first question to answer in analyzing the relations between land-water ecotones and fish diversity seems to be: what are the factors, which stimulate the increase in biodiversity of the ecosystems? It can be answered by two components l) the nature of the ecosystem (Mac Arthur and Wilson, 1967; Magurran, 1988) and and its latitudinal position (Pianka, 1983). Among all aquatic habitats, rivers, due to their spatial and temporal heterogeneity, are most appropriate ecosystems for the analysis of the relationship between fish biodiversity and environmental properties. The four fundamental components which determine the productivity of any riverine habitats are: 1) the flow regime 2) water quality 3) the physical nature of the floodplain and 4) energy budget of the system. Habitat evaluation methods must attempt to quantify the interaction and relative importance of these four components (Cowx and Welcomme, 1998). Much of the freshwater aquatic sciences have aimed at assessing waterways and their connnunities to provide some index of their health and functionality. Initially, the main problem was to improve degraded water quality to a point where aquatic life could be restored to systems. Later it was realized that degradation had not only occurred in the 34 quality of water but in the structure of the environment itself, and many recent models have been aimed at defining the role of the form of river systems on the processes that make them work as viable ecosystems (Cowx and Welcomme, 1997). A fluvial hydrosystem comprises of the river channel, riparian zone, floodplain and alluvial aquifer. It can be considered as a four dimensional system being influenced not only by longitudinal processes, but also by lateral and vertical fluxes, and strong temporal changes. These models provide the basic guide as to what types of intervention are needed to rehabilitate systems (Cowx and Welcomme, 1997). While analyzing the data from different rivers, Zalewski and Naiman(l985) concluded that abiotic factors are of primary importance in regulating fish communities. According to Lachavanne and Juge(l997), along with temperature, salinity, current speed, dissolved oxygen, pressure, light and available food and the physical and ecological factors also play a substantial role in the dispersal of fishes. The presence of quality habitat is a critical factor in the health and diversity of the biological community. Many studies indicate that the pattern of distribution for many fishes is the result of both local-habitat conditions and larger scale biotic and abiotic processes (Rabeni and Sowa, 1996; Dunham et al.1997; Schrank et al.200l). The physical characteristics of the local stream reaches have significant influence on the variation in fish density (Rabeni and Sowa 1996; Watson and Hillman 1997). On the other hand, large-scale watershed or landscape features such as stream size, basin area, spatial geometry and stream temperature as well as biotic factors such as the presence of non native species and degree of isolation from other populations also have substantial role in the distribution and abundance of fish species (Bozek and Hubert 1992; Fausch et al.l994; Riemann and 35 McIntyre 1995; Dunham et al.l997, Osbome and Wiley, l992; Dunham and Rieman 1999). Based on the study in the streams at Minnesota region of United States Talmage et al. (1999) reported that factors such as impervious cover, water chemistry, water temperature, geomorphology, substrate, instream habitat and migration barriers have significant influence on the fish community composition in these streams. Comprehensive assessment of aquatic systems starts with an evaluation of habitat quality. The habitat quality can be determined by various aspects of the riverine environment in several categories:channel geographical units,riparian zone, substrate and instream cover and biology(Stauffer and Goldstein, l997).The sum of all these parameters will decide the complexity of aquatic system. According to Cowx and Welcomme(l997) and Stauffer and Goldstein(l997), areas with the greatest intensity of habitat complexity will support the maximum biological diversity. Habitat data have a significant role in biocriteria interpretation because the physical habitat of a stream has a major influence on the presence and abundance of fish and may therefore overshadow or confound the identification of other factors affecting the biotic integrity of fish communities (Muhar and Jungwirth, I998). Thus, quantification and interpretation of stream habitat are an important aspect of biocriteria development. In the present study, a pioneer attempt is made to evaluate the influence of various habitat components such as the nature of microhabitats, instream cover, substrates, riparian zone and water quality parameters to the fish species assemblage structure in six major river systems of Kerala. Based on the river morphology, the river systems were classified up to Rosgen’s II level. The objective of the integration of this classification system in the present fish habitat survey is to determine the potential of the stream reach, current state, 36 and a variety of hydraulic and sediment relations that can be utilized for habitat and biological interpretations. An attempt was also made to develop location wise index of biotic integrity (IBI) scoring and habitat quality (HQ) scoring in each river system by which one can rapidly assess the health of a local water resource. Moreover, it would evaluate the effect of habitat quality on the biotic integrity of the river system and will provide adequate information on the physical and biological components of the ecosystem. 3.2. Materials and methods Materials and method used the study is illustrated in chapter 2. (Please refer chapter 2) 3.3. Results 3.3.1. Kabbini river system Kabbini is one of the east flowing rivers in Kerala, endowed with a wide range of fish diversity and endemism. The river has a total length 56.6km in Kerala with a basin of l920km2. The origin of the river is from Thondarmudimalai having an elevation of l500m from the MSL. The important tributaries of the I‘iV6I‘ are Mananthavady, Panamaram, Bavelipuzha and Noolpuzha. In the present study detailed habitat inventory surveys were conducted at 15 selected locations giving representation to various habitats of Kabbini river system. The locations where detailed habitat inventory surveys were conducted in Kabbini river system are shown in Plate 3.1. The overall physical, chemical and biological habitat structure of Kabbini river system is given below: 3.3.1.2. Physical habitat structure In Kabbini river system instream cover was dominated by overhanging vegetation (59.6%) followed by depth (24.8%). All the other types of instream cover together 37 constituted only 15.6% (Fig.3.l.) .Among substrates gravels (38.4%) and fines (18.6%) together constituted 57% of the river bed while the contribution of bedrock, rock, boulders and cobbles were l3.5%,4.8%,l2.l%,and 12.5% respectively(Fig.3.7). Sinuosity of the river system varied from l-2.6(SD=0.58) while stream gradient ranged from 0.001-0.l(SD=0.03). Mean entrenchment ratio and w/d ratios werel.33 (SD=0.87) and 8.l7(SD=7.78) respectively (Table 3.1). Heterogeneity of channel geomorphic units was comparatively less and was dominated by run (39.6%) followed by lateral pool (18.8%) (Fig.3.13). Mean flow velocity was 0.3m/s (SD=0.23). Riparian zone having 26.1% shrub cover, 58.6% tree cover while 15.3% of the riparian zone was without any vegetation. Habitat quality score varied from l4(Sugandagiri and Tariyod) to 56(Palvelicham) with a mean value of 33.4(SD=l9.'7) (Fig.3.l9).The habitat quality score at various locations selected for habitat inventory in Kabbini river system are shown in Table 3.1 3.3.1.3. Species assemblage structure Fifty four species representing 14 families were collected from the total 15 locations selected from habitat inventory surveys in Kabbini river system which accounts forl00% of the total species so far reported from Kabbini river system. The total number of species and the location wise species abundance at various locations of Kabbini river system is depicted in Table 3.7. Cyprinids were the most common family with 24 species, representing 83.3% of the total number of individuals reported from Kabbini river system followed by Balitoridae and Bagridae with 6 species each. The classification of different species identified from Kabbini river system under 10metrics used for IBI scoring is shown in Table 3.13. Of the total 50 species reported from this river system during the 38 present study, suckers contributed to 10%, loaches 14% and midwater species 12%. Suckers were collected from 80% of the sampling locations while loaches and midwater species from 40% and 73% locations respectively. intolerant fish species and tolerant fish species respectively formed 24% and 14% of the fish fauna. intolerant fish species showed their occurrence at 93% of the selected locations while tolerant fish species were reported only from 67% of the locations studied. Among the different trophic groups, omnivores were dominating (46.3%) followed by herbivores (22.6%), insectivores (17.3%) and camivores (13.8%). Omnivores were reported from 96.4% of the total locations surveyed while herbivores, insectivores and carnivores shown their occurrence at 78.6%, 71.4% and 53.6% of the total locations surveyed. Index of biotic integrity ranged from 5(Aranagiri II) to 65(Kuruvadeep) with a mean of 38.4(SD=l8.8) (Fig.3.20).The location wise index of biotic integrity at the selected locations of Kabbini river system is shown from Table 3.19. The range of water quality parameters at selected locations of Kabbini river system is shown in Table 3.25.A few typical channel reaches identified from Kabbini river system is shown in plate 3.2. 3.3.2. Bharathapuzha river system Bharathapuzha, one of the largest rivers in Kerala, has a total length of 209km and has a total basin area of 6l86km2 shared by both Kerala and Tamilnadu states. The origin of the river is from Anamalai hills with an elevation of l964m.The main tributaries of the liver are Gayathripu2.ha,Kunthipuzha, Chitturpuzha, Kalpathipuzha and Thuthapuzha. Detailed habitat inventory surveys were carried out at 28 selected locations of Bharathapuzha river system. The locations where detailed habitat inventory surveys were 39 conducted in Bharathapuzha river system are shown in Plate 3.3. The overall physical, chemical and biological habitat structure of Bharathapuzha river system is given below: 3.3.2.1. Physical habitat structure In Bharathapuzha river system, instream habitats varied among sites. While considering the entire river stretch, depth was the dominant instream cover (38.68%) (SD=l5.86) followed by overhanging vegetation (18.9%), emergent vegetation (17.5%) and turbulence (12.1%) (Fig.3.l). Riverbed was dominated by bedrock (28.6%) followed by cobbles (19.5%), gravels (l7.85%), fines (l6.57%), boulders (13.2%) and rock (4.2%) (Fig.3.8). Among physical conditions, sinuosity varied between 1-l.63(SD=0.l4) and stream gradient ranged between 0.001-0.25 (SD=0.06). Mean entrenchment ratio and w/d ratios were 1.46(SD=0.9) andl6.42 (SD=l9.3) respectively (Table 3.2).Midchannel pools (23.3%) were the dominant channel geomorphic unit followed by run (18.35). glide (12.3%) and landslide (9.6%) (Fig.3.14). Mean flow velocity was comparatively less with 0.31m/s(SD=0.35). Riparian vegetation was comparatively less and 29.4% of the riparian zone was without any vegetation while 26.2% having shrub cover and 44.4% of the riparian zone was covered with trees. Habitat quality score varied from l4(Churiode) to 63(Pambadi east) and the mean habitat quality score was 39.6(SD=l2.l) (Fig.3.l9).The habitat quality scores at various locations selected for habitat inventory in Kabbini river system are shown in Table 3.2. 3.3.2.2. Species assemblage structure Fifty eight fish species representing 23 families were collected from this river system, which formed 92% of the fish species reported from this river basin. The total number of fish species and the location wise fish species abundance at various locations selected for 40 habitat inventory in Bharathapuzha river system is given in Table 3.7.Cyprinids were the most common family (represented by 25 species) and constituted approximately 64.35% of the total number of individuals collected. Balitoridae and Bagridae, the next most common families, were each represented by 5 and 3 species respectively. The classification of different species identified from Bharathapuzha river system under 10 metrics used for IBI scoring is shown in Table 3.14. Of the 58 species reported in the present study, 8.6% were suckers, 10.3% were loaches and 6.9% were midwater species. Among the 28 locations surveyed, suckers were found in 57% of the locations surveyed while representation of loaches and midwater species were observed only from 25% and 32% locations respectively. Tolerant and intolerant species formed 13.8% and l7.2%respectively of the total number of species reported from Bharathapuzha river system. lntolerants have representation at 60.7% of the total locations surveyed while tolerant species were reported from 50% of the locations surveyed. Among the different trophic groups, omnivores dominated (50%) followed by herbivores (18.2%) insectivores (16.9%) and carnivores (14.9%) in the order of their dominance. Ornnivores were collected from 85.7% of the total number of locations surveyed. While herbivores, insectivores and carnivores showed their presence at 75%, 67.9% and 53.6% respectively of the total number of locations surveyed. Index of Biotic Integrity scores ranged from 0(Velampattapuzha) to 60(Yakkara) and the mean [BI score was 21.7(SD=13.7) (Fig.3.20), which indicated that the biotic integrity of Bharathapuzha river system is very poor.The location wise index of biotic integrity at the selected locations of Bharathapuzha river system is presented in Tables 3.20. 41 The range of water quality parameters at selected locations of Bharathapuzha river system is depicted in Table 3.26. Some typical channel reaches identified from Bharathapuzha river system is shown in Plate 3.4. 3.3.3. Kallada river system Kallada river system has a total length of 121 km covering a basin area of l699km2. The origin of the river is from Karimalai at an elevation of l524m MSL. The river has three tributaries l. Kulathupuzha 2. Chendurni 3. Kalathuruthi Detailed habitat inventory surveys were conducted at ll selected locations of Kallada river system (Plate 3.5). The overall physical, chemical and biological habitat structure of Kallada river system is given below: 3.3.3.1. Physical habitat structure While comparing Kallada river system with other river systems, habitat heterogeneity is very less. Overhanging vegetation (35.2%), depth (25.7%) and turbulence (21.9%) together contributed to 82.8% of the total instream cover in this reach (Fig.3.3). Gravels (30.2%) and fines (10.2%) together contributed to 40.4% of the riverbed, which indicate high degree of bank erosion and embedness. While the contribution of bedrock, rock, boulders and cobbles were only 21.9%, 7.1%, 1 1.3% and 19.4% respectively (Fig.3.9). Sinuosity ranged between l-1.4(SD=0.l5) and slope ranged from 0.001-0.l(SD=0.037). While mean entrenchment ratio and w/d ratios were l.2S(SD=0.5) and 5.9(SD=4.94) 42 respectively (Table 3.3). Three microhabitats such as midchannel pools (28.6%), run (25.5%) and riffles (24.3%) together contributed to 78.4% of the total river reach in this river system (Fig.3.l5). The remaining river reach was contributed by plunge pool (9.9%), cascade (7.9%), falls (3.4%) and rapids (0.39%) respectively. Flow velocity was comparatively high especially in the upper reaches and the mean flow velocity was 0.48m/s (SD=0.78).Riparian zone having 17.9% shrub cover, 62.6% tree cover while 19.5% of the riparian zone was without any vegetation. Habitat quality score varied from 12 (Ariyankavu) to 70(Meemnutty) with a mean value of 40(SD=16.5)(Pig.3.l9).The habitat quality scores at various locations selected for habitat inventory in Kallada river system is presented in Tables 3.3. 3.3.3.2. Species assemblage structure 23 fish species belonging to 8 families were collected from the ll locations surveyed at Kallada river system which formed 53.7% of the total species so far reported from Kallada river system. The total number of species and the location wise species abundance at different locations selected for habitat inventory in Kallada river system is shown in Table 3.9. Family Cyprinidae represented 14 species and constituted 93.3% of the total individuals collected from this river system. All the other families were represented by l species each. Table 3.15 shows the classification of different species identified from Kallada river system under 10 metrics used for IBI scoring. Of the total 23 fish species, suckers represented 11.9%, loaches 17.4% and midwater species by 21.7%. Suckers were collected from 82% of the locations studied while loaches and midwater species have representation only at 36.4% and 45.5% locations. lntolerant fish species formed 26.1% of the total fish fauna and were collected from all the locations 43 surveyed while tolerant species formed 30.4% of the fish fauna and were collected only fiom 63.3% of the locations. Omnivores (50.4%) were the dominant trophic groups in this river system followed by insectivores (22.8%), herbivores (l9.6%) and carnivores (7.2%). Omnivores and insectivores were present in all the locations surveyed while herbivores and carnivores were identified only from 90.9% and 36.4% of the total number of locations surveyed. Index of biotic integrity ranged from l5(Chenturuny) to 45(Meemnutty and Chenkali) with a mean of 27.3(SD=lO.5) (Fig.3.20).Index of biotic integrity score at selected locations in Kallada river system are presented in Table3.2 I . The range of water quality parameters at selected locations of Kallada river system is given in Table 3.27. Some typical chamiel reaches identified from Kallada river system is shown in Plate 3.6. 3.3.4. Pamba river system Pamba river system has a total length of l76km with a basin area of 2235km2. The origin of the river is from Pulachimalai having an elevation of l650m.The major tributaries of the river are Kakkiyar, Kochupamba , Azhutha and Kallar. Detailed habitat inventory surveys were conducted at 15 selected locations of Pamba river system. The locations where detailed habitat inventory surveys were conducted in Pamba river system are shown in Plate 3.7. The overall physical, chemical and biological habitat structure of Pamba river system are given below: 3.3.4.1. Physical habitat structure In Pamba river system, instream cover did not show much oddity. Among the three dominant types of instream cover depth alone contributed to 48.8% followed by turbulence (22.3%) and overhanging vegetation (16.8%) (Fig.3.4). In the riverbed, 44 bedrock was dominating (24.8%) followed by fines (19%) and gravels (16.8%). While the other types of substrates such as cobbles, boulders and rock together contributed only 39.5 %( Fig.3.l0). Sinuosity varied between 1-1.3 (SD=0.l5) and channel gradient varied from 0.001 0.l(SD=0.04). The mean entrenchment ratio and w/d ratios were l.21(SD=0.28) and 7.l3(SD=5.6l) respectively (Table 3.4). Heterogeneity of channel geomorphic units was comparatively less and midchannel pools (45.5%), rapids (19.8%) and run (18.8%) together contributed to 84.1% of the total river reach (Fig.3.16).The remaining 15.9% of the river reach was contributed by plane bed (4%), riffle(3.9%), chute(2.7%), falls(l.5%),trench pool(l.4%), lateral pool( 1.3%), cascade(0.6%) and glide(0.4%) respectively. Mean flow velocity was 0.38m/s (SD=0.3). Riparian zone having 66% tree cover, 13% shrub cover while 20.25% of the riparian zone was without any vegetation. Habitat quality score varied from 20(Pamba and Moozhiyar II) to 66(Kakkad Ar II) with a mean value of 41 .9(SD=l5.4)(Fig.3.l9). The habitat quality scores at various locations selected for habitat inventory in Pamba river system is presented in Table 3.4. 3.3.4.2. Species assemblage structure Thirty species belonging to 13 families were collected from 15 locations selected for habitat inventory in Pamba river system, which constituted 57.4 % of the total species reported from this river. The total number of species and the location wise species abundance at different locations selected for habitat inventory is shown in Table 3.10. Cyprinids were the most common group with 21 species and represented 89.8% of the total number of individuals collected from this river system followed by Balitoridae and Bagridae with 2 and 3 species respectively. Classification of different species identified 45 from Bharathapuzha river system under l0 metrics used for IBI scoring is given in Table 3.16. Suckers, loaches and midwater species represented 7%, 7% and 13% respectively of the total fish fauna of Kabbini river system. Of the total l5 locations surveyed, suckers and midwater species were collected from 67% locations while loaches were observed only from 7% locations. Intolerant species formed 27% of the total fish fauna and were collected from all the locations studied. While tolerant fish species contributed to 17% of the fauna and collected only from 53% locations. Among the different trophic groups, insectivore was the dominant group (42.5%) followed by omnivore (34.7%), carnivore (14.2%) and herbivores (8.5%) in the order of their dominance. Presence of omnivores were reported from all the locations while insectivores, herbivores and carnivores were reported from 93.3%, 73.3% and 33.3% locations respectively among the total number of locations surveyed. Index of biotic integrity ranged from l7(Nilakkalthodu) to 50(Peruthenaruvi) with a mean value of 34.2(SD=9.7)(Fig.3.20). Index of biotic integrity score at selected locations in Pamba river system is shown in Table 3.22. The range of water quality parameters at selected locations of Pamba river system is presented in Table 3.28. A few typical channel reaches identified from Pamba river system is shown in plate 3.8. 3.3.5. Chalakudy river system Chalakudy, one of the biodiversity rich rivers in Kerala has a total length of l30kIn and has a total basin area of 1704 km2 shared by both Kerala and Tamilnadu. The origin of the river is from Anamalai with an elevation of 1250m.MSL.As part of the present study detailed habitat inventory surveys were conducted at 20 selected locations of Chalakudy 46 river system (Plate 3.9). The overall physical, chemical and biological habitat structure of Chalakudy river system is given below: 3.3.5.1. Physical habitat structure lnstream habitat and physical conditions were highly heterogenic in Chalakudy river system, which are very ideal for supporting rich fish diversity. Depth (38.1%) was the dominant instream cover followed by overhanging vegetation (26.8%), emergent vegetation (8.5%), turbulence (7.1%), large woody debris (4.8%), undercut bank (4.3%) and overhanging stream boulders (4.2%)(Fig.3.5). On an average bedrock constituted 47.8% of the riverbed followed by fines (14.9%), boulders (12.9%), rock (12.6%), gravels (8.9%) and cobbles (2.8%) (Fig.3.l l). Among physical conditions, sinuosity varied between 1-l.5(SD=0.l5) and stream gradient varied from 0.001-0.1 (SD=0.03). While the mean entrenchment ratio and w/d ratios were 1.23 (SD=O.27) and 9.59 (SD=9.74) respectively (Table3.5). Channel geomorphic units are highly heterogenic dominated by midcharmel pools (30.5%), riffle (17.9%), run (16.9%), rapids(l3.7%) and pocket water pools(9.9%)(Fig.3.l7).Mean flow velocity was 0.25m/s(SD=0.23). Riparian zone having 87.65% tree cover and 7.6% shrub cover while only 4.75% of the riparian zone was endowed with bare ground. Habitat quality score in Chalakudy river system varied from 24(Malal 3.3.5.2. Species assemblage structure Fourty fish species under 16 families were collected and identified from the locations selected for habitat inventory in Chalakudy river system, which formed 58.2% of the fish 47 species reported so far from this river. The total number of species and the location wise species abundance at different locations selected for habitat inventory is shown in Table 3.11. Cyprinids were the most common family represented by 2l species and formed 93.7% of the total number of individuals collected. Bagrids appeared as the next common family represented by 4 species followed by Cichlids with two species. Table 3.17 shows the classification of different species identified from Chalakudy river system under 10 metrics used for IBI scoring. Of the total 40 species, suckers represented 7.5%, loaches 5% and midwater species 22.5%. Suckers showed their representation at 95% locations studied while loaches and midwater species were collected from 40% and 80% locations respectively. Intolerant species and tolerant species fonn 27.5% and 12.5% respectively of the total fish fauna. Intolerant species have representation at all the locations, while tolerant fish species were collected only from 65% of the sampling locations. Among the difierent trophic groups identified 48.8% of the species were omnivores, 28.2% was insectivore and the remaining 23% was represented by herbivores (15%) and camivores (8%) respectively. Of the total 20 locations surveyed orrmivores and herbivores were present at all the locations while detritivores and carnivores were collected respectively from 95% and 60% of total locations surveyed. Index of biotic integrity scores ranged fi'om 25(at Malakkapara) to 64(at Kuriarkuutty) with a mean of 44.l(SD=9.5) (Fig.3.20). The index of biotic integrity at various locations selected for habitat inventory in Chalakudy river system is given in Table 3.23. The range of water quality parameters at selected locations of Chalakudy river system is presented in Table 3.29. Pew typical charmel reaches identified from Chalakudy river system is shown in plate 3.10. 48 3.3.6. Periyar river system Periyar river, the largest river system in Kerala, is identified as one of the biodiversity rich river system in Kerala. It spreads in two states-Idukki and Ernakulam. During its course, the river is passing through Periyar tiger reserve, one of the wor1d’s most fascinating natural wildlife reserves spreading across 777sqkm. The Periyar Lake —stream system consists of 74 km of long streams that drain into the lake and 26 kmz of Lake System within the Periyar tiger reserve of the southem Westem Ghats. The lake is formed by the construction of a dam across the streams, Mullayar and Periyar in 1895.The river Mullayar originates at an altitude of l780MSL, has a total length of 3 lkrn and joins the southern tip of the lake. The Periyar stream joins the eastem tip of the lake from the southem direction, originating at an altitude of l593m MSL, has a length of 43km. Further down a number of small tributaries join the main stream before it drains to the Idukki reservoir, the technological aspiration of Kerala. Tributaries Muthirapuzha and Perinankutty join the main stream before the river reach at Perinj ankutty and Kallar. The river then takes a turn to the North west direction and reaches the legendary Bhoothathankettu believed to be constructed by demons, as per the local folklore. The reservoir at Bhoothathankettu is the main source of irrigation under the Periyar valley irrigation project. Before reaching the legendary reservoir, the river passes by the hydel projects at Sengulam, Neriyamangalam and Panniyar. The Idamalayar tributary joins the main river here. At the downstream the river bifurcates into the Marthanda Varma and the Mangalapuzha branch. The former drains out to the backwaters of the Lakshadeep sea and the latter joins the ‘Chalakudy’ river. Mathanda Vanna branch fiirther bifiircates into 49 two- The Eloor branch and Edamala branch. Eloor branch mns in between a cluster of industries on both banks termed as the industrial hub of Kerala. As part of the present study detailed habitat inventory surveys were conducted at 29 selected locations of Periyar river system (Plate 3.11). The overall physical, chemical and biological habitat structure of Periyar river system is given below: 3.3.6.1. Physical habitat structure In Periyar river system, among the various habitat variables, the instream cover was dominated by depth (40.8%) followed by turbulence (31.4%). The percentage occurrence of different types of instream cover in Periyar river system was shown in Fig.3.6. On an average bedrock formed 45.5%of the river bed followed by boulders (14.6%), cobbles (14.5%), gravels (12.6%), rock (6.6%) and fines (6.2%) (Fig.3.l2). Among the physical conditions sinuosity varied from l-l.4(SD=0.l2) and stream gradient ranged from 0.01-0.15 (SD=0.03). Mean entrenchment ratio and w/d ratios werel.39 (SD=0.03) and 5.1(SD=3.6) respectively (Table 3.6). Midchannel pools contributed to 24% of the total river reach followed by run (19.8%), riffles (15.5%) and cascade (11%) (Fig.3.18). Mean flow velocity was 0.49m/s(SD=0.35) and the riparian zone having 22.9% shrub cover, 55.2% tree cover while 21.8% of the riparian zone was without any vegetation. Habitat quality score varied from l0(Kuntrapuzha) to 7'7(Purakkallu) with a mean value of 49. 1(SD=20.6) (Fig.3.19). The habitat quality scores at various locations selected for habitat inventory in Periyar river system is presented in Table 3.6. 50 3.3.6.2. Species assemblage structure Fourty six fish species representingl4 families were collected from the 30 locations surveyed in Periyar river system, which formed 60.5% of the total species so far collected from Periyar river system. The total number of species and the location wise species abundance at different locations selected for habitat inventory is shown in Table 3.12.Cypiinids dominated the catch with 21 species forming 91.3% of the total individuals collected followed by Balitoridae and Cichlidae with 8 and 3 species respectively. Table 3.18 shows the classification of different species identified from Periyar river system under 10 metrics used for IBI scoring. Of the total 46 species reported during the present study, 8.7% were suckers, 17.4% were loaches and 15.2% were midwater species. Suckers showed their distribution in 75.9% locations, loaches in 62.1% locations and midwater species in 41.4% locations selected for the study. Tolerant and intolerant fish species respectively constituted 13% and 29% of the fish fauna. Distribution of tolerant fish species were identified from only 27.6% locations while intolerant fish species showed their distribution at all selected locations. Among the different trophic groups omnivores contributed to 56.2% of the total species collected followed by insectivores (20.9%), herbivores (18.6%) and carnivores (4.3%). Among the 29 locations surveyed omnivores was collected from all the locations. While distribution of herbivores and insectivores were recorded only from 80% of the total locations while carnivores were confined to only up to 20% of the total locations surveyed. Index of biotic integrity score varied from 0 (Kuntrapuzha) to 52(Thandamankuthu) with a mean value of 34.l(SD=1l.8)(Fig.3.20). The index of biotic integrity at various locations selected for habitat inventory in Periyar river system is presented in Table 3.24. 51 The range of water quality parameters at selected locations of Periyar river system is given in Table 3.30. Few typical channel reaches identified from Periyar river system is shown in Plate 3.12. 3.4. Discussion In Kabbini river system the low hetrogenity of channel geomorphic units and high embedness of sand and silt on the river bed are the major threats to fish diversity. The increased proportion of bare ground in the riparian zone is the major reason for the low heterogeneity of channel geomorphic units and high embedness of sand and silt on the river bed. Due to the conversion of riparian zone to agricultural lands, large number of trees and shrubs were removed which in turn resulted the increased proportion of bare ground in the riparian zone.Williarns et al.(l997) reported that roots of trees in the riparian zone held the soil particles together and improves the bank stability.57% of the river bed in Kabbini river system was fonned of gravels and fines , which manifests the high degree of bank erosion and embedness due to the conversion of the catchment areas of the river into agricultural lands. The present finding strongly corrobrates the view of Judy et al. (1984) who opined that silt, which is often associated with agricultural land use, could be one of the most important factors reducing the availability of usable fish habitat. In Bharthapuzha river system, the increased proportion of sand and silt in the river bed, comparatively less pool-riffle type channel geomorphic unit in the river reach and increased number of check dams across the river were identified as the major fish diversity threats. The result of the present study revealed that the low contribution of bigger substrates like bed-rock, rock and boulders when compared to smaller substrates 52 reduce the fish diversity and this finding is in full compliance with that of Talmage er al.(l999) who reported that percentage sand within the reach was negatively correlated with IBI scores in streams in the Twin cities metropolitan area of Mimiesota. He further added that when there was a paucity of bigger substrates there was limited habitat for fish. The present study revealed that the sparse and sporadic occurrence of pool-riffle habitats in the Bharathapuzha river system have a negative effect on the fish diversity which is corroborating with the findings of Talmage er al. (1999) who opined that streams with greater percentages of riffles often had higher IBI scores. Presence of 9.6% of landslide among channel geomorphic units was due to the presence of numerous check dams constructed across the main river stretch. According to Hynes (1970), waterfalls and dams act as migration barriers for fishes, which will reduce the species abundance and the consequent decrease in IBI scores. Dams affect fish communities by altering stream geomorphology, substrate composition and stream flow. Moreover, siltation behind dams may alter the substrate composition within the pool, causing the pool-habitat even more homogenous. Goldstein er al. (l999) reported that dams form pools, decrease stream flow variability, and can result in a shifi from lotic to lentic species. According to Talmage et al. (1999) water in small urban impoundments gains heat because the surface area got exposed to the sun is always higher. Due to the low habitat quality in Bharathapuzha river system, the percentage contribution of top carnivores, herbivores and the coloumn feeding fishes together with the total number of species was less. Conversely, the number of carnivores was found high. This finding strongly supports the view of Karr (1981) who opined that when the habitat quality decreases the proportion of omnivores increases while the number of 53 species, the percent contribution of top carnivores and herbivores will decrease. The low level of water column or midwater species in Bharathapuzha river system are fully mpporting the view of Hughes and Oberdorff (1999) who supported that that the density of water column or midwater species declines with urban development but particularly with sedimentation, turbidity, decreased dissolved oxygen and warming .Due to the low habitat quality, the mean index of biotic integrity in Bharathapuzha river system was only 21.7, which is very low when compared to that of the streams at Washinton region of United states, where it varied from 24 to 57(Lyons, 1992). The high degree of bank erosion and embedness were identified as the major reasons for the low microhabitat diversity, which has a major role in the low fish diversity in Kallada river system. This finding is highly corroborating with that of Lachvanne and Juge(l997) who reported that due to human intervention, the river systems become more homozygous which will drastically reduces the faunastic diversity. The mean index of biotic integrity in Kallada river system (27.3) was very less when compared to other river systems such as Chalakudy (44.1) and Pamba(34.2) river systems. Among the 10 metrics which determines the index of biotic integrity, the low number of native species and the high percentage occurrence of tolerant species negatively affected the IBI score of Kabbini river system. Similar finding was reported by Noss(l990) who observed that number of native species declined with increased habitat degradation. Similarly high percentage occurrence of tolerant species in the community structure in the Kabbini river is corollary to the view of Ganasan and Hughes (1998) who reported that tolerant species are the last to disappear following a disturbance and the first to reappear as the system begins to recover. 54 In Pamba river system, the highly degraded condition of the riparian zone has significant impact on the low heterogeneity of microhabitats and high embedness of fishes and gravels on the river bed. Talmage er al. (2002) while studying the relation of instream habitat and physical conditions to fish communities of agricultural streams in the Northern Midwest of United States revealed that the most effective restoration efforts for Midwestem agricultural streams are those that focus on the riparian corridor because riparian restoration addresses instream habitat and physical conditions at multiple scales. When compared to other river systems such as Bharathapuzha and Kallada the habitat quality score was little high in Pamba river system(4l.9) which also manifested in the high mean index of biotic integrity score (34.2) in the Pamba river system. In Chalakudy river system, the instream habitat and physical conditions are comparatively good when compared to other river systems. The present finding is corroborating with the findings of Krebs (1985) who opined that within certain spatial and functional limits, the more heterogeneous and complex the physical environment, the more complex the flora and fauna and higher the species diversity. When compared to other river systems, the distribution of pools and riffles were maximum in Chalakudy river system. According to Cowx and Welcomrne(l998), reaches having altemating pools and riffles supports the maximum fish diversity in lotic ecosystems. Riparian zone in Chalakudy river system has high tree cover (87.65%) and shrub cover (7.6%) and the contribution of bare ground was very less (4.75%). The presence of high percentage of tree cover and shrub cover reduces the bank erosion and thereby the embedness on the riverbed. The present finding is in compliance with that of Talmage et al. (2002) who reported that vegetation on the riparian zone provide fish communities with cover, 55 temperature stabilization, a food source, and reduced fine sediment.Mean habitat quality score of Chalakudy river is far higher than the other five river systems in Kerala. Due to the good habitat quality the resulting index of biotic integrity score was also highest in Chalakudy river system. In periyar river system, the increasing bare ground contribution in the riparian zone was found responsible for reducing the heterogeneity of instream cover, which was found as the major treat to fish diversity. During the study period, the river bed was dominated by bigger materials like bedrock, rock and boulders. But due to the increasing human intervention into the riparian zone there is every possibility for the dominance of silt on the river bed in the near future. Periyar river system showed the second highest habitat quality score after Chalakudy river, among the six major river systems in Kerala. Eventhough the average index of biotic integrity score is only 34.1, except in some few locations, all other locations are having an IBI score above 40 and coming Lmder ‘good’ category. The results of the present study revealed that, among the six major river systems in Kerala, the best habitat quality was shown by Chalakudy river system followed by Periyar, Kabbini, Pamba, Kallada and Bhrathapuzha river systems, In the case of index of biotic integrity scoring, Chalakudy river system showed the highest followed by Kabbini, Pamba, Periyar Kallada and Bharthapuzha river systems. It would thus appear that the physical, chemical and biological integrity in Bharathapuzha and Kallada river systems were undergoing drastic reduction due to increasing habitat alteration interventions. The extent of ecosystem degradation undergone by these six major river systems of Kerala 56 and appropriate management plans relevant for various river restoration programmes are discussed in the subsequent chapters. 57 Table 3A.1A |1alfltaAtcluaAli!1§HAQ Asgorjngai sAlecteg Igca§ioAn§_oLKgbQinA§ riyeg AA AA A AA A A A A A A A A. 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" ’ ’ ** * “ * "A " ' '* * * * if be " T * b* W ' I” '1 T ‘Main;PA!9!-A’=A<='i9'1 A 7 Achannel AA AA A AAQ§>g!eQ=iAreA bedrock 11A A AA @liAXtgfl§ivAe A A 7~r 0rE> Jboulderspverhanging\ stream M \‘ r “ ‘ .90uIdeArsAunqec¢ytbqnk AAA»AAA A A A A_AlAA A A A A A A A AA A A A A g2A.2A}@ A AA 3Asr A A A A A A AA A14] A A A Aug A A A A 31.1w reg Mverage maximum’;fA;il;' Talweg A r * *444* W * 7* " ’A Ar\ * * ‘* * A," 7" " " *'; *“f_*111 W ~de li1Qfi9gp§$A1A<1Aegl§As)_§@ Ar 1.6M A A A A01 1.3m 0* A A A\ A A AA jar A A A gs» A A A A 1_.r)A5,AA A Ag‘ $!!1?r9§i':/AAAAAAAAAAAAATAA2A1AAA1> TA§AA‘fAf*AA1j.A2ajAA‘f‘A'”2 jTAfjff1.2 A A A A2 A A AAA1A.s AAA A0 WIDFQHQAAAAAAAAAAAAA A AA A A11-8 A A A A6 A A AA4A.1§ A*f"e ’ N ‘ ” 'o;51 ” ‘ ‘s ' * * *6.1é'”"*'s \9Y¢"!'?jQ$A99‘¢A A A ‘AA lj ’A*AA*AAA‘A ATAAAT5 AAZTATA TA A113 A b'A"A*‘AiA1A1AiA*‘‘r 'A“7f3A?s ;”"’ f :36 I'P!°A3-A1-1¢9'1!"1"9¢!)LJ=!Pi!A=1 "2'igLH9L=e<>:irAmgtgeqtedjoéagiéné <>?! AAfi‘iA;; A A A-A A A__~:4‘:~_:,_*T—-J-F-—-V-.1 \ \ \ N \ Aitwii‘ QA’ AAT .>___..T__r..Z¢.¢;A:;;:::§-X; :4-F--H-1% -J O7 -i -nl ;gi4444 ; 3”miiiiA A? QAAAAQAAAAAA A i \ A O\:;;::11;iblA:-A:-—v--A A¢A__1 AQAAAAAAQA <=A2AA?5AAAAAAAAQAA AAA, ilr O’) 4J1--+L—Trm 4-¢-L--Tb——¢ A: :L-i; ;14AA:: :oi<~ i:——V-—‘i rb AAAAA(Q O9 AAAAA Lréii —i—44liti ri. WA; AfiAA AAAAAA AA co' AA\'AAAAAAAQAA.AA cn J.-+-4 AAAA A AAAAfAi_.A._., AAi_._L.4\ ._"‘_"______1_._.LA m AA-A AAIQAA AA AA 1 Fvailable cover fer ad utt T 7 77 P 1 N 77\ r7debris.vegetation_ game fish(turbulance,w0ody turbulant ~ \ ‘F “, r‘ 7» Twhiterboulderspverhanging water tr 7 stream , U “‘ H7 r\‘ » Xboulders,iverage r7mde7rcutpank)7 maximum J; 7_ __7_4£;37._§7 Tatweg 7 7 7 16777 777 77 77 QQT 7777 771§_r_7_7 7 7‘ 7 A7 7_ 7:@ 7777_ 7 7rt Mde 1114 d7eepe§tde7gths)_§@ 77 7 77 77 7 77 7 _7 7 72-5% 7 7 7 _ 77 _ 7 77 7 Ii 7 7 7 vq/ojr;;;qt‘77t‘77t 777 7 77 76.3 7 7 _7 7 §726777 OverallSi7nuosity__ _ 77 HQ 7 7 77 7score 7 21i_ 7 7 77 7 _7 7 77276 7 7 _ 7777 7 7 7777 7 7 77 77 7 2-5 777 7 7 777 LabIa73.g.Hat7>ltat77quaI!7gy_tHQ goring at gdected I97¢ati_0r\s_qf B_h7qratl1a yl7ha77!iv9r7 7 ,7 77 7 _ 77 77 77 _ 7 7 7 7 7 7 Cherythuruth 77 7 Kana7k77kanq7qr 7 77_ 7_ T11opik7a<7ia\Lu_ 7 7777 C7h9@!B7kU§"'7 7 777 7 I#o;7rics777 777 7 7 7 Qua7n7tifjr;5tio7n HQ77sg_or7§ Quantificatiqn HQ sgore Quantifigatiog 7 HQ_§co:37Q7uant7ificatign HQ score \B7ankerosibr1,faiure7and7tYank7 77 7 7 777 7 7 H ' 7_p[0tgc_tiQn777 77 7777 77 _7Limited 7 77 t3tlnt7errng-diate 777 77 775rgt7ensjve 7 _7 1377 _7 Q;7E><13!1$iv§ 77“ 77 7727 ‘substrate*vtvarrabre(c5verr0%d..rt‘Mair: channel%of area | 0"F" bedrockO "10r ‘ "tr 0a 90*» *7 1 " f2:57 a"r *W 7r 7 71" "107 7 " T7,7 a 70r "W ‘ \deb|is.vegetation,77game fish(turbulance,wQody turbulant ‘\ M X “7 7 ,7 rr “ M r‘boulders.overhangingrwhitewater stream M ‘7 ‘7 7A 7‘ 7 rr \ 7» H J ‘Average7maximurn7bggIders,g7ndercut7bar1k) T7atweg 7 r 7 7 7 Q7 7 7 77077 T 777 77 7“ 29¢ 7 77 7 77 e“ 77 7 7 §.41‘7 7}‘ 77_ Q 7 7 7733,77 7 77r ‘ or‘ 1 de @7(§9egpe7==-tdgglhgltfl 7 7 77 377 7 gr 7 7 77 74* 7777 77 7 _7 ,7 7777 77 77 7 7 _7 7 77 7 _ 7 Sigluvsjtv, 77_ 7_ 7_ 7 77 77 7717 77 573 77 7 J 77 7 _7 7 7 1 77 77 7 _ 777 1 77 _6 WID7rati70 77 7 7 7 7 7 8§.3 7 70 7 7 29 77 7 7 7 7 7 17.17 7 7 7 715.17 77 74 02<==@"7HQ$9i>£<=777_777_7 7_ 7_777_7 T 77 7 77 77 7 7 i 7 7 7 7 _7 ; 77 7 7-?-6 T=b!!=§-2;L¢79I1l1n\1<-!<1)eH=bl¢gt 7u§liy_(HQ)7=<=70rin97=ts5z<=te§ Ios=at7i9n=70f7Bha:ath= u_zha_river _ 77 7_ _ 7_ 7 7_77 7 _7 7__,_777 _7__ 7 7_M7°§."Y?"§'!‘_'_7 ; 7_ ¢7h7eer7=@ku;hi'! 77_ 7 Pambadieast 7 7 Man§7" L;5!b5t@‘e@59f3F7°37l7757 7 _iq_ 25]7 7 7 7 7_25 77 7 a“7_7__ 0 7 7|._I 777 _ _ .7 7 77 0] 377 35* Available. coverfor_ adult r 7 M7 7 “ 7 W77} 7 * * W‘) 7 * *7 7 7"; 7'1 ‘white‘gamerdebrisyegetation,turbulant flsh(turbulanoe.woody water “ r 1»‘ 7 r 7‘77 7‘ rr 7 r‘\ tr M \ ‘ r 1>0ulder$,under<=uH2an1<)\boulders,overhanging__ 77 77 77 7 7_7_ 7 777 W, 7 _stream _7 711,677 _ _ 5 7‘7 7 or 77_7 r42 H 16v 7‘ 19M7Q “7 _ ‘A3”77_ _7L1273 7r‘ 0*7 7A ‘Average maximum\ Talweg\ r j 7 * t my * * 7" 7?rt 7 a" 7 77. 7 7 ar ‘whmdeepeetdemhsltml$imw§i1i7 7 _7_77 7 7 ‘ 17‘ 76777777771777 7 7678* 7167 ’ 6 “ a2-18» “1;;3“t*“0 0,, 1.5 0 25 0\ W'°7@1i7<;_7_7 777 7 13.747 7 74777 7 7 7547* 7 7 6 1 * 3731 * " gr 1 * 7 rt 2 7°Y¢@'7'HQ$9¢r§ 777 77 7; 7 7571‘ 7 * 7 7* ‘ * Z2 ‘ 1“ ‘t *7‘ a ‘ W4 “I "*3? .** on OJ O>’O>OQo P‘ OJ reoorocaoo tomovoo A A re 4,r_T|__l Q-ucvooas O0oovooo 4.-_-L_T Q1 _l Q Table 3.27.(con7t7lnt7:ed) Habitat u_al7ity_(7§Q) ;7corin7g7 at alected location; of77B7har7a7tha 7t17zha77rivg7r77 77 7 7 77 7 77 7 j 7 7 7 77 7 7 7 Peghurnkara 7 7 7 7* 7C!100r_a7par7a Chitttir 1 7 7 _ 7 77 lfavaralfundu 7 ‘BankMetric; 7 7 7 7 77 777Qqa_ntifi7cati71_o7nerosionjailure lig sce7re Q7uant_i7fica7ti7pn and 7H7Qbank scpre Quantification 1 71 777 7H_Q7sco7re' 7. 1 7Qtgantificati97n ‘ ‘ 1 HQ score ugrgteqienMain 77 7 777Ext7ensive channel 7 7Q7E>7 Bank erosionfailure and banky 1 7 ‘V 1 1 . ‘j 1 Uarotection 7 77 {*7Extensiye 7 7 17 77 7 Ofixtensive 777 7 0] Extensive 11 111 1 Olflflfled 11 31 1 Main channel bedrock . . 1 "fr 1 1 1 7sub7strate(%of area) 7 7 1 7 15717 121 1 01 1 0L O1 1 01 Q1 1 Q 7 ‘Available cover for adult 1 1 11 11 1 game fish(turbu|ance.woody A . whitedebris,vegetation, water turbulant ‘1 boulders,overhanging stream 1 \bou7Iders.7 undercu7t7 bank) 7 777 7 12.8 1 1§. 2711 1 161 1 13-5111 641 23. 16 ;Average maiimum Tativegi 1 1 1' 11 111 77dep7th(47deegest 7dep7t_h§)§m)_ 4 7 127.71‘ 25 1.5 Sinu0sity77 7 7 7 7 7 77 777 1 .17 717 78;"a7 7 77‘ 718 71.31 251 7 1.2 4 1 17'/Dratio7 7 77 7 7 72.67 5 7 0.236 7 * 712.3 6 7 21 .2 Oyerall HQ scare 7 1 7 f 7 as 7 7 7 7 7 77 Q 77 7 1 ‘[able*3.27L:o1717tln1Je7d} Habitat 7t7i§|1qLHQ7p¢oring3t slepted locations of Bharatha uzha ri*17rer17 17 7 7 7 it . .11 _. ¥1aW1Chen' 1<|<*|*"|<‘ala 1.11_1ad anngat7 1 odu 11 hem/awaiakn 771 c”‘1<|’ 1 77 adl 17 is7 ren d"7 fl 71’ 7 77 BankMetrics 7 77erosionjailurefand Quantification HQ score Qu7antificati7o7n bank 1 HQ1 Wscore 1* Quantification 1 1 ' * 77 HQ score Quantification Q0 scgre Mainrotectiori channeibedrocki7 7 Intermediate 77 7 4 Extensive if 1 77 1 7 f77 1 0 Limited' 1 if 771 77 1 78 '1 Extensiye W 7 77 0 sub$trateQ>7of areal 0 7 0 0 O 07 O 0 77 770 -5 -L C) O.) N) NO) O Available cover for adult game fish(turbuIance,woody ; ~debris,vegetation, turbulant while water bouldersovemanging stream , boulders. undercut bank) 8.. - 11 491 16 131 0'11 1 1 511 1 0 Wrerage maximum Tarweg ' ’ de 1th(4 deepest1depths)(m1111 1 16* 125 251 1 9 11 251 Z15] Sinuositl ff 11 1111 H 6 11 1.1 i 14 11 1 W 11 1.2" -4" 1 __ 14 WlD1_ratio 1_ _ 6.08 T5 0.77 6 119.11 1 13 6 915311 HQs1oore __ 4o __ _1_ 1 __ 1—11 1 1_ 35 Table4 Y 3.3.!-labltat ‘I Urukunnu quality scoring 1at slectedOttakkal locations _of 1Kallada Meenmutty river 11 1 _ 1 [latticeBank erbsion,faiIure *4 lQuantification%Qscore]LQuantificatiqn and bank , HQ scoremQuantification l1HQ_1score! _p_rotection1 11 1 11Exte1nsi1ve 0tmnneq1 Q 1 21j1Exten_s_ive a“1 1 Main channel bedrock 1 T 1 substratqiof areaL 11 241 191 17.4 9. It/ailable cover for adult V 4 _ . 01 1 _. °1 game fish(turbulanoe.woody 1 debrisyegetation. turbulant gwhite water boulders.overhanging stream 1 boulders, undercut bank) 44.6 A 251 Tlltrerage maximum Talweg W i Us 11 1 13.41]? 0‘ 25 25“ do th_(4 deepest dept1hs)(mL11 11 3;15__ Bi 1 2_5 1 11° Sinuosity 1 1111 1 11.38 2 1 _ 1 6 1 15 4 6 "ninnm 171 411 7-5 £3 0verallHQs1oore 11 11 1 1 11 11 14 _ 38 70 Table4 3.3.(gmtlnued)Hab|tat1. _ Dali 1 11 ualiqscorin 1 MSL at slected 1 1locations 1 C_lf|e1nkali of1Kallada1 river _ 11 11 11 1_Kazhuthuruty11 _1 Ietrlcs 1 4 ' liluantlflcation 1HQscore'Quantification"1 HQ score Iiluantification ‘HQ score Q_uantificatio1|11:l_1 HQ score Bank erosion,failure andlbank K _gfotectio1n 1 1 1111 11Exte1nsiye 1 _ 1_ 01 Limited 12 Extensive 11 1 11101 8'HNo si_gnificant__bank 1 Main channel bedrock l 1;substrate(%of area) _ 311 011 01 01 01 0 10: liiailable cover for adult , 4 f Y 7 game fish(turbulance,w0ody Watefdebris.vegetation, turbulant ‘ boulders,overhanging stream _1>oulders, undercut bank) 1 1131 _ _1 91. HI 221 31$ Y _ 101. . '1 1V ~s2 — 116 " -11 {Average maximum Talweg de th(ideep3st1de_gt1hs}§m) _ 1 11 10 251 15' 251_ 5.2» 1 16 31 Sinuosm 1 1 1 1 1 . 1.05 1.4 1112 WID ratio 3,93 1.3 11 6 . 16.4 5 1 ea Overall HQ score 11 it 4 _ 1 135 1 1 1 1 as lletricsTable1 11 3.3.Lcontin1uedu-iabitat 1 _ 1A1riyanka1v‘u _ Quantificat_ion1 ualityHQ score11Quant1if1icatir_>g4 scorinj 1 PaIaruvi_l1| at elected locations 1HQ1score1Quantif11icatio_n of 1" Kallada Palaruvil river 1 11 '1 11 HI-IQ _E €|LChenthuruny score Quantification 1HQ }score % Bank erosion,faiIure and bank 1 L 0 Extensive 10 1 1 1:1Extensive I 1 O_ Extensive Extensive_1 1 11 0 4 ii I HprotectionMain channel bedrock 11 1 11 4su_bstrate(%of a1reaL 1 1 10 |_ 1 4% 1 5 se 1e. O 0| Available cover for adult In “I ! game fish(turbulance.woody debrisvegetation, turbulant white water bouldersoverhanging stream 1 0 1 16 boulders, undercut bank) 1 44. 45 161.1. 1. 33.11 1 113l1 Average maximum Talweg [_1 11 1 t__ 0 1 |1dg|@(4 deepest depthsum) 1 59 251_ 15 25 4 8*1 1 8070'! Q 8010: E W10$invq§ity 15115 5 5 555.55 1.155 5 0.25 5556 5 1-10.55 5 55 4 11.25 55 1-2 [able 3.4. Habi5t5at_qual5ity scoring at elected locations of Pan_1ba5 river _ 5 55 _ 55 [5 5 5 _JTh95ttap_u;h5asse5r¥5 _|5Ti5ru5\_/illapra 5 |Perunth5enaruvi 5_5_ 171211111115 I Metrics 55 5 5 ;Quantificat_i0n HQ 8C0f055;5QUilfltifiC3fiO_t15 HQ score Quantification 5!5HQ score Quantification HQ score ‘Bank e7rosion.failure and bank 7 7 7 7 77 77 Nosignificant 7 7 7 77 7 7 77777777! 7 7 _p5r5otection55Main channel5 __ 55lnte5rmediate 5bedrock _ 4 bank erosion 5 5_55]2_ ' 7 Extensive 7 7 amount 5 o1_ 50_5_L55ir51§ed 5 55 8 ‘;AvailabIe7coversubstrate(%of area) for adult 5 5055 7 1 77 0;_51 05555 0 5 98$ 25 10 O5I ' game fish(turbulance,1-voody 5 debris,vegetation, turbulant 7 1‘boulders,overhangingwhite water 5 . stream L 1 1 lboulders,Averag7e undercut maximurrTTalv1eg bank) 5 55 Tl 05 _5 5 13.477 1 5 15 0575 16 8] 13.1 0 deSinuosity 111514 55 deegstdepthsxmi 55 777 5_5 57 5 1 77 1511 510.05‘ 55_ 55 55_ 155 U55525 11 55 5 30 1 155555 515.2 21 255 4 WIDratjoOverall HQ 5 55 score 5 55 5 7.74 5 5 5 55 55 41 57.35 5 55 4055 55 7.555 51_ 55 555 55543 2.5 5 5 55 7 5- Anqflmoelhl 7 I l*li'@' (‘$151.1-8 ioaovo re re NI O r~>o>_Q Main—— I channela~ _ _ —— bedrock — W _ 1 — _'_ ‘ l$dJstratei%of area) Q Oi .Oi 77 0Q QQ 7 OQ-—— Q 45 Q 16\1 ligaineAvailable fish(turbuiance,woody cover for adult QQQ ‘ l 1 Q 1 AQ 5 A Whilédabiisyegetation, turbulant W818!’ H 4 1 tboulders,‘bouldeispverhanging undercut bank) 9 QQstream 0 14Q @ 0Q ' 5Q Q27; 15, iAverageQQinaximuml h(4 deepesidePths)_[n_1) Talweg1 21 251 Q17.51 l [ 1 25 * 21Q SinuosiiyQQ Q 1.3 Q QQQ Q QQ Q2 1.33 Q2 QQ QQQQ Q 1? Q Q WIDOverall ratio HQ Q scoreQ _ 0.9 Q QQ Q6QQQQ 33 OQQB8 QQ Q 33_ 6 _ 9.25 QQ Q Tabla 3.5. Habitat qlality scoring at QsQlected_locations of Ciialakudy river QQ Q QQ Q *[Ictrica Q T7Bank QuantificationQQ |Vettilap_para HQ erosion,failure score J QQQ Quantification Athiragpallyl HQ scoia ‘Q QQQQuantification Athiragpaiiy Q HQand IIacoia P Q Quantification Vazhachal bank % HQ score I yoteciioi_1QMain channel Q _No sigQnificaQntb:‘bedrock 1 1 12_QLimitedQ 1 Q Q 8iQlnteimediate Q Q; 4 No significant UL 12 §ubstrate(§6_ofarea) l Q Q 9s.97QQ QQ 2st Q so Q Q 16 Q 73,6 251 Q Q46 16; {Available{game fish(turbulance,woody cover 1 1 for'adult Q 1 1 l iwhitedebris,vegetaiion. turbulant Q water " 1 i -bouldeispverhanging stream i boulders, undercut bank) _ 12.7QQ 0Q_ 16:7 Q Q 18.4; Q; 15; _ 8Q I Average maximum TalwegQQQQl Q Q ‘ Q F QQ de tlQ1(4deep1Qgstdepths)§l1)Q QQ Q Q 6.9 QQ 16 4Q QQ QQ OverallWIDSinuosity ratio QQQ Q Q QQ_ HQ Q QQ 20.5 Q 1score Q Q6 2 Q Q Q 21.8_ QQ1Q61 QQ QQ QQ2.6 QQ QQ6 1 ___Q Q Q 6 QQ28.1 Q1 Q Q |_BankMetricsTabloQ3.6.§continued) _ Q QQQ erosion,failure Q QQ Karagpara Quantification Habitaq_guaiity_acorinflQat Q HQ Q score_ andQ }OTU|(0fi'lb3rI_iQQuantification bank electedQQQHQ score Qlocations it1_QuantificatioQn Q Q Qof ChalakudylShoIayarl QQ_ HQ riverQ scoip% QQ Quantification Q }OrukombanQQ QQ Q Q HQQQ scoQife|l{ Q I _@teQctionMain Q Qlntermediate channel QQQ4 QLimitedQ Q QQ 81bedrock intemiediate Q | Q Q1] Extensive l QQ 1» Ol QAvailablegamesubstrQate(%of iish(turbuianoe.woody cover area) ft? Q ad Q ult16,21 _ Q Qol Q QQ QQ20 0 Q‘ iaQ 1 QQ 25Q_A ‘ Q1 45I Y16 dobiisvegetation. turbulant Qvmiteboulderspverhanging water I Q stream A A l 'lAveragebouid_ers. undercutmaximum bank) Talweg Q Q22, Q Qal Q Q Q 33.7 Q QQQ Q 16Q1QQ ‘ QQ 19| a Q 34.1 Q 161 deSinuosig thigi deejiestdepthsliml QQ Q Q Q Q; _Q Q1 QQ '6 if/.21 T 1 2,56 Q1Q QQ Q7Q.3 QQ 6_ Q16Q QQ Q 3.5 Q 81 Q 16 4 WIDOverall ratio HQ Q Qscore Q 2.51 Q QQQ 49 Q6 Q QQ52 Q 711 Qt "657 is Q 6 QQ Q7 Q6 as Table 3.5.Q(continuqd) HabitatKuiiarkutty ualiygcorin at Puliyaia slected locations Thekkacfiyar of Chalakudy river Q Thekkadiyar Q _ QQ QQ Q Q ll _ MetricsBank Quantification er0sion,failure HQ scone Quantification HQ score andQuantification bank HQ score Quantification‘ _ , HQ score Qprotection Q Q QNoQsignificant bi| 12\LirniteQd QQ 1 §QExlenQsivQe Q QQ Q O Extensive Q Q Q 0 l§QuiQ>siia1e(%of%iMain channel area) 1 Q 77 Qbedrock gal 697* 25 56.91 ' ‘16 !or 0Q H Availablegame fish(turbuiance,woody cover for adult1 6 1 1 1 #‘debn's,vegetation,white water turbulant Q Qbouldersoverhanging stream lboulders, undercut bani_ : oo|\: 0U1 ~l Ix) oi in 01 no>o> _L .—~.-.<>> .*‘* °>—*£\_ an an ooo>Qoo Average_|'r'iaximum Talweg 1 I de tl1{7d_1=:_eJ>estdepths)§m)4 _ s 7 7777 7 77 20 7 77 7 7 51:/757 7 16 WIDir1u7<§i1x77777 T370 li7 7 21.8 __ 7 W77 7 17 7_7J52 7 36 777___*__7 _7 7 7 7__7 __7 77 ___7 77 717-_5 2-26 77 60 Overall61 HQ 7_score 77___ 7__7_ _ 7 __77_ ___7 7 _7 77__ 7 Tabla 3.5.(continued} Habitat uaiity scorin at slsgtgd l0ca7t[qn870f Chalakudy I'iV9r __77 77 Thekkadiyar Ill 77 Orukomban Malakkapara 77 7 7 Vallakayam 7 |i6t_r’iEs*mi ltsauantiiicatloflflfit scora1Quantification Hqgcore Quantification 77 J!-IQ Score QuflI1iifi<==fi7Q7" HQ $76.97???) _protectionBank er0sion,failure 77 !Extensiv_e__7 and ba_rlk‘;v' ' 10_Limited 1 W I 8_7Limited Limited 7 8') Main channel bedrock ’ s7u7b$trate(f»60f area) 77 77 59.7_7 7_77_ 7 5Oi 7 7716777“ 7 O vi 760 12% Available cover for adult 1 game fish(turbu|ance.vvoody deb|is,vegetation, turbulant white water bouldersnverhanging stream 1 boulders. undercutjbiajk) 1 21.4 251 161 0.8 0 gs 16 Average maximum Talweg 1 ! Wfi '1 1 de th(4 deepest depths)_(m)7 _ 9.3l 1e 7 3.257777 45 25 $iou7Q§i1y 77 __77 1'1 _ e_ _7 _77 ___7___74 1. 4 6 3"iii 6 7_7 47 76 WIDOverall HO ratio score H U it Tabla lflcontinued) Ha_bi7ta7t uality scoring at slected locations7o_f_Qi1ai_a__7k7udy river 7 7 Metrics liuantificatioyrfifif Anakkallanka HQ score am Quantification Padi_l<_u7t_ty77 Ho”s¢aia Karagpara Quantification river HQ 77___7\{e_ttiscore Quantification Ar HQ77 score7 Bank erosion,failure and bank TprotectionMain channel bedrock {Extensive 777_777__777 0_E7xtensive 1 07l|1termed_7i7a_7t7__<-;77 4:lntermedi_at_e_ 77 4 substrate(%of area) 7 63 1 167 77 25 8.5 i O 7 Q_7 1/Wailable cover for adult ) game fish(turbulance,woody _ debris.vegetation_ turbulani 1 while water boulders.overhanging stream boulders, undercut bank) 77 7 161 15! 8 32.8 16 52,1 I 25' Average maximum Talweg de th(4 deepestdepths)_(m)77 77 77 7__77§_1_.§: 251 15 zsi 15.51 257 751 1 5 WID$_imiQ=‘~itL_7,___7_ ratio 77 7 77___77_ 0.79 77 I _771 6 7 4 2.81 6 7777__77_____7717.37 1.15 _ 6 5-5? “"4 6 overaiii HQ score 1 as 7__Lo 7 77 7 77 7 53 777 755 Table 3.6. Habitat quality scoring at slocted locations of Periyar river Habitat quality score Bhoothathankettu 7 Ne7n7'y_amanga|am7 7 Pooyamkutty Purakallu __7 lMetricsBank ' 777 ‘Quantiticatior#HQ erosionjailure s_cor7e_7Quantificatio2]Hgscore and IQuantification bank 'l-IQ 7 scor7e_ 1 7Quan7tjj7ication1 HQ score P7919919" intermediate__7_7 _ 7 4§ Limited 7 a Limited sl Limited a }Main channelbedrock 77substrate(%of a7rg_a)_7 0i oi oi) 7707777 1 7 ssi 7 87777 77 92.51 251 Available cover for adult game fish(turbulance,woody 1 debris.vegetation, turbulant 1 while water boulders.overhanging stream bouiders_,7_7u7ndercut bank) 7 74-71.77 70777 77 25-3.5 7 7 77 7 16 40.5) 161 5.2 oi ‘—| *§iAverage maximum Tamas @p_th(4 deepest7d§pths)_(m) 1 7 77 15’ 25, 677_777 ___77 7 1§7 7Sinuosity ____7 _7717-17 7 77 4 1-717 it _i 717 6 QigrallWIQ ratio HQ_777 score5.7 5 __7 7 1 101.8_ 55 10.9i““i“*__7 _ 7? 6 ‘fzlble 3 6 (continued) Habitat uality scoring at slecte_d locations of Peri ar river [Habitat quality7_score7 7 ____fihandam3_nkuflu it .1Neenda;gra__[_y 'i_]Mag§p]>ara 7 7___7:77777__]P7idiQ@@7____7__]7_77 7 I _A ‘Kai b C5 -5 @ .-L IQ ta» C7 O3 -§ O5 l\J OJ ‘Q7 l,i1i'"'<=' 1111611 1 1 1 ]1QlL1i="""=="°"I'1°2-6°16I9va"=m¢="°fl*i9 6196n2TQ~=23i"12a*i2"1 JHQ 6¢9~I°v1§"Ilfi<=§1"°'J1I'iQ 666*»! Bank erosionjailure and bank 1 M M 5 q A \ MainQg5>161<1i0!1\ 11111 channel11111 1 1“h§1osj1qni1jca1r1tb1;l1 bedrock 1 11f¢21E>gen§1iv<=-:11 1111 1H 1Q_I151=dg1nsiv16 V q11 11 T1H 1 11 Q1EX1§n§§v6111111\‘111M 6 *1 110% 1w!I1611'6*°i%Q?q!61§)’A6vaila5leEovérforad6ult 1 1 A 1 1 1 317-5J\11 ‘ 1 ‘ ‘ A‘ 1 1257 A ifQ1 A‘ 0% ‘2% M 0 50J1,1 ~~ 11 A1§1\ . ‘!debris,vegetation,‘game fish(turbulanoe,woody turbulant ‘ 1 M M ‘*A A\1 H ‘ 1 AA *1 1\ qboulderspverhangingwhitewater M ‘\ stream “ H 6‘1 \ M6‘ 1 ‘*q w H 1 1 1‘ 1‘ mgm¢§m.1ungg@1gpqnx)1 11“ 11 11 1 161.21 1 01 1 11 §‘1 191 1 1 1 1191 1 1861 1 112.41 1 1161» *6'A\ioragé 11"\(i6¢@as==-1d6PLh$LL"1>1 maximum 1 1 1 6 116» 1 1 1 151Talweg 1 16*; 1 1 1 166* 6 12166 ' “ 1 16 Y1 ‘11116 6111l%x11116111611 1161 1 1 11131 1 16 1 1 11 1 1 6 1 1 113-2,1 11 1 1 1 1 11 11ID1raLi161111111111 1 1 1 1 19.51 11 1 6 1 2131 1 1121 1 11 1 11-16 1 16 1 1 16-7 11 16 Ov_9m1|Hsgc1>r§11:11° 11¢!4 11_1__11165_1111 1.071 1 _111261111_111t11:}311111_1 11 1 114 1_'§_2 T166116L 216- <1=96t!'!wg)H§b1!=t u9!ItL=96fl1!\ $616669 Ig¢=ti6n16<11P9ri 9' rivsr 11 1 1 1 1 1 1 11 11 1 1 ‘Bank{ll'"">*I-l0.llItnggaIigy1_s§1o|11e11 161611 .161 161 11 erosionjailureE1"='"'"<=="<>" 1 Thgnnig1m1oqL1 "°==¢°'°}2u="l"1¢=*~" 1 1 =1§°'1!:gangiarguzti 1QIs'='1l-"@619"1 11and 1 %|iukkan11 1 1!1*Q;<=¢@>1'6 bank1 11 1 ¥ 1Q"=2*'f£~=="11<>"111 1 6_[Nallathanni H 1 1!*Q11==<=<:'_<: 1L 1111 111 i 4 11E1§r0te1§l0p1Maincharinélbedrook6 _1 _1 1 ;UE§te|lsiv§1 1 L 1 11g‘Exl1gnsive 6 H A 1 61 O1\intermed[ate11 ‘J 6 *6 _1_6 1111606 11 _1{H1Exte_nsive_ 6 6*‘ 6 11 )1 1_ 111%16 flgameMvailable“.§!b§t5=@Li=6!@r92)11 fish(turbulance,woody 1cover 1 1 1 911 1 9&1for 1 1 1161adult 1 11 mg 1 W1 1 512111 6‘ M 11291 Uw 11\ M1105116 \ W‘ 1111011» T A , ‘boulderspverhanging‘fnhite11dobris,vegetation, water lurbulantM 1 streamM 1» \M A ~nU AA\ “N AA ,6 A 1\ L‘bguld1er§u|j§|er§ut1baqk)1 1, 1 11 1 53.9111 1 11011 1 1 11129,‘ 1 1111§W1 11 1 U11 11 10111 11 111;; 111011 ywemzede_ (51aee1ges1:1ae£:ns;gm; makimum \ Ta6lwe691 11 11 sw 16 61 616 622 i. 1 12s\*6 *1, * 113.51» J1 11 “ $1'1\l_i6Q6i!111111111 1 1 11-3 6 166162 6 1616 16611116161 1% 1 1 1 16 1 1116 1 1 1 1 16 V§7Q1{a;io1 11 11 111 11 1 11 1 1 3 11_ 1_ Q 11A 11 11 41.13 11 11_ 1§ _11 11118] 111 1112.1 111 1116 11 111111016 1 1 16 1Qv2@I!F1Q6s6r§1111 1 1 1 1 1 1 1 124 1 1 1 1 1 53 1 1 1 1 1 11 1661 1 1 11 1 1 12° T3119;-16-Lcqntipugd)Habitat ualitygcgriq agslegteq I61==1i1<3ns11<>f1Ff6ri 3[1"i1!3'1 1 1 1111111 11 1 1 ,1 11 11 1 11111111 I-lgbltgtgualit)-1ac<;re1 1 Kugchitha11ni1_:1 11 1 ly1angrqgPa[a 1_ 1 1CI1oor1rapg1ra11 1 1 1 11 Qmg11]ikL£Pa[\1thogu_1 1111 [Ditties 16 661 61 6 1 Q6@aniifig§tlc§n HQscoro]6E!uantificatlo|d6:2 scoro+Quantification 1 iHQscore]6Quantification1HQscorej fBa6nke6rosi6bn.féiIu6reé6nd bankA66 A‘ A6" ” ‘ ‘ A I6 6‘ A ‘ " ‘ ‘ ‘ ‘ ‘ ‘ 6* * A“ 6 I Lrprotection 1 1 1 1 1 11TEx1§nsive11 1\1_1 1 10_§xtepsi3_e 1 M1 1 1 0161Ex1ensive1\ 1 ‘61 ,_1_ 11 110\\1§_xteg§ivg1 6 111111 111 Q] \Mainch§nn6:lb6:df0cJ6<6 A" T * " A A w " W 6 6‘ 6 M» 6* 6 6“ 66 6 6 66 6 A 6' f 1 A fiviilabfi1w9=lr16¢ T§P|°_3-15¢1(§°_Tlt|1|11U9g}|f|3b1i§it wgligg sgorig 1at§1e<=1t1e9 logati9ns1of1Pgr1i1gr rjver 1 1 11 11 111 11 1 111 1111 11____1______1_ 11"!!>"!F1£1\!!'*£¥=1§°!¢ 1 1 T"1§1"QikvQL11 1 1 1 /\01a'1k9'1'§"'1<19 6611111, Pylimn/=3'1\1111111 1 11 11 MI6gg6ug1§l6l*s>'11 1111 t Bénk66éroéiorY,faiTuré aiid b6ank 6 6 6 6 6 6 6 66 6 6 66 6 6 6 6 6 6 6 6 6 rgtectiop 1 1 1 11 1 lpte1rmgdia1te11 1 1 4 Eageqsivg 1 1 1 1 Q Limited 8 Limited 8 Maifich5nn6elb6edrocR 6 6 6 6 6 6 6 6 6 6 6 6 66 6 6 6666666 6 66 66 666 66 6 666 6 66 66 SvyatwiefletrlcgA 1 11 ‘>1§16f1§re1a)11 1 1 1 1 Qgagtiflgatlon 1 1 HQ 11 sqom 111132 Quantiflcfllo?HQ 111 1§ 1 111111151131sgcorp Qugntfllczgiog 1 125 11 HQ1 1 1§co1re 1 90.135 _Qu1gn 1 1 gsificqtign 1 1 164.5 flQs§10re 16 w-———P*°r—+*—1+—— 6631 Available cover tor adult game fish(turbulanoe,woody deblis,vegetation, turbulant white water b0ulders.overhanging stream 7 p0ulders.undercutbankL !7 771-1.317 7 9. 77 13.97 0.7 13... 0 l 14-7.1. 1l1Aver1afg1e maximum Talvieg [11 1 11 I detl1(i7dee@stde7gths)_(n_|l7771 7 5.85‘ 7 7 1761 7 10_ 251 2317 25t_ 6_ 7Sinuosit7[ 77 7 7 1 7 767 7 17 77 76 6 1.1 WfDratio 77 10.9 6 4.06 7 s 7 72.473 1 6 10.8 Overall HQ Score 11 4011 7 7 1 62 770 Ta1bl1e1113.§4con17t1i1nued)Habltat111uality1ecorl7n_ atslected locatione of Perl ar river 77 77 7___ _ _ 1 Metrics 1 1 1 Quantification HQ score Quantification HQ score Quantification 77 HQ score 7t72ua7nti7fi7c7a7t7io7n Hqecore .Hlbitatjuality 7 ._ 7 score _ Thannikudyll __.‘ 7 m Fillalgyam. ._ _. {Y .tiadathottam _. _ _1‘7 7 77 7Moo7Iavaiga 7 { flank eros1on,fa|lure and bank f 4 Limited7 8|7intermediate L7 4 Intermediate 77 _protec7t7i7onMain channel 77 7 7 7bedrock 77i7nterme7diate7, 1 "1 1 [substrate(%ofareaL 7 ‘ 857 7 25|7_7 7 38.1_ 787 7 65.27_7 257 _7 0.. of Ukeailablecover foFadult. ,.. _ . W71 . I 1 l game fish(turbulance.wo0dy . 1 debn's,vegetation. turbulant white water lbqulders.bouIders,overhanging undercutstream bank) 77 267.3{ 16 26.5; 161; 6.1 077 11.57 Average maximum11Talweg T 1 “-9. . I .. 7 _. . .7 25‘ rde th(4 deepest d7t=5pll'\s)(n1L7 77 207 7 251. 20 7 72757 777 15 7725 7 170 Sinuqsitl 77 7 7 7 7 7 7 71 7 7 6‘ 1 771.14 14 77 7 72 77 1 . 77 2 . 7 4 7W!Drati70 7 7 77 77 27.77174 6 7 7 1.8 76 7 2.9 67 3.35 6 Overall H0 score 77 7 7 762 7 7 7 66 672 7 7 7 7 39 7fI'able Z§7._6.7{gontlnued) ljabltat ualitlscorin at slected locations of Peri ar r7iv7er 77 7 7 7 7 7 7 777 I-iabltatquallty score1 7 7 Kundamkallu 77 7 _ 7 Mukkar 7 7 7 77 Chembakavallithodu 77 7 Kattamadithodu Q BankMetrics 7 7erosionjailure Quantification HQ score Quantification and 7bank I HQ11 score1 1- Quantification 11 1 7 1IHQ score1 Quantificatlon|HQ1111 1 1 score 1 QrotectionMain channel7 7 ]7lnterm7ediate777_?7_7 bedrock 7‘ 4 “Limited 1 " _7 877 intermediate 41 Extensive _°! g1bstrate(°/tiotargl 77 7_77 7 1577 7 07 0 7 t 0. ...._ 0. _- _ .7 9. .._ ,0. 1 7Available game fish(turbulance,woody cover tor adult 7 11 I1 whitedebrisyegelation. turbulant water 1 1 b0uIders,overhanging stream ‘boulders undercut bank) 2 571 16‘_77 41 7 167 56» 3577 15 F/llverage‘ 77 1 maximum7 6. Talweg 1 1 1 - . 251, | de th§47deepestd7ePtl1s)§m) 7? 7 7 7 7 377 157 251 712 25' 714 15. 1.66 Sinuos'EL_7 7 7 7 71.50111 1 1 1.1a 77 7 1 1 7 1.3 7 3 7.7.70 WID ratio 7 73.7 _ 76 7 71 7.6 1 0.92 6 7770.7 6 Overall HQ score 1 1 11 1 1 1 62 as Table [email protected] ualgpcortng at _sle7ct7ed locations of Peri ar I’i\{6f FabitatBanklletrtca quay 7erosion.failure 7 7 ccore 7 Quantification Kattama7dithodu_l and I-IQ scorebank 77 1LKuntrapuzhazaJ:LQuantification 1 I 1% 1 1HQ _ score11 7 Jlotection 7 7 7 7 J7iEXtensive 11_ t]77l§xtens7ive . 7 1_7e (7)7 Main channel bedrock 11 11 -7 1 1 1‘ 1 L7substrate77(%oflAvallable coverT‘-_.0t area)for adult 7 7 5166 111 Q77 1 1 Q7 1 or game fish(turbuIanoe,woody ‘ 1 1debn's.vegetation,white water turbulant 6 boulderspverhanging stream » ' {AVGTHQG7boul7ders, undercut maximum1 bank)in 7Talweg1 15,5777 "1 1 77 l 1637 Q Q .$_‘""°$l5L.de th(4dee@s7tdept7hs1§m) . . .1 7 91 7161777 6 1 1.17 4_2 W/D ratio 7 7 7 7 11 1Q_7 1 1 5 1 1 1_5 Overall HQ score 77 7 1 7 73751 7 1 1‘ 1' __+_._. is L--1-— <'51cnJ=~=g 5536”. O ‘gown 24_L 9 Table 3.7.Fish species collected from different locations of Kabbini river system? ” I I VSUIBEI I Rasborinae I " Cyprinidae I_ IX ._ IIIIIII I IIIII I _]-I I II/-I.melettI'nus B-bakerI' I;_ I IIIII H II I IX I I IX Ix I Ix ‘IX IX IX K I B. gatensis I IX IX"I I =X IX I5 IX II I I IXIXI I D.maIaban'cys I iv . 1 Ix Ix IxI I‘ Ix Ix M X IR.daniconIus I I XI I iX IX1I ——. IxI VY =IIIT I Aplocheilidae I I I I I“ IIIII I I I I I I I I/qpfochei/us fineatus I I JI Ix III I I__||X I I _I I Icyprinidae Ix I I ICyprininae I. __ I I . II I I I Ix _IX I I l ILPUHIIUS camatfcus I x ' T.1 x I I I>< IX I I I I I Ix "I I II I I 7 I Grebe I I I-I . IKantaka brevidorsalis I IX I _ I._II x.I I II-I.duII>I‘IIs IX IX Xx I, I ‘II xIxI I I IX II I I I I . I : I .._»X 20.1788)-"1, I IX Ix I Ix Ix? I ‘ I "I IIP.choIa III I "II I ‘IX I II I I I Ix I P. conchonius I I IX I I I X I Q II.X X “IX II _I_P. fasciatus_ I I X X I f X IxI . _ ii I I' I I I I I P. filamentosus I I I I 1 I 4__ I I ;P.parrah I 4_I I I I I I I I V I IP.sarana subnasutus p. g. II? ’_P. ticto I I .IX I X I I IXI I I I ._I~ I II I T I I P. vittafus I II l>< II Q I I II _I_I I I I ; N. wynaadensis IX Ix I5. I I I I c‘ I I T. putitora I IX ._ IX; I - I I Y I_ V I I I I I I I Nandidae I I I I_ I II I Qhanda name I I III W I x Igyprinidae I IIGariinae I I I “I I I ~ I J. I I I;7 G . g. steno rhynchus Ix X I I I x IX Z I A I I_IG.mCC[QII8fldi IX IX z IX IX? I ii TIX I I I I I ‘X I_G.muflya _ X “X XI IX IX _ X IX Gobiidae I X I "I I “II . I I _I_ Gobiinae I Y I IX ‘I IV I I'IG.gI'un's _ I I ‘ I I IX IX; Sisqridae _ I, V .I fl "T I Z.‘. .. I X . I I IIG.Ionah IxI I ‘I I IiI I II_GIyptothorax annarIdaIeI' I I I I I I X V I I I I I LI I I J I I V IHeteropneustIidae I I I1I I 1‘ I I I ; H. fossifis III I IX — I I I‘ Cobitidae I I II I I I IICyprinidae I I "I I I I ' "X I _I I I TX I Q fhermalis __ -I IL.I I IX L I I ‘XI I I I I I Bagridae I I I I III I I I .IX IL4 9”'"@'"I$ I I II I>< IX II I I. I>< IIX _I__fl II I I IIX Ix I I I I I I I I M.bIe6kéfi I II I5 I ‘ Y I ' ' I> I cai/asI'us I .>_< IXI I I I . I I I I. I M. gulio I . I _ I_ II IIIIX I I 7 .,_ I Ix I*I M. malabaricus l_. I I .’I ‘ I I —I |IMysfus punctatus I I I _I I I II __I I I” I LI I II I I I Macropodinae I Belontidae I I I I I I IMacrop0dus cupanus I I I I ‘I IIII I I I ~I Ihflastacembelidafe _ I I I IX.III—e ~ ‘I '"'\I‘I Mastacembeles armatus IX Ix xLxII I _ Ij I1 I Channidae I I .,_ I I IIII I II. I I I Ix I Q. marufi us I I Y ' I I C . striatus I I _I= I I I I IX ‘ I I I 'II IBalitoridae §a|itorinae I , I_ I I_ -2-II I‘YI4 II IIiI I I I I I IlV.guentherI' _ II I .I- I I I I I I Ix I; I I I I II _N.monI'II's I V _ I_ _ I XI 1 I Ii. I N. semiarmatus I X Z I —|_i LIX I_I FY X § I f‘>< >< I____I 4+ __+ _§ >< TI 'Y ¥>N.trianguf;?ris E =" x*IxA’._ .1 .> i;fiL‘ IB. australis x j 5 1 ‘ \ x " xI i-‘I Nemacheiius dénisoni day! W [ i(i M _ _.1:f % _( X A> A'_ 1 ( A>E (_ l__ . ._‘ 1 lhtoggeridae ! " _ .| .7 . I» .i.__[\ Y .__ if _,|, ‘. T ! 7 Notopterus notopterusf ‘H_ AXEX‘ |\ ‘:_- 1FlI i %. , _ 7Siluridae j _ , . __ ‘ L_.; _ 1. _ _._\ I|* 7 Omjaok malabaricus 1 = JXX1" J E _S.v/ynaadgansis _ E . _ \ Ambassidae % i i h é L1 Ti .'.1, A|_. |V i Parzsymbassis thomassi _%_’i 2(x\j ; A __ aé g Pseudambassis ranga% i_ _ . 7 % AW» Xi J I ,. gmrinidae j f §Culuinae i | _ A A | E S_a!mostom_a boopis i w & 1 X [X X \ EX .‘ L ‘[SaImostoma sardinefla " x 3< Su - Sugandagifi PA( - Pa|veIicham* % TA - Thariod L PO - Ponkuzhii" BE I - Begur I AC - Achoor AR I - Aranagiri I NO - Noolpuzha KU - Kunnambatta BE - Begur AR ll - Aranagiri ll MU - Muthanga KR - Kuruvadeep BE ll - Begur ll AR - Aranagiri _ | é_ ‘IA: L ‘ 7 __ k\‘i7 W I i [1 l',_‘I|‘|’l:I‘ H! A ii‘ \ [ @ Efismwmfiwbfiwg X$O£O_%_o‘ |_| ] 'i\‘l HP1‘? __&_wg_wE_w XsO£O__§6 Y _iI‘ _I ]_ ITI 1 [I é MU é_[_: _: IV _H iv It } % °g___3_mA I\L -fit ‘}_ _||_ _; y FA H t‘ A_ _[‘h_l X " T f X? N‘MBOBEWMWOE $895090; I‘ ___t_ V _|I‘\ _| ‘_ Q ‘} “ XJ ‘w__2®§__m__\ gag“ I“ A_[ > >\i‘l‘ XL X! ‘|_ XXE ‘Weggwg g_|O@m W] ‘]_' Av__“!‘ _|1‘ >_ _v 1“ [‘ IT i“ “_ g______u_° ‘I ‘J H: TL J[k!_ |X]_\ [A mo_:_gm_mE mamxmm ‘|‘ _i|AII If AU _[ ‘]_ Ii.‘ Q> g__:=°__on_ AA g_U_&=_Ao 7LfiN_IX _35% mé___§_ON} _£ L‘ F\lX\ A|% K Q‘ wgakws mgmmg >| J‘ “‘[‘ ‘IL’O%_____£m j "Q X_|X1 8288 WEQBQXQQOCOQ T‘_ I]_L_ _Y _1 IV: l[“‘LY X“_mp 022$ ‘OEQDOBEQEQ Wg§n_> Xxi”1 Tl _l}_ X_!'xi 3 fiI: OB: waccam ‘:_ 7! _>7 _‘| _fflyéM W2%_wg_6 gmgw Q___E___Q L% Tm X1”X_XXA %[ ____mt& g___~§m\ N TX {Ax XXfxxX‘5N wqwoucmgmwt gfiah >iV x_|__l_‘ 7_ _' _? X1] F QMil_ _I_|él l ml :_ TI “LWBNEOQQM Wbbfifim g_m_e% WBMMCDQ QOEU gcgm H_ it ‘Y q [Mi ‘V M @l_ 4 1% [AH 4L \LlXXgO_E§OQ gagm “two £8_ |_ __]_v _|: __iv|v|f ii _’_ I} '1 'i' k |_°~:l:_~%q 1\ g_o____:_No (X Vi J ¢[_ N‘ xv[;]_ II >\| _i NI '[ i‘ ' 5 !"> “Z X» ‘IL II_ Xjimg_EOO_E% $OQWm_m 9_O_tg$mE wawmccgwgmm G IL _|é X_: A‘ U macgmnmo g%émm% VD” (‘TL "ll EL FMi X_ WW %0_mpc°Q Qstmm XITQX4; 1|_ IILX% m_§§m$:\__%m Ax _[I \~kgmQAA_w=___\kmm __'\‘ “L _! ‘L 3, JV d ‘j_ 5‘J i‘I QM W_%_°__0__E __O8&§g%_BE¢\ fi b $_____°£Wm_k HA o~u_=__a _§mb_u WM v_% _l ‘_v‘ I! hv J! \\ _[\ AI ‘N < ix _[y__ Iv _w l_||' ‘Ii! [IL ‘X1LX? X”‘I xi Wwmmaochmamwmagmkmm m3gQ8ocE\a mamgsq __v_i Io&Dn_L L XX x IxI IXX X I I ,B.bakeri $ j % I gatensis L I I _ [ X__. X X X D.malaba_ricus% j %u A X @ x_. Ix. . ___ _Ix Ix I ‘X IX I" l T . R. datiiconius H_I I I IICXhannidaeIi ' t‘ X ._ :I I . I Cmicropeltes XX I _ Ll __ I. II . _ X. I I Qobiidae Gobiinae ; __l It I I I I I'I ,_ I X . l | G.giun'sfi X X j 1 It I I Cxprinadae M Garrinae L_ . Gmullya 7 __? I X XXIX XXX X Ix X Ivx o_ Ciprinidae Clprininae % A> I I. _4_ . I A XXIX XX -’—1X1 _H.CU!TTIUC3 A ? I I cLXtI,_[ . I I H. thomassi i j I Ix X >< _ _, {ff- _ _.7 l i I Cobitidae { M A I I I I Legidocephalus thermalis o % X I I X . I I N. guentheri % f Y 7 ‘XIl N. tn'ar_1guIaris F X _ XX { 'f‘ i I X XX X Cmrinidae Czprininae _ O,bakeri L XI l ' 7 l I. II _P.emphib:'u§ I X '0 P.aruliusX K __ I, c_[ A P. fasciatus V . X i. xx I I I. P. filamentosus X X IX I I AI X _ T. khudree _ 7 A x Ix X ><~ I l ;IP.n'¢ro X ‘ _ I Ambassidae I Rasborinae A I Parambassis thomassi X I * I F XHII l " | I L I_Belonidae X I » I 1>X.cancila I A I A IXT ? X I. IX Balitoridae I x I I I I I_ A ‘XI X B.australis*X X N ¢ ‘I A X I _ . 7 I :Cichlidae I l __ ‘l I " ! I Oreochromis mossambicustl H i X, Li UR-U ru kun nu KA-Kazhuthuruty OT-Ottakkal AR-Ariyankavu ME-Meenmutty PA I-Palaruvi I DA-Dali PAIl-Palaruvi ll MS-MSL CE-Chenthuruny CH~Chenka|i >3 >< >< >< ll!-_ $< Table 3.10.Fish species collected from different locations of Pamba river sysfiem _? I I ‘I T IAYTI-I ITI PE I/$2 AN Nl__? AT [KAI IIKAIB/§_ M0 I IIAQ KKI KKII KO Igxprinidae M _ Rasberjnae. II __I_I__ I, I' I I II I XII I LIX I X 1' __I ._ IX 'X B.bakIeriA _ " I ( “ x I %_x X X X X XII I gateljcis X IX X I Ix xix x I II I _ _ I I X x I flaeqgipinnatus j W 7 @.%maIaban'cus _ _u IX X X I X7 XXXI!XX R.dam'c0nius i___ II' JIII I Bagridae A j W I ' I I XII _Batasiotra\(a;_1oorI'a j I wk Iflorabagrus brachysomau I IX T I Iflysfdé armatus _ I IX XI I X X X I I__I I I “I Channidae A J > L I IChanna_maruh'us M X I rlnidae ICultri_|jae I I Chela fasciata % W X A Salmostoma 5:-lcinaces X II“ X IX Q IP.ampg;'biu§ % * I I Ix ‘ I P.c!'g0Ia HM XIII __I I _rI . . _ x P. fésciatus XI XX IX IP.fiIamentosus I X X IX XXIXIXX x xx I 'P.samna sdbnasutus X I I _ X I__I I I.iW: .,II IX __v WX ' I P. tictq _ _ I . I i ' I I T. khudree 1 IX__ 'X I I ..II_ I ‘ , I Ifleteropneustideje I I I I I A I H. fossilis I + I I I _I.l A V W I I Mastacembelidae I ‘ 1 I III A I I*II . WastacembefesI III armatus X X I . I X I XI I Balitoridae Balitorinae Mguentheri fX IX X I_ I XI _1.!.tn'anguIan's I ‘X IINandidae ___ Nandus nandus 7 X I __ V _ _. ._._ Pristolepidinae _ .I 7_ Q. __I I X I I IP.ma(g:'nata M 4___ I _ I_II_ Ifpecilidae W 7 _ 4 I IX IX Poecilia sg i _x xIxx L ~Sflufidae I Iwaflago aitu W X I I _4_._ ‘ : Ambzissidae I I ‘I I A I I I I I II I I Parambassié thomassi XI I _ , I__y .._ I _ TH-Thottapuzhssen] KA I Kakkad Ar I TI-Tiruvillapra KA II-Kakkad Ar II PE-Peruthenaruvi PA-Pamba AN—angamoozhi MO I-Moozhiyar I AZ-Azhutha MO II-Moozhiyar II NI-Nilakkalthodu KK I-Kakki I AT-Attathodu KK ll-Kakki ll KO-Kochupamba 4 I§< >< _ ‘ _X Ti ‘J1 1 _l_ j__ I [L _| XXX ‘I ‘\ _“ _mmU_C&_fiaNO W §E&_Q[L XHL‘ _X“ Xl__ _[‘Xi |X __ A? A XY [X xi? 5 WM N X_0%_____%Q Wi Agm8:®EflE‘n_ ‘II ‘A’ L; F X 45 XX Xx” _I _y "‘ _|_"8_v_c___%O it om_U_c___%_“_UL ‘LI i[' ‘hUV _v if __‘ 7Av ‘HIM MIL _\i X_m F- \ 1“ ‘N’ Lmnkmaommwm” w__mm__§_m_ gofimm%_c__fl_NO omgct Og__m__€_§__'n_ IL Y '1XXXHAX X; omgctfioA &_@°b__%Q_o TX 5" up XX_ XMD L V w=_9__I 7% "l_ T ‘L Xx»Jfig E30 HM_]_F“ ii iii ___ _Y LI: M_ ;‘ |_ J XA kw ;‘:] Ofln_C_&a QDOMEW Wem__%§Q__ lg! ]7 k‘! 1| _‘ A“ ]_ ‘A % w>ix__I? mw_§mg5°m§w_o _iN‘ t ' _[I “ H_ H_|__ ;_ > } >_ONEBOQA |°g__n8 V‘ X“X_ __||_Xx||_N_ x_1\H__EW£N___EbC9DW 6 _\] *_g[I I_ YXx" K X;Al Xx’ VNXMéagd X_ _LIt >_ i!ggtmo3_u_L_|XmHL fixX? i“W 1] ‘J jTL I1 XF! >ll {IN,’ __: O_§mbcgcm_0é gu_h3_q_Ab’fi_AX L‘ 4 I_‘ 4| A_| XV _] XMIA ‘M m___g&Eg_m _|}_A 5L__; ] ‘bv X7 j_ _! XX? me_w_\£\mE_m_? ‘MyWA H _l_[_KJ _|| _[_:_ _o_§__r_2oXX IEX WA_W1 ‘AX _i A_ _L; ArY :7 k ‘V III‘, _[\|i ______w__Eaw%_O °%_h__~_o __[:J _? l_ £1“ __v ___W_cOOCQ> gab L_AI >__ [F >7 l YX_ j 3 J“ XXXX1 §_____%OU hwmutmumWD_EOO__Cm__b_m _i_é}_i _____\1 2 JXX“ IF xxxfXX x_| ‘X ml_§__wg_m_E OEWQ _[_\ I’X “X ‘Igpgflg gsamXX__ ‘J? x_! ®%_____%O§ Lg_~mcc_a_§Uom__Q XIX“‘>" W! _]_ X‘[\X §_A XI m_W%Em_m Xx;XXIXLVx_XI ‘W ‘T T‘ v XFW x_ fl fi wxggmswolm ‘Ii 7 F! ‘> " _m_8_%___g_m_ PX‘ X]_'1 ‘\ll] _|V: X“ X\ _IéL My_ ‘]1 XTAXXW _J_ XV?“ M5 _J tmxmnom Q _A0m______°n$MQ :%_u______%q f II!‘ TIL_| N;_XVNA _V [ '‘ J] A‘ Y‘ U f0_“___§_é §_2_8_ g$______\mqVw2N_V_?_n_vz5|___>L_ <2 mOX____E_¢1__¢*T an D! N_Oi_l_w_N_Oi Table 3.13.Classification of different species identified from Kabbini under 10 metrics _t _ I it it vsedforlbltscodtng TC ~S|;ecies It If YINAT' LO ISU4!-— IINTSMWS ._fi. ___% __ -1 ‘TP A V. IIHE MOM I WIIINIW .L_ _A.meIettinus _ I IB.b&k6n' Y II IIY I I I ‘ JIY __T[ H W ._t it _ ' _ I IIBI@ensis I IY .’~ L I T ID.malaban'cus i QY Ii I I1 I I!III I 'R.damcon' ius I Y IY to A ~I Ijpiocheiluslineatus fit! 7" "TI F In I 1 _Puhtius Eamaticus I i I IYI TII eh“ I‘_ \_ 1 I IICirrhinus reba | 4 T“?L gt _II I I Y "I ;Kantaka bnevfdorsalis it IIY I IH.dubius I I I _t! L I F IQ? L7 I I FY." I Io.nash;ii‘ _ _1, .. on I. I I IYI I chbla E — — ——\ L [ T Li __ I T‘ I0? I _ I IP.bonchom'usI IL I it O, P fasciatuéi ' A X II, I (I0 IKIII i‘-I I ;I* I Iifilémentosus I I _t I1 I I I I Io I Imnah Y F" in ;P.sarana subnasutus I__ IY I , Y _ I ifltictott If ii 7 77 [Ye 4 IQ IP- vittatus ' L _ IVY _I 1 I 1 II“I 1 ;IY IN, wlnaadebsis I I _ tiIIYI II! I 7 IY "'%; Y L Ilputitom t | _IChanda_nema I I i* i>Y I ; ewe“ ' ;G.g.¥s§enQrhynchus _% h It Weif, w I IG.mcc!9!!877di I "Y JIY In .[_ RL" Ii L ‘I W Y I §.m_ugyaI H N * H I ‘—I' lG.@m's _ W 77 IY _ Ii I T_iI _ 4 ‘ _ _,, Glonah it I * _ Iv __H IIH ' 1 .[_ TY? __ . qr’ §&'P@'"°@Xtt8~h@"da'éf I IY | T "H F:.rqssm's it I III I IIL I , , *L.thennaii's It “W MY I Y ITCIIQZO “ IM.armatus IY ,,,;[ I . 1._ . _ I5 I I II I II Y It[V 7. 7 1*!I My-_-e. _'M.bleeken' _ _ { _ Y fl ,, dc I IIM.ca vasius if U IY L I _t|[_ IC I Ifllgqlid A I I 'i Y I I ice _ I I "W I I “WI ‘Z aIC IM.ma!aban'cus IY I ___‘I . ‘I . I I I , _I I 1 I':{¥stuQunctatus_ t i _ dc II IY -I _t _ I _tI IL flacmpodus cupainusf W‘ II,_, ' IT ‘_, _ ' I“I I i IIIOKII] it Masifioeriibeles annatus I I I __1 I TY I fi—_._‘_ TC "_'I I___i,i‘. Y | I'I§,niaruIiusM I W i I? 3% I, I I (TI I; ITC Y (3.stn'qrusI*_ It I L, _ V . 1-[C IN uentheri I _i L IY I fl I j/@mQ0l"$ I "TI I _ ‘I i IIN.semiannatus it ,Y I _ I _N§*tn'an@ian'S__ I 7 ;IY IIIif I IB§austné!is I I YII I? , I If 7 I _t _ 77 _I 7 H I Q if If III It I‘! ,Ii .I__ _ I jvemacheiius denisgnii dqyi v A I01 _ I 4| I~°QP'9t"4$ "°@f"3'”$ |t_t ~i I ITC I I I°£'P°* maiabaficvs I I QII Tc '4_’l@°?d9”3"5» W Y i It I __I” T "H -It __i LCI IIPammbassis thomassi __ _7I III TC fseuqambassisi range I It ; TC .,| II_SaImostoma poop}; fIT §Y ' I I’ I I I I ,ASa!most%oma _s:-miinelia Y I Y I II I I I. Table 3.14.CIassific tion of different species identified from Bharathapuzha river under 10Imetries S cies it __ f W NAT 1:0 SU INTS MWS TP HE It OM I“Amba$sisq1mn9cepha!us_tParambassis a thomassi I I %I nI Itj _QI if Iit 1"it I Q -< -< 3?-< Y -< -f -< -< -< _<_ -< -<7:-< if __.I -< -< -<" _I _ -< -< . Y5 O b O O onto 6 O O O 6 O inI; / ""1 7 ?P~d@¥"7 7 WY L7 77 | 7_ 771‘ ” \ TT0 \ ;F $77 W” Y 1 * T1" \/UnbIgpharLn'_godon micmlggaisw ‘Y 7 % L... x i \ 7L 7(L__C \ Ban'!iu§baken"* * fiY _jA fT LY ff 7 77 Y 1 I T it '—‘ f I Tfiariliuggiatensis K ¥Y \ 1* Barilius bendeiesis _ \Y _ I 77—s7 77 I1. 7_77 » \1—i 7__ 1 7!1 71F: 7 7 vy 7‘ 7 \77 tgariiius canamnsis ?_ _ %* 7 L’L W 4 _7 1‘w 7 7 ‘ ' , 77 7; I D‘aggginnatus 7 77 7 7 1 W?_ F Y . 7 177 1 77- L “D.*maIabap'cus_WY _ ‘ T7 I *1 \ J7 77 [ Rasbora daniconius 7 1 1% 77 7 7 77 7 ‘X7 4“ T7 TY* * { * ‘6 T ‘ 5# v ‘O 77, 7 Qatla_catIa H j +‘ly y j * | k " I . 771‘ ‘_-Puntms bqvangcds _ ‘Y \ J TY ‘*v( *Nmr*F% lPvn7fius?=hIva F17 7}’ 77 7Y i 7 ii7‘7IQ%%W77 4P6ntiu§7. 7 7 7dotsalié 7 7 7 WJYW .7. 77, ‘\ j ‘*77 7&7. V ;7_,__ 77_” _ _J 77 V_ 1 I \ '0i 77F if W 4fyntius fascigtusr _ % _ ‘Y _ > _ “L 777 I .7777 ‘7]7.7 7 Q7777A 77.{ .7L7. 7, \ 777 .417 * _7 ‘ “VP-fi!5fli6~lv8587"77%%* 77 ?7Y{ K T L i 77 I. .7 __ 7 7 .7 “P"""~#Pa"H" W 7 T ‘ \ 71 7J7 Lg 7 777 077 7 L 7T \Punubs sqranq subnasutus| 1 7 _H Puntms nqto _ * —'F_” I L1 7 - V .L 7 7 ll! ‘ l 7Tvr£ I \!G£yptéthQEaxg1admsp*atn_a}n j ” L ' 1\ “ Y NH ~ 7i C-ilossogobmls g:'un's7 W 7|j ' . 7 _ _ U * _ 7 [ 7‘7l——_77 ;7 -"_7%—- 7T— Y J HT _§ L>TC LGan~a?men%om'? W _ M 7 L77 77 J7 7. 7 . 7 W 71 7 7 7 7 [Ganaimulyaf7 77 ?_ TY _ ?_ iY _ 777 7 1. TH7 7 7 7 HGarra_hugi _ _ Y 7 7777 A7H7 I 7777 71777777 AHete;0pgeustesfossilis_ j , ** @ I . 'f-Ion5Iepterla?L'I!ai _ ‘Y 7 77(Y PHH “_7 J W 77777 _%TC 7 L memacheilus triangilla ‘s * 3‘ I 7_77, \777 7 __7[ 7 _. 7‘V 7 W }_7 ‘.7 Fgemameilusiguenthen * " \ *5 [ -w * flhjesonemacheilus hemadev: J i H Memirhqmphus Ifmbatus _ * _? _ . \ 7 Lgpidoqpphglué théfm1a!is_ f_ 74 T \ ‘ T 7 77 .17 77 77 7L 7 7\T ;_h¢1ystusannatus. _ ‘ W j T' j ?i' '1?LM "’*\ 1*’ '1’ 7 ——7 7 77 7*»“C <7 77 7 7 77 7717 7 7 717 7 QC 77 wxstusg_.M sw#1>'@¢7<@'*7 cgvasius 7 Z g_ 7 T 7 v7 WT.\7 I§j —\v ~ '7 _7‘c 7- 7_ LM@¢r9P¢d~s7¢~2@'?és77 { jig 7 ' \ 7 77 777 710 L 1 '7\ | 77 7*! Wastacembeles armatus n f L i777 7 .7 ” 4 7; *VIC ;N_QIOéf6@'US ?r1ot§pt%e?ru?s% j 1* Y _ J WVTC ‘ K 7 ‘Oiggk bim8CUl8ft]_8 " f _ jjr ; "T ‘ 1 j Y *“TcT ” ‘ ‘ TPn'sfoIe_QiS malgihata _ _ *[Y _ ‘T X I7 77_; fi‘'7 NO 7 ' 17‘ Tl7 ' ' Lsalmvstoma acfnaves * 7 7 7 H! Z 7 7 M W7 (Z . L 7TI‘ I —' \. if ‘ 1 ? “ii'1 Q 7 7* |[ Lsalinogrpgvapqgpis‘ 7 _ f Ty A‘7.777 77 \ ‘. 7 .\7r ' ——r7 __ j —%vl _H I7V» 7 Ietraodon travancbricus ij [Y f 7 _ ___7;} _ To l ‘n[' .T 77 ' 77 7 77? __ ' 7 7 — —, ;—_ V ,_ _ {v_7_ 7? [7 L 7L 77 H7 ( ( 1 _;WaIl§ggatty_ j % _ T j _ 7 717 7 7\ “'7.7 77_~— \*~~ 77 ~_7. 7| 77 7 7 fii @(en9n(6dgb cancffa“Y f= x w ‘ 7'T\ 1 C 7 7_7 77 7 _ 7 5T0 1'7/*"§b?$ f°$'¢!di'i°'4§‘ 77 MY 7 L77 7_77_ LY i7 *777 jy 7 _\l,7 __7 i L7?[ _771%: 1 ""w =;f\_ploc;heiIus_ Iinpatys JY i7 7! F777 7 71 L7 A77} M 7_ 7 _ 7_L k_Bhavania_;=‘ii:§t*rqlis_7 *7 j Ly7 J7% 7 7 7 7 7 7 L Table 3.15.Class?ificati6n or différerit speiies idenfifiéd from Kalladaflvierwunder10ihetfic§ 7_ 7 ; 7 7 7 _* _ uied for|Bl_s_coring_ __ i 7 j _ j BbakenS _ <={e8 _ _ _ NAL _ L0 _ _su{ Y ylN_TS * " MWS‘ * j1|? %*f7 Hefgm " "IN | 7" "Tc" j F"Bgatensw 1 7 ( *77E * * j HY * é 1 *1 3 |_* _ *7 J 747714? 72-. 7< -<-< -< -<-< -<-< 1?? -< -Z72T-<1 F-<6 i< I‘? % *** 7 ;| I 7|—747 '1—*—r—‘4'77 7H—‘7 7414 *1“? 4?. 71* 71+ \ E7 % =7‘ 7 I —77F_L'4 of 6P1; 67 O O 6 O 7L ‘J17-7, F7-—— 5-an 1“ 77 1-—‘—7-17):-7 77$ \ \ 77‘: 7Jr 71 71-‘ i" / RdaniconiusD.malaban'cusfi__”_ -, _._ 7_ H 17777Y1 _ . 1 1 1 5 7‘1 1110 71 1 Qmwmws Q "f _;111 11Y 1 sq‘ W sf1w1 fi1TC im 6.giw!'sGimullza 77 1"_ 7_1 FY _11,77 1777 1 1 _11H % f H.curmuca V_1 H._ 1 Y “FY 11*! _ ., J - Y_i 1I1 i L071__ _H 7'77 QalusY1 1 thennalis .;~I Y 11'77YI _1*: 1’1 77 1 1 i7 H 7 1 1 1 11 _ 1 1 . _~__. V |'__ . V '_ N.t|1?a@uIan's7~.a¢ma_ 1 __ 7 77]Y7. __. 771Y , F 1_1 7 E.amp!y'!;iusO.b§ken', _, __._ 1\ _. 1.7 _'j7 17 --1 -» T77 - -7-_ PfasciitusP. arulius 7 7 7 7 77 7 77 T1 7 1 71 1”P.fiIsmontosus1 1 17;7[”7f A M _7% 11__? ,. Y71;i j._ 1 V ,1, ,7 _ _ P.‘7T.khudme1:hcto W 1 11_ ,777 H}111 1M 717 1“ YW_ 11 ,_1 1 l xthorirassi77 "77 ' 7 ‘ H1 7_.77. ___1 . _ 1 .__7 _ 1 '_. ., 77 I_ .1'__1' 7 71____ 7. .71YTC 1_ Hfrc ._.__ H%austmI:'smossambicus j 731 W :5 1 7{ 1 { 1 Y ~ W H so 1 ~ I Tabla 3.16.ClssslfIc57tion bf differentused species fgrlBI Identified fromscoring Pamba river _under j 10j metricsW A 1 B.baken' N j 1_%NAT7TLo'%W_1fsuM7|NTs7Mw$(TPQHE_ _. V.7 _.. 7 . ,OM 7]. 77§77|~1__ I1 C 1 a. 710115137777Y _7 1jy_ KY 7. 7, .|. 77v _17 .(_ . 177 717 .. ___ 1 I 11|. _ D.maIaban'cusD.aeq_1_:3pin7:7istqs? M .1_ jQY77 __ .111 17 V17 Y 17. 1--- Y71v |--1.. ,1 1 7 -,1 Tl1111 W L 17§818$i0%RYd@niOvnivs f!‘8v8"<>0fl'<'§777 .1 __1 77L . __ Al ,____1 77 WTY . __ 1 77771 ,1 _ = 11 7701 _is 1» _C .__, _ _ ___ 1.. ~ [ _ ,, ~ .__ ._ _ Jljystus7anna!us7_M1H-brwhysoma _, .. W __.__ _1 . __. ___1 __1 WT 71 g 1.'_ 1 % 1i17|r___ _ I1 1._1» 1c1 . C. Ch7anna_n17£|n:_!ius 777_ _,1 11 1 A 1, 1 1 is =7Che!afas7a7‘ata,_ _, 1-_ _ , 7 Y 7"___\. .._77 7771177771]. 1‘ I ,_ _ . Y-i ._. _$almost0ma acinaces\ 1 1 W .2 1 1 1 __ 1 _ 771.. 7_ L 7__ __To 1, _.. _. [gmaéqlateslmullya6' 1 L "17 ‘Y71 711 77 1177\ 1+1 * 7 7717 1 1 lG.surendranathanii1 1 1 H __ 1 1_7_ 7 71 1 YIYYA 11“7777Y 7‘ I7 7 A H 1 1 1 Hcurmuca 1 1 \Y 3 1 O ,1 j 1 1 LfiamghibidsP.choIa 7 7 7 1 7 7 q ?_ i711 Y 1 _1 1 10101 1" Li I J --1 1 _ r.N: . . 11 1j _M ;__ so r__ 1 . PP.fi!amen*tos:71s7PR fasciatus 77 _ j 1_7 I 77,1 7 _”__ 1 A *0? % J1 1,1 ‘7' ' '7 —1 '—- 1 1% V --11.1 _ , .._ 1 18-ticroBsarana Hsubnasutus 11 71‘ 777 1 777 11 17 Y 17 1‘ 0710 1“7 Ikhudme YY N 7777 7' 77 70 1! I T I-*7\ -1; ~_Mastacembelesan7natqs7Mmm Y717Y"”"f7w 7i1Y77 7 777 77 17 F \? 1 ’ 11 3 ’N77uen7t7hen'777 . 1,_ _ 7 1_ 77_ +____ \Y 71v 77_ 1 _1 __ A W0"Tc 77 1 111 _ 1, (as , A 1 V 1 TTCY Lmvandussjvjrianggfarfs N 7Y__ 1 JY 1_ 7 11'7_l 1 7 j771 _H 71“ 7 1 T ‘viQ 7 LP.ma;Q'nata _ j 7 1 7 1Y7 7711 J6_ Ai ._£()9(;fl;'31 Y 5p_ 1 j M1 .. 7_L7 _ 71. 77 ,,777 7_ 777 _ _ 7 _ 17 ‘77 _70 _ 1 I . *1 fihomassr1wa11qqoa~u1 n ‘Y_ , -1Y_11 11 ‘ 17 1 1*1 TY __H 7 1117 5}? ;!Tc TC 77 Table 3.177.Classificatid7n of diffeient species identifiedfrom Chalakddy river unde|710 nietriss _1 1 % W used for IBI scoring _ 1 77 77 77 % NAT 1.70 7s%u7 gms Mws TP HE_7 0M7 IN Tc 7 A._!ineatusB.ba{ __1 4 -<77?.¥7< -<-<<7-< -<-( -<1 7?? -< - -< -ii -< H O O O 0 6 O 6 5 06 _,._¢ 4 4 Y‘ ——1— 711 W m@%hEfT7f§fTCf17”*7“f“77T717777771 '7 777 7 7 77 7 7 77 77. 4 4 7 777X 44 4 .44*7 4 4777 1 T‘ 44 - 4-44 <4 t@e¥@w$444444444 \Y ‘ \ 44 4 “.79-@@q2'Pi~~§f~§ 4 4 4 4 "I 74 77 44444 ‘ 4 4 777 4 M4 71 4 . #\ “!75$5n1vs47dan?1ri5y$744474 7 47 447JTY7 4 4 _4_ 4_ _(_4_4_\ 4 » ;"\\ ,'7°@'4"'°"*8'aba'i¢"847~ 47 74 7 7 I 4[ 44 4 MR.*daniqon;'us______j7Y_wv _ 7 7W 4(_ 4\ 4_ 4__4_4*4@7*.*44 _4_4 MB7§réyénI04n‘a7 74 74 74 74 LY 7 \ 4! ‘ 1 ‘>0 ! *_TC.7du§stImi§ri 7 7 7 7 77 7‘Y 7 777 4 4 44 44 177 “Y 77 7 V 4 YTQ4 4 4 4 4 w 47 447477 47' 74 T4 74 474 474 74‘ 744 4 74 71} % nlaculatusé _ _ _%,Y__ _ _ N »A 7 77J7 77474 b4N4 . x 4 4 4 4 {J 744 Q1 +4 7744 44 74-K4 4 4 744 T47 44_ 1 “E-surare9si§ 4 4 4 4 4 4 4 4444’ 7 7 77 ‘ 7 4_4Y4 4 I444 J. # \‘7e.7an7:aHda7ef 7 7 7 7 7 [Y7 TY77 7 77M7 1 4 L4 \ 44 VH 4 747417 747 4 7 7 j nsf4 muliya- 7 :7 I 4 >74 4 477 4 47 _7+ =4 Y 444 44,44 4 4H 4 .444 4 44l_4 4 44 4444 *1 IQ-§2?P:*?!r@?'2'52~7i4 74 7447 44. 47 7 4 44 11 L4G'9$£°99b'7‘!$49'1L”7$4 4 I 4 4 4 4 4 Hsiqgpierys gn'§¢u§ 4 4 4 JY4 44 ,4 J44 44444 44444 41454 '_4 44‘.747.474447447 1+7-QQMYHQ8 4 47 47 4 7 4 7 47 4187 4 4__ 4__ _ 4______\ . M01054 4 44 I 4 44 7 47‘ f 74 ‘ 47 74 " 7‘ 4 W if .4 V 7744T7\ 4' ‘.4‘l47'47_4 ‘Y L77 J4 »4 4 44.I 4 44 4 _ 44 4 4 4 4 4-441 "6 44 JY44 4444 44 7? ‘I \' 7‘\ P -'<>@9"(='4@"$ 4 4 IY 44.44 4P-48mph1bIy$ 4 4 4 ¢ ‘7 \ \ l L 7 { 7 7771' T’-67101577 47 7 7 74747 7L4Y7 7 71‘ 7 4 7 474 744474 1744770 7L4 4 i \ H_P.qen§sogii_7 7 7 7 7 V7 W W73 4 _?317 m AY 7 _?7‘ _ 77 77 7 77 "7 777 47 47 _.4_TT7 7 7 4 '777 .4 '777[ 4. “O7 A44 777 4477V 444 7 774 w7P.?a§_§:ia_?us;_7 j 4414 T [ 4L 4 L04 4 4 747444 44 44 4 44 4 44 W4’-4"{@4"17"£§@@ 47 47747 447 47 [Y 4.7* L4 7 44 ‘ 444_7 \7 4 T 7 7N7 7‘77 7JO7 77 4 4 4i 4 44 4_ 4.. 4. ‘i 4 \4 4 4 gem: 4 4 4 4 4 74Y "4 4 7T4 44 4 7 v"7i@;o7iI4 *7 4.14 '7"7 44 " KT-Elvfiraé 4 474 44 44L 4_ W J4 .74 4 4 4_.\.4.4 4474 4:‘04 4 4 4h 4 4 4 4444 A7H7 0 7 ‘"7A 7444 77 77 774 74 HY 4 14 4 4 4 44 4,4 weL4 44 4 4 4 _44 4-10$-ws444é_44}‘447 4744744414 WYJY 4144 4144'4 44 .4 44 WC 44 44 44 4 4 ¢'°"’1b@Q'"$ "'Y9"'94°”§"'€44 44¢*Y4 4 47 4_ 4&4 4_ 4_ 4_4 Ffloabqqws b4r==1eby§<>@a44 4 4»4Y 4 4 4 4 4 4 ; 4 X44“ 4L4 474% 4 4 4 T 44 4 44 44 T L7then_na!jS __7_7_7_7_7_7_(Y Q 7j'Y7 " L 4 4 4A_44_44_4 4‘4 \ if _.f 4_fLQ_ V V,V__ 4_H4 4* 4L_ 4_ 4 4_ 4 44 Ab 77M-arm-‘aw; 747747 4 7474 774"/7 74 74 414 4_“4__44 44_4_4LY4._4” 4_4_\ 4477 47_\ w7.cavasi:Js777777W 7] 7 44%‘ Q: 47 4 444 47 4 4 4 4 4 7 4474 *4 4 74414774 4474 T 1 ¢FN._triagnggIa(1's* 4 _ _ _ ;>Y7 Y7 7 4 w-— *1 i-— 7% 44 44_ } p@m@w@"44¢4g7 414! 747 4 4 A ,_P.ma§gin§tam _ 4 _fi _ _ WY_4_ _ \ LP-fhOma7$si44747477 74 74 77;Y74 444 7 71 47T 4444 4 4 4 ? 7 7 747 57095954 74 74 TY 44 4+7 74 47 L 44*4*l_,_44_4.\L_4;4_4.._4_4.J 4? ‘iXeHen7todon7ca5ciia 7 7‘ 7‘ 7W7 ‘ ‘.7 7 7K 17717 4 L 4 4 4 4444444‘. 4447747 QLIC44447 47 Table 3.18.ClassIfication of different species identified from Periyar river under 10 metrics used for IBI scorin % f —7—1 77 7 '7 LF47 ii-I7-4 7744 iv%797Ty477 4 7 4 ,7~744 7 \ \ \4$_|_>9¢i4¢§_4 44 4 4 4 4 ,~gT4 L!-Q4 [444;§v4 ,I~Is4Mws4 4[ JIP 4 4I77wf7w|*FIE7 17079747 JN47 77 4 {T54 44 4 4 4. A5'9¢#1'? 4 7 4 474474474 4 4#~4 #44. 4‘,\._4_4_*4§_44_44 4 44. 4 4 :4 4 44 .4 4 ,4 ¢A '44 lineatus \A \ ‘ L .4’-4‘TL4 4" "47 *4 .4 ‘4 474 j.n;eii{ti?;us_1 74 _774 _74 _ 74 74 74 77_ 7‘ 7.4 74‘ 4 i I7 7 ’ -‘:4 4 .‘4 L 4 W \ W '1 4B7-@bs17m£7s4474I7 4747474‘ if4 4 44w 4_4\4 7 \ 44 4 .,, L tHefmahs7 7 7 7 7 ¢4 *-4 H7 44 447" 74 4_ 4 44 4_440 44 9| 447 447 4 7 77 ‘77 7 Y7 77 7771' 77 77 77 7! 7 7* \ x 4 4 44 4 4 4 44 44 WY44 44‘ 4 4 4 4 44 7'4 74 74 744 74 ‘ [Vden:§oQn_ _ _ _7 _7 4 44 W 44 7 7 NY77 » 77 777 77 ‘ \ J I 4 4.\ _ 44 44 44 4 4 4 WY 4 4 4_ 4_ T 4 _4. 474 '"_47[74 ’ 4 ’]':4 :44 74 4‘ Alguemhpn 4 4 4 4 4 JY4 74 4 4 74 74 -4 7}i4 _ <14 744 1744 "4.|7‘4 74 7.4 7; 7;4\[ 7.4 7., 74 74 74 ‘J NlsIw5Iqns1§ 747 7 7 4 N 7\Y£4 77 44.44 \Y4 4 4 T ‘ I * J 1 T~I:@?»g~:ans 4 1 4 "1? 4 4 7 7 7' '7 "71} '7 "7 -» V T \ .4 74 _7.;"4.74 7 ' \ 7' I 44 47 4 447 47 47 F4747 7797377 .77?\77}777777L4 74 L74 74 774? 74747 \ 4 4?‘ If vflgatensiq 4 4 4 4 4 4 _ X4Y4_ 44 4444 44 44444 x4 4 _ 1 [B?€"@$?495§¢?'4774 74 74! 4 J4 4.4 44 J4 44 ‘J4 4444' I 4 44444 44 1 \ 1 Qanio mafabgflsvs 4 4 4 47 JY4 >44 4 47'Y744 44_ 4; J 4_ J4 4 74 74 74 _ 4 4R-d§"£4¢°45i*{§4 47 4 7 7 JY 74 4 4 W 4 L 4 Y 4 4 44 4‘.7Q7 4 J7 4 HY ~\.4 4 44 4 ,4 47 7 7 7 7 7‘ 7 1 4 4 4 4L 4. 44 M4 4 .dussumien' »Y *7 ‘L M ‘I A Q 7 77H 7 7Q’°§SQ9'?§"4‘!$ 7 7 77 7 P92 7}/a@4~$!§ ",yY 74 4 44C; v44 4 44‘.7 .4 444'w"7;r 4 4,|44 F ‘ 4 J9 4 4 7; J 1;!-mi¢50Q9_94vnw4p§fiyaren§is4 TY 4 \4 4 4 .\Y4 4 . 4 4 4 44 Q9744 7777 F!-4¢2"7"4" 4 44 44 44 441 44 4» 4447ji4iJ6?77 44 44 4 4 ;v4_4*4 l 4L... Q-< -<7-<7 < -7<7T-<7 _4 4._L_-2_T '<-< -< 4 4 4 4\4 41» 4‘ 71 $4 44: 4 1'74I 44 Y-<7’ 217 444 44 J54 77 444 44414 T 4* —4-4 *7?‘-?T"T 4444 4 4 1L-4 L444w .4 4 _‘4 7% -<7F717 7'77 7357-3 -< -37 44. 44 —\~ 444* .44? 417 47:; 4 71 ‘+ 7--J-5 -4+-T -4~‘—4i—; T 7777 } \ 7 4 4.4 < J4 44444 :44» 4. 704 7->--PL‘ F T 1 ;'<‘ J \ 4 4 47:“447u¢74 =#k4-~ 4 4? 7 44 w‘ 7 4. 144 T I I .2: 4 4,4 \ at ‘V 7 7 TO7 “T670 065767 i *1-” 700 OT 70, . \ 4Pl744‘-P4 1+7 ‘ f——4 f—-4 <477-1 W 4 _,4_T,_44 44747 4__;-4 A Li \ #4 4 4; 44 5 4 T4j.4 -P 444 6 O & 4 \-L it 4-\_ 4 A 4 __i4 4+ Jli 4J7 447IL ii 44 44; 47L’ 4.4 L _‘l47 4444 i'| IQ-lzpvs QQQ QQQ)YQ —~QQQ Qj—_Q—QQ YQ Q*Q 1Q 7QQ 7Q7Q—QQ *_Q*QQ 7‘. 4 7 Q 7Q 7 I W. QQQ Q Q -QQQ <@Q-Q QQQQQ —QQ»Q JI i i0 i iiY E-QQsu?§f€n8i$ QQ QQ QQ 1IY IQ Q Q Q Q Q QQ Q Q J0 Q i‘Q Q } Q Q Q Q 0Im§ss§ni5icQ5sQQQQQQQQQQQJQYQ QQ Q QQ QQ Q Q L GQ sU;eQndfanéth5niiQ Q Q ‘ Q Q ii i QiQ="99"Q QQ QQ QQQQYQ * -~' * A-Y4 Q — — * 4Q ' 7*-Q * ~5T * 43 -1 4-Q *— * Q *‘~ " ;§J22"z@@Q~$i=QpiQ+G'[email protected]~ ; 1 —Q —;QQ —QQ —Q QQY Q QQiQQ"’TiQQ QQ Q Q Qit Q ‘QQQ Q QQ QQ J Q Q Q Q QisiQQ Q 1" Q jQQ W Q1 QYQ Q Q i QQQQ Q QQ QQ Q .i Q Q Q QQQ H M-qzmatqs QQ QQQQ QQ QQ 7Q Q*;Q*.Q QQQ .7 Q’TY Q ‘V QTIQ .Q QQ QQ‘ Q Q *0 QM-cvp&rwsQ Q Q Q Q QQ Q Q i L Q Q. Q Q Q Q Q Q Q i QQ Q7' I i @@>ékQm8£Qébéfl3Q>v$QQQQQQ Q QQ ‘QQQ! Q Q iTC i iW i QaI_!eg5gQtiuQ_QQQ_ Q_Q Q__Q;_Q_ Q Q QQ Q. "Q1QQ QQQ ‘ WY Q Q i Qewe Q Q i Q ‘ Q "'“+ Q-*QQ~Q ”QQ* !9L""?laQQQQ * * * QQ* "Q"QrQ‘*Q*“i‘*Q”Qi'* QQ QQQQQ QQQ QQQ Q.i Q QQQQ Q Q Q.Q Q QQ QQ Q »Q QQ, Q O ”Q”Q'Q*Q‘* i Q‘.Q _Q Q Q QQ M " "F ~ ‘i 1,iPoe Q_Q~ QPQ _— QQQQ!iéQ§ Q QQQ __JY QQ_QQ[QQ QQQ Q i QQQ Q QQ. We Q Q Q QQ Qi Q, QQ Q IF 5§‘°~@~1<>~<-a~<=i'~=NAT-Native sBeE:|e§ Q Q INTS-|5to|erantspecQ:ies Q LQYQ HE-Herbivores i;Q i ii TC-Totali i Q we carnivores ‘LO-Loaches ‘\MWS-Midwater species OM-Omnivores C - Carnivores SU-Suckers yTP—To|erant individuals IN-Insectivores T6 1*? -Y TT..< Q_ Q QQ 4 J »-+ QQQQi.Q_._QQQQ i < -<] @ -—\ -Qj -z-¥—_Q< we-e*~+—~iQT -Z1‘ Q Qi Lgifi T Q Q QQQJQ QQQQQQQQQQQQ ‘T fi Q i QQQ. Q Q QI QQRQQ Q Qi I ‘|—‘Q JL —~*i QQQQQQQQQ QQQ Q QQ QQ QIQI I Iv i L Q Q ‘Q QIQ i ai 0* * Q Q0 6 OO OQ O OQ ~iQ Q J; Q Q Q Q Q QQ-Q.QQ.L-Qi.— QQQ Q_40 QQQQ Q Q Q<.QQ-.- QQQ QQL Q.Q Q4‘_||@ Qi._.i.QQ ,- Q‘Q Table 3.19.Percentage contribution of different metric groups,lBI scores obtained by different metrics and overall IBI at selected Ioca_tions of Kabbini river _ i'[nein¢;pp 3 j 3 3i1su3i_f1Biscon=iBE'iiisiscorq3Ku "1IBl$¢qre_KURJBl$<§9r¢i‘ "Total3 numberpcf ‘ " native 10i pecies; W 10‘ Q‘; 15 5 29i 10i 0 iNumber ofloach species ip pi p 10j Oi p To I . Q i 4" 10 1Oi p 1 _i_Nurnber of suckernspecies p M p V Si‘ 3 l 5if 3. 1o ,iNurnber of intolerant §ecies ii Si 4‘ 10 4 inf 1' it iop T 2 3_ |~_ . “Number of midwatecspecies A Zip 3.5 i si 2r st 10 1.3 iNurnberoft_olerant§pecies Tiff? 1Oi 7.8i V 3 _10A _ 3.8] 10ii ._‘l'rophic W -3 metrics 3 3_ p _pas if” 3% j i T ,Peroentl1ervivores p __i 20i _0|_ 20i in 1o 3 12'1i. 33 fi P9rcentomnivores _ 3 -3 3 i‘“80i 33 0i*267 33 i T40? 453-5 3 oi -20 ji§eroentjnsectivores' at 0% _p 0, 33.3 i i i12.1j 0 peroenttopcamivcres W T , _ Oi p 0i_p13.3 T TO 17.2i if 1o1L Fish abundance and condition correlation fctors i jlumbef ofindipviduals per 300 §9'- T 129' 379 29’3i3 " 1 ;pPeroeént fishes withqanomalies 0 ; i O 0 01" 3 Overall IBI score T ' 7* ' 30 ' i 65 37_‘ i3 65;l SU-SugandagiriBE-Begur KUR-Kuruvadeep KU-Kunnambatta Table 3.19.(continued)Percentage contribution of different metric groups,IBl scores obtained _ by different metrics and overall IBI at selected locations of K_abbini river p _p H “"'i ilifletrics 3 PAL‘ lBlscoreiiAC ilB*l scoreiBEl_ ‘_lBliscore|BEll ‘IBI score._3__| ii i_Total numberof native peciesj W f T _ '[33i 3 oi i Si 21‘33 193 i_Num_ber of_loach species p 2i 10i 35 0 i€>i33 Qi illumber of sucker species p § _33 "103| Q 10] p iii p_ 10} Number of intolerant species L p 2; p 5” i 10 i1o'iW1oL 7 "10 iNumber of rnidwater species pp p 5 Oi 75 "a 34i33 10it_. 3 Number oftolerants cies "Ei T U if 10 33 3 3 re- °3i 3 33 1o,. _333.8? “ . ..__ ___,|10 ‘Trophic metrics A lg? p p pi i ‘I Percent hervivores T 303 I “'1 3 30 3 0; 1a.2i T iPercent omnivores W k”30i if e333 soi on I345-Bi; iPeroentin_sectivores T 10 Oi 16.7' Q *0‘ 227 iperoenpttopcarnivores H H 3O 10! Oi 1Oi 53_ _ f fish abundance and condition correlationI -3 fctorsé its 7 i ;_ H3 N333 3 _lNurnberofindividualsper300 33? -1Oi 32¢ 7 -1o’ 128? J, 10533“ ' iiPercentfishes with anomalies Oi T Oi? pi i Oi iOvperailllBl score. _ _' '45i T? _ A Soi3A if0" . 55}. A i AC-AchoorPAL-Palvelicham BE BE-Begurll-Begur lll Table 3.19.(continued)Percentage contribution of different metric groups,lBl scores obtained b different metrics and overall IBI at selected_locations of Kabbi ° river _ Metrics TA -lBlscoreiARl llBlscoreiARll ilBI ill’score 3 iAR iisiscorifii Total number of native pecies p_L_ p __i _ _ W T o 3 of i o 50 iNumbero_f loach species i 03 3|-— _ __ I iNumber of sucker species N H T? _ Qi 0 ‘ I 10i plumber of intolerant species” it p p 2 i 5 i I 3“ 3 1Q i ii; 3 5. kgiumberiNumber of oftolerant midwater species speciesi in |___6 p_i_ p 3' 5‘ 'if 1Oi i' 10i iTrophic metrics? pp |i p @ ii i i 3°, 6 50i T Percentpheniiivoresi * p i';'_10073 10% O i Peroentomnivores N Oi T 0 6336.63“ 100 i 6 i1e.7i1 iPercentinsecti\i/ores‘ if Oi WOT 1334i if T W 0.3 Oi 1p6.7i p iperoenttopcarnivores L _ ‘Oil Oi 30;‘ oi or 1431 r i Fish abundance and condition correlation fctors T T . J i li Numberofindividuals per300| 2ii -10 19,' -1Oi 32 -10i 34; H-1o i ;Percent fishes with anomalies Oi - T if Oi 0; i 0‘- i Overall lfilscore T pi _ W 15} p T 15! l si 477 ARTA-Tarivod I-Aranagiri ‘AR I AR-Aranagiri ll-Aranagiri ll -nl -L C) _\ o -5 03$ -\ d~|\J U1 i _L 5‘ Q (D U1 Q 01¢ Q 9° O —b O7 w_o 2 -<.o _\ U1 Q3 (D O1 C) Q CDC \| P‘ U1CD NJ _\ -A '_; —\ (.0 O 000-7 LO (D Q ac OLQ U1 U1 3°‘ O. O j__ O O f\J pod 9°. C) _.s 01 co O N m_ 5.5 O -|J__O _QJ_ .20 Q9 Tabla 3.19.(c0ntinued)Percentage contribution of different metric groups,lB| scores obtained Q! dllferent metrics and overall IBI at selected locations of_1Kabbi_ni river mime; 14 1' 1 P0 _1lB1liscore§11\i0 1l_Bfil scorei:MU IBI scorei ilfotalnumberofnativepecies1Nurriber ofloach species 1 2 291 _fl 10*1 101! A1 13_ 5? _51 W O1 01 1NumbW_eFofsucl§er§pecies 101 _ 1L 5; 1 151 Plumber ofeintolerant species 11 141 1011 101 11 §‘ HNuml_:er1NumberTrophic ' 1of of 161tolerant midwater metrics s species1° sggjcies51 1 10 Y 1 22.6141 10 1 105 01I ._fercenthe1vivores_ ‘ " ' "" 11 _ 123.1 1_ K 7.7 0111 20 1F_'erce_n_tomnivores7 K T36. _ss,51 1 H A W 11_percenttopga1mivores_Percent insectivores 131.4% 20 1 011 23.1111,7 L11 40; 1' I 01 H F_|sh-r abundance1 i . and . condition’V— correl a tipn sy fctors 1 1Number of individuals per 300 17 - 1351 - = 621 - 1 |1Percentfishe_s111i1/ith1Overall IBI2 score anomalies 12.31111-1*1 ”601 1 _ if4s _| 1_ 221 0E_ 1 PO-Ponkuzhy MU-Muthanga '1 1 1 NO-Noolpuzha Table 3.20.Percentage contribution of different metric groups,lB| scores obtained §_y_different metrics and overall l§I at selected locations of Bharathapuzha river 1_ H Qjetrics __ 1 1CH l_Bl score'lj(A §|B| 1score1TH__1 1|B| score 1 CE 1lB_l score 1TotaI number ofinative geciesw 13 1 5! 1115 1116 es _ 0 131 1115 _Nu_mberof*Ioachspecies11 1 1 1_ 1_| Q‘ 0 O1 _1U1 1 101 1011 1 ;1Numberof'§uckers eciesO 11 11“ 511 1 it 1 ‘$11 Pi,1Nurnberof__intolerant 1 ,1 d_1 species 1 as11 __ 51W0. A21 101 0. 01 01IL 01 11 1Num;berofmidyiiaterspecies 0‘__ _ 0 211 5”’ O1 11 O 1 11 1Number of tolerant species 122.21 W51 8 101 0' 111101 7 61-'11 1 PercentTro_p_l_1ic hervivores‘_ q7 _1metrics 10_1_f _--s _14.31 , 1___~ 1 1 1 16.7 1 AL_ A M 0 1 . 1 1Percent0rnnivoresI; 1 ,_. ‘ _, 1 381_...,_ 1 57.1‘ ._, 1* 66.71 A W I 58.31 feroentinsectivores 15.4 _1 0 _f A 1 A 1_ 1 16.791 fpercenttopcamivoresifjsh abundance and condition 12131 101 correlation 28.61 116.7 fctors 1 25111111 1 1* W 1 1Numberofindividualsper300 121- 331 -10 _ 251 ~10 79 1PercenYfishes with anomalies Q1 - 1 _' 01_-_ TM 0 1 W 1 1 - _1 10vera_llCH-Cheruthuruthy IBI score 1 1 TH-Thonikedavu 30 1 1171 40111 * 101 1 1 11 1 30 KA-Kanakkanoor CE-Cheerakuzhi Table 3.20.(continued)Percentage contribution of different metric groups,IBI scores obtained By different metrics and overall IQ! atselected locations of Bharathapuzha river? _ _ 1 _ 1Metrics A _ 1ME I AIBI sc0re_1CE 1lBl score LPA 1lB_l score 'lVl_A IBI score _1TotalNumber number of Ioachof native s pecies eciesw 1 61* O A 1 _rij _01 I15 O in 1 1-1 , 5 .5‘191'” _ 0. 101017, Numberofsuckerspecies M 1 >5 1 51 111 51 21 10' 1_Number of intoierantspecies pi _‘11 51 A 15; 01 0 5 10 1v_Number1ofmidwa_ter species 1% O1 1 A 14 1 1 57 7 2' 51 _’Numberoftolerantspeciesophic metrics[ _. _ 7* H M _ _1 __ 7 101'”1_ _1 _ 1107 _.: 12 ,,~ 101 ‘ 4.31_~ 10' ‘PercenthenrivoresTY is11 11116.61 f. 11 20111 10] 011 10.51111 1 ' TPeroentPercentomnivores insectivoresi 133.3 1331.131601191 1 4o_ 01 1311 01 42.1,_ 1115.8 1Qerce1n119p¢a1miyores 1_ 11__of 11 0_ 01 1 501 191 211 Fish abundanoeand condition correlation fctorsv 11 1_” 1 1 11 1 _1 1 Numberofindividuals per300 25 -10 191 -10 25 W -101 69 - 1 QerceritfishesvwithOverall IBI score anomaliesi 1 1 1 W0; 11 10 111_10 _' 1 -1101 1 O11_ H 3211 01 1011- 551 1 MEI-Meenirallam I 1 PA-Pambadi east CE II-Cheerakuzhi I MA-Manarkkad Table 3.20.(continued)Percentage contribution of different metric groups,|Bl scores obtained J:-‘ow-A 0100 Q 29 mo oooi~*i——" ro oo-~_¢~o<.n o oooo oooo—§ ooug A ->CJO7 Q Q QQQ0_L Oowmo oqoo-L oqoo18 oowooo.—L b different rnetrics and overa_Il% lB[_at§e_Iected [ocetionc of _Bbarathgpuz_ha_ riyer _i e _ _‘ Nletrics'4 r _' V if 7 0 __ fJlU‘j|BIscore1'YA _ _ I V _, _, _|__ AIBI _ scoml_§IH ___ ‘10 _ ,lBI_scone M78 .. W7 >|é?ogntne~‘6res_T:6pm‘¢me¢ri§sii_‘V ,‘_ ,_ <,_ i_ ._¢_ 2s iA_e.2sf _e if H 0‘ _ _v0 T0 ‘_ 0Q4] 14.3“;,,,_; 0 ,,_ _ 0“_ _Percent _ 0 _ _. 1.ornnivoresf __~ f 0 We _f 25 1_ f _ 62.5 \.\___f_ 71.4 __ 0H 0 W5"/.1Kibe A,__ ,0 _ 0‘ _0 f, ‘feroentinsectiyores f ;L 25% to of ?e.25f 7 W _ oi? _ M Q _14.3_L _t 3% LF|$htTgercenttofcamivores , '- abundance ' * e W and *. _condition -0A _" 10% ‘Pr correlatuon 25‘ r 0_ _' 125$"0 fctors ’ _ "' 28.6\_ fW _ \ 0’_ f10 if lN"@P@i<>fivd1v@"?!$P@'3°° 55; _ J 1151- J9? -12% _ 56N~ K _». fbveralloielscoretWeroerltifisbesvyithanomalies 0 _ 101- _ ?_(J‘[-_zsft 05060 __\_ Off : _ L if *O1Si L, -__ 025* _?_ MU-Mudappallur CU Churiode YA-Yakkara KA-Kalpathi Table 3.20.(continued)Percentage_contribution of different metric groups,lBI scores obtained b different metrics and overall IBI at selected locations of Bharathapugha river f _? fftygtriw i 0 Z V [PE iIBl3<= \Total§un1berofnetigei>3cie§ ii __ _0_, ._ .. Qy , _ ill__, j 8 _[ %_ \ ._ j Ow_ Jflumberofloachsbecies‘ Number of sycker _;_ _ _ 0A 7sgecies___ .__* 7 OL ___ __ A?_ if_ 0_T __rV (ilk __5 f _ e0_ _ __, 0‘L00_? 0' V_ _OL 7i H_ _5# 5‘A LNumberif ofWinto*ler§%nt§pecies_[ if f "ff j _? _ Q;11% W _0* __ *Q_ W _ H ofqr ?_ _ 1 Nu_mber of midwatepspeciesi L ?_ (1 j; 0% 0* f 0‘ blumberofioleranlspeciesJ'9e'!i="\°"i°$ Q01‘ Tf f ,7*10 _ 671, 0.7 - if 0 7 o_ i f 0* if 1* LPercenfhervivore§ _ : 414.1% 70+" _ _A 25, %P@r@e"f<>mniv<>fé§ f V 5°-T it c4%9‘*_ _L<>J 62% °iP»Y§ I 7 *Percentinse_ctivores§0 _o_ o_ no _ ‘>_f_o_ 1611 o_t _ _ 23.6;0 We of _ Q;to _ 0-_ 0j_ 00, 315; 0 _t 0 _ 9 Lrpi eroent_toQcarnivo_res_ é ”_ j __ j j __ in of j *1U__ $166, i. 43% j_ _ _ i _M 7 25 _ 10 U 70; _n ?__ ,Fi_sh abundance and condition correjatio_n fctors _ “_ _A \ i A I 1 \ \ 0 i" " 0 " "0 ' 0 ii" '0" 0 ‘ 0 *‘ * r F Wnmberofindividualgper300 17 _* -jolt 41e_ -19\_N _ 30“ 110; rm; _ _ H [Percentfisi1esfwith*anomzflies_ Oi? f in _ QL f foo” _i OK? 0* §;A"_T* QXQJ j K03/eraJIIBI$60réQPE-fieihunikare i it" f_i *0!-Chfittur Q _ Qt JOY if ‘ §0 f _”Qf no " _f“10lj 0 " 0 "7Q i 0 §5j 0 CO-Choorapara KV-Kavarakundu Table 3.20.(continued)Percentage contribution of different metric groups,lBl scores obtained _’_l_J1di_ff8f8fl1!flQl!’i§$ and overalI_l§1a;t §elec_ted_locations?of Bll3Wf‘QI|l3J)UZhf3*|'iV8I' *_ __ __ n|\'|i9t"i<§8_t_ o_ 0 __ 0 V it \!§l8qO_r¢fKN_ €71BIsc0reTKR J_lBl_sc0re1TH_ ;FlBl§cor_eH ,I<>t§Inqmberqfinafivepgciqs t_1H _ _9c PerQer1tin§ectiv9res ___t 0f__’ _A>_0 25: __ 0 _t_ _ 0]0 _ f‘I _ _ of ¢rQen3}Qpcar9iv9@s _7 _ L’ QT ' 0:* ‘OJ i, 00?M if i if 0’ 0 “oi Fisriabjundanoe and condjtio_n correlation fctors*_7 __ -—— [_ _ _ _ — 1‘ > __ f; — 1 — T — T I if Numbero_fir1dividugIsper300 24f 110* '2sf 116' 12" 10‘ 23 0 Percentfieheeyvithjénornalies _ %A6'LJ_ '| 1* of0," iii-A ife;0' f 7;! i * f Qv¢re'IIB'§¢orec_ Table 3.20.(continued)Percentage contribution of different metric groups,lBI scores obtained -A f -L--H 00O 00 I o¢‘Z*“* Z9 £ *4; W-f 9 TCEOOE’ -1‘ ' { 00‘L§>A ocllqpw 000 0000 lb -l ir%‘j=_F 1— "r vi <2 JTOMO,‘-?Li":9_.°l \f ‘.-.5‘N i we ' i Q. 0-il_J _ :._+Jk)vC‘E;—-‘ONT or l:'i°jJ° * <19 -5 -L _Li 00_0p 01 ,@p=,<> <22 <22 -§§ ‘ 00_?< A00|\.>4--00AT 0; 114*, QB) 0010.0 0101 Q C3fU'l—l C: Q _ ire 019 Q- fT__.t, - f9_°‘2»-f° CH9 °l."“" A—§ -—\ 51¢; 53L CD m00 A P1il‘9;¢L ,0 b different metrics and overall IBI at selected locations of B7harat7hapuzha river 77 7 77 lieu-ice i jp Qlsccjre MEII =il7Blsco'reiA17‘7 J‘_V7|7Blscore‘7PU i7lB7lscore77 iiflumber|%-‘ital number of loachgpeciesw ofnativewpecies 7 7 77 ifQL7 '1 6\7_ 7 7707 ' 7 ‘_Q? 7 7 7 2 77 517 Oi 0 i7Numberof7sucker§peci7es 7 7 71i7 7 57‘ i_ 7 b ilflumbergf‘_Number of intolerantmidwaterggecies sgeciesfl 2;_7 77 Oi77 5‘ 7 iOL 01 3%, 0 10%1 5 7 ‘Number of tolerant sgciesi L17.7§r_’_ 7 7107' 7 — — 1 ‘_]'roghlcPercent l71ervivores7' metrics.e .v * *77 7* F7 *0%F 7|i ‘ 25i 1 i 1 i 4"Percentomnivores 7i ‘@3a.:sT ii 7 1ooi_ or 7257 _ 777 7 7 7 ‘_Pe77rcentinsectivores 77____177€737.6i77_7i 707 0; 0 507 lperoénttepcamivoresFish abundance and condition _7 l7 Oi correlation Q OT Z fctors7°17r t *L7 1 ‘ 7_ 7r Numberofindividuals Qer730O 1317[77- 7 i7 37 j -15* 7 -10 29\7 -10 lfercentifisheswvvith anomalies 7 W 7 7 5' - i 7 O4 - T __Overa|l|Blscore _ _ V V LJ _ ‘ 20! 77 7 7 ‘7 77 7 7 77 TO-Thodunnampara_ 77 AT-Atla -7 7 .7 O7 I ME ll-Meenvallam ll PU-Puchappara Table 3.20.(continued)Percentage contribution of different metric groups,lBl scores obtained Tb] different metrics and overafl IBI at selected loeations of Bharathgpuzha river 7777 7 77 7 L_ll7l7etrlcs 77 7 TTsY77 Trial score4_KN flsiseere, cu I is: score 7‘CH7 ll 7 ,|s| score ii [Total[N77 numberWflih7 7 7 of 77native ‘i 7 iaecies if7 75 i M577 if j 7 i7 —7_W7 l H1 (YT7 ‘ 5,7 71* i 5] 7if 7 2T 5i 0‘ 17Nu7p1be7r7ofsu7cker7§Qecies7 umbero 7oac 7SJ)8Cl8S 710“77 17 0% 7 7721 7 77 710;77 J7 77 07 or 7 LNum7ber of intolerant ispecies_ i -7 H, L7 W, 10; _7 7r 5l7 47 10 i ljlumberofmidwateregcies 7i 0 Q7 7 7 Q7‘ 7 7 Number7oflo7l7erant¥cies 757 10] 7 7107 67.77 7 7107 7 7 7' LTrophicmetrics ‘* bi W7 7 77 77 7 7 777 77 77 7 7 feroenthewivoresii 7* 7*}7_7_5i07'7 7 il 7__ 50? .i i_ OL _,.\ 607 77 7 7 ‘7P7erc7entomnivoresiPe7rcentins7ectivpres77 7 777 257 7 777 7 77 7 75Qi 0'77 7 7 5i977 0" 72077 507i_ 77 7 7 L7per0enttopcarnivores*_*77_Fish abundance and condition7 correletionfctors 77 _gr 77 ofl._ 77 077 77 7_\7 bio” 7,7 777 — zoi7 7 777_ fr _I 7 c7 7Li_ 7 \_Numberofindividualsper3O0 721i -1o 15¢ 7-1o 15177 77-iof or 7 -710i“ Pgroentfishfes with anomalies “oi; Fl oi i 7*7 7oi-7 7 l7 i oj- ii ,7Overalll7BIscore i “7 i ii 7 3017 f 7 1517 i 7 497] 757’ 5, CE-Cheriyawalekkadl ii * i CEII-*CheriyawaIakl Table 3.21 .(continued)Percentage contribution of different metric groups,lBl scores obtained by different metrics and overall IBI at selected locations of Kallada river $ .44 U1 01 ("Q ADC) -§ Q'Q¢;'\>-‘Q37 ,2 E5 00100 7.4? *.?|—~_-P-J-4 ojoio 7o coo i'® i Qi1;e,Q’Qi3‘l5’2“" oowio_ #7 “.7 to _Q7O_oQi7o"‘ ‘—-\ ‘-§ -§ l9_°l»‘.?_ 2 <37_ 07707 Qh7f777-‘ Q 7% J-~7o oo i -5 .-L A if 0:70 Jq Q0010 CHOP #3 91$. mw 9° c:>7-fro-~c> 0) 7lo oo=:\> _ 9 v~g1,¢>e A79 ~ Q7'°_14> ‘ ._L I-L; _=_omoc>77 _Q77o7__o7l Qooo lo c7{7qw7o7Q7_ ;1Metrics 5‘ 15 1MSL11lBl score CH 1lBl1score1KA11 “1lB|sco_r_'e11AR 10185515 1 Iotalnumber1 ii ofnat1ive_peci_e§ 10" 31 5‘111 11 1' 1 0"W71> 5 5 Number of Ioach species 1 0 11 11 1 i__ 1 1 11 _._ 0: 5 1] _Number of sucker species 1 ' 5511 11 1 511 15i 1 51 :1Number of intolerant §pecies”11 1_115v 191 5% 53 Number of midwater species O11 —1 1” 5. 11 011 16 ?1Number19f tolerant species_1 V" 3.5 _1 O11‘ 101 76.11 1 Q1 2585* 1Trophic metrics 1 "5111 11 '1 1 111 10; 125 1 14.31 "T Percent herviiiores 5 ' 1671 01 I . Percent omniyores 1 _616.7 1 01 6Q 1557.1 1Pe1rcent insectii/ores 11 11°1 1301 W 50 1 2118.61 rcenttogarnivores 11 111 0,11 1011 1 011 1 0 _1 11__ Q1 12211V ._abundance ___ and condition . 1. correlation .- . .fctors __ 1Number1 of individuals per 31001 115 11- f 1371 571T 1 "5 102 Percent fishes with anomalies 011 - _ 1 110 — 1_ 0 or 1_1 1 W11 OverallMS-MSL 113! KA-Kazhuthuruty score 5 11 201 1 4511 11 __ 121° _1 25 CH-Chenkali AR-Ariyankavu Table 3.21.(continued)Percentage contribution of different metric groups,lBl scores obtained by different metrics 3l'1Id119V9I'3|| 1|Bl at selected locations of Kallada river Metrics 1 1 PA ll IBI score PA I1 %IBI score CH _ ‘IBI score |To1talnumber1ofnative11 .1 . 1- pecies 1 11 511 1 51 11 0»1 1 1.0.J Number of loachspecies 1 2 1 101 _ if 1915 1 1 1Numberofsucl Peroentfishesiivith anomalies’ 1- 11 1 __011-' __1_ 1 Overall IBI score“ if by 1 15 PA I-Palaruvi I CE-Chenthuruny40 , 20 PAII-Palaruvi II Table 3.22.Percentage contribution of different metric groups,lBl scores obtained b different metrics and overall lBl at selected locations of Pamba river _1 Metrics _ 1 1 11TH 1LB_l1score1Tl “ITBI scor1e1PE fl5Blscore"1AZ 11 IBI score 1AN"5§Bl score 1 Total number of native pecies 101' 1 _ 5 1 511 3L 5 5 1 5 10,1 5 111 Number of loach species 1 11 01 0 0 1 1011 1 1 01 161 O Number of suckers ecies 01' O 0' 0; 5; M 21101 5101 Nurr_1berof11intolerant species 3 1 10 1 1 51 101 11101 _ 1110 5 1 5 Number of midwater species 11 151 __1 1101 01 I Numberbf__ P tolerant1, 141 s ecies 1 1101 V if 1 1291 7 1 5 10 101 10‘ Trophicrnetrics 1_*:__11 1 1 _ 1 1 '1 Percent hervivores 11 0'11 _ 7 71 0 1 11.1 1 251' _0_1 26? Percentorrlnivores 1 _ 50 11 111 130.81 01' 55.6] 1 37.5 151 30 Percent insectivores 1 1 _1 W V 33.3 1 37.51 51 501 11 10' 1 ercenttopcarnivores 5 111 161; 5 5114611211 101 1 1 Q Fish abundance and condition correlation fctors” .| _.11 1 1001 1 1 Numberof individuals per 300 1191- 1 1151 53 - 38 1 -10 Peroentfishes with anomalies 311- 1 4; -171O1 1 11 O1 1 1 01 1 0 “ Tot1allB1l score _ 11 5 11 40; 27 50 45 401 TH-Thottapuzhssery 5 5 AN-Angaimoozhi Tl-Tiruvillapra AZ-Azhutha PE-Peruthenaruvi Table 3.22.(continued)Percentage contribution of different metric groups,lBl scores obtained co $9 K) —L 9 Q Z 1 _L ..-x ow oo Q Q O U1 (J1 O _; 14*‘; o 19.3.10 |\) 1} P CD O DO Q __J 1° (J1 P O to _L _A_L 1L _.L _L U‘ i I\J _(O C) C) 9° O CJ 1". #1 ‘-1 _b O O-C) <3 O O _1<.-1“U‘ U1 C) O01 1 an O F” ~—1 Q Q O Q G_ J? #1Q _\ O O O O Q1 2 91 O _h O) F_ O O1 U‘! O by different metrics and overall IBI at selected locations of Pamba river i1lI!ie§?1§?1:1i1"‘1;11111111111 1? 1: 1: 151i1N1 JL11 :13 ?1<=?>1r€1“»TI1fi§l1éE16rJL<3fiilélééérijiai ‘,a 111.111 1.1 T51 §c3?1€?1PAi'B'1$2°'@i“ {!11L1n!3e§ilTo_tal_numpi=;r i ~i~ Q1 of : I9a9h1$gegie§11natiyepegigs :” :: 1; :::: ‘ \:1Qi%6": :: :111_10T~1 6+‘ £1jwjj;q1 5;] tji __8_i;%<1 11: :5;931 :o::__ 7“ 0‘OH 1 1g1 1 __ 111 10 ~ mber of $1~2!<2r §P1‘~i9i§1$ 11 1*” F11 1111 1 1 15111151 1 1 5‘; 1 9U 1 11Q% 1i '~Ll!@!<:'1Q'1 N *1<.>'§Ia1n* 5| §P§°'1§$1 i 2“ 5 4"in; i i j a i" ' 1 11 1 1 111 1 1 1 JOJ111 141 111 101 1 §i1 1 1191* 1111i lNLJm4bQf_(lll'E_ld\fV8l8LSB8_111 '111111 ci e111111111111L11_11_i111.111 e§ i ?__ N % (Li j 1}; 5M 0 01 ~.aJ 1i 1 L §H _ Lblumbgrpftolerantéspgcjeg23* _ \10] H 11 10¢ 1 si201» 1 17\1l3Z_.3j¢A_1_1_1_+ si oi *Ir§p51i€1m*9tji¢i5 1 1 111 1 11 111711: W 1 11 1 J1 11 11 ‘*1 1 11 1 1 \PgFc§n_trh§W'*orés*f*;;__rvnr;;;_;*JAW*2O~ : :1 Q * oi 421% _ _o[11 14. ii _ 1 oi 1_ grit *__r** <;L1111“k S 'FP<_=.;rc§ntog1rlivgre§é 1 A 1 1“ _40‘ Q_ 1 A _% Qs _ 4 _5“\ gasg 501 _ 1 A5 _1 _ é _ g 0__ _A§2.§>é , _ _ QT we---Jae.P8[CQfit_ll'1§8§ilVQl'§S_ e — — e ———fi+:i1*:*=::i::::i:::<::::i::::::w::‘ A A A Z01 _ _ 40‘ 50 5 57.11 5 3% 2L42.9i__ :___§> Kain @@@‘i§p@§r@iv&§§1:1 ii of 1;? i;.s::1:;:1@*:i@1:111161 @@ij1i1?11 1F?§"1a121uF9525s 51"31¢éfié1*ti§~1¢ Table 3.22.(continued)Percentage contribution of different metric groups,lB| scores obtained 191 difisfqyt I11\1e}§i5=1s_§q5i _9vgrg!I 1Bl1at11sgIe1¢t§1d1<>ga§<>gs1<>§P§"1berigeg 1 1 11 1 1 11111 11111111 1111 ‘l1!e1!ri38111 11 1 11 1 1 1_1‘~1M10§l§I §¢9r€N1<11II11l§I1§¢1grsT$K1I 1iI1Ei1I §1<=91re1iK1K_1_I “ 1l§§9r<=1‘!59 N51 §991r@ 1? HIO@IpumQeL0Lflati!epe<=ie$ ii W l I1 1 W 1 1 1' 1 1 1 1 1 1L 1 1 5*" 1111181ll\TurnberofLF1émi>eioi11 Table 3.23.Percentage contribution of different metric groups,lBl scores obtained ,.'2¥F'i“¢'§1"l"1°t'iE§1°"d°"°!§" !§!?1!1$1°1'?9F?d 1'1‘!‘??!‘52'1§19§ 9'Ji!'§1"PfiY1'il!"{'T 1 1 1 11 1 1 1 1 1 i1'i'9!'i1°§1 1 1 111 11 11 11 11 11 1 111\\1/15 1 i"1B11$1<;<1L¢;T*1AT11 111181 §§9!@[5I1 11 _i11§1§1<=91r§1i!A11 1 M119! §g<>@ 1; M'[0tal11 1111111111111e1rg number ofnativ 9 'es1j__g f 1QQc-1 f 11_~[1 11111 sy 1 1111 11 _ 111 1 15; _1 18; 1 1 1 1 '3'lE'H1*!9'1°!!Q€9“11$B§1°lph*sme1ri¢§111 1111 1 *1‘1"T“T 1”“ i “‘j1‘1'1“~1 1‘i;1;1:fi iEer¢@nt1h§wiv@r@s111U? __ E1 % oi 19.1l 1 11 ___ 1 1&3 __ OT 0“ 118* i ‘ 0+ lP ¢1'9e1'!*19'P1'1'Y°'e$ ' i : Q2-9t i 1 1 Q"1i 54-5“ ‘ i 7 i 0»‘*6167?Tiii i I* 115l15§-51 * "1 i i 61%: ll? 1'@§r11t@§§1¢1*iv91r§§1111111i1 119111111 9“ 22i-1* K 1 '1@Ii1i?~2iii 1 0 2%111112? i 1 ‘T i .B§111” er<=§n*!9e9ar@*v@ce$1 1 1 1111. 1 111115» 11 1 1 ’“ 1 1 15571 Q1 9-11Q11 1 1_1 101 _V_ 152* .1_1_ W12?’ _ ‘lF|Sh i—'~"Tiif'_:f-;1::i;11f:abundance and condition ,11—':1::—1—i—~:;—1— correlation fctors ;;11—111 1 1i 1lg 1 ‘.’1N19m1be1rQfifl9ividua!$ per 309 11-1 1 1 i 1125~1 1 1 1 151* ~?P1er<1=er1iI fisb€§l~ii1h*aF1¢rhaTié§ 1W1-1 111115? Z Z K 0~1- l 1 :0 L9v§wII1lB!1$<>qr€ 1 1f )1 I 11 JD I 155! 717111 5017‘ i ii: 14 L 1 15?‘ VE-Vettilappaira 7 * * 7* j 7 j j "AT ll-Athirép5aT|y*|F * * 7 * * '* ii * 1 Z : i: j J " ' Ifl ::::—l'F 11L 11 1,11 1; 41 of ro — w FQ‘ < 1 T . 7Q F1 -A -1K ié id é @ 0 one lf §Lieo1t‘-’l:.$1 A :1: : 1 1 11 N re’ I A 1191 1. -1» Q A 1 1 1 iL°‘_111”? OLFPNif fir--yr —: 1 1_, @ - lqqowg la1 T‘ in’ 1- 1‘ 1__.1°‘ii 1‘Z9 -L ‘ " 4 _J o .-L ou‘ t t .-L111 *1 11L 1: 14 1 1 i<> 11<2j1-:43 119$’ fifiiilfi F‘: 1 1 11 ‘.1 11 1 ‘ l 1 l T l‘ 1 l o ‘ \ L 1-111% 101 we1Q11 1 ~;1Q< 911110“ +11% 1:1 _r 1 111 V \ H T“ Us on 1 i a 2° N11 11-1 l 1: 1:’ 1 9M91 O1-:* 1 kar 'ih*444* F 1-:1-l: I T7 T W?”“To:"Lm€E_r ‘l H A r T J = m \ H t 1 l H 1 ‘ i -L __\ coo W 3‘o1.E; 9 91 “A191 1 1 1 _1 L910‘9' Q‘ #3 —:i,i ill —:‘ 1 <1? 9 1 .1 111 1!°1Pi‘° 1110:82‘ 11 1 1 1 ‘J;co;- 1 0&5: 1 -K 1 91111CZ1°l_1£" 91L-11 __”_; C) 1 l-14111 119111 1911 1 AT I-Athirappally I VA-Vazhachal Table 3.23.(continued)Percentage contribution of different metric groups,lBl scores obtained by different metrics and overall l_Bfilv at selecteid locations of Chalakudiy‘ river Metrics 5 MKA iBlscore1ORl _1lBIscore“vOR _l§Isco_re_51SHi ‘lBlsco_re__ j'otal nu_mber of native 101pecies 511 55 12Li 5 » 2 551 11i 55 10 W5 11 55 51 02 _Numberofloach2 _ sgecieslL 0‘ 5 m “J Qt jlumber ofsucker sgecies 1 1011 5 _ 115 A 22:? 101 2 . 1501 7i Number ofriintoleriantsprecies_2 L 1 2 5 .21055 __ 7555 2 101 5 w 11 10 1Numberofrnidwater sp_ecies_1 u 55 5 4' 10‘ 355 10 3 1 01 Numberoftolerantspecies if _ 1Q 1.61 101 2.1“ 10 O 10‘ 51Trop_hic metrics i 55 55 515 L 51 5.21 1Percentl]ervivores 1 205 r_ r _ rm _1 21 1Percentomnivoresi. I __ 77 <1 "y 5 5 —7 r50 1 5 46.25” —— ; V5 5511 63.6 12 31 50 9.11 1 Percent insectivores 30 23.1 1 1__ 92 _30‘ Qercent topcamivores W_15.4 i 05 5 50 01 0 1 J 2._ fish abundance and condition correlation fctors |_ 5 2 1~umber of individuals in 5 per 3005 M64, 54" - _ i _- _ 51 26112; 11 2 15121 -2 Percent fisheswith anomalies 01- W ii 5 Qi; 5 0 - 01V 21 Overall IBI score 5 42 2 _ 501 22 2 550 22 _ 455‘ 55KA-Karappara 5 5 SH-Sholayar 5 OR I-Orukomban I OR ll-Orukomban ll Table 3.23.(continued)Percentage contribution of different metric groups,lBl scores obtained b different metrics and overall IBI at selected locations of Chalakuflriver__ tviietricsi 5 _ i5 55 [Ku_iB|s¢ore5P5u 1IBlscoreT_H 5551151 scorg15THl_l51lBlscore5I flotal number of' native ' 1 pecies 15 H i ii 101 51 01 01 1l\lumber of Ioach species? 1, 5, 01 02 5 0 10 iNumber of sucker sgecies A __. 01 22 5 55 5 101 10i 15Number of intolerant species ii _ lb; i 10% 210‘ Number of midwater species? 5 5' 1 101 51 52 2 22 2 2_ .1 101 lyumber of tolerarlispecies_1. _ _,1 _ 5 2: 10 101 Irophic metrics V 5 _ _ ‘ ii W_‘i _ 2 23.1 *0 1 Bercenthenrivores 5113.31? _ __1 521 12.5 ‘I 2 26121 52.5 Percent omnivores Mir 4O|__ 5 _46.2 5 01 2 fig 2 922 55Percent 5 insectivores5 5 5 1 12335 33.3 5 . 0555 ' 401 1 72.5} if 01' 1 0,2 9 iircenttogcamivores _ 56.7 _j55 215% 1 Fish abundance and condition correlation fctors 5 1 ‘1 NumberofindividuaIspe_r300 151 - 5 i 11555-5 1“ 125; _ 1261 Percentfishes with anomalies 0 _ 5 1 _ Oi; i i'_ 01- i 01 Overall lBl score 5541 5 1; 45 1 1 7 30 1 30" 5 5- 5- 55 T1-1 ll-Thekkadiyarl PU-Puliyala TH-Thekkadiyar Table 3.23.(continued)Percentage contribution of different metric groups,lBl scores obtained Ybvdiffemnt metrics and overall IBlat selected locations of Chalakud river Metrics ‘ l 1lBVlrscore1i5NlAL5 5 i__TE ll1lBl scoreiQR ‘Félscor§1VAL I §L5iBl score ]T0taI number of native12 pecies ' 5 1 i H2 10, i 5 552 5 ‘ 5 01 ' 555 1 51 5 012 O. 11Number of loach spgcies y 51 55 0;; 1Numberofsuckerspeciesi 5 5 5 55 5555 10155 1.1 10‘ Number of_intoleranl species L 7 A ‘_i 192 21 22% 2 10; 1Number ofmidwalerspecies 1 55 5 51051 202 7.1% 101 TNumber of tolerant §ecies 1(Jj 5"1 1Tr0_phic__met_ricsi2 2 22_ Q 5 15 515 _l2 5 f5 5 12 ;Percenthervivores 22 22 22 22 _ 3-32I 11_3115 01 5 5“ 201 51 33.31 5 1_Percentom 5vores 5 505 5 OT 5 62 16.7 2 2 22"'2 2 2 55-32 605 16% Percentiinsectivores 5 33.35up 51529.4 5A 201 01 50 5 Qercenttopcarnivoresi 5 '5 055-5? 0% 5 IT O22 OF __Fish abundance and condition correlation fctors 1 _ 5 51-5 2. 12 L. I 1Numb5er22 ofindividuals 5 . 3002 i 945-_ |5_2061_ 2 - 5 15 1 2561 " 1_ 535 01 5 1 1 §’erce_nt fishes with anomalies 01- 7 1? of 5"_ 1 W0 ‘Overall IBI score 5 _ 5 1 5455i 5 1 5 57 251 4551 TH lll-Thekkadiyar 1| 5 7MA-Malakkapara 55 that 5' § -.a U1 —L O -IO’) M O>(O_I\J < __Q -L 1§ Q9 C.’ 2" O'\l\J C) mo ca T -.1 oi cn 74 £0211‘ ll‘-‘12° _O ._L O l\JCD Q @ Q OD -5 :5 N) —l-bu 2 Q2 U1 P6 91 U1 ?U1 001:: O 19 C) E? U1 M9 O) 9 ->0: ._L C) _@ QC Q29-r OR-Orukomban VL-Vallakayam Table 3.23.(continued)Percentage contribution of different metric groups,lBl scores obtained £1 different metrics and overaIl_l_Bl gt selected loca}tio_ns of Chalaixnud}; river 1 _ _? _ W f W ‘ LMetri2c_s 22 2 ._ i}\NA lBlsg0re*l_Pl_\D_ lklBlscore2ll§AR \*lBlecore~VET§c_or_eW. Iota! nurnb_er of native pecies212n_ 28 . _?. Q1. 7j 14“ Q 5} 22_ 5t — _ 07 1Nur11ber_ofwflumberofloachigecies sucker species 112. _ 9f 12;5.. 11%5i2 2 i2 022 10L 254i i 51 %Number_of_1ntole_rantspeciesiyumber of midwategspecies‘-_A W 21_ if i __ 5_. 7‘/LA _.. W .1é _ __1 i0 . _ _Oi ~iM10‘; i_ 2 i H ‘I _ . 52.2 _ ~—i 77%' <‘ 1?Ol 0 ‘glumber'-r2 0 2oft6lerantsepecies2 o 2 22 22 2 . 22_ 10% 22 5.5 i 101_ _ 2210 2 1_O i_Percenth?ervivpres_1 rggbic metrtcsue _ ?.'12.5i_- -1 _. .2 _? '2 22.2 Q’ 20 12.512 22 L 2 2 Peroentornnivoree 2_ _ _]§7.5. 2- 2‘ 50L 2; 1244.4. _ 6. 37_.5 _ u_ ~[Percentin2sectiV2ores _ 22_ ]_25_.41 _ {_21_ %@332 K _.3, 237. 5 _? 2 7. rcénttoQcarniyorese_ 2 225 2210.;oi H W _21‘ _ 0\_? _ O‘ _ A W \_Fisi1 abundance and condition correlation2fctor§s2 22 M i 212 2 2 22 2 Number__-. of individuals .__- per 300 150T-._..-.e Q 2 229. 10% - j _\? 961-_ j __fi >:/31 - j _ _-Q 12 Percent fishegwith anomalies 0 3 _ j Q5 i j MA Oi - _ 1 - _ e 2AN-AnaRkayam2lOyeralllB| score 2 f2 22_ __ 2 22 40‘ 2 22 l 452 2 1 22 5 PA-Padikutty VE-Veiti Ar KR-Karappara river Table 3.24.Percentage contribution of different metric groups,lBl scores obtained rbydifferent metrics andove|'all_lBla_t selected logationeof lferiyar riyejr __ ‘ V; _ _? j _ f _>Nletrics f _ _ j2BH_2iIBl_sco_re NE -‘IBI scorei 0 ?\_AlBl*sco[e 1T PU M %-TIBI score 1‘T2<>!=-‘iinum9§r6fnafl~{eizq<=ie$w.Nurnber?ofIo*ach sgecies i2 0. j W l1 .11; _ 11_ 051; _ 2__2 "515 _? _0| _ _0? , LNumberofsuci2 q-L -L .210" 91L C)QU1Q ooiqF Q. --L ‘*1 C) (O Ti ~l —\Ll'1T_Q - 01 _Afcn_ --_ —$_L Ul(DQCJ |\J1 1 a__L .0; ooog c>A_c301_ _r~.>, l\) 2i gr‘ 1 T. 3-15> 0° -L—;,£=> c> o_-§ _ 10-o1i\>c:g mi olgioo Elm 2 . 2‘ L3‘-’1Q2'J_c3. INE-Neendapara | |Pl-Pindippara Table 3.24.(continued)Percentage contribution of different metric groups,|Bl scores obtained by different metrics and overall lBlat selected locations of Periyar river __ 3 flglseore PA? lBlscore3iMU_ 3lBlscoreiNLe WlBl score Metrics TN I J3Tot_al number of native pecies i Q 0 ! \VNumber3of loach species 3 1 i 5 L3 P33]. 3Q _Number of sud Table 3.24.(continued)Percentage contribution of different metric groups,lBl scores obtained by differentmetrics and overall IBI at selected locations of Perjyarwriver Metrics 33 _ _ ]i3KU lBlscore3iMN _iflBlscoreiQO lBl score UM 3 ilBl'score s “OW ilotal number of native Jaecie30L P °3i i‘0i Number of loach species _ 3 3 5 5, ' oi 0. 5? 533. 0. 0' mumber of suckergpecies W 3 i [Number of intolerant species if ' P 310i wt 3 10. [Number of midwaterepecies 933 33 33 oi 3°‘ 3 93 0 ihlumber of tolerantspecies V 3 3 3 103 10 17? 310i ‘l'ropl313ic metrics _ 33 ? 33 3 3 J, iPercent herbivores M ' 0| 3 or 16.P 6 13.7 K 3 3 9. Percent7-7 omnivores 7 . _.. Z 33.315' 3_i AP50 J 8333i . 1003‘. -TPeroentinsectivores =66.6i 10 16.6? i 3Z0 Oi Fish abundance and condition correlationoi 0Llctors oi P 3i [grcenttgpcamivoresii P _ 3—| 3 3 3 33 3 blflumber er individuals per 300 58. - P P P 531 _ 62|_ Z 43 ~10 ifercent fishes with anomalies? 33 QM; 3 33 0 Oi Oi. {Overall IBI score j 30 30 1i KU-Kunchithanni CO-Choorapara 30 310. MN-Mandrappara UM-Ummikuppanthodu Table 3.24.(continued)Percentage contribution of different metric groups,lBl scores obtained b different metrics and overall lBI3at selected locations of Periyar river Elfitrics 3 riTA 3lBlscorei'AN lBlscore"LTE I IBI score i ML -j3Bl score 333' _ 8 ' 0.. .LfTota33lY it number I of Oinative pecies vi! i _ P *5 } T iii 5 [Number of loach species Q T 5i P01 9i3 Z 130" ihlumber of sucker species _ _ . 3 19l 3 ii 10‘? 2 2 1 ioi Number of intolerant species_,i _ 10 ioi P 338i 101% *39 ‘Q _il‘ ' 5. iblumber of midwater jpecies _3 f 53 0‘ 0l TL 5 ii ‘Number of IO|Bl'8l'll§BeCl6S _[ 3 3 3 J-T 16T Oi 1_o7“ oi W i Qrophic metrics f ”_e i_ At i 3 _3I 33 J Percent herbivores 3 Y 37.513 ii 37.5” T 2si 053 3322.2 E Percent omnivores it 501* it 37.5_[ i 37.5 55.6‘ Percent insectivores A Al 12,5} 3 25L 37.si 5’ 22.23 rcenttowcamivores it i N i oi 9 oi P P0” ‘i ‘P9 _ J’ _ .3 3 0|, 0 I 4 Fish abundanoe3and3 condition correlation fctors T 3a 33 e iNumber of individuals per 3003 esi P284 P I 54' i3 3104;. T Oi ‘I 6T‘. 1 LOverallPeroent fishes with IBI anomalies score 0L- 404 P ii‘ 0i'-P‘ T 50 _1 TA-Thannikudy 7 P TE-Thekkudukumpara P 40i i H soi OLI:-00 '2-‘Q Q C C) O (.0 -5 O (DO @ O Q‘ C) O O O O T <._-1 __ _§ _\ C) --<0 53> i F9 QC3 -A O) _L O O) Q -B O) T__i_O F -A U1@ O O CD O U1 (DO DO .2 Q _ _(3 O 53 C) —l _L O! C) D 0'1 N-L m C) O O O _2 Q‘ U1 Q 2 U1 (D O3 0 C) .§-L O A *_. 3° 'l_ O O Cl|@ _Q Q __O C) (D O1 U'l O AN-Anakkallankayam ML-Mlappara Table 3.24.(continued)Percentage contribution of different metric groups,lBl scores obtained b different metrics and overall IBI at selected locations of Fferiyar _ri\(er _ _7 _ 77 _ 77 2!‘-"e*[!li9=2l* 2 2 22 2 2‘ 2 2 2 T"A]'B'$<=°'e!PL psi s¢<>rJ§A i us: scoreiMO Lie: scorej \7Tot7al number of nativepecies 77 8127 7 07‘\77 _ 7 2|7 22 7 277 7572277 7 27 0" "pmmberofloachigcies 7 _07\ 77 77 l7_ 7_ 5!‘ _i 52¢ 57 ,7Nuin1berofsucker§p§cies_ _ 7 277 _7 7170,l _ sji it 22 19122 22 52* Qlumber of intolerant species 7 777 77 _710i77 0 . ‘IQ LN umber of midviateri species? 7 _ 2 Q 512 2 2 2 924 2‘2N11rr1ber9it0i§ér§nispeciesW_ 15* 7715*? 170“ ‘Tropfiic metrics 7 77 _ 7 7 0?2 21 wi 72 2 272210; \F* Percent herbivores . 7 it J[ 2 3323i 77 7 Q‘ ”FT eroentomnivores 2 2 2 j 2 _ 22 44.4* 312522 233 is 37777 7 2 2521* ‘__Percehtinseotivores 7_ 77 7 7 25‘i7 7 9? 22.2 7 257 77 N 77 33.31 52‘ perwnttogwrnivows 27 22 2 0*, 70¢ QL ‘E22 22 22“ Oi kffish abundance and condition correlation 7fcto7rs_ 7 J7) 2. —- __ 72 2 —- 2_ —2 7_ ——Li ‘Number of individuals per 300 103? 77 iszii 77 7 J7 284_'_- _ _ 94L -i it 2|) \TPeroent_fishe*s7 7_ _ vqith _ anomallies 7 \_ _7 Q;of 17 7 2 L oii‘ 777 T _ 2I I ‘27 .@_s @7T0veraIllBls7core 7 77 1 77 as; 7]‘ 7 _74oi7 \__7 777597 2 49‘ TNA-Thannikildy W W W T j * l NA-Nadatholtam PL-Pillakayam MO~Moo|avaiga Table 3.24.(continued)Percentage contribution of different metric groups,lBl scores obtained £1 different metrics and overall [Bl at selected locations of Periyar river __ 7 7 7 7 777 twew6s2 1 2 T 12 5111181s<=<>=-quK22T@I:-¢2<;r@i_"q&27%IE9s=o Table 3.24.(continued)Percentage contribution of different metric groups,IBI scores obtained 77b! d|fferent777metrics_an_d7 over7a|l_l7Bl_ at selected7locations77 of Periyar river HM@¢I'i¢$2 2 2 f 7 7 _ QGVI lTLBlscore‘iKUl* il7*Blscore‘l Ljotal number2 ofnative 2 4+2pecies T7 7 7 oi 722 2“N~mbs? Qilsschspéciés 21“ ii F2722 Number of_sucl _J.e_ O A € Q 4% -00 ui O 0170 U1 *5 21 it Ii‘ 1 c9_Q B‘ _2IQ o_2rc> 9 2.20 C)‘OO Q 5:» Q‘)-A Q l\.Z@ -2 O P L53 L; 790 OCD Q O 2°; ‘-‘AP Q22 OJTLDO co 7*‘ °2EJll ism 2 Q -jcoit|\J ..t_ (Q7 _)2 Q i DUI o -A 29_l‘3lLt°2+9" Q CL .A_s 5292 -:7_|\) 0: 22 O7 ":2 °°%2 -A C? Lo 77_U'1 u7_U‘l ‘fioi Table 3.25.Ran eof water quali parameters at selected locations of Kabbini river system 77 Air ternjgrature Water_temperat11r§ H _ Q0 Total hardness Iotal alkalinity Flow vel_o7oit¥_ Kunnambatta 7 297.3-32.3 26.1-32 7.4-7.6 3.23-3.7 14-22 7 7 3-10 7 7 0.11-0.2 Amn57gi71~i 7771 7 77 20.3-23 7 19.1-27 7.3-7.5 7-7.3 _ 3-72 35 77 0.221 -0.24 Aranagiri II 77 20.6-26 19.5-25.8 7-7.3 3.77-7.3 _1_7_07-1 6 5-8 77 7 0.305-70.313 I $0gandagi1fi__77 22.9-30.2 20.3-28.2 7.2-7.377 6.9-7.2 _7 10-14 7_ 3-10 77 0.239-07246 B691." 77 _ 25.4-31.8 24.2-29.3 7 7.6-8% 7._27-777.577 14-2707 710-71477 0.713-07.71737 Aranaqigi 7 7 7 21.9-26.2 19-25;? 77.2-7.37 7.5-8 7 7-10 _7 24 _7 0.531-0.556 1 Beggrl _ 26.2-30.9 21.3-28.7 7.4-7.7 7.1-7.5 12-1377 7 3-7107 _7 70.247-70.231 I Begur ll 27-31.7 24.5 -723.3 7.2-7.5 7.3-7.3 7174-22 7777 7 7-12 _7 0.33-0.903 Muthanga 7 _ 25.8-29.9 1 9.73-723.5 7.5-7.8 7.4-7.8 10-13 77 10-13 0..9@4-9-963 I Noololiiha 27.6-30.47 20-25.9 7.4-77.3 7.5-7.9 10-1477 3-170777 Pdnlguzhy 20.5-27.27 15225 7.6-7.977 7.9-8.3 12-137 _ 7-5-8 7 7 0.744-0.47 Kuryadeep _ 27.9-32.2 23.2-27.6 7.5;77.73 7.777-73 1677-247 77 3-14 0.47-0.482 1 Palvelicham 26.9-32 237.2-27.1 77 7.5-77.3 7.75-7.3 77 170-20 7 3-3 0.49-O. 503 Achoor 22-31.1 19.4-25.6 7.3-77.6 5.93-3.3 7713-24 7 3-10 7 0.32-0.3761777 Tharioq 777 257.3-2971 1 9-24779 77.3-7.5 7.1-7.5 77 13-227 77 4-3_7 371 Table 3.2_67.Ran eof water quali parameters at7selecte4_1 locations of Bl_1a7r7athapuzha river s stem 7 Air ternjgrature Water temperature 7l_-I Dissolvegox Totalh77ardnes5 Total alkalinitl Flow vel7oci7t7 Karin athodu 77777 2137-223 19.4-271 .2 7.8-8.3 5.32-5.33 23-26 4-8- 7 7 0.437-0.41172 Q_l)eriya_w_alakk7a3l ll 725.2-728 21.5-22.4 7.6-8.1 5.95-6.26 22-28 .4-8 0 Puchapara 275.1-27 7 21.7-22.5 7.77-3.2 5.74-5.93 13-247 7 7 4-10 0.371-0.7335 Karimala 23.2-23.7 22.8-24.2 3.79-7.37 5.24-75147 22-7278 7 M 74-10 0.932-1.03 I Cljeriya walal_ 1<-111111.16/1;;17 7 7 7 7Air7ter@e7r7a7tu1fe * * 376-62.77 Watgr te7r171Qer76turg-;» 7 727.72-317 H 777 _Dis7solv7g.=7.:d 7 7.5-6 7 5.42-57.637 07>; To_t7a1hgrdne7ss7 24-367 77 '[0ta7alka7linity7_ 7 47-6 7 70.127-0.165 Fl7ow velocjta Az11u1na** 7**777 267-317 7 6 23-275.67 7 _ 2,2-7.77 775.9-6.477 7_ 8-14 77 24277 777 __ Q-7-0-724___1 K;1<1 ]'g7t1leI7>‘7.2Q7R7a7n eof7w§te£ qu7ali p7ara7me7ters7s at7se7lec§ed1ogati9nsof7ChgIal§ud7 ri7\7rer7§ystem 77 7 7 7 7 77 7Air7ternperature Water temgeratpre H77 7 Dissolved ox Tqtalharqpesi TotaI7alkal7init7L7 F7low1{eloc7ity Anzflkajérp I7 6 7 ' 25 -30**********-*7 22.4-723.5 77 7 77.37 **7**1.5- .93 715-2727 ** 736 -7 7 7 0.§34-0.6417 QFuk7o*mba'n7‘*7 7 -07 77 7 2§ 77 3 5 7* 7 *77 242*-*26 77 .6-6.7 * *7 6*6*3i 77 .376.57 24 637-77 * * 4-67 7 *7 7 7 770467-07.744177 7 77 T131a*k1 valglgyag 26.67-267.75 7 77 273-275.27 77 7 76.1-77:77 7.6-6.1747 7 16-247 77 7 6-12 77 7 0.437-0.45271 1 0ru7ko_[n7ba7gI_7 7* 60.27-33.75 77 2:1-276 7* 7.27.7-77.7772 16*-20 5171*-5.76 * 410 7*7*701766-0146, 77 7 7 7 7- 77 7 .7 Qmk9mban7Il 7 7 61.2-731.6 7 7 23.7-27.9 77 7.3-77.97 5.7-5.67 716-207 7 7 74-6 0.169-0717271 Th§kk6di)7@r 7* 3076*-617.*9 * 7 724.2-277 7 76.7-76* 4.776*-576*377*572-75'*7 76-170*7 *7 7 7 77*707‘ 1 V°""§Pa7@ 7 317-3-_§2-if .7 .25;69-2§-77 27:1*-742 7-6-8.-1 * 12-16 . 7- * -.*6-10 7 .7 * . * . 066-9672]._ -_ -_ Vazh§chal7 77 7:;1.9;a4.7 7 723.2-26 7 7 7.7-76.27 7.1776 714-20 77 6-14 7 7 0.24-0.62 7, *. 5111T5171J39311y_**7 7 2*76.6731.5 7 7 724-276.27 7 77.6-76.47: 77.671-7.763 *7170-16 7 *7 76-17-7177*7 *7 0.5-0.54 .1 Sgolzgyar 77 7 7 60.57-31.6 77 7 25.77-297 7 777-7.747 75.6-6.627 20-276 77 7 4-6 7 7 7 __-Q 1 A111i*ra71gpa11y7*7*7*726.5-60.67*7*7 265*-26*47 * *7 7.7-6.47 7.5;7.6*7 7 170-16 7 7 6-12 7 70.7-0.773 |<*ur1€r1<1I11L* 77*7 32-62.67 * ‘ 26.6-297 7 7 71.6-6.1‘ 51175.26 726-3577 77 7 76-1217 77 77 76.172-0.171 7 Padikuttl 7 7 26.1-730.6 7 24-277.27 7 7 7.77-6.5 6.2-5.41 7 24 377 77 7 7 476 7 77 7 0.166-0.714677 1 K6@p7qrg*r17Jer7 77* 26.77-30.6-_77** 726-72*5.6*77*77** 77177.7-67.2*7 67.2476.35*7 22-267 *7 74-1077 0.21-0.27777 ] P05761711 77 7 77 627.7-673.27 7 25.5-277.47 7 7 7.4-77.67 6.4716657 66-42 7 7 76-6 7 0.297-0.315777‘ Thekkadivel Y. 29-2.0-2 *7 *7 277.4-279 7* * 7* 7.6-*7.67* 4.579-5.6 7 22-275 7 7 77 67-6 70.*1076*-0.712571 VettjA§.7 7 - 7 7-5-24-4; 7 2 - ; 22-5-24-7:“ -7 7-71.1-»7 45175.56 7 24-267 77 4-170 7 77 7 071 K8f87Qp8@ 7 1 371.5-737.4 7 7 26.76-2§7 7 7 7.1-[.67 7674.676-5. 26-327 7 7 7 7 7 77- 7 7 7412 77 7 777i 0 M6l6kK6v6£6 - 2 73°-§-31-47. 2 _ Z2-252-3_ .7 7 .7-5:3-3 57-1915-57§ 77 1261577 7__ - 774-7§ _ .7 _7 _ -7 __ -91 1'a7b7le73.7§07.Ra7n gaf 1ga7§er qgali 77_pa§amet7ers at se|e7§te7d |7ocati7on7§ qf P7erLya§ r1'7!e[ s7!st§m7 77 7 7 7 7 77 7 7 7 7 511 tem7pe_r7atu7re_7 V1Ia1ert7emp7erature 7H 7 7DO 7 To7taIhargne7ss T7o7tal7alk§|iniy77FI0w velgcity Ngdathofiarfi7 7 7 77 7* 77 707. 3 2-33 7 .4 77 77 2*5.7i6p 7 7 6.27-6.9 *7 7.12-7.63 6-147 *7 2147 7 7 0.31-0*.35*7 6 ]j1a5n11§uq7y A7 7 7 277.4-29,6 _ 7 7227.1-7277.67 77 7 7 7.79-67.577 6.66-77.1777 2676077 777 77 73-6* *7 * ** 0153-0.562 Mgndgagpafa 7 28.76-29.87 77 77 275.4-2776 77 77 77 7.57-7.6 775.93-6.59 6-16 7 7 7 2-67 7 *7 77 0.45-0174677 Qmmikuggaqthgdu 7 25.47-2§.87 7777 __77 271.6-25.17 _7 7 7 7 7 77.6-*6.2*7* _7 _ 7 775.467-5.627 _7§~786 6-127* 7 *1 ** :07-18-70-22 7771 inukkén 7 7* 7 W 7 6 7 31.6?-38 77 729.4-733.577 7 7 7.9-6.277 57.637-6.0727 272-7276 77 7 72-67 0.26-0.347 7 A2akFa"é~5a1@*m. 26-*9-111 Q6 7 277427677 77 7 76.4 6.67 6.6677357 76-717477 7 7 2-677 7 7 7 0.46-0.467 1 l{u7Iikj 40 30 20 o ,-fll!tS~~,f~!!f lnatream cover L ____ . _ --.-.- . ~~-~- Turb-Turbulance TWW-Turoulant white water boulders SWD-Small woody debris SOP-Scour out pools LWD-Large woody debris OSB-Ovemanging stream boulders QV-Overhanging vegetation US-Undercut bank SV-Subrnerged vegetation EV-Emergant vegetation Fig.3.2.lnstream cover composition in Bharathapuzha river syetem 40 , 35 • 30 25 f 20 ,-fll!tS~~,f~!!f InstrNm cover . -- -- -_._- -- --~~~~~- -_. - Turb-Turbulance FV-Floating vegetation SWO-Small woody debris TWW-Turbulant white water boulders LWD-Large woody debris SOP-Scour out pools QV-Qverhanging vegetation OSB-Overhanging stream boulders EV-Emergant vegetation US-Undercut bank Fig.3.3.1nstream cover composition in Kallada river system ------~ • ~ •e :. Turb depth LWO QV $V EV TWIN SOP OSB UB InatrNm cover I ______------______1 Turb-Turbulance TWW-Turbulant white water boulders LWD-large woody debris SOP-Scour out pools OV-Overhanging vegetation OSB-Ovemanging stream boulders SV-Submerged vegetation US-Undercut bank EV-Emergant vegetation Flg.3.4.1nstream cover composition in Pamba river system ------, f Turb Depth SWD QV sv EV SOP 0S8 UB IMtrum cover -'------Tum-Turbulance EV-Emergant vegetation SWD-Small woody debris SOP-Scour out pools OV-Overhanging vegetation OSB-Overhanging stream boulders SV-Submerged vegetation US-Undercut bank t ~ :. Turn SWD OV TWW OSB IMtream cover ------. - - ~ Turb-Turbulance TWW-Turbulant white water boulders SWO-Small woody debris SOP-5cour out pools LWO-Large woody debris OSB-Overhanging stream boulders OV-Overhanging vegetation US-Undercut bank EV-Emergant vegetation Ftg.3.6.1nstream cover composition in Pariya, river system & 40 .l!I 30 ~ :. LWD DV EV TWW aSB Instream cover Turn-Turbulance EV-Emergant vegetation SWO-Small woody debris FV-Floating vegetation LWD-l-arge woody debris TWW-Turbulant white water boulders OV-Qverhanging vegetjtion SOP-Scour out pools SV-Submerged vegetation OSB-Overhanging stream boulders US-Undercut bank 40 f= 35 3. 30 ~ 25 20 e 15 f= f= f' :. 10 5 o I- I- ""'" I... J• Subslnte. Fig .3.a.Substrata composition In B.harathapuzha .!iver SY8t.~ _ _ 1 30 f= • 25 , 20 f= f" F • 15 F I! 10 t. 5 .-==iI o I- l- f- ... !o Sur_b . ... ------ _ __ _ ----"Fl!iIg"'.31.!.9~.S!!'UIllr-~b'!.!!.. ~ COI'!'!'m!lpo!lt!on!!!!!I!!!!!JoIn!!Ka~I!!1acI'!!.. !.!! rIv!'or!!.!oystem'l!1i!!!'~ ____ _ 35 30 & 25 i 20 e 15 :. 10 5 0' __= Substntes ,- Fjg.3.10.Substrate composition in Pamba river system 25 20 F 15 F 10 F 5 o <- f- ~ I- 'F Il ~ 11 I! g c > .0 u: .0 " a: ~ ~ 0 ~ Cl 0 lJ III" ~ Sut.b.tw Fig.3.11 .Substrate com_pos_H_i~n in Chalakudy river 8ystem ___ --, I 50 •co 40 ~c 30 •e 20 10 G.• 0 w m e I! "" .5 !! ~ "" ~ LL" .0 " 8 ~ 0 'll a: Cl lJ .il ~ Sut.b.tw Fig.3.12.Substnlte composition In Perty., river system 25 <= 20 <= <= j :: <= F 5 o -- ~ ~ Ip- • • • ~ • ~ • ~ ~ !! .0 ,. ~ ~ 0 , a: 0 ..0 ~ " Su"htM - _ .. ------.------! Fig.3.13.Channel geographical units composition in Kabbini river system i •c :.I! RI R TR MD POW G LP PL Ch.noel geographical units ------.. .-1 RI-Riffle POW-Pocket water pool R-Run G-Glide TR-Trench pool LP-Lateral pool MD-Midchannel pool PL-Plunge pool Flg.3.14.Channel geographical units composition in Bharathapuzha river system ------25, I i _ 20 1 t 15 e 10 :. L ______------' FA-Falls MD-Midchannel pool CA-Cascade PWP-Pocket water pools RA-Rapids PS-Plane bed RI-Riffle G-Glide SH-Sheet L5-Lateral scour pools R-Run ABC-Abondoned channel TR-Trench pool Fig.3.15.Channel geographical units composition in Kallada river aystem ,------ FA CA RA RI R MD Pl ------' FA-Falls R-Run CA-Gascade MD-Midchannel pool RA-Rapids PL-Plunge pool RI-Riffle Flg.3.16.Channel geographical units composition In Pamba riveraystem ~------ :.f , ~ ~ RA ~ ~ R ffi ~ ~ G ~ I Channel geographkal unHs L ______.J FA-Falls TR-Trench pool CA-Cascade MD-Midchannel pool RA-Rapids lP-Lateral pool RI-Riffle G-Glide CH-Ghute PS-Plane bed R-Run Fig.3.17.Channel geographical units composition in Chalakudy river system i:. 0).-_ I(.TJ~~iJ' ~~.i ~Q.~ttl:'l~ Channel _rophlcol unlta ' ~~~-:;;~~~~~~~----;:-=-:-~~~~~---.. FA-Falls G-Glide CA-Cascade PB-Plane bed RA-Rapids PW-Pocket water pools RI-Riffle PL-Plunge pool CH-Chute BW-Back water pools R-Run AC-Abondoned channel TR-Trench pool MO-Midchannel pool Fig.3.18.Channel geographical units composition In Pertyar river system :.f .." u ,;r ~ IJ FA-Falls TR-Trench pool CA-Cascade MO-Midchannel pool RA-Rapids LP-Lateral pool CH-Ghute LS-Land slide SH-Sheet BP-Backwater pool R-Run ABC-Abandoned channel Plate 3.1 Kabbini river system - Detailed habitat inventory locations , A ..... ·1 I I ..; I. Sugandagiri 6. Achoor 11 . Aranagiri 11 2. 8rgur 7. Beg"rI 12. Aranagiri J. Kunnambatta 8. Beg"r 11 13. Ponkuzhy 4. Kuruvadeep 9. Thariyod 14. Noolpuzha S. Palvelicham 10. Aranagiri I 15. Muthanga Plate 3.2 Few typical channel reaches from Kabbini river system Braided reach Regime reach Bedrock reach Pool-riffle reach Plate 3.3 Bharathapuzha river system - Detailed habitat inventory locations I. Chcruthuruthy It. Cburiodu 20. Thippillikayam 2. Kanakkannor 12. Kalpatbi 21. Thodunnampara 3. Thonikadavu 13. Pezbumkara 22. Meenvallam 11 4. Cbeuakuzhi I 14. Choorapara 23. Atla S. MeenvaUam 1S . Chittoor 24. Pucbapara 6. Cbeerakuzhi 11 16. Kavarakundu 25. Cberiyavalakad I 7. Pambadi East 17. Velampattapuzba 26. Karingatbodu 8. Maooarkad 18. Kanjirapuzha 27. Cheriyavalakad II 9. MudappaUur 19. Karimala 28. Synendri 10. Vakkara Plate 3.4 Few typical channel reaches from Bharathapuzha river system Cascade reach Bedrock reach Plain bed reach Pool-riffle reach Plate 3.5 Kallada river system-Detailed habitat inventory locations 1. Palaruvi I 7. Urukunnu 2.0ttakkal 8. Dali 3. Palaruvi 11 9. Kazhuthurutty 4. Meenmutty 10. Ariyankavu 5. Chenkili 11. MSL 6. Cheruthurithy 12. Chenthuruny Plate 3.6 Few typical channel reaches from Kallada river system Step-pool reach Pool-rime reach Braided reach Bedrock reach Plate 3.7 Pamba river system - Detailed habitat inventory locations I. Thottapuzhassery 6. Nilakkalthodu 11 . Moozhiyar I 2. Thiruvillapra 7. Attathodu 12. Moozhiyar 11 3. Perunthenaruvi 8. Kakkad Ar I 13. K.kki I 4. Azhutha 9. Kakkad Ar 11 14. K.kki 11 S. Angamoozhi 10. Pamba 15. Kochupamba Plate 3.8 Few typical channel reaches from Pamba river system Pool-rime reach Cascade reach Braided reach Bedrock reach Plate 3.9 Chalakkudy river system - Detailed habitat inventory locations 1. Vettilappara 11. Th.kkadiyar 1 2. Athirappally 1 12. Th.kkadiyar 11 3. Athirappally 11 13. Th.kkadiyar III 4. Vazhacbal 14. 0rukomban S. Karappara IS. Malakkappara 6. Orukomban I 16. Vallakayam 7. Sholayar 17. Anakkayam 8. Orukomban 11 18. Padikkutty 9. Kuriarkutty 19. Karappara river 10. Puliyala 20. Vettiya r Plate 3.10 Few typical channel reaches from Chalakudy river system Plane bed reach Regime reach Braided reach Bedrock reach Plate 3. 11 Periyar river system - Detailed habitat inventory locations TAMILNADU I. Bbootbathankettu 16. Ummikuppanthodu 2. Neriyamangalam 17. Tbannikudy I 3. Pooyamkutty 18. Pulikkayam 4. Purukkallu 19. Mlapp.r. S. Thaodamankuthu 20. Tbannikudy 11 6. Neendapara 21. Pillakyam 7. Manjappara 22. Nadatbottan 8. Pindippara 23. Moolavaiga 9. Thannimoodu 24. Kundamkallu 10. PaoDiarkutty 25. Mukkar 11. Mukkan 26. Chembakavallithodu 12. Nallatbanni 27. Kattamadithodu 11 13. KUDchitbanni 28. Kattamadithodu I 14. Maodrappara 29. Kunthrapuzha IS. Choorappara Plate 3.12 Few typical channel reaches from Periyar river system Plane bed reach Bedrock reach Pool-rime reach Cascade reach Chapter 4 Fish diversity vis-a-vis altitude in the major river basins of Kerala 4.1. Introduction The convention on biodiversity signed by 156 countries at the Earth summit in June 1992 in Rio de Janeiro defined biological diversity as the variability among living organisms from all source including interalia, terrestrial, marine and other aquatic ecosystems and ecological complexes of which they are a part; this includes diversity within species and of ecosystems(Lachavanne and Juge,l997). The challenges thrown down to humanity by the loss of biodiversity and the hazards which the reduction in the number of species could pose to future generations have been discussed by numerous authors (Brown, 198 1; Ehrlich and Ehrlich,l98l; Ramade,l98l;Ehrlich,l984; Wilson,l985,1989;Clark and Munn,l986;Soule,l986;Wolf,l987;Ojeda and Mares,l989; Reid and Mi1ler,l989;Mc Neely et al., 1990; Myers,l990;Groombrodge, l992;Barbault,1994). These challenges are at the centre of the line of research currently being pursued in the context of the international collaborative research programme IUBS-SCOPE-UNESCO-MAB ‘Diversitas’(Solbrig,1991b) and are one of the key issues of the UNESCO~MAB programme. There are many reasons why humans should be concerned with biodiversity conservation. Organisms provide a wealth of resources and ecological services that benefit humans. Biotic resources include food, building, materials, firewood and medicines. Many organisms bring significant pleasure and humans also have a moral and ethical responsibility to care for the environment and the variety of life it supports (Osborne, 2000). A most disturbing observation in recent decades is the acceleration of species extinction due to impairment of natural habitats and pollution (Soule, 1986; Wilson and Peter, 1988; Ulfstrand, 1992). The ever increasing demand for resources in terms of land area 58 (agriculture, urbanization, industry, leisure), materials (food, construction materials) and energy from an ever-increasing human population and the attendant array of harmful effects(pollution,degradation,fragmentation and disappearance of habitats)constitute the greatest threats to the integrity of ecosystems and, consequently to biodiversity (Lachavanne and juge, l997).Database from the well-known vertebrate groups, plants and extent of habitat destruction showed that over the next 25 years more than one million species will become extinct(Wilson,l988;El1rlich and Wilson,l991;Soule,l99l). On this basis IUCN/UNEP/WWF (1991) reminded that the threat of extinction to human population had become worsen and for the sustenance of human beings conservation of nature and biodiversity is mandatory. In the case of fluvial ecosystems, one of the most important factors responsible for the sharp decline in biodiversity has been chamelization combined with wetland degradation. This is due to the reduction of water retention in the catchment, reduction of flow variation and loss of habitats resulting in increased abiotic stress (Ward and Stanford, I989). The Western Ghats, one of the 21-biodiversity hotspots of India, is unique for its high rate of endemism (Gadgil, 1996; Pascal, 1996). The Kerala region of Western Ghats is encompassing an area of 20,000sq. km from where 41 west flowing and 3 east flowing rivers are originated, many of them drain mainly through forested catchments and empty into Arabian Sea and Bay of Bengal respectively. These rivers support a rich and diverse fish fauna comprising of l70species, which represent many rare and endemic species (Kurup, 2002). Data base on fish biodiversity is very essential as a decision making tool for conservation and management of fish germplasm, declaration of part of rivers as 59 aquatic sanctuaries, protection and preservation of endangered species and mitigation of anthropogenic activities, etc., so as to fulfill the obligation on the part of India under convention on biological diversity. Fish gennplasm inventory of the rivers of Kerala is still partial and are being continued. Among them, the notable studies are those of Day (1865, 1878, 1889), Pillay (1929), John (1936), Hora and Law (1941), Menon (1952), Silas (l95la,l95lb), Jayram ( 1981,1999), Remadevi and Indira (1986), Petiyagoda and Kottelat(l994), Easa and Shaji (l996),Zacharias et al.(l996), Menon and Jacob(l996), Arun(1997), Manimekhalan and Das(l998), Ajtithkumar et al.(l999) and Kurup(l992, 2002). However, hitherto no attempt was made to bring out the extent of diversity and influence of altitude on fish diversity in the streams and rivers of Western Ghats.Against this background, an attempt was made in this direction on the basis of four diversity indices such as Shanon-Weiner diversity index (Shanon and Weiner l949),Simpson index,MargaleF s index and Pieolu,s index calculated from different altitudes of six major river systems viz;Kabbini,Bharathapuzha, Chalakudy, Periyar,Pamba and Kallada in Kerala, which form 34% of the total riverine area of the state. 4.2. Materials and methods Materials and method used for in the study are illustrated in chapter 2. 4.3. Results While comparing the fish biodiversity at different altitude ranges (given as MSL) in 6 major river systems of Kerala it was observed that species diversity showed an inverse relationship with altitude (Table 4.1-4.6). In Bharathapuzha river system, between altitudes of 0-l200m, the Shanon- Weiner diversity index (H’) varied from 0.67-1.59 (Table 4.1) and the highest average of 1.59 was observed at 0-200m height while the 60 same showed a reduction (0.67) from 1000-l200m. Locationwise study (Table 4.7) showed highest diversity of 2.373 at Kanakkanoor having an elevation of 39.4m from the mean sea level while diversity was nil at Velampattapuzha and Tippilikayam situated at an altitude of 212m and 477m respectively. Simpson diversity index (D’) was calculated for all the stations which fluctuated between 0.4-0.74(Tab1e 4.1) .The maximum value (0.74) was recorded between 600-800m followed by 0-200m(0.73) while the lowest diversity of 0.4 was registered at 1000-l200m range. Location wise analysis (Table 4.7) showed highest value (0.9) for Simpson index at Kanakkanoor and lowest ‘0’ diversity at meenvallam I (ele.589m),Ve1ampattapuzha(e1e.212m) and Thippi1ikayam(477m).The species richness (d) was highest in the 0-200m stretch(l.76) while the lowest richness of 0.58 was recorded in the river stretch located between 800-1000m range(T able 4.1). Highest location wise richness registered at Kanakkanoor (4) followed by Pambadi east (3.11). While 0 richness was registered at Meenvallaml, Velampattapuzha and Thippilikayam(Tab1e 4.7).Pielou’s eveness measured ranged between 0.45-0.86(Tab1e 3.1).The highest value was registered between 600-800m while the l0west(0.45) between 400-600m. Highest location wise evenness of 0.96 was observed at Atla(ele.607m) while it was 0 at Meenvallam I,Velampattapuzha and Thippilikayam(T able 4.7). ln Periyar river system, an inverse relationship was observed between fish diversity and altitude. However, at the upstream reaches between 1000-1200m, the fish diversity showed an unusually increasing trend. Between altitudes 0-l600m the Shanon-Weiner diversity index (H’) varied from 0.3-l.87(T able 4.2) with the highest average diversity index of 1.87 between 0—200m followed by 1000-l200m(l.77) and 400-600m heights (1.68). The fish diversity was very low in between 1400-l600m range. Location wise 61 diversity was highest at Bhoothathankettu (2.03) having an elevation of 20m from the mean sea level. While fish diversity was 0 at Kunthrapuzha (ele.l540m), the highest altitude surveyed in this river system (Table 4.8). Simpson (D’) diversity index also showed an inverse relationship between fish diversity and altitude. The maximum diversity of 0.82 was registered at 0-200m range while it was lowest (0.24) at 1400 l600m stretch of this river system(Table 4.2).Location wise diversity(D’)was maximum at Anald 200m range and the lowest at 1400-l600m range(Table 4.2). Location wise species richness was maximum at Bhoothathankettu (2.41) and lowest at Kuntrapuzh(0)(Table 4.8).Species evenness which expressed in terms of Pieolu’s index was ranged between 0.43-0.83 . Maximum evenness or equal abundance (0.83) of all the species present were registered at 400-600m stretch while it declined to 0.43 at 1400-l600m stretch (Table 4.2). Location wise evenness was highest (0.93) at Anakkallankayam and lowest (0) at Kuntrapuzha(Table 4.8). The Chalakudy river system, with an altitude range of 0—l000m, the Shanon-weiner diversity index (H’) ranged between 1.59-2.43(Table 4.3). Highest average diversity of 2.43 was found at 200-400m height followed by 0-200m (2.13), in contrast, it was comparatively low at 600-800m (1.59). Location wise diversity was maximum at Orukomban I (2.58) and lowest at Thekkadiyar II (1.4) (Table 4.9). Diversity measure on the basis of Simpson index also revealed more or less similar trend as shown by Shanon Weiner diversity index. The Simpson diversity index (D’) was ranged between 0.81 62 0.88(Table 4.3) and the maximum diversity (0.88) was observed in the river stretch located between 200-400m and lowest (0.81) at 800-l000m stretches. Location wise diversity (D’) was at the peak (0.88) at Omkomban I ,Karappara and Vazhachal and lowest at Thekkadiyar (0.72)(Table 4.9). Species richness was between 1.27-3.00(Table 4.3) and the maximum (3.00) was registered at locations between 0-200m and the lowest at 600-800m.range.Locationwise observation revealed that the highest richness (3.4) was registered at Vettilappara and Athirappally I having an elevation of 40m and 87m respectively from the mean sea level. On the contrary, the lowest richness (1.24) was registered at Malakkapara having an elevation of 743m from the mean sea level (Table 4.9). Species evenness ranged between 0.8-0.91 and was highest (0.91) at 600-800m stretch and lowest (0.8) at river stretch located between 200-400m.Locationwise species evenness was highest at Malakkapara(0.91) while it was lowest at Thekkadiyar and Sholayar(0.7)(Table 4.9) . The Kallada river system, which is located between an altitude of 0-800m, the Shanon Weiner diversity ranged from 1.01-l.l6(Table 4.4).Fish diversity was highest between 200-400 m (1.16) while the diversity showed almost similar trend in the height of 0-200m and 400-600m ranges (l.l3&l.l2respectively). In the upstream regions, a decreasing trend in fish diversity was quite discernible. At 600-800m height, the diversity index declined to 1.01. Location wise diversity (H’) was highest (1.89) at Meemnuty having an elevation of 89m from the mean sea level while the lowest diversity (0.33) was recorded at MSL (ele.l94m) (Table 4.10). On the contrary, Simpson index (D’) was highest (0.7) at 600~800m stretch and lowest (0.54) at 0-200m stretches. (Table 4.4). Location wise diversity (D’) was highest (0.83) at Meenmutty and lowest (0.15) at MSL (Table 4.10). 63 Species richness which indicated on the basis of Margalef’s index was in the range 0.68 1.45(Table 4.4). Maximum species richness (1.45) was recorded at 400-600m while lowest richness (0.68) was recorded from 600-800m. Location wise species richness was highest (1.77) at Meenmutty while the lowest richness (0.42) was registered at MSL (Table 4.10). Species evenness ranged between 0.66-0.92(Tab1e 4.4) with a peak in between 600-800m and lowest at 0-200m. Location wise study revealed that the evenness of species was maximum (0.92) at Chenturuny(ele.641m) and Dali (ele.ll5.5m) and lowest (0.3) at MSL(Table 4.10) In Kabbini river system, the surveyed locations falls in the range 600-l000m height and the fish diversity (H’) varied from 1.42-1.63(Tab1e 4.5). Highest average diversity of 1.63 was observed at 600-800m height. Further increase of altitude brought about a reduction in the diversity. At 800-l000m altitude, the diversity reduced to l.42.Locationwise diversity analysis revealed that maximum value for Shanon-Weiner diversity index (2.47) was registered at Begur I having an elevation of 783m from the mean sea level while the diversity was 0 at Thariyod (ele.796.5m)(Tab1e 4.11).Species diversity measured based on Simpson index revealed that there is not much variation in diversity in the two altitude ranges and the highest value (0.71) was recorded at 800-l000m stretch and the lowest (0.69) at 600-800m stretch(Table 4.5). Location wise diversity (D’) was maximum (0.86) at N0olpuzha(e1e.946m) and Ponkuzhy(e1e.914.8m) while diversity was nil at Thariyod (Table 4.11). Species richness showed not much variation in both the stretches and was 1.88-1.89 (Table 4.5) between an altitude range of 600-l000m.Locationwise, highest richness of 3.1 was registered at Kuruvadeep(ele.769m). While no species richness was observed at Tha1iyod(Table 4.11) Species evenness ranged between 0.71 to 0.78(Table 64 4.5) and the highest evenness was observed in 800-1000m of the river system. Location wise, highest evenness of 0.89 was registered at Ponkuzhy while no evenness was registered at Thariyod (Table 3.11). In Pamba river system, the Shanon-Weiner diversity index varied from 1.08 to l.85(Table 4.6) in between an altitude of 0-1000m and the highest diversity of 1.85 was recorded in between 400—600m altitude ranges. While the lowest diversity of 1.08 was recorded in the river stretch located in between 600-800m altitudes. Locationwise, highest diversity (I-1’) of 1.99 was recorded at Kakkad Ar I1 having an elevation of 300.3m from the mean sea level and the lowest diversity of 0.91 was registered at Kaldd I (Table 4.12). Diversity analysed based on Simpson index was highest at 200-400m (0.82) while it was lowest (0.78) at 400-600m (Table 4.6). Location wise, maximum diversity of 0.92 was registered at Kakki I having an elevation of 824m from the mean sea level while the lowest diversity of 0.65 was registered at Angamoozhi having an elevation of 133m from the mean sea level (Table 4.12). Fish species richness ranged between 1.11 l.74(Table 4.6) in the altitude range of 0-l000m and the maximum richness was registered in between 0-200m while it was lowest (1.11) in the 600-800m of the river system. Location wise analysis revealed that highest riclmess (2.47) was registered at Nilakkalthodu while it was lowest (1.09) at Azhutha(Table 4.12). Equality of species abundance measured based on Pielou’s evenness index varied between 0.74-0.9l(Table 3.6) with highest evenness in 400-600m and the lowest in 800-1000m. While comparing different locations, highest evenness of 0.91 was registered from Kakkad Ar I (ele.257m), Moozhiyar 1 (ele.413.9m) and Attathodu (ele.145.8m)while it was only 0.64 at Kakki I(Table 4.12). 65 Table 4.13 and 4.14 show the result of analysis of variance of Shanon-Weiner diversity index and Simpson diversity index at different altitudes in six river systems of Kerala. The results showed that there is significant difference in fish diversity at the same altitude in the different river systems studied. Difference was also significant in fish diversity between different altitudes of the same river system (P<0.0l). Table 4.15 shows the result of analysis of variance of species richness at different altitudes in six river systems of Kerala. There is significant difference in fish species richness at the same altitude in the different river systems studied, and also significant difference in species richness was also observed between different altitudes of the same river system (P<0.05). Table 4.16 shows the result of analysis of variance of species evenness at different altitudes in six river systems of Kerala. There is significant difference in fish species evenness at the same altitude in the different river systems studied, and also significant difference in species 6V6l‘lI‘l6SS was observed between different altitudes of the same river system (P<0.0l). Fig.4.l-4.4 depicts the fish diversity based on four diversity indices at different altitude ranges in six major river systems of Kerala. 4.4. Discussion The results of the present study revealed that altitude has a very significant influence in the qualitative and quantitative fish diversity in six major river systems of Kerala. The fish diversity studied on the basis of Shanon-weiner (H’) and Simpson (D’) indices revealed that even though some minor variations occur with the suitability and complexity of habitats, the altitude showed an inverse relationship with fish diversity. 66 finding is in compliance with that of Dukes er al. (2000) who compared the E diversity in the second, third and fourth order streams of Cullowhee creek in United states on the basis of Shanon-Weiner and Simpson diversity indices and reported that the fish divasity increasesd with the increase of stream order. Lachavanne and juge (1997) reported that the decline in abiotic stress and increase in habitat heterogeneity towards downstream is mainly due to the increasing space in land-water ecotones by transmission of the riparian zone into floodplain and also added that the tendency for fish diversity to ‘nexus: downstream in natural river ecosystems is not only the result of the reduction in harshness but also due to the increase in riverine habitat complexity by riparian/floodplain interactions. Schiemer and Zalewski (1992) reported that habitat complexity creates conditions for the coexistence of a large number of fish species and their life stages, reduce competitive interactions, pressure of predators , catastrophic disturbances and provide feeding and spawning /rearing grounds. Though altitude showed an inverse relationship with fish diversity, conversely, the upstream reaches of Chalakudy and periyar river systems are an exception to the trend. The unusually high biodiversity observed in the high altitudes of these rivers can be attributed to the presence of moderate populations of hill stream species (Fig.1). This situation was very well glaring at 1000-l200m stretch of Periyar river system. The dominance of some of the critically endangered endemic species such as Lepidopygopsis typus,G0nopr0kt0pterus micropogon periyarensis and Crossocheilus periyarensis which were characterized by high degree of habitat selectivity and assemblage with the microhabitats prevailing in these areas have already been reported(Manojl-cumar and Ku1up,2002). Habitat suitability index models of the above three species revealed that 67 abundance of L. typus showed a positive correlation with the amount of bedrock substrate, chute type microhabitat, overhanging boulders, overhanging vegetation, total shade and stream cover (Manojkumar and Kurup, 2002). Optimum habitat of G.micr0p0g0n periyarensis has been reported as midchannel pools with comparatively good depth, overhanging vegetation, slope and excellent shade while that of C. periyarensis are lateral pools and scour out pools with enough woody debris, overhanging vegetation and tree cover (Manojkumar and Kurup, 2002). In Chalakudy river system the 800-l000m stretch was blessed with moderate population of hill stream fishes such as T or khudree, Barilius gatensis, Barilus bakeri,Dani0 malabaricus, Garra mullya, Hypselobarbus kolus and Garra surendranathanii which can survive well in the alternating cascade and pool-riffle channel reaches prevailing in these areas of the river system. Diversity measures based on species richness (d) showed that maximum richness was observed at 0-600m altitude in all the river systems studied. This may be due to the presence of more species in these altitude ranges when compared to the high ranges, a finding which corroborated with that of Boyce and McDonald(l999)who reported that the highest value of Margalel‘ s index denotes highest alpha diversity and is actually correlated with total number of species(S)alone. The species richness towards downstream is due to the increasing habitat heterogeneity and complexity towards downstream which supports the view of Horowitz(l97 8) who described that the fish diversity in rivers increases in the downstream reaches due to the declining abiotic stress and increasing habitat heterogeneity. The results of species evenness indicate that the species equitability is more in the 400 800m stretch of all the river systems. This is due to the habitat homogeneity observed in 68 the high ranges and high rates of habitat degradation in the lower stretches. The upstream torrential reaches of many of the river systems are highly homogenous and supports only those species, which can survive only in these peculiar habitats. The present observation also corroborates with the findings of Dukes et a1 (2000) who reported that at the second order sites of Collowhee creek in United states, where the habitat is of riffle type the number of species is comparatively less when compared to the run habitats prevailing in the fourth order streams. On the contrary, the downstream reaches of all the river systems were posed to high degree of habitat destruction in the form of pollution, agricultural activities and illegal fishing activities. The low fish species evenness in the 0-600m stretch of Bharathapuzha river system when compared to 600-l200m stretch and 0-400m stretch of Kallada river system with that of 400-800m ranges are clear manifestation of the high degree of habitat alteration brought about in the downstream regions of this river which led to the selective proliferation of some species. Gatz and Harig (1994) and Dyer er al.(l998) reported that antropogenic changes in physical habitat parameters of streams leads to more homogeneous stream conditions and consequently to the depletion of fish communities. While comparing the altitude wise overall fish diversity in each river system studied, Chalakudy river showed the highest value of Shanon diversity index 2 (D’=0.83) followed by Pamba l.5(D’0.8), Kabbini l.5(D’=0.7), Periyar l.4(D’=0.67),Kallada l.2(D’=0.62) and Bharathapuzha 0.9(D’=0.57) (Fig.2). The optimal physical habitat conditions and less human intervention on the riverine habitats might be the major contributing factors supporting the high fish diversity at Chalakudy river system. On the other hand, Bharathapuzha and Kallada were prone to severe anthropogenic activities like 69 construction of dams, commissioning of hydroelectric projects, conversion of catchments into cultivable lands, sand mining, pollution, etc. which might have brought about serious alterations in the habitats and consequently the decline of fish biodiversity. Lachavanne and Juge (1997) reported that due to the construction of dam eutrophication rate will increase which intum results in the fluctuation of many biotic and abiotic characteristics above the tolerance level of many fish species which may leads to the decline of fish diversity in the system. Talmage er al. (2002) reported that agricultural activities in the catchment areas of Red river basin and Minnesota river basin in United States adversely affected the hydrologic regime, channel morphology, riparian zones and water chemistry of the river systems. In Kabbini river system majority of the locations surveyed were coming under protected areas and characterized by very good fish diversity. While locations outside the protected areas are suffering severe habitat destruction activities, which led to low fish diversity in these zones (Table 3.1 1). Andren and Angelstam (1988) reported that landscape degradation and reduction of the spatio-temporal heterogeneity of the streams have a direct and far-reaching influence on gene pools, population and communities as well as an indirect influence on biotic relations. 4.4.1. Longitudinal zonation and distribution of fishes in Western Ghat streams Fish assemblage in rivers and streams worldwide show longitudinal zonation (I-Iynes, 1970; Hawkes, 1975; Fisher, 1983) and the relationship between assemblage composition and physicochemical variability continues to be actively studied (Matthews, l986;Hughes and Gammon,l987;Meffe and Sheldon,l988).The results of the present study conducted at six major river systems of Kerala also revealed the longitudinal zonation in the fish assemblage from the mountain peaks in Western ghats to lowland plains. Although zonal 70 boundaries cannot be simply demarcated by the icthyofauna, however, the presence of certain fishes may be very typical of some of the regions in these Westem Ghat streams. Based on the species assemblage structure the stream reaches of these six major river systems of Kerala were classified into following zones following Edds (1993). 1. Mountain zone (<1200m) In the mountain zone of Western Ghat streams, the diversity is comparatively less and there is the dominance of some loaches belonging to the genus Nemacheilus among the fish fauna. Members of the genus Garra and Homoleptera are also showing their presence in this zone. Eventhough some cyprinids like Barilius bakeri, Danio spp. etc. are present in some regions, however their occurrence is very sparse and sporadic. This part of the riverine habitat is mainly of step-pool and cascade type. The fishes occupying these areas possess some peculiar anatomical and behavioral adaptations for their inhabitation in the torrential streams such as vibrant colouration, sucker like disc for clinging to the substrate, etc. 2. High hill zone (600-l200m) This zone of the riverine habitat was mainly dominated by bedrock and pool-riffle microhabitats. Dania malabaricus, Barilius gatensis, Barilius bakeri, Tor khudree suckers like Garra mullya,Bhavam'a auz'stralis,Glyptoth0rax sp_p., T ravancoria spp. etc. were found very common at these reaches. Many of the endemic fish species of Westem Ghats such as Lepidopygopsislypus, Gonoproktopterus. th0masi,G0n0pr0k10ptems micropogon periyarensis, Crossocheilus periyarensis ,Oste0cheilus longidorsalis, Neolissocheilus wynadensis, Silurus wynadensis etc. showed their presence at this zone in various rivers studied. 71 3. Low hill zone (50-600m) The low hills zone was dominated by several geneus of the family Cyprinidae, especially Puntius. Regular occurrence of species such as Garra spp.,Bhavam'a ausrralis and Glptothorax spp. were also observed from this reach. The riverine habitat was mainly of pool-riffle, braided and plane-bed type. Carnivorous species like Clarias, Heteropnuestes and noctumal species like Anguilla showed their occurrence in this zone 4. Low lands zone (0-50m) The riverine habitat was mainly of regime or plane bed type. Occurrence of pool-riffle microhabitat was sparse and sporadic. Species like Puntius sarana subnasutus,C/zanna striatus,Channa marulz'us,Prist0lepis marginata,Clarz'us dussumieri,Parambassis thomassi, Wallago atu, Mastocembelus armatus, Aplocheilus spp. etc.were found very common in this zone.Flow velocity was comparatively negligible in most of the areas of this zone. Fish assemblage in the mountains zones of Westem Ghat streams bears some resemblance to that of other mountain fish communities. In the Mountain zones of Himalayan Gandaki river, comparable ecological equivalents can be f01ll1d, including Noemacheilus, drift feeding cyprinids (Barilius) and snow trout Schizothorax (Cyprinidae) (Edds,l993) (Lepidophygopsis typus is one of the Schizothoracinae member abundant in the upstreams of Periyar river).In North America, this zone is generally inhabited by trout(Salmonidae), Sculpians(Cottidae), Suckers(Catostomidae), and dace(Cyprinidae) (Moyle and Herbold,l987;Rahel and I-lubert,l99l).While in the northem European streams the mountain zone is mainly occupied by trout, Sculpins, Loaches(Balitoriade, mainly Noemacheilus), and Minnows(Cyprinidae) . 72 According to Groosman er al. (1990) in order to discem long tenn structure of fish species assemblage and variability in stream fish populations, a short term study is insufficient. However, this scheme of work was ecologically meaningful and that it may be of use to plarmers and administrators of Western Ghat fish conservation policies and river management. The present study revealed that physical parameters such as instream cover, substrates, distribution of microhabitats, nature of riparian zone and flow velocity have vital role in determining fish species assemblage structure in six major river systems in Kerala part of Westernghats. Edds (1993) reported that geography, waterquality and stream hydraulics such as substrate type; stream depth and current speed were the major physicochemical parameters goveming the fish assemblage structure in Gandaki river. Seasonal changes have substantial, but secondary effects while abundance and composition of vegetation were also found significant in supporting biodiversity. The results of the present study indicate that combination of physical variables such as the percentage occurrence of different types of microhabitats, nature and quantity of various instream cover and riparian zone along with components of ‘stream hydraulics’ (Statzner and Higler, 1986), were the major abiotic factors characterizing longitudinal zonation of fish assemblage structure in the six major river systems of Kerala. According to Sousa (1984) and Schlosser (1987), both physico—chemical and biological interactions were involved in determining assemblage organization in streams. Edds (1993) reported that biotic interactions may increase in importance as abiotic conditions become more benign downstream. The present study also revealed that there exist very high correlation between physical parameters such as substrates, instream cover, nature of microhabitats in different stream reaches, type of riparian zone and flow velocity with fish species 73 assemblage structure in six major river systems of Kerala. However, the actual mechanisms determining community organization remain to be investigated. 74 AltitudeTable 4 1 Fish rangglml diversity at d differentaltitude j‘ W d ranges §h(lodg_e) in Bharatliapuzhaiiver <1lambada system 0-200 _ ” 1.76 " 0.131 " 1.59 1.101 10.58 _. 0-33 1.4 0.451 if 7 1.1, 6 i _ _._1.08 1.86 11341 1000-1000 0.58 1.83 0.191“ _ 0 53 0.6 A ' 0.5L 0* 0 0.51 Table 4 2 Fish diversity at diffeient altitude ranges in Peiiyar riyer systeni mhllodgjj i Altitude rangelim1 91 d 0.041 1 .87“ 200-400 1 .470 A 0.11 1.511 0.871 1.68 Pi 400500 _ 1 1.411 _g _ 0‘ I 1.341 000 000 g 1.25 0-097 L 000-1000 E 0.99 0.69 1.11‘ 10001200 1 M 1.521 0.19. 1.11 1200 1400 1.21 0.14 1.271 1400-1600 0.26 _ 0.4? 0-34 Table 4 3 Fish diversity at different altitude ranges in Chalakkudy tiver systvem _ Altitude rangejij I d JD l‘l|°d92l . 1 lambada _ 31 0.83 2.13. 2.8 0.81 2.43 400-600 7 2.03 0.09 .2. 000-000 F 1.27 0.91. 1.59 1.97 0.827 1.84 AltitudeTable 4 4 Fish diversityran e at differentm d "altitude lg rangesg hglod in Kallada e griver : 1system Iambada g . 3 0 2 1 70.02 6 A-9 6 1 1" 0.05 0.19 1,10 400-600 E 1 .45 it 0.1 1.12 0.50 0.92 1.01 Table 4 5 Fish CIIVGFSEY at different altitude ranges in Kabbini river qstem Altitude600-800 rang_eLm) 7 d g " 1 _ h lodge) g 800 1000 1.88 1.89f 0.78 A 0.71g H A H W 1.42% 1.693 Table 4 6 Fish diversity at differentaltitude ifan es in Pamba river s stem? - Q . . Y __ . I Altitude ran e m)_1d W . 1-in 0 200 f 1.14 0.84 1.71 1.611 0.86‘ 1.10 1I . _ 400-600 7 1.33 0.91 1.85 1.111 0.15 1.001! 1.25 0.74“ ‘ 1.2 is Table 4.7 Location wise fish diversity at different altitude ranges in _, _4 4_ 0, 4, _, _,, _ _ 5h§'§fl“!4B9¥hiL'TiY@F,5X§t€"J,W4, 0,,__,_,_4,_4,0,,0,_ ,0 ,0 , ; 7 7 , , , ,,17!\liiwsi07(ml 74107, , , ,4 1,11‘ ,4 , ,4 , ,1h1l00da 4, Che4ru14l1u_,{11tb4y,44,,, ,4,,4, 4 ,4,1",4418_4,1, 4 ,20241,4,444 4 ,0,90,1 4, ,41J21. ,41. ,0_v741 1?gngkkagoog 44 44 4441447 j;,I,j,4,4004 44 4 440488 4394314,f 41 4 434j 17 . ‘7 .70 1,. 1 991 7. 14,110,4f,T 51k}.-1da7vu7 , 4 j,j,f,4i419,-1,14,,4,4,4,44 4 7 15s‘44444444494.8414f4444 J4,444 .81 , ,44 , 4,0-,0 44 071 1011901910011, , , , ,1, , , 40,911 , 2,10‘ 44 4 4 40.80 4 42.02 0.814 V |!l4egrflr4a7li§m4l 4 4 j 14 4 4 4 41550.01" "7 97*7* 77oTo0‘ * "71 7,74 7, 4 7 407-9(7l74,4,4 4 7, 4 ,4 49-00 '1011e1~a1<~z1=144,,,,2 4 T 4 42.31T f J 44I 4 4 40.14414 4 4 40.4804 44 4 4 4 414.§§ , , , 0177414 *Cfie<74=§raj1u;7hi 4, , , 1 ,1; @149-911,49 ‘ 91ise1,‘,‘,*,4‘0,821i 4 9 41,-9§"i, ,‘,0§z41 995929019091, _ , , _ , _ ,5?-,91, ,, ,, ,, §_-117 4744747, , , '4404871 ,4,7 7 ,2 '7 09 ,44 4‘,4 44 04' J,87 M939£E*<§9_ , _ , _, _ 4, _ , , , , 4444,4 40§0 -‘ 444 ZQ2, 4 9-4, 4 4‘ 481 2. 1 1 MuqaQBall4ur4 44 44 444 4 1 , ,4,7 557,21, ,7 ,7 ,7<>,7‘/15,7 47,7 ,7 Q-8,51, 7,7 , 1-101, , , ,0-06 7‘7Ysk7k7ara 77 7 7 777 777772879‘1”444444444.44144444 7 7" 77000‘ ' ‘ fg*8g1‘4 4 74.4 "44 47407 .483 7 1777 7- L777’ 77777777 4 7581 . 1 1“Chunode 7* 7- * ‘*7 7 4 , ,4 51-571, , 7, 2927 1 , ,0,91,1,4 , ,1,-9% , , , 0-8% 1,K§lp,1hI 34,, 7,4,4 , ,4 ,7,,,4,,,,,4 '47 7,7 ,7 ,7 39,17 ,7 ,7 7 1747-55717 j f i 0.801, J 5 1.51, ,7,7,,70-711 1P9zhumk9r94i, ,4,Z§-5‘ 4 444,47,7 7 4477,447,717 17,7 47,77,!-‘>784 1,4 44 4 7,7,714-5,0417 74 744 4072641 1, 0800r9p491'a , , ,4,441 1041 ,4,4,4, 1.81 0.701 1.41 7 7 7 0.6871 1 40404040 1? :4 44040440414444 0040,0401. 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ihll 77 77_7 17777777 756? 0.69 1.24 0.57 '1 7 797 77 7 7 7 77 7777777777777 %/iranagri _ 7 7 Q79? 7 7 7 1-49T 770-077777 _717-0Q7_777777_0-§61_ 714411114411 1‘ 7 ;7 1 ‘ 7 914-8 0 7 0 _2f22 o.a9*_7 77 71795747 7 7 _70.§61_, P"Wj0ol7 7 R 7 uZT1a77 7 7 777 7! 94617 777777777 210077 77 0-07,7 77 77 0-70717 77 77 7707-067 *7M9*Da'k1a777 7 7 7 7 7 7 7 77 77959-27777 77 17-78317 77777977§1777777777175l!7 777777770161 7T=!2'e74-1? kocétiev wi§7<=-'7 078" 7-1&7 7 196? 07-701 1Pg=:runthgna7ruvi\ 1 _ _ _F_ 7 7 4s.1_[ _ 7 7 1.71777 _ _7 0736} _ 7 _1.qo[ 7 77 70.8731 AZut5a77 77 7 777717“ 7 777847817 7 7 71170917 7 77 70i87“7 71-4791 77 7 0-757“ 1T7\nJ9§mQb1hi77_77777777¥7 77 7 777 771733_§77 77 77 717175177777 77015’ 77 7777 71l4727*‘777_777_7 70-637 ‘_fljla§Ea_Lthgdu__ 7777 7 7 7717 777 7345917 77 777 77 37-41/1'77 77 Q1891} 77 71-921L7 7 7 °-84; ”7Afla§h05Iu7 7 7 7 7 7 7 145-§17 777 71-54,7 7 779-917 7 77 71-7437777 777 70-3*57 7Kékka&AFI 7 7 7_ _ 7 _ 7777 77 _ 7'7 7772§57j 7 77 1.3;; *70Y§>17f*_ 1 *1.i31'*7*_“_ Q82). Kakl-pad Arjl _ _ _ _ “r 77 77 774Q@-=47 77279277 77 77 7707411777 7 71-4277 77 77 0-451 Pz17mf:a_g777 _7 7 _7 7_ 7 7 7 7 7 3733-#7 7 7 71-44L 777 0-8Qh7 7 71-75% 7 7 79-737 M01444»/4=r| ‘ 7 471417741 70 7 0 7' 0‘13aT' 7J7 7 7 07477777 00091100‘ 7777 01851‘ 7'7 77 0 77 0 678*:7 7.‘ 7M°°\ Izfiig-4rII' 7 77 ‘ 7‘ 177 7 76127 7\ 7 17171740151 .p8‘7 _ _ _0.§4’ i7<0l$KI! 7 7 7 77 777 7827417777777 1.1 1 0.640 7 77110791711 ‘ 7 0.435 '_K_aki i_l J J 17 l‘L;" % 'fi' A é '7 7777‘ 4|‘ Table 4.13.Analysis of variance of Shannon-weiner diversity index at different altitude J_9 So9un:e9 9 99 99 ofrangs \(an'a{i0n in six 99‘m9a9jor9river9§y_s9tems 99 SS 9 qf MS 99‘ F 9 919 of KeralaP-value 99 999 9999 F cn'9t99 9 9 9 ll9 Rows 1 1“ 1192226912599 1 1 11’ _1.99999449e11_§.9750969;f 9.209525-05} 9.199949 TColumr9is ii 9T95.9995919592fl1 9 9115191.177?2534]Q4.9499499910.o09497253"199.591919 %E"<>' - Y 9-4784658°7.1 Q 354°-270313317 if § 1 ll ‘9T0ta9l9_1 9 .. 99_ 1 f9 .. 1'9 _.. 1299.59997101_1“9 . _ _ ‘L. 19 47,919 . _. 19 9 .159,19 _ 9 J+1 1 i Table 4.14.Analysis of variance of Simpson index at different altitude 9 9 9 9 ranges insixmajgr river systems 99f Kerala 9 99 9 9999 9 [9Source9<9>fVariati0ni9 1938 19 99 19F 9 ‘P-value 99 criti -LRows99” 9 9 1 a.0991994557F9_ 97.1o.4394553919.71o0995?1_9 5.4919995-09‘ 9.19994‘ 1Cpl umns 19 11 . I9 192059007999 . T _ _ 1_ 1 159199241150169-_\ .‘ 4,21 39237029" .._ 1; oo01195222211135919911 f.._ .. 5. ~.‘_ ‘9Erro|f 9 1.1499199 95 9* 00499949291? 9 9 -*1 i 1 ;' 9 ‘ _ _ #99 ,_ *~9_ _> i 9 i 9 i ,__' f 99 _f1 i 9 *59 . -1 * , * __. .To9t9al919 . 91—i‘ 99.0249914249 1 é I 43 _1 9 99 9 999 9 9 99! L Table 4.15.Analysis of variance of Species richness at different altitude ranges 9 99 jn si9x majgr river syiterrls of l9(era9la 99 9 9 9 1 Sour9oe0fVa9riatio}19fl ss1 1 at )9 MS99 9| 9F 99 T?-value I 1F¢n'r91' Bows 199 99 19 14.21204919f 11 1 791‘12.09o2921491‘5.4774957‘. 0.o00291016599i 3.1999491 4Qolumns91 1 1 1 9 11 95.799935991922291 T 1* 1* 1 91 5911.158:l1824139.1269O831 1 ‘ 1 1 111 1 1 09019506814 11 1 1* 93.591919 * ‘” 9E_rror99 191 19 1 ]912.9"/9149199'> 9 119 95199 0.3"/0991999 91 19 11 11 91 9_.To9tal9 99 99 9 f92.97997995Z" 99 41%. 9 99 9_j999 99 99 9 199 J Table 4.16./knalysis of variance of Species evenness at different altitude ranges _ 9 9 9 in six major river systems of Kerala Ll Spurce of Variation M 988 1 df 1 .1“ MS? I W E 1P-value i Fcni‘ . 155»-199 U 9* 3.64199442ji *9 99710.5202t}4921’ 8996496737. 92.71916iE-067 31.117999?” HColumns 11 11 1 11424574512‘ 1 1510294914921"419109173§ 1 10.010165521959191“ flEnor9 .9 29031330353799 9 9 9§35l'_O.O§8O37249! _ L‘ -1’ ,1Total17 9 9- 99 7.09191/2599? , __9 - IT 4'/R ,91 ,9 -9 9_9 J_9 .. ,_9\99 _€$ 99+ T Fig.4.1.Fish diversity based on Shanon-Weiner diversity index at, different a~itude ranges in six .!"ajor river systems of Kerala , .,= 1.5 I t• 1' ~, I a ""'-- Kabinni I ~ -*-Kallada I ~ _ Bharathapuzha ,I I ...... I:-+-Periyar__ .______1 Fig.4.2.Fiah diversity based on Slmpson divery index at d ~ attitude I'IInges In .Ix major river .ystema of K.~'- ! I ---'---,-c-- Fig.4.3.Specles richness at different aMud. ranges r ___-2 ln~.g~ma~~~riv~M~.~ys~bM~m~.~~ K~MO~~~ ___ , d P !¥7~ -+- p~ -I I lo lR c ______- ~ Chapter 5 On the extent 0f degradation of fish habitats in the major river systems of Kerala and management plans for fish germplasm conservation 5.1. Introduction We do not know how many species live on earth. Estimates vary from 5 to 50 millions (Osborne, 2000). Like determining the number of extant species, it is also difficult to determine the number of species going to be extinct each year. According to Groombridge(l992) the rate of erosion of biological diversity far exceeds any reasonable estimates of background extinction rates and identified habitat perturbation as the major reason. Significant areas of natural habitat have been replaced by human dominated systems, and this process of habitat destruction is probably the major cause of biodiversity loss (Osbome, 2000). This process is escalating owing to enhance the living standards and our ever increasing capacity to exploit natural resources. It has been estimated that 90 million kmz, roughly 52%, of largely undisturbed land remains on earth (Hannah et al. 1994). If we exclude inhospitable land (rock, ice, deserts), the proportion of human impacted land rises to 75%(Osbome,2000).National Research Council outlined the five important and widespread human impacts on biodiversity and placed habitat loss and degradation as the prime factors responsible for the biodiversity decline(Hannah et aLl994) Habitat is a principal determinant of biological potential and can be used as a general predictor of biological conditions (Plafkin et. al, 1989) or there are links between the diversity of species (biological diversity or biodiversity) and the way ecosystem functions (Osborne, 2000). Petts (1990) reported that the diversity increases with the heterogeneity of the environmental conditions and with the types of microhabitats. According to Rabeni and Sowa (1996), the physical and chemical characteristics of the stream and landscape features such as stream size, basin area and spatial geometry have high correlation with the variation in fish density. Moreover, there is some experimental evidences that reduction of the complexity of aquatic ecosystem drastically reduces establishment of large specimens (Portt er al., 1986), so that the trophic structure of the fish community is modified(Schliosser,1992)and, even more important, the reproductive potential of the population might be sharply reduced leading to the greater variability and smaller numbers of specimens in a population (Lachavarme and Juge,1997).So assessments of any aquatic system start with an evaluation of habitat quality(Stauffer and Goldstein, 1997). Restoration of stream habitats towards pristine conditions is an utopuian view. In most cases river basins have experienced extensive land-use changes because of human activity. The most dramatic impacts resulted from deforestation, land use, intensification of agricultural and industrial activity, and the modification of river channels to control floods, provide power and improved navigation. Moreover, recently, demands for water resources and electricity have created new impacts. All these changes have been superimposed upon enviromnental changes caused by recent climatic variations. In 1972 United States introduced ‘clean water act’ to restore and maintain the chemical, physical and biological integrity of the nation’s waters (Talmage et al., 2002). In India, there is 18 major river basins. The rapid industrialization during the second half of l900’s leads to severe land reformation, habitat destruction and aquatic pollution (Tiwari, 1988). As a result, the physical, chemical and biological integrity of most of the freshwater ecosystems were lost. The water Act of I974 and Enviromnental Act of 1986 are concentrating mainly on the water quality of the aquatic ecosystems. Even though the Ministry of Environment and Forest introduced many promotional measures and research 76 projects covering studies on impact of development activities on natural ecosystems, sun/ey and monitoring of environmental indications, pollution control, ecoregeneration energy use etc., standards for measuring the instream habitat and physical conditions are still lacking for Indian rivers. On the contrary, according to Sreevastava and Sarkar(l998),the habitat of freshwater strem fishes is more dependant on physical features rather than on chemical features, which indicate that a multiple scale approach ,considering the physical chemical and biological integrity is essential for the conservation and management of natural aquatic ecosystems and thereby the resources. The purpose of the present study was to examine the relationship between instream habitat and physical conditions and fish community composition in six major river systems of Kerala and to isolate the habitat variables which are most important to fish communities. The study also pays attention to find out the extent of ecosystem imbalance by comparing the species diversity, abundance and index of biotic integrity scoring with habitat variables. With knowledge of these relationships, the stream restoration activities may successfully target on those features that are important to the stream fish community, which will helps to achieve the physical, chemical and biological integrity of our river systems. 5.2. Materials and methods Materials and method used for in the study are illustrated in chapter 2. 5.3. Results 5.3.1. Bharathapuzha river system Mean fish community diversity was relatively low (mean=l.3, SD=0.65.). Location wise diversity was highest at Kanakkanoor(2.37 3) and lowest at Meenvallam and 77 Velampattapuzha(0)(Table 5.1). Fish species abundance ranged from 3(Meenvallam I) to l3l(Thodunnampara) and the mean abundance was 39.3(SD=34.6)(table 5.1). Index of Biotic Integrity scores ranged from 0(Velampattapuzha) to 6O(Yakkara) and the mean IBI score was 21 .7(SD=l3.7)(Table 5.1). Instream cover varied among sites. Depth was the dominant instream cover (38.68%) (SD=33.3) followed by overhanging vegetation (18.9%), emergent vegetation (17.5%) and turbulence (12.1%) (Fig.5. 1). Riverbed was dominated by Bedrock (28.6%) followed by gravels (l7.85%) and fines (l6.57%) (Fig.5.7). Among physical conditions sinuosity varied between l-l.63(SD=0.l4) and stream gradient ranged between0.00l-0.25 (SD=0.06). Mean entrenchment ratio and w/d ratios were 1.46(SD=0.9) and16.42 (SD=l9.3) respectively. Midchannel pools (23.3%) were the dominant channel geographical unit followed by run (18.35). glide (12.3%) and landslide (9.6%)(Fig.5.l3). Mean flow velocity was comparatively less with 0.3l(SD=0.35). Vegetation cover was comparatively less on the riparian zone and 29.4% of the riparian zone was without any vegetation. While 26.2% having shrub cover and 44.4% of the riparian zone was covered with trees. The first 10 PCA axes explained 78.3%of the total variance in instream habitat and physical conditions (Table 5.7). The variables with greatest loadings in each axes were w/d ratio, percentage of large woody debris, fines, total instream cover, riffles, floating vegetation, rapids abandoned chamiel, pocket water pools, sheet type channel geographical unit and turbulent white water boulders (Table 5.7). Multiple linear regression analysis of the selected habitat variables which showed maximum loadings in the first 10 PCA axis with Shannon -Weiner diversity index 78 revealed that these parameters together explaining 70.6% of the fish species diversity in Bharathapuzha river system. Except in the case of percentage large woody debris, total instream cover, riffle,floating vegeation and rapids all other habitat variables showed significant positive and linear correlation with the fish diversity in Bharathapuzha river system (Table 5.13). While the selected habitat variables explained only 24.5% of the fish species abundance in Bharathapuzha river system. Among the 10 habitat variables except w/d ratio, percentage sheet, riffle and abandoned channel all other habitat variables showed significant negative correlation with the fish species abundance (Table 5.19) .In the case of index of biotic integrity scoring the selected habitat variables explained only upto 14.8% of the trophic structure. All the critical habitat variables except floating vegetation showed significant positive correlation with the Index of biotic integrity (IBI) scores. While the relationship of floating vegetation with IBI scores was negative (Table 5.25). 5.3.2. Chalakudy river system Mean fish community diversity was 1.96 (SD=0.3 1) which was highest at Orukomban I (2.58) and lowest at Thekkadiyar II(1.4)(Table 5.2).Fish species abundance ranged from 53(Vallakayam) to 206(Orukomban II) and the mean abundance was 98.3(46.1)(Tab1e 4.2).Index of biotic integrity scores ranged from 25(at Malakkapara) to 64(at Kuriarkuutty) with a mean of 44. l(SD=9.5)(Table 5.2). Instream habitat and physical conditions are highly heterogenic in this river system. Depth (38.1%) was the dominant instream cover followed by overhanging vegetation (26.8%), emergent vegetation(8.5%), turbu1ence(7.1%), large woody debris (4.8%), undercut bank (4.3%) and overhanging stream boulders (4.2%) (Fig.5.2).On an average 79 bed rock constituted 47.8% of the river bed followed by fines(l4.9%), b0ulders(l2.9%), rock(l2.6%) and gravels(8.9%)(Fig.5.8). Among physical conditions, sinuosity varied between l-l.5(SD=0.15) and stream gradient varied from 0.001-0.1 (SD=0.03). While the mean entrenchment ratio and w/d ratios were l.23(SD=0.27) and 9.59(SD=9.74) respectively. Channel geographical units were highly heterogenic dominated by midchannel pools (30.5%), riffle (17.9%), 11.111 (16.9%), rapids(l3.7%) and pocket water p0ols(9.9%)(Fig.5.l4).Mean flow velocity was 0.25m/s(SD=0.23).Riparian zone having 87.65% tree cover while 7.6% of the riparian zone was with shrub cover and bare ground occupied only 4.75% of the riparian zone. The first 10 PCA axes explained 74.2% of the total variance in instream habitat and physical conditions (Table 5.20). The variables with the greatest loadings on each axis were flow velocity, mean channel width, percentage shiub cover, tree cover, bare ground along the bank, total instream cover, falls, riffles, midchannel pools and water temperature.(Table 5.8). Multiple linear regression analysis of these selected habitat variables with Shanon-Weiner diversity index explained 90.5% of the fish species diversity in Chalakudy river system (Table 5.14). Except percentage falls and mean channel width, with all other habitat variables, the fish diversity showed a negative correlation while with falls type microhabitat and mean channel width the relationship was positive. The habitat variables explained 67.3% of the fish species abundance in Chalakudy river system and except bare ground, shrub c0ver,tree cover, riffle and total cover , with all other variables the fish species abundance showed a significant positive correlation while with bare ground, shrub cover, tree cover, riffle and total cover the relationship was significantly negative (Table 5.20). In the case of Index of Biotic 80 Integrity scoring (IBI) the selected habitat variables explained 58.9% of the biotic integrity of this river system. Except percentage bare ground along bank, shnib cover along the bank, midchannel pools, tree cover , riffle and total cover, all other habitat variables showed significant positive correlation with the IBI scores while the relationship between IBI scores and percentage bare ground along bank, shrub cover along the bank, midchannel pools, tree cover , riffle and total cover was negative (Table 5.26). 5.3.3. Pamba river system Mean fish community diversity was l.59(SD=0.33) with a peak at Kakkad Ar I(1.99) and lowest at Kakki I(0.9l)(Table 5.3).Fish species abundance ranged from 38(Attathodu) to ll9(Thottapuzhasse1y) and the mean abundance was 70(SD=30.8)(Table 5.3). Index of biotic integrity ranged from l7(Nilakkalthodu) to 50(Peruthenaruvi) with a mean value of 34.2(SD=9.7) (Table 5.3). Among instream habitat conditions, instream cover did not show much oddity. Depth alone contributed 48.75% followed by turbulence (22.3%) and overhanging vegetation (16.8%) (Fig.5.3). In the riverbed, bedrock was dominating (24.8%) followed by fmes (19%) and gravels (16.75%). While the other types of substrates such as cobbles, boulders and rock together contributed to only 39.45% of the total riverbed (Fig.5.9). Sinuosity varied between 1-1.3 (sn=0.15) and channel gradient varied from 0.001 0.l(SD=0.04).The mean entrenchment ratio and w/d ratios were l.2l(SD=0.28) and 7 .l3(SD=5.6l) respectively. Heterogeneity of channel geographical units was comparatively less and midchaimel pools (45.5%), rapids (19.8%) and run (18.8%) together contributed to 84.1% of the total river reach (Fig.5.15). Mean flow velocity was 81 0.38 (SD=0.3). Riparian zone was having 13% tree cover, 66% tree cover while 20.25% of the riparian zone was without any vegetation. The first 7 PCA axes explained 89.1% of the total variance in instream habitat and physical conditions. The variables with the greatest loadings on each axis were temperature, dissolved oxygen level, percentage of bedrock type substratum, cascade and falls type channel geographical units and overhanging vegetation (Table 5.9). Multiple linear regression analysis of the selected habitat variables which showed maximum loadings in the first 7 PCA axes with the Shanon-Weiner diversity index showed that these variables explained the fish diversity in Pamba river system upto 72.6% and the habitat variables such as Cascade type microhabitat, sinuosity, and overhanging vegetation showed significant negative correlation with the fish diversity. On the other hand, variables such as atmospheric temperature, percentage bedrock and dissolved oxygen showed significant positive correlation with the fish diversity in Pamba river system (Table 5.15). Abundance of fish species was explained upto 40.9% by the selected habitat variables and among them except dissolved oxygen concentration all other variables showed significant positive correlation with the fish abundance (Table 4.2 l).Index of biotic integrity can be explained upto 50.9% by the selected variables. All the variables except cascade and overhanging vegetation showed a significant positive correlation with the IBI scores while the relationship of IBI with cascade and overhanging vegetation was negative (Table 5.27). 5.3.4. Kabbini river system Mean fish community diversity was l.5(SD=0.62) with a highest recorded value of 2.47 at Begur I while it was 0 at Thariyod (Table 4.4). Fish abundance ranged from 2(Tariyod) 82 to l35(Noolpuzha) and the mean abundance was 67 .6(SD=43.6). Index of biotic integrity ranged from 5(Aranagiri ll) to 65(Ponkuzhy) with a mean of 38.4(SD=l8.8) (Table 5.4). Among the habitat variables instream cover was dominated by overhanging vegetation (59.6%) followed by depth (24.8%). All the other types of instream cover together constituted only 15.6%. (Fig.2.4) .On an average, gravels (38.4%) and fines (18.6%) together constituted 57% of the river bed while the contribution of bedrock was only 13.5% which is indication of the high degree of bank erosion and embedness of fine materials in the river bed (Table 5.10). Sinuosity of the river system varied from 1-2.6(SD==0.58) while stream gradient ranged from 0.001-0.1(SD=0.03). Mean entrenchment ratio and w/d ratios werel.33 (SD=0.87) and 8.l7(SD=7.78) respectively. Heterogeneity of channel geographical units was comparatively less and was dominated by run (39.6%) followed by lateral pool (18.8%) (Table 5.16). Mean flow velocity was O.3(SD=0.23).Riparian zone having 26.1% shrub cover,58.6% tree cover while 15.3% of the riparian zone was without any vegetation. The first 7 PCA axes explained 89.1% of the total variance in instream habitat and physical conditions The variables with greatest loadings in each axes were sinuosity, shrub cover along bank, percentage of small woody debris, submerged vegetation, emergent vegetation, overhanging vegetation and pocket water pools(Table 5.10).Multiple linear regression analysis of the selected variables with the Shannon Weiner diversity index revealed that the variables explaining the fish diversity in Kabbini river system were up to 70%.Among the habitat variables except submerged vegetation and overhanging vegetation all other variables showed significant negative correlation with the fish diversity. (Table 5.16). The selected variables explained the fish abundance 83 only upto 29.3% and the variables such as sinuosity, shrub cover along bank, percentage small woody debris, emergent vegetation and pocket water pools showed significant negative correlation with the species abundance. While variables such as overhanging vegetation and submerged vegetation showed significant positive correlation with the species abundance (Table 5.22). In the case of IBI scoring, the selected variables explain the variation in IBI scoring up to 50.1% and among the seven habitat variables, sinuosity, shrub cover and pocket water pools showed significant negative correlation with the IBI scores while with other habitat variables the relationship was positively significant (Table 5.28). 5.3.5. Kallada river system Mean fish community diversity was l.l3(SD=0.45) with highest at Meenmutty (1.89) and lowest (0.33) at MSL (Table 4.5). Fish species abundance ranged from l8(Urukunnu) to l5l(Chenl Compared to other river systems habitat heterogeneity was very less in this river system. Overhanging vegetation (35.2%), depth (25.7%) and turbulence (21.9%) together contributed to 82.8% of the total instream cover in this river system (Fig.5.5). Gravels (30.2%) and fines (10.2%) together contributed to 40.4% of the riverbed, which indicated high degree of bank erosion and embedness while the contribution of bedrock was only 21.9 %( Fig.2. l 1). Sinuosity varied between l-l.4(SD=0.15) and slope ranged from 0.001-0.l(SD=0.037) while mean entrenchment ratio and w/d ratios were l.25(SD=0.5) and 5.9(SD=4.94) 84 respectively. Three microhabitats such as Midchannel pools (28.6%), run (25.5%) and riffies (24.3%) together contributed to 78.4% of the total river reach in this river system (2.17). Flow velocity was comparatively high especially in the upper reaches and the mean flow velocity was 0.48m/s(SD=0.78).Riparian zone having l7.9% shrub cover, 62.6% tree cover while 19.5% of the riparian zone was without any vegetation. The first seven PCA axes explained 90% of the total variance in instream habitat and physical conditions. The variables with the greatest loadings on each axes were mean channel width, percentage of shrub cover along bank, cobbles type substratum, sinuosity, temperature and total alkalinity (Table 5.11)). Multiple regression analysis of the selected habitat variables with Shanon-Weiner diversity index explained 77.4% of the fish diversity in Kallada river system. Among the habitat variables mean channel width, total alkalinity and overhanging vegetation showed positive correlation with the fish diversity while variables such as shrub cover along the bank, cobbles, sinuosity and rapids showed inverse relationship with the fish diversity (Table 5.17). Habitat variables defined the fish species abundance only upto 27.4%, which is a sign of severe habitat alteration and highly unbalanced ecosystem. Except shrub cover and sinuosity all other habitat variables showed negative correlation with fish species abundance in this river system (Table 5.23). In the case of IBI score the selected variables explained the trophic structure only upto 26.8% and among the habitat variables, percentage shrub cover,cobbles and sinuosity showed negative correlation while all the other variables showed significant positive correlation with the trophic structure of fish species in this river system (Table 5.29). 85 5.3.6. Periyar river system Mean community diversity (H’) was l.48(SD=0.52) which showed the maximum value (2.04) at Anakkallankayam while it was 0 at Kuntrapuzha(Table 5.6). Fish species abundance ranged from 0(Kuntrapuzha) to 284(Nadathottam) and the mean abundance was 7l.6(SD=5l.8)(Table 5.6) Index of biotic integrity score varied from 0 (Kuntrapuzha) to 62(Thandamankuthu) with a mean value of 34.l(SD=l l.8)(Table 5.6). In Periyar river system among the various habitat variables, the instream cover was dominated by depth (40.8%) followed by turbulence (31.4%) (Fig.5.6). On an average bedrock formed 45.5%of the river bed followed by boulders (14.6%), cobbles (14.5%), gravels (12.6%), rock (6.6%) and fines (6.2%) (Fig.5. 12). Among the physical conditions sinuosity varied from 1-l.4(SD=0.l2) and stream gradient ranged from 0.01-0.15 (SD=0.03). Mean entrenchment ratio and w/d ratios werel.39 (SD=0.03) and 5.l(SD=3.6) respectively. Midcharmel pools made up 24% of the total geomorphic units followed by run (19.8%), riffle (15.5%) and cascade (11%) (Fig.5.l8). Mean stream velocity was 0.49(SD=0.35) and the riparian zone having 23.7% shrub cover, 48.8% tree while 17.38 of the riparian zone was without any vegetation. The first ten PCA axis explained 81% of the total habitat variability among instream habitat, physical and chemical conditions in Periyar river system. The variables with the maximum loadings on each axis were water temperature, tree cover along bank, flow velocity, falls, lateral pools, gravels, overhanging stream boulders, slope, abandoned channel and cascade (Table 5.12). Multiple regression analysis of these selected habitat variables with Shannon-Weiner diversity index explained 68% of the variability in fish species diversity in Periyar river system. Except flow velocity, mean channel width, total 86 alkalinity and dissolved oxygen concentration all other habitat variables showed significant positive correlation with the fish diversity while the relationship of flow velocity, mean chamiel width, total alkalinity and dissolved oxygen concentration with that of fish diversity was inverse (Table 5.18). Fish species abundance in Periyar river system could be explained up to 59% by the selected ten habitat variables and all the variables except flow velocity, w/d ratio, submerged vegetation and mean channel width showed significant positive correlation with the species abundance (Table 5.24). The habitat variables explained the index of biotic integrity up to 61.8% in Periyar river system and among the variables flow velocity, mean channel width and total alkalinity showed negative correlation with the index of biotic integrity score. While variables such as air temperature, percentage cobbles, rapids, w/d ratio, submerged vegetation, overhanging vegetation and dissolved oxygen concentration showed significant positive correlation with the biotic integrity of this river system (Table 5.29). 5.4. Discussion The results of the present study suggest that channel geomorphology have substantial role in determining fish diversity, fish species abundance and biotic integrity of the river system. According to Krebs (1985), in a healthy ecosystem where the interaction between habitat variables and species diversity are more, the abundance of each species is the product of same integer while overcrowding or degeneration of any of the species occurs due to some habitat alterations. Among the six river systems studied only Chalakudy river only showed the sign of a healthy ecosystem where the interrelationship of habitat variables with species abundance and diversity was high. On the other hand, in Bharathapuzha, Kallada and Kabbini river systems even though the relationship between 87 habitat variables and fish diversity was high, the habitat variables failed to explain the fish species abundance and their trophic structure .The extent of relationship of habitat variables with fish abundance and trophic structure in Periyar and Pamba river systems revealed that even though not severe as in the case of Bharathapuzha and Kallada river systems habitat degrdation activities were also high in these river systems. While when compared the instream habitat and physical conditions prevailing in Bharathapuzha and Kallada river systems with other river systems studied, it is very clear that both the river systems were subjected to high degree of habitat alteration activites which led low fish diversity, dominance of some tolerant species and highly altered trophic structure.In Bharathapuzha river system, the high w/d ratio indicates that the contribution of pool type microhabitat was very less in this river system which is in well agreement with the findings of Schlosser (1992) who reported that both fish species richness and fish species diversity increased with the presence of pools. Felley and Hill (1983) reported that combination of niffle-pool microhabitats have very high influence on the faunastic diversity in streams. The marked contribution of Glide (12.3%) and landslide (9.6%) among microhabitats indicated the sign of increased human intervention, which have significant negative influence on the fish diversity. The present finding strongly supports the view of Cowx and Welcomme(l998) that on an average species diversity is 60% low in altered sections of the river systems when compared to natural conditions. Due to the over dominance of depth (38.68%), heterogeneity of other types of instream cover was very less which in turn affected the fish diversity in Bharathapuzha river system. The present finding is highly corroborating with that of Lachvanne and Juge(l997) that due to human intervention the river systems become more homozygous 88 which will drastically reduces the faunstic diversity. Among substrates, high contribution of fines (l6.57%) and gravels (l7.85%) are indicators of the high level of bank erosion and siltation which have a significant effect on the high w/d ratio, low heterogeneity of microhabitats and high contribution of low productive glide type microhabitats. Cowx and Welcomme(l998) reported that increased sedimentation will reduce the spawning grounds and heterogeneity of river bed which will adversely affect the fish diversity. The high level of siltation also pointing towards the high sand mining activity going on in this river system. In Many areas of the Bharathapuzha river system the shallow areas of the river itself was converted into agricultural lands which was reflected from the high contribution of bare ground (29.4%) in the riparian zone. Riparian zone was identified as the most disrupted component in Bharathapuzha river system and restoration of stock is possible only through the replenishment of riparian zone. The present finding shows full agreement with that of Thalmage et al. (2002) who opined that the most effective restoration effort for Midwestem agricultural streams in United states is possible only by giving maximum attention to riparian zone. In Kallada river system, high contribution of fines and gravels in the riverbed was an indication of high bank erosion and siltation. It also has significant influence on the low heterogeneity of microhabitats and instream cover. The present finding is in compliance with that of Judy et al. (1984) and Waters (1995) who reported that silation is one of the most important factors reducing the availability of usable fish habitat. Talmage et al. (2002) reported that when the substratum type increased from silt, fish diversity in the red river and Minnesota river basins responded positively. In the present study it can be seen that the low heterogeneity of microhabitats and instream cover is highly influencing the 89 low fish diversity in Kallada river system which is in compliance with the view of Denslow(l985),Doeg et al.(l989) and Lake et al.(l989) who reported that heterogeneity of microhabitats are positively correlated with the community structure in a river system. Low heterogeneity of instream cover and the associated low fish diversity in Kallada river system are well in agreement with the findings of Cowx and Welcomme(1998) who reported that the fish abundance increases with the increase of hiding places such as undercut banks, pools, overhanging vegetation, submerged boulders, woody debris, stumps and roots. Presence of 19.5% bare ground in the riparian zone was an indication of high degree of human intervention and ecosystem degradation, which were shadowing in the low fish diversity of this river system. According to Williams er al. (1997) tree vegetation in the riparian zone improves the bank stability and improves the instream conditions. In Chalakudy river system the w/d ratio (9.5) and flow velocity (0.25m/s) was minimum when compared to other river systems. The heterogeneity of microhabitats and instream cover was comparatively high. The contribution of fines (14.9%) and gravels (8.9%) in the riverbed was moderate which was an indication of low level of embedness. The high concentration of trees (87 .65%) and shrubs (7.6%) in the riparian zone and low contribution of bare ground (4.75%) are indicators of low intervention into the ecotone between the land - water ecosystem.According to Schiemer and Zalewski(l992)the most important direct effect of diversified habitats is that which create conditions for the coexistence of a large number of fish species and their life stages, reduce competitive interactions, pressure of predators, catastrophic disturbances and provide feeding and spawning grounds. 90 In Pamba river system, heterogeneity of microhabitats and the contribution of alternating pool-riffle microhabitats were very less. According to Rabeni and Jacobson (1993) riffle pool combination is very essential for stream biodiversity on local scales. Contribution of fines and gravels together upto 35.75% was an indication of low bank stability and high degree of siltation in this river system. Berkman and Rabeni(l987) reported that increased siltation affects fish cormnunities by decreasing fish production and diversity , specifically by reducing the abundance of benthic invertivores, herbivores and simple lithophilic spawners. When compared to other instream and physical variables riparian zone was the highly altered component and 20.25% of the riparian zone was without any vegetation. According to Cowx and Welcomme( 1998) in spite of providing the hiding places for fish and invertebrates riparian vegetation is very essential for water purification, nutrient recycling, establishing physical link between aquatic and terrestrial ecosystems, affects flow pattern and providing spawning areas and food source for fishes. In Periyar river system w/d ratio was comparatively less while flow velocity was maximum among all the river systems. Heterogeneity of microhabitats was comparatively good and the low concentration of fines and gravels (22.5) when compared to the bigger substrates (77.5%) indicated that the bank erosion and embedness were comparatively less in this river system. High proportion (l7.38%) of bare ground indicated that the ecotone between land water ecosystems were under great threat in this river system and according to Cowx and We1comme(1998) healthy fisheries may depend upon or be considerably enhanced by the vegetation of the riparian zone. Ward and Stanford (1989) reported that tree roots, fallen trunks and branches increase retention of 91 organic matter and therefore can maintain large amounts of invertebrates, which become food for fish. In Kabbini river system heterogeneity of microhabitats and instream cover was comparatively less. Among substrates, the high concentration of gravels (38.4%) and fines (18.6%) in the riverbed was the sign of conversion of undisturbed areas into agricultural lands. The present finding is in well agreement with that findings of Waters (1995) who reported that silt, which is often associated with agricultural land use, can be one of the most important factor reducing the availability of usable fish habitat. The high contribution of bare ground (15.3%) was an indication of the increasing human intervention into the catchment area of the river system. Portt er al. (1986) and Schlosser (1992) reported that reduction of the complexity of instream habitat and physical conditions drastically reduces the establishment of large specimens , trophic structure of the community and also reduces the reproductive potential of the population leading to greater variability and smaller number of specimens in a population. The significance of instream habitat and physical features in this study demonstrates the necessity of management and restoration of multiple-scale features in the river systems of Kerala. Instream habitat and physical conditions are not independent each other they are linked by direct and indirect casual relationships (Talmage et al.2002). These features need to be considered while preparing restoration design and its implementation. Hawkes et al. (1986) stated that environmental variables function in concert to produce a system of dependant interactions that define the community structure in an ecosystem. Based on the result of the present study it can be stated that the most effective restoration efforts in the streams of Kerala would be the one focusing on riparian zone. Riparian restoration 92 increase instream habitat with inputs of woody debris and overhanging vegetation. It also stabilizes stream banks, provides allocchthonous organic material encourages geomorphic diversity and reduces the nutrient and sediment run off from the neighbouring fields. Management implications From the above findings it can be concluded that the biotic integrity in Bharathapuzha, Kallada and Kabbini river systems were drastically declined due to the destruction of instream habitat and physical conditions. So in order to improve the biotic integrity in these river systems, increase of microhabitat diversity, instream cover, development of riparian zone and improvement of substratum are inevitable. The following management measures are proposed for restoration of fishery wealth. 1. Keep the longitudinal comiectivity of rivers as intact not only to permit passage of migratory fish species but also for the free movement of all species within the maximum range; obstructions presented by dams and weirs may be bypassed by fish passes but the influence of water quality barriers must also be considered. 2. To maintain the lateral connectivity between the channel and river margin or flood plains in the middle and lower stretches, should not remove the flood plain ponds and backwaters associated with the river system. 3. In Bharathapuzha, problems of effluent discharges should be assessed and consideration given to the influence of any reduction in flow or water quality parameters. 4. In braided reaches, improvement of current speed diversity through the installation of rapids by the construction of different types of low weirs. The weirs 93 shall be placed over the full or partial width and at different angles to the riverbank. It may be straight, ‘V’ shaped in the upstream or downstream direction or with an irregular crest form. The weirs can built with boulders, cobbles, stone filled gabions or with concrete. But maximum height of these weirs should not exceed 1.5m or it should be completely submerged in water. lnstream and stream side cover can be improved by boulder placement, placement of stumps, roots or debris, artificial undercut banks formed by overhanging cover structure, tree planting in banks and stop the removal of overhanging vegetation Because pool-riffle reaches can be identified as most diversified macrohabitat it can be achieved by current deflectors, stream narrowing deflectors, installation of low weirs and mechanical construction of pools. Substrate reinstatement by replacing the sediments with well-sorted gravels, cobbles or even with crushed rocks which will helps to improve the fish and invertebrate habitat. The micro invertebrates which form a good source of food to stream fishes can be motivated by increasing the concentration of woody debris, wet land vegetation and restoration of riffle type microhabitats in streams. 94 Table 5.1.Fish diversity, abundance and Index of Biotic |ntegrity(lBI) % at selected locajjons of Bharathapuzha river $E;tem. 1 Shanon~Weiner Location % mdiversitxindejx IBI MAbundance j Cheruthqruthy2 -. -_ 1.72;30. . 2 72 Kgnakkanoor _ % 2.37355 9.01 3351 ;Thonikqdavu 1 { 1 _ 1 .434 10% 25 1Cfieerakuzh5i X .1 2.013755 31> 79,} 5Meenva|lam51 H W. 0 1 O 3 5\Cherakuzhi55 1.3531. 1011 191 Pambadijeast 1 2.0731 32 251 1 2.02 55 69 15 Manarkkad 55' Mudagpwallur __ 55 1183” 25“ L. L1Yakl{ara 1 1 i 2.32 501 1 12 Ch_uriode _ 1 _ 1.3991 5 15 1Kalpathi5 _ 1 1 5 1.51 25 5755 1Pezh1umkara1 __ 5 5 1.498j 20 1 J75 14 %Choorapara "1411 4} 1Ch5ittur 1 1.371 150 30.1 Kavarak5undL1 1 1.51 35; 1171 Velampattayzha % % - 01 1 241 1Kan'Lir;apuzha 1.154 15 7 7 karimala 1.334 20 14 _T@Ep1il%ikefiyam 1 55 0]! 15 Z4 .-|. Thodu1'1nampa5|'5e 1.35 201 141 25 Meenvallam ll 1 2.113 9 Atla 55 5 5 1.3341 20 14 1 Puchzggpara H 5 1.04 5 29 Cheriawalakkad 0.33. 30 15 0.554‘ 15* 515 1 Karingathodu Q___ 1Cheriavialakka5d 0.507 40 9 1Sjyrendri L5 % 1 _ _ 0.577 51 211 Table 5.2.Fish diversity, abundance and Index of Biotic lntegrity(lBI) at selected locations of Chalakudy fiver system Shanon~Weiner Location j A diyersitlindex % 1 131 Abundance .Vef!i!aPara . 2.17 55 1 1 5461 40 ’Athirag_Qa||y L 2.17] 41 LAthiraEgaIlL_ 2.0411 5 1 5‘ 40 101 Q/azachal é j 11 2.43 52 1511 115549515 j % 2.093“ 421 [Qrukomban I 7 2.573, 50 ‘_Sholaya%r? _ 1.9993 55‘ 151' Orukomban ll 2.14 I __ 45 LKurir%kutt)Lé L 1 2.165 64 2065157 _PuLiyala 2.205151 45, 51165 1T“¢'<'<5a.dl>’a' 1.457 30 126 * Thekkediyar ll 5 301 5425 1Thekkad1¥arl_ll 5 1.720 45. . 594 ' Orukomban 2.15 571 5 515' L[Malakkapara L 1.5633 1j 25 56.’ Vallalfalyam A 1.5511 45* 1 53 Anakka7llankayam77 7 7 1.701 - - 40 60 Pa7dikutty7 7 7 7 2.093 45 7 109 Ka7ra£para7riv7er 77 7 7 1.749 9 45 7 95 Vetti Ar 1 .797 7 95 T3 Table 5.3.Fish diversity, abundance and Index of Biotic lntegrity(lBI) _H at A selected A 1Sh”anonJWeiner locations of Pamba ifiver1 sgtem. Location 7 7 7 diveragy index 7|BI77 7_7 Abundance 1 17Th7ottap7u7zhasseQ/ 7_ = 7 1.87 40 !_ ._ 1191 Tiruvillagra 77 7 1.95“ 277 115 1 1 P7erunthenaruv7i 1 1.91 59 1091 Azutha 7 7 7 if 1.49 45 59 Angamoozni _ 1.421 19 381 Nilakkalthodu 7 77 1.921 171 38 1Attathodu A 71.421; 40 9 381 Kakkad Ar I 7 77 77 1.7797 1415 501' 1Kakkadr_. ,. Ar ._— 11 1 1.991 341 A 971 Pamba 1 1.55‘ 7’ ._ 65. Moozhiyar7| 77 71.95 45 54 491 Moozhiyarll A 7 1191 _ 17.0517 2°. HKakkil _ _ W H 1110.911 25 541 1Kakkil| 1 . 1 2 307'71 1121 Kochupgmbai 7 1 1.41 35‘ 77 1415 Table 5.4.Fish diversity, abundance and Index of Biotic lntegrity(lBl) at selected locations of Kabbiniriver 75;/stem. Shanon-Weiner 1 1_Location 7 7 diverggy index 1131 7 Abundance 7SuJgarda_9iri 77 77 77 0.557 30 .51 Bequr 7 7 7 2.251 62 14“ l(arnambatta7 7 1.761 371 5.57 1K~.w\/99999 7 1.97 151 _P7a|velicham _ 7 1.9991 1 45 101 “Achoor 1.504 20 1 50 S1 17 BGQLJI I 1 2.466 IF. 1.957 55 14 jlegur ll 7 77 77 1 1Tha7r7iyod .7 A 9 151 - 1 15 Arnagin I 7 7 7 1.1351i 1 1A;7na@7 ll 7 11 7 1.24 5 117Aranagiri 77 7 77 7 7 1.891 471 Ponkuzh 1.95 9 1 _-Y _ . -1 65 1 7Noolpuz7ha 7 77 1 7 0.751 45 121 Muthanga 71 1 7 1.571 22. 61’ Table 5.5.Fish diversity, abundance and Index of Biot'1c Integrity(IBI) 1' — at5- selected - ., locations of Kailada river aystem. Shanon-Weiner 1 "1! Location 7 7 1 diversity index 1l_BI Abundance yrukunnu ' 0.531 20 181 %770ttakka| 7 1.05 25. 451 Méwflliufix 1.591 45 92 11 Dali - V V —— V 1.727 257 93} MSL A 0.311? 201 92 Ehenkali A 7 11_7 1.54 475 1511 Q’ (.0 C10 é AriyankavuKazhuthyruiy 11111188163 0.88 8 2520 68 RelaruviPalaruvi 11888888 I _8_ 8 88 1.12 1.07 40 8 8 8 so Chenthuruny 8 1.0113 1 28015 1925 Table 5.6.Fish diversity, a51undance and Index of Biotic lntegrity(lBI) 1 1 1Shé1non-Weiner888 at selected locatiops of Periryar 1 river syst_e8n].888_ Location \diversity index IBI 88 Abundance 8B8h8oothéth1a1nkettu ____ 8 88 11 1 21131218 .§Q 1 1 1 63 I Neriyamangalam 1 8 5 1.912 351 68 1.991 1Pq9yamk8u8tty11W 1 ' I 4<> 88 76 8Pura|g8l58alIu 8 1.541. 40 117; Thnadmankuthu 8 1.951 1 5112 98 Neendapara 1 11 881.8394 1 1 30} 27 q Mangagpara 88 _ 1347 257 777 Pir]q_ipa|1'q8888 888 0.87468 3011 78 ‘Thannimgodu ' 8 1.57 3011 80 Panniarkutq/8 8 8881,6338 1120 63 Mfikkan 1 8 8888_888__ 1-723 . 1111415 56 Nallathanni 8 8 1 -13142. as 8 111 Kuqchithégnni 8 O1.13027§ 39 57 Madragpara 88 1.564} so 531 Qhqcirapara 1.657 1 301 - .5? .|1PN_©| P®N_©| ¢@@_O @qH_@‘ ©@O_@ @fiN.© ©@@_©| @@fi_@ ¢fi%_©| ©@O_© O®©_©| @@@_@ H¢H_@J ®q@_Q| @Q@_O ®%©_O| ©%@_© ®@@_O| %W©_@ ©%@_O ®@©_O H@@_O ®q©_O PHH_O N©Q.O QWOOO ®@O_© ©@O_Q @N@_© ©NH_Q @PH_O @Pfi_@ ©@H_@ ¢@€_© P@fi.© @Ofi_@| @@fi_O OFH_© G®U>XO U0>HOWWHQ mgQHDUMHQQEOU HQMMB ®HDp®HOQE®p HHG WHQGGMSU U®GUUCMQ¢ Obfiflmufiflg QUHHQU02 Qflflfim WHOOQ Hwpmg p®xUOm H®GC@£UUHz SUGQHHCgmp00£mQduufimmoflmflm®U©UmQU mflfifihH0>OU HMUOH xfifin QDUHOUGD mOO_O1 mmO_O WHQUHSOD EMUHQW MoGMnHm>O P@O_©' @¢Q_O| H50 H:OUm HPH_o OmN_O mHUUHDOQ HWUMS Qpfinz PGMHSQHDB @O©_O ®PQ_©| ©Q%.Q ©®%_@| @®©_@‘ ®@N_© Hmm_O- PP@_Q ©@@_@* W@@_@ P@©_@ N@%_©| F®H_@ O®N_O @©%_O m®fi_@l ©@fi_© ®@fi_Q H®H.Q @NN_© %Pfi_Q| @WN_O ®©fi_©i NNO_Q fiOfi_O TN%_@' P@©_Q mNN_@| ¢@H_©| H®H_@ @®H_@’ @©O_©| WmN_O| @%N_© ©N@_© H@@_©| N@©_@ NNH_@ GOflU©P®m@> mCHaMOHh COHpmp®m0> pGOOHOEm COHHflp®m®> mCHmGM£H0>O WHHQUU >UOO3 UOHQA QHHQOU Hdflew spawnQUGMHSQHDH xOOHU®m£00mmHOUHDOm MUHQQOU WH®>MHO WQGHMxfifln @COHM UQSOHO Qflflm xflflp UGOHM H®>OU QUHH xflfip OGOHM Q5H£m OHMMH U\3 ®mOHmOHpMH UCWEQUCUHMCM >pHmODCHm o_UmmUmA Awa: pom‘ §_ \ at am A W2 8m &_UAH_\ H H! 1 mo_§§ m_X’\Egg“ __mE._ @__N_:__:=_“_::_m E m___OE_E°U __3____2_?O£mb___ Es H_3E_w__ ___g_:m___ '5“ mag 2 Ea 2: he w__=§_ H__2_2____8 _2__5__F__b_“ “_____H_“F 22 @Un_ wg Bfi_ _ RE am gm M2 N8 6% D_n_fia>EvaEgg“ __g___ _::a_fl__:_U E m__cEH___8 __§E2_U'°£m%_____ Ea H532 ____3_:mE _s__ 8: 2 25 2: he w__%g_ E2_2_EOU _gE__m__A__w_“ “___n__wrH mfixfl £U©® CO OCHUMOH pmwgmfln mg“ cpfiz MCQCOQEOU wflp QUMUHUCH m®DHfl> UHOm_ N_@ @_@ H_W @_Q V.m m_@ 00% N_® @_HH m_mN Uwcfimfiflxw wUCmHum> %muOU W O¢H_© @@@_© ®@©_O, N@N_o @®H_O ®®H_O| %P®_@ PH@_Q| @@©_@ §mH_Q BQQQU Hmccmgu Coax ®Q@_©| NHH_©| [email protected] vm®_O FN%_O PQO_@l v@®_O HN@_Q ®®@.O| H@N_Q, CUUH3 fiwccmflo cmwx O@H_O| ¢HO_©| @@O_@' ®V©_O' OWO_O [email protected] q©®_o| @HO_O| @@fi_Q H®H_O %MHUoHm> 3O%m ®©@_Q @V©_© PO%_Q' @@©_o[ ®mH_© VF@_Q' HH@_Q ®@®_© [email protected] ®m©_Q' xuflcfifimxfim fimUoH H@O.@ m@©_Q' [email protected]| @@@_O| @P©_©| ®O@_O ®WN_Q NN@_@| @@fi_©' mmwCUHm: %mUo% E5 H_§Q_w______3_:wE __p_ 8: 2 fie 2: he w__=§_ ___2_2_EOU __w&UE_£_m_W Be; 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moH_O- muflaflm ®mO_o| mUflUw©U HoH_O| mfififlh HmH_o Hm>OU Amok NhH_O' xcmn UDOHUUGD Nmo_O mHwUHDOn EMWHQW oCHOcMQHm>O HvH_o| mHOOQ #30 HDOUm Table 5.13.llllultiple linear regression analysis between critical habitat variables and Shanon-Weiner diversity index in Bharathapuzha river system H'(R2=706, P<0.03) g Coefficients Standard Error t Stat Pgvalue _ Constant 0173883882 0.146799073 1.184501092 0.253512375 w/d ratio 0.028985341 0.052654081 0.550488129 0.589589798 Large woody debris -020322237 0.08609816 -238035871 0.031287636 Fines 0099214955 0.044352028 2.238988019 0.039873144 Total cover -0.088108085 0.09031 1 597 -0.754145503 0.461717464 Sheet 0.322088358 0.7791 86935 0.413384879 0.684826605 Riffle 0055388434 0.043348376 -1 277704927 0.21958153 Floating vegetation -0032535821 0.09883169 -o.3292o2311 0746272765 Abondoned channel 0.052429418 0.091 967621 0.570085815 0.57653793 Pocket water pools 0.092388253 0.070946084 1 801949978 0.21 1366204 Bapids 1 y -0.041258855 0.053626605 -0789389149 0.452883285 Table 5.14.llllultiple linear regression analysis between critical habitat variables and Shanon-Weiner diversity index in Chalakudy river system H'(R2=90.5, P<0O04) Coefficients Standard Error t Stat P-value Constant 171 .6534095 81 .76972876 2.099229289 0.065199776 Flow velocity -0.065887693 0.057268084 -1150513305 0.279582971 Mean channel width 0.134705298 0.12917961 1 1 042775231 0.324252085 Bare ground along bank ~03090681 89 0.237882412 -1 .299247749 0.226153424 Shrub cover along bank -0279641857 0.223736039 -1249873998 0.242868198 Midchannel -0.041948851 0.037393793 -1.121813215 0.290978752 Tree cover along bank -252. 0408552 120.21 02 348 -209888719 0.065471395 ‘Falls 1 106.993694 527.307349 2.099332954 0.065188809 Riffle -0033095151 0.031420021 -1053314082 0.319653281 Water temperature -0.5517529 0.651654649 -0.848895258 0.419108756 Total cover f -0.013576552 0.06962827 -0.1949882o4 0.849734462 Table 5.15.llllultiple linear regression analysis between critical habitat variables and Shanon-Weiner diversity index in Pamba river system H'(R2=72.6,P<0.002) Coefficients 3 Standard Error t Stat P-value Constant -4. 140033272 1 .327807551 -3.1 17946776 0.035597196 Air temperature 1 .16101 1087 0536478403 2.164133876 0.09644143 Percent bedrock O.101933893 0.055666793 1.831 143643 0.141040219 Percent cascade ~0.008384148 0.15869054 -0052833317 0.960398039 Sinuosity -0.16937042 0 728699478 -0.232428353 0827613257 Dissolved oxygen 5.396545485 1 .3031 1 3768 4.141269641 0.0143617 Overhanging vegetation -0.1 14406212 0.051 161655 -2.23617104 0088999164 Table 5.16.lllultiple linear regression analysis between critical habitat variables and Shanon-Weiner diversity index in Kabbini river system H'(R2=70,P<002) Coefficients Standard Error 3' t Stat it Plvaiue Constant i 10.053169238323 0690129498 007490309 7 0942387461 Submerged vegetation 0.178323522 0259807904 0888895582 0514252928 Sinuosity -0.598675199 0.404834184 -1.478815826 0.182722048 Shrub cover along bank -0.064341753 0.080694744 -0797347515 0.451443603 Small woody debris -0012650986 0.187487217 -0.067476528 0.948089242 Emergent vegetation -0089921689 0.121050248 —0.742845968 0.481754924 Overhanging vegetation 0. 1 71 037628 0.383825322 0.445613194 0.669332439 Pocket water pools g -0.029691139 0.121474828 -0.244422155 0.813913659 Table 5.17.Multiple linear regression analysis between critical habitat variables and Shanon-Weiner diversity index in Kallada river system H'(R2=77.4,P<0.01) Coefficients Standard Error 7 tStat P-value g Constant -0.061 127097 0.565028819 -0108184034 0.920679468 Total alkalinity 0.062302154 0.730656047 0. 085268786 0.937419528 Mean channel width 0.14600512 0.287036101 0. 508664659 0.646035267 Overhanging vegetation 0.0540081 1 0.141900006 0 38060682 0.728846446 Shrub cover along bank -0.066294925 0.224550762 -0.29523358 0.787069022 Cobbles -0054612052 0.160430467 -0.340409479 0.755990955 Sinuosity -2.548522996 1 .786601725 -1 .426463973 0.248995946 Rapids -0.264698739 0.51701269 -0.511977258 0.643973633 Table 5.18.Multiple linear regression analysis between critical habitat variables and Shanon-Weiner diversity index in Periyar river system H'(R2=68,P<0.05) ' 7* g it _ 7 g 7Coefficients H Standard Error”? Ht Stat P-value Constant _. it 01748758426 0. 871 035668 -0.170783392 0.86629917 Air temperature 0.437477304 0.295391536 1 .481008257 0.15589726 cobbles 0.069780718 0. 069867769 0.998754056 0.331151893 Flow velocity -0.198504783 0.139340772 -1 .424599421 0.171380681 Rapids 0.05952509 0.057907777 1 .0279291 16 0.317599188 wld ratio 0.053363849 0.079614457 0.670278374 0511189092 Submerged vegetation 0.003768094 0.1 19823586 0.031447016 0.975259118 Overhanging stream boulders 0.118578876 0.1 03447921 1.146266405 0266695372 Mean channel width -0.014504896 0.13444686 -0. 1 07885718 0.915279823 Total alkalinity -0.054021359 0.26054516 —0.20733971 5 0838072183 Dissolved oxygen g g-0505539104 0830946245 -0.608389661 0550529871 Table 5.19.Multiple linear regression analysis between critical habitat variables and index of biotic integrity score in Bharathapuzha river system lBl(R2=14.8, P<0.04) _ 1 _ ' it Coefficients 3Standard Error t8tat 7 P-value Constant 1 .263003556 0.4651 13897 2. 71 5471 551 0.01527978 wld ratio 0.075788989 0.166827653 0.454295124 0.655718734 Large woody debris 0.334915669 0.272790897 1 .227737703 0.237302154 Fines 0.0521 14362 0.14052367 0370858249 0.715607486 Total cover 0.016874171 0.286140627 0058971602 0953704992 Sheet 1 .035808399 2.468753137 0.419567426 0.6803809 Riffle 0.08071 1085 0.13734373 0.587657586 0564964506 Floating vegetation -0.01 1345976 0.313135443 -0.036233444 0.971544431 Abondoned channel 0.160144261 0.291387527 0549592027 0.590188755 Pocket water pools 0.126622428 0.224783502 0563308368 0581034183 Rapids 0.069271 136 0.169908969 040769558 0688900326 Table 5.20.|lllultiple linear regression analysis between critical habitat variables and index of biotic integrity score in Chalakudy river system lBl(R2 =58.9,Pf0.009) Coefficients Standard Error t Stat P-value”? 9 Constant 216.1735457 127.6535388 1.693439506 0.124618755 Flow velocity 0.045412347 0.089403178 0.507950025 0.623703013 Mean channel width 0.221874725 0.201666738 1.100204863 0.299798156 Bare ground along bank -0.510337296 0.371366424 -137421496 0.202624371 Shrub cover along bank -0.424194993 0.349282034 -1.214476989 0.25546'838'2 Midchannel -0090358209 0.058376737 -1.54784616 0.156065574 Tree cover along bank —315.2502032 187.6643362 -1.679862085 0.12728745 Falls 1380.300939 823.197657 1 .676755184 0.127905405 Riffle -0.007472857 0.049050877 —0.152349107 0.882272298 Water temperature 0.151 164145 1 .017320509 0.148590482 0.885152836 Total cover -0.023852734 0.10869909 -0.219438208 0.831204736 Table 5.21.l\llultiple linear regression analysis between critical habitat variables and index of biotic integrity score in Pamba river system lBl(R2=50.9,P<0.0005) 8 Coefficients g Standard Error t Stat it P'.Y§'@e. Con§tant -0.945106505 1 621938286 -0.58270189 0.591362228 Air temperature 0.236658343 0.655317001 0.361 135668 0736264021 Percent bedrock 0.070604794 0067997883 1 .038338125 0357755286 Percent cascade —0.198150176 0.193843048 -1.022219668 0.364467167 Sinuosity 0.21 1483158 0.8901 18137 0237589988 0.8238725 Dissolved oxygen 2.829465039 1 .591774433 1 .777554018 0.1501 1 1615 Overhanging vegetation -0.033400806 0062494785 -0.534457494 0.621349316 Table 5.22.lVluItiple linear regression analysis between critical habitat variables and index of biotic integrity score in Kabbini river system lBl(R2g=50.1,P§g<0.Q03) g 7 _ Coefficients Standard Error H t Stat “P~value M g Constant 1 .218794153 1 .882603458 0647398234 0538018813 Submerged vegetation 0.669196136 0.708184101 0944946568 0375151821 Sinuosity -1 .69974246 1 .104346702 -1.539138439 0187852792 Shrub cover along bank -0.275504152 0220127098 -1 .25156855 0.250928918 Small woody debris 0.137172542 0.51 1446163 0268205242 0.798273155 Emergent vegetation 0.153322287 0.330212832 0464313532 0858517941 Overhanging vegetation 0.41789495 1.047036652 0.399121606 0701899877 Pocket water pools -0.045221609 0.331371043 -0.136468197 0895293088 Table 5.23.?-lultiple linear regression analysis between critical habitat variables and index of biotic integrity score in Kallada river system lBl(R2=26.8,P<0.005) Coefficients Standard Error it Stat P-value Constant 1.468223971 0152400821 9.63397632 0002373888 Total alkalinity 0324239909 0.197073903 1 .645270646 0.198464478 Mean channel width 0062483848 0.077419909 0807077255 0478676045 Overhanging vegetation 0.063919513 0038273533 1 .67007088 0.193498005 Shrub cover along bank -0.223601997 0.060566248 -3.691858177 0034472055 Cobbles -0.023310079 0043271503 -053889229 0.627504971 Sinuosity -1309748089 048188553 -2717985137 0.072674031 Rapids 30122477529 0139449521 0.878292301 0.444446348 Table 5.24.Multiple linear regression analysis between critical habitat variables and index of biotic integrity score in Periyar river system lBl(R2=61.8,P,0.05) g Coefficients Standard Error tStat P-value Constant 7 -1 .786769541 1724530669 -1 036090325 0313879594 Air temperature 2.070958636 0.584834562 3. 541 101653 0002333837 cobbles 0.054477974 0.138328561 0.393830263 0.598332709 Flow velocity -0.434140364 0.27587554 -1.573681975 0.13297321 Rapids 0.082810284 0.1 14649424 0.722291325 o.479395032 w/d ratio 0.065217834 0.157625661 0.413751377 058394423 Submerged vegetation 0.206706308 0.237234199 0.871317495 0395053913 Overhanging stream boulders 0.116990104 0.204812636 0.571205499 0.574923744 Mean channel width ~0.512521201 0.266186268 -1.925423142 0070124803 Total alkalinity -0.085614094 0.515843537 -0.165969113 0870031233 Dissolved oxygen _ 1127529448 1 .645159132 0.885381938g_ 0591847391 Table 5.25.llllultiple linear regression analysis between critical habitat variables and fish abundance in Bharathapuzha river system 5A(R2=24.5, 3 Coefficients P<0.004)g Standara Error t Stat P-value Constant ‘ it 1793029056 0.460617614 3.89266281 1 0.001293615 w/d ratio 0.074583968 0.16521492 0.451436033 0.657734173 Large woody debris -0.437920215 0.27015381 1 -1.621003284 0.124554859 Fines -0112541886 0.13916522 -0808692619 0.43055334 Total cover -0.228642451 0.283374489 -0.806856156 0.431580376 Sheet 0.589453639 2.441-1887555 0.241096421 0.812542778 Riffle 011938483 0.13601602 0.877726242 0393081838 Floating vegetation -0.047291691 0.310108344 ~0.152500545 0.880698705 Abondoned channel 0472203738 0.288570666 1 .636353909 0.12128124 Pocket water pools -0.110096792 0.222610506 -0.494571408 0.627624614 Rapids -0.014158845 0.168266449 -0.084145386 0.933984681 Table 5.26.llllultiple linear regression analysis between critical habitat variables and fish abundance in Chalakudy river system AlR2=67.3, P<0_._03) Coefficients Standard Error tStat W P value _Hg Constant ‘ 264.9558284 249.1300192 210635242965 0315245781 Flow velocity 0088807946 0.174480204 0.508985797 0.62300532 Mean channel width 0.072937375 0.393574974 0.185320155 0.85708707 Bare ground along bank -0.4384045 0.724762707 -0.604893844 0.560189325 Shrub cover along bank —0.303634141 0.681662574 -0.445431732 066652911134 Midchannel -0.091851056 0.1 13928668 -0.806215478 0.440900436 Tree cover along bank —388.671 1016 366.2477369 -1 .061224582 0.316234406 Falls 1706.078605 1606.561401 1 .061944227 0.315924781 Riffle -0.155824366 0.09572821 8 -1627778818 0.138013718 Water temperature 0.457358296 1 .985413646 0230359199 0822963521 Total cover -0.010190859 0.212138314 —0.048038747 0.962734504 Table 5.27.llllultiple linear regression analysis between critical habitat variables and fish abundance in Pamba river system A(R2=40.9,P<0007) r-.. Coefficients 7' Standard Error tStat P-_VaTUé Constant 0.351162457 3.080858815 0.1 13982003 0.914744093 Air temperature 1.382167231 1 244769407 1 . 1 1 03801 42 0.329084764 Percent bedrock 0.113953448 0.129161435 0.882255978 0.427467938 Percent cascade 0.08268316 0.368203321 0.224558432 0.833327394 Sinuosity 1.531154917 1 .690772288 0 905594992 0.416366088 Dissolved oxygen -0.890094007 3.023562816 -0.294385816 0.783108317 "Overhanging vegetation 0052486089 0.1 18708344 0.442143213 0.681239474 Table 5.28.Multiple linear regression analysis between critical habitat variables and fish abundance in Kabbini river system A(R2=29.3,P<0.02) U y Coeflicients Standard Error t Stat P-value Constant.. l 1 .071278352 0.677901278 1.580286669 0.158052852 Submerged vegetation 081272841 0255007981 3.187070483 0.015339013 Sinuosity -1.56806514 0.397661036 -3.94322048 0005580262 Shrub cover along bank -0.07161 5418 0079264935 -0.90349431 1 0396289992 Small woody debris -0.448929056 0.184165182 —2.437643488 0.044913964 Emergent vegetation -0.161571876 0.1 18905391 -1.358827168 0216358517 Overhanging vegetation 0093972356 0377024424 0249247396 0.810324896 Pocket water pools 7 f -0.135806958 0.1 19322448 -1.13815095 0292507787 Table 5.29.llllultiple linear regression analysis between critical habitat variables and fish abundance in Kallada river system A(R2=27.4.P<0.008) Coefficients Standard Error t Stat P-value Constant 0287725858 0.412986181 069669609 0.536123983 Total alkalinity 1.033501936 0.534045061 1 .935233583 014840296 Mean channel width 0658355728 0209798048 3.138045068 0051741802 Overhanging vegetation 0228079278 0.103716376 2. 19906717 0.1 1527241 1 Shrub cover along bank -0.521947402 0.164126781 -3. 180147677 0050088339 Cobbles 0079570816 0.1 17260507 0.678581 546 054606079 Sinuosity -0.537395374 1 .305848122 -0.41 1529767 0.708318567 Rapids 0.656215581 0377890629 1 .736522503 0.18087044 Table 5.30.llllultipIe linear regression analysis between critical habitat variables and fish abundance in Periyar river system §(R2=59,P<001) H y Coefflcients Standard Error t Stat P-value y Constant 7 7 7 -2773751344 2.72548534 -1.017709141 0.322301 159 Air temperature 246055571 0.9242851 14 2.662117644 0.015876795 cobbles 0009928562 0.218617431 0.045415234 0964276394 Flow velocity -0507605598 0435999633 -1 .164234002 0259528862 Rapids 0.091608293 0. 181 194414 0.5055801 15 O.619286423 wld ratio -0.044048728 0.2491 14983 —0.17682087 0.861623454 Submerged vegetation -O.390640188 0374930027 -1.041901579 0.31 1250047 Overhanging stream boulders 0.019688718 0323690293 0060825792 0.952168228 Chapter 6 Habitat Suitability Index (HSI) models of selected endangered and endemic fish species of Kerala 6.1. Introduction The convention on Intemational Trade in Endangered species (CITES) was established in 1973 under the auspices of the United Nations Environmental Programme (UNEP) identified that because of the biased nature of endangered species list and the lack of information regarding the endangered species the species to species approach to biodiversity conservation faces a major hurdle. They also pointed out that habitat conservation through the establishment of protected areas is the suitable method to overcome this problem. There are links between the diversity of species (biological diversity or biodiversity) and the way ecosystems functions (Osbome, 2000). From this statement it is clear that any change in the ecosystem will have significant influence on the inhabiting fauna and flora. With this view Conservation Intemational (CI) was formed in 1987 with a mission that is focused on the protection and sustainable use of biologically diverse ecosystems and in 1989 they developed the Rapid Assessment Programme (RAP) to provide information necessary to develop a rational conservation management strategy for a particular area. More than 48%of natural habitats have been severely affected by human activities (Hannah et al., 1994), and this process of habitat destruction is probably the major cause of biodiversity loss. This process is escalating owing to the enhance living standards and our ever increasing capacity to exploit natural resources. River fish provide a major source of food and recreation and are also useful in predicting ecological conditions in streams and rivers. The biotic diversity and natural characteristics of fish communities are directly related to the variety and extent of natural habitats in a river basin (Cowx and Welcomme, 1998). In its broadest sense, the term 95 habitat defines where a fish species lives without specifying resource availability or use. (Cowx and Welcomme, 1998) Many species of fish are endangered because of habitat change brought about by human interventions, and many more will be affected as alteration of habitat and human abuse of freshwater resources continue (Postel et al., 1996; Sala eta1., 2000; Tilman et al., 200l).Understanding and managing human impacts on fish require a clear understanding of the relationship between a species and its enviromnent (Rosenfeld, 2003). The habitat associations, usage and requirements of fish species could reveal delicate relationships with their environment (Arun, 1998). Habitat requirements of fish have to be considered in any effort to maintain or rehabilitate rivers for fish biodiversity (Freeman et al., 1997). Studies on the habitat use and requirements are very essential for the proper management and restoration activities or translocation of populations to new habitats (Harig et al., 2000). Basic information on life history and habitat requirements are essential for species conservation. So identifying the suite of conditions that defines the habitat requirement of a species is a primary goal of aquatic research. The concept of habitat requirement, however, is poorly defined (Rosenfeld, 2003). Suitability criteria rest on the assumption that animals preferentially occupy areas that best support survival, growth and reproduction (Freeman et al., 1997). Broadly speaking, requirements can be defined as features of enviromnent that are necessary for the persistence of individuals or populations (Bjomn and Reiser, 1991). The concepts of habitat selection, preference and requirement are sometimes confused in habitat studies, and information on habitat selection is frequently used to infer habitat requirement (Rosenfeld, 2003). Habitat selection (ie. differential occupancy) occurs when an organism avoids a particular habitat (negative selection) or uses a habitat in greater 96 proportion than its availability in the environment (positive selection) Selective use of different habitats is often used to infer habitat preference. But true preference can only be estimated when the influence of extraneous factors like predation risk, competition, availability of different habitats etc. are controlled (Rosenfeld, 2003). Therefore, differential use of habitats in the wild is usually referred to as habitat selection rather than preference. On the other hand, habitat requirements are abiotic features of the environment that are necessary for the persistence of individuals or populations. The individual habitat requirement considers only the essential habitat conditions where individuals will achieve positive growth and reproduction. But the requirements for a population (fundamental niche) will include the habitat requirements of individuals and the metapopulation requirements such as landscape-scale features related to immigration and emigration rates between populations and the minimum population size (Pulliam 1988; Dunning et al. 1992) as well as broader regional constraints acting as conditional filters on species presence (Poff 1997). Most habitat models are based on covariation between environmental variables and habitat use in the wild (Rosenfeld, 2003). Stream habitats are strongly hierarchical (Frissel et al. 1986; Hawkins er al.1993), and habitat associations can be modeled at a variety of spatial scales. According to Rosenfeld (2003), there are usually three fundamental types of predictive models which can be used to define habitat requirements fi'om correlative data; distributional or macro habitat models, which predict the presence or absence of species at large spatial scales (eg., within different drainage basins);capacity models(multiple regression), which predict density or population size when a taxon is present (usually at the reach or channel unit scale);and microhabitat 97 models, which predict habitat associations at a fine spatial scale.(eg. water velocities and depths selected by different species). Bioenergetic habitat models for stream fishes have recently emerged as an additional class of habitat model (Hughes and Dill 1990; Guensch et al.200l). These models differ fundamentally from other model types in that they are inherently mechanistic (ie., their predictions are based on explicit biological mechanisms rather than observational data). In the present study Capacity (multiple regressions) models were used to develop the habit suitability index models of l0 critically endangered and endemic fish species in Kerala part of Western ghats. Regression models can be applied at any scale but are typically used to model fish abundance at the reach or channel unit scales. Multiple regression models give more insight into the critical factors that influence the abundance of each species than any other methods (Rosenfeld, 2003). Habitat suitability index models have a wide range of applications. To conserve the extreme fish gennplasm resources and endemism of Westem Ghats, declaration of aquatic sanctuaries and mitigation of anthropogenic activities development of habitat suitability index (HSI) models are very essential. With the help of this information, the species can be conserved in their natural habitats by way of maintaining the critical habitat parameters at threshold levels. These models are also vital in deciding the factors governing endemism. Habitat Suitability Index models are widely employed as an efficient conservation and management tool for conserving the stock of indigenous fishes (Hubert and Rahel, 1989). These models are also useful either in simulating the required habitat in other regions of the same river or demarcating identical habitats where the species can be transplanted. Suitability Index (HSI) models will give some technical guidelines for stream restoration and management activities. By the monitoring and 98 maintenance of the critical parameters deciding the distribution and abundance of endangered species an automatic ecosystem management will occur which will helps to maintain the physical, chemical and biological integrity of the river system and in effect reduce the ecosystem degradation. With this view the U.S Fish and wildlife service has developed a series of Habitat suitability index (HSI) models to describe and quantify habitat influences on the abundance of particular species (Terrell, 1984), which were immensely used for species conservation programmes. Even though the importance of HSI models in endemic and threatened fish diversity conservation are very clear from the remarkable progress happened in U.S.A, Canada and many European countries, unfortunately in India, there is no concreted effort has been done in this line. Studies on community level of fishes are rather very common in temperate systems (Ross, 1986), while tropical fish communities especially of the Southeast Asia, are thoroughly under investigated (Moyle and Senanayake, 1984; Wikramanayke and Moyle, 1989). Against this background, a pioneer attempt was made to isolate and identify critical controlling habitat parameters which govern the availability, abundance and endemism of l0 threatened freshwater fish species in Kerala such as Lepidopygopsis zfypus,H.micr0p0g0n periyarensis, Crossocheilus periyarensis, Osteocheilichthys longidorsalis, Puntius jerd0ni,Silurus wynadensis, Neolissocheilus mg/nadensis,H0mal0ptera pillai , Garra menoni and Mesonemacheilus remadevi . Habitat suitability Index models of these ten species were also established for a clear cut understanding of the relationship between a species and its enviromnent enabling understanding and managing human impacts on fish (Rosenfeld, 2003). An attempt was also made to evaluate the impact of National level policy of river interlinking on the L/\~ §Q-.\ 1/ ;Q 9 sustenance of threatened fish species. The resurgence of constructing the proposed hydel project across Kunthipuzha has evoked much controversy recently on the potential negative impacts on the aquatic ecosystem of this biosphere and therefore, in this study, the possibilities of obliterating fish habitats of Kunthipuzha and inter alia the extermination of endemic fish gennplasm due to the construction of the proposed dam has also been evaluated in the light of the HSI models of three species developed from Silent valley national park. 6.2. Materials and methods Materials and method used for the study is illustrated in chapter 2. 6.3. Results 6.3.1. Lepidopygopsis typus (Raj, l94lb)(plate 6. l) Order :Cyprinif0rmes Family :Cyprinidae Subfamily :Shizothoracinae This species is an endemic to the headwaters of Periyar river system and is commonly known as Peninsular hill trout. Because of its peculiar scale pattem through the lateral line this species is locally known as Bramnakanda. L. typus is a typical coldwater species of Himalayan origin and is the only species, which is found outside the Himalayan ranges and its existence in Periyar remains inexplicable (Arun, 1998). In periyar river system, the distribution ranged between Mukkar(90l9’27N and 770l6’30E )in the upstream having an elevation of l254m from the mean sea level and Thannikudy in the downstream(9°28’56N and 77°l6’22E ) having an elevation of l029m from the mean sea level. In the present study, specimens upto 25cm were collected. Menon (1999) included I00 this species under endangered (EN) category and Molur and Walker (l998) placed this species under critically endangered category. As per the IUCN categorization conducted in the present study, the species is coming under CR (critically endangered) category. Relationship between habitat features and species abundance Wide ranges of conditions were found in the 29 sites selected for habitat inventory studies in Periyar river system (Table 6.1). L.typus was found at 7 locations and the maximum recorded population size was 32.0ut of the 54 habitat variables studied 8 showed significant positive correlations with the abundance of this species (Table 6.5). Habitat Suitability Index models 8 habitat variables showing significant correlation with the species abundance were further evaluated by simple regression analysis to study the effect of each parameter on the abundance of L. zypus individually (Table 6.15). A single multiple regression model was developed for L. zypus using 8 habitat variables (Table 6.16) is as follows. Y = 0.618078 + 0.090476 B + 0.733442 C-0.00054 L+3.00l654 OS+ 2.767946 OV+ 0.057609 S- 48.0834 SL + 0.09624 T Where Y-Species abundance, B- Bed rock, C-Chute, L-Lux, OS-Overhanging stream boulders, OV- Overhanging vegetation, S- Total shaded area of the stream, SL- Slope, T Total tree cover The present regression model showed a significant correlation with the biomass of L. typus (R2 =0.s64733 P_<0.004717) 101 6.3.2. Gonoproktopterus micropogon periyarensis(Raj,l94 l a)(Plate 6.2) Order:Cypriniformes Family:Cyprinidae Subfamily:Cyprininae This is an endemic species to Periyar river and is commonly known as Periyar barb. Locally this species is known as Kariyan and is distributed in between Mukkar in the upstream (90l9’27N and 770l6’30E) having an elevation of l254m from the mean sea level and Thannikudy in the downstream (9028’56N and 770l6’22E )having an elevation of l029.m from the mean sea level. The maximum recorded size of this species was 50cm and is commonly using as a food fish. In the present study, specimens upto 27cm were collected. Menon (1997) and Molur and Walker (1998) included this species under endangered category. But as per the IUCN categorization, in the present study, this species is categorised as CR (Critically endangered) category. Relationship between habitat features and species abundance Of the total 28 locations studied in Periyar river system Gonoproktopterus micropogon periyarensis was foimd only at two locations and the maximum recorded population size was seven. Out of the 54 habitat variables studied, abundance of Gonoproktopterus micropogon periyarensis showed significant correlation with 7 parameters (Table 6.6). Habitat Suitability Index models Seven variables such as depth (D),midcharmel pools(MD), overhanging vegetations(OV), total shaded area(S),slope(SL), total instream cover(TC) and total tree cover(T) were further studied using single regression analysis(Table 6.15 ) as these parameters are having significant influence on the distribution and abundance of Gonoprktopterus 102 micropogon periyarensis (Y). A single multiple regression model was developed (R2=0.872885 P_<0.0047l7) (Table 6.17) which can be depicted as follows Y = 0.426997 - 0.08742 D + 0.027539MD + 0.837430V + 0.065797 S-8.17775 SL + 0.012339 TC - 0.02475 T 6.3.3. Crossocheilus periyarensis(Menon and J acb,1996)(Plate 6.3) Order;Cypn'niformes Fami1y;Cyprinidae Subfamily:Garrinae Commonly known as Periyar latia and is locally known as Karimbachi. This species is also an endemic to periyar and have a stratified distribution in between Mukkar in the upstream (9°l9’27N and 77°16’30E) having an elevation of l254m from the mean sea level and Thannikudy in the downstream (9°28’56N and 77°16’22E) having ah elevation of l029.m MSL. The maximum recorded size of the species is ll.5cm but in the present study specimens upto l3.4cm were collected. . Because of the smaller size, peculiar behaviour (sucker) and vibrant colouration, this species is getting some ornamental value. Molur and Walker (1998) categorised this species under vulnerable category while Menon (I999) listed this species under endangered category .ln the present study, this species was identified as one of the rare varieties among the 145 species identified so far from Kerala part of Western Ghats (Kurup et al., 2003) and as per IUCN categorization this species is treated under CRBI (Critically endangered, extent of occurrence estimated to be less than l00km2 and severely fragmented) category. I03 Relationship between habitat features and species abundance Of the 28 locations where the habitat inventoly and species assemblage studies were conducted in Periyar river system, Cperiyarensis was identified only from 3 locations. The maximum recorded population size of this species was seven. Out of the 54 habitat parameters studied 5 were showed significant correlation with the abundance of C.periyarensz's(Table 6.7). Habitat suitability index models Five habitat variables such as Lateral pool (LP), Large woody debris (LW), Overhanging vegetation (OV), scour out pools (SOP) and total tree cover (T) were identified as having habitat assessment value in the stream reaches where abundance of C. periyarensis (Y) was obsewed were further subjected to simple regression analysis to find out the extent of influence of each parameter individually (Table 6.15). The multiple regression model so developed (Table 6.18) is as follows Y=-0.52679-0.00702LP+0.859692LW+0.254735OV+0.13984lSOP+0.0l0297T The regression model showed a significant correlation with the biomass of Crossocheilus periyarensiS(R2=O.78362 P-<0.004l29). 6.3.4. Silurus wynaadensis(Day, l868)(Plate 6.4) Order:Silun'formes Family:Siluridae This species is commonly known as Malabar Silurus and in Kerala its distribution is recorded only from the headwaters mainly I order streams of Kabbini river system. It is locally known as Thonnivala or Wynadan mushi. This species is highly nocturnal and due to the increasing human intervention its distribution is restricted to some isolated patches 104 situated between Kattikunnu(l l030’42N and 76002’09E) in the upstream having an elevation of 879.m MSL and Aranagiri(ll°30’47N and 76°02’l2E)in the downstream having an elevation of 824m.The maximum recorded size of this species is 30cm(Menon,l999) and is a food fish. In the present study, the maximum recorded size was 20.2cm which is an indication of its endangerment. Molur and Walker (1998), Ku1up(2000, 2002) and Shaji et al. (2000) included this species under critically endangered category. While Menon(l999) included this species under rare category. As per the IUCN categorization conducted in the present study Swynaadensis is coming under CRB, 2a,b, c, d, e, 2D (critically endangered, extent of occurrence estimated to be less than l00km2,severly fragmented, continuing decline in the extent of occurrence, area of occupancy, extent or quality of habitat, number of subpopulations, number of mature individuals estimated to be less than 50) category. Relationship between habitat features and species abundance Wide ranges of conditions in respect of nature of microhabitat, instream cover, substrate and nature of riparian zone were found in the l5 sites selected for habitat inventory studies in Kabbini river system (Table 6.2).S. wynadensis was found only at two locations and the maximum population number registered was 8. Out of the 53 habitat variables studied, 7 showed significant correlation with the occurrence and abundance of this species (Table 6.8). Habitat Suitability Index models 7 habitat variables identified as critical in deciding the occurrence of this species were fiirther subjected to simple regression analysis to bring out the effect of independent parameter on the occurrence of Swynaadensis (Table 6.15). Subsequently, a single 105 multiple regression model was developed for Swynaadensis using 7 habitat variables (Table 6.19) which can be represented as follows: Y=-0.20-1 .01AT-0. 1 ICW-0.05 F V+0.3300SB+0.05TC+0.13TP+l.29WT Where Y-Species abundance, AT- Atmospheric temperature, CW-Channel width, PV Flow velocity, OSB-Overhanging stream boulders, TC- Total cover, TP- Trench pool, WT-Water temperature The regression model so developed showed a significant correlation with the occurrence of S. wynaadensis (R2 =0.75 P_<0.0805) 6.3.5. Neolissochilus wynaadensis(Day,l873)(Plate 6.5) Order: Cyprinifonnes Family: Cyprinidae Subfamily:Cyprininae Commonly known as South Indian barb having a fragmented distribution only at the headwater streams of Kabbini river system in Kerala. This species is locally known as Manjakadanna. It is highly sensitive to physical and chemical habitat variables and having comparatively good abundance at Kattikunnu I (1 1°30’42N and 76°02’09E ele.879m.), Kattikunnu 11 (ll°30’59N and 76°02’06E ele.862m.)Aranagiri(ll030’47N and 76°02’12E ele.824m.)Thariyod (ll°38’10N and 77°58’43E ele.796.5m.) and its adjoining areas. Due to the increasing human intervention the population of this species showed a drastic decline in the past three years. The maximum recorded size of this species was 25cm (Menon, 1999; Talwar and Jhingran, 1992) while in the present study specimens only upto l7.4cm could be collected from its place of inhabitance which is f 106 indicating of its endangerment. Even though this species is having the utilization status as a food fish because of its attractive colouration it also gaining some omamental importance Molur and Walker (1998) and Shaji er al.(2000) described this species under endangered category while Menon(l999) included this species under rare category. As per the IUCN categorization conducted in the present study N. wynaadensis belongs to E,Bl,2a,b,c,d,e, D (endangered, extent of occurrence less than 5000km2,severly fragmented, continuing decline in the area of occurrence, extent and quality of habitat, number of subpopulations and number of mature individuals estimated to less than 250 ) category. Relationship between habitat features and species abundance Of the 15 locations studied N. wynaadensis was reported from 4 locations and the maximum population size recorded was l5.0ut of the 54 habitat parameters studied four habitat variables showed significant positive correlation with the occurrence of N.wynadensis while two variables have significant negative correlation with the availability of the species (Table 6.9). Habitat Suitability Index models The relationship between Nwynaadensis and variables such as Alkalinity (A), channel width (CW), hardness (H), lateral pools (LP), overhanging stream boulders (OSB) and plunge pools (PL) were further examined using simple regression analysis (Table 6.15) .The single multiple regression model so developed (R2=0.82 P_<0.0l22) (Table 6.20) can be expressed as follows: Y=7 .62-0.38A-0.007CW-0.5H+0.1LP-0.300SB-7.7PL Where Y=Species abundance 107 6.3.6. Osteochilichthys l0ngid0rsalis(Petiyagoda and Kottlet,l994)(Plate 6.6) Order: Cypriniformes Family: Cyprinidae Subfamily:Cyprininae It is an endemic species to Kerala and is described only from the headwaters of Chalakudy and Pooyamkutty river systems .The common name of the species was long fimied barb while it is locally known as Kadimeen or Modon. In Chalakudy river system, the distribution of this species is limited in between Kuriarkuuty((l0°24’26N and 76°43’ l4N ele.524m.) in the upstream and Athirappaly in the down stream(l00l7’53N and 76°34’ 17E ele.l04m.).In pooyamkutty river system this species is distributed from Puraldcallu (l0008’48N and 76047’20E) in the downstream towards the upstream reaches. The maximum recorded size of this species was l3.5cm while in the present survey specimens upto36cm were collected. Even though the species is treated as a food fish the young ones have some omamental value Molur and Walker (1998) included this species under critically endangered category. Biju et al. (2000) and Thomas er al. (2002) described this species under endangered category. As per the IUCN categorization conducted in the present study this species is coming under E, B, 2a,b, c, d, e, D (endangered, extent of occurrence estimated to be less than 5000km2, continuing decline in the extent of occurrence, extent and quality of habitat, number of subpopulations and number of mature individuals less than 250) category. Relationship between habitat features and species abundance Wide ranges of conditions in respect of nature of microhabitat, instream cover, substrate and nature of riparian'~ zone were found in 108the 20 sites selected for habitat inventory studies in Chalakudy river system (Table 6.3) .In Chalakudy river system, out of the 20 locations studied, the presence of O. longidorsalis was encountered only at 5 locations. In Pooyamkutty tributary, out of the 5 locations surveyed, Olongidorsalis was located only from 2 stations. Highest population number recorded was seven and out of the 54 habitat parameters studied, the abundance of Olongidorsalis showed significant correlation with six parameters (Table 6.10). Habitat Suitability Index models In the case of Olongidorsalis, six habitat variables such as abandoned channel (ABC), backwater (BW), emergent vegetation (EV), glide (G), overhanging stream boulders (OSB) and charmel width (CW) were found important in developing habitat assessment value in the stream reaches where abundance of Olongodorsalis (Y) was observed(Tab1e 6.15) . The multiple regression model so developed (Table 6.21) can be expressed as follows Y=-0.104+0.l49ABC+4.82BW+0.179EV+0.l23G-I-0.09OSB-0.09CW The regression model showed a significant correlation with the abundance of Olongidorsalis (R2=0.89,P-<0.0000l). 6.3.7. Puntiusjerdoni (Day, 1876) (Plate 6.7) Order: Cyprinifonnes Family: Cyprinidae Subfamily:Cyprininae This species is described from Chalakudy river system and is commonly known as jerdon’s barb. Locally\ this~ species is known as109 Chameen or tolu. Its distribution range extended from Kuriarkutty(l0°24’26N and 76°43’l4N ele.524m )in the upstream and Athirappally (l0°l7‘53N and 76°34’l7E ele.l04m)in the downstream. The maximum recorded size of this species is 46cm (Talwar and Jhingran, 1992) and in the present study the maximum recorded size was 30cm. Even though the larger specimens are known as a food fish the young ones are having good ornamental value with comparatively high market price. Menon (1999) treated this species under endangered category while Biju er al.(2000) described this species from Bharathapuzha,Chandragiri, Chalakudy and Meenachil river systems and treated under vulnerable category. As per IUCN categorization conducted in the present study this species is coming under E, B, 2a,b, c, d, e, C2a (endangered, extent of occurrence estimated to be less than 5000km2, continuing decline in the extent of occurrence, extent and quality of habitat, subpopulations and number of mature individuals estimated to be less than 250) category. Relationship between habitat variables and species Out of the 20 locations studied the species was identified only from 3 locations and the maximum recorded population size was 5.0ut of the 54 habitat parameters studied the abundance of this species showed significant correlation with five parameters (Table 6.] l). Habitat suitability index models In the case of P.jerdom', five habitat variables such as abandoned channel (ABC). Cascade(C), rocky substratum(R), alkalinity (A) and channel width (cw) were identified as having habitat assessment value in the stream reaches where abundance of P.jerd0m' (Y) was observed (Table 6.15). The multiple regression model so developed (Table 6.22) is as follows: 110 Y=-0.38+0.34ABC-0.04C+0.03R- 0.45A +.04CW The regression model showed a significant correlation with the abundance of P.jerd0m'(R2=0.78, P-<0.0003). 6.3.8. Mesonemacheilus remadev:'(Shaji,2002)(Plate 6.8) Order: Cypriniformes Family: Balitoridae Subfamily:Nemacheilinae This is an endemic species to Kerala and is recently described by Shaji et al. (2002) from the silent valley region of Kunthi river system. The distribution range of the species extended from Valiya Walakkad (l l08’4lN and 76025’l8E ele.995m) in the upstream and Synendr (ll°5’49N and 76°26’44E ele.100lm) in the downstream. During the present study specimens having a total length of 6.8cm were collected. As per utilization status this species coming under ornamental category and based on the IUCN categorization it comes under CR, Bl (critically endangered, extent of occurrence estimated to be less than l00l Relationship between habitat variables and species Wide ranges of conditions in respect of nature of microhabitat, instream cover, substrate and nature of riparian zone were found in the 27 sites selected for habitat inventory studies in Bharathapuzha river system (Table 6.4)Mremadevi was found only at 5 locations and the maximum population number registered was sixteen. Out of the 54 habitat variables studied, 6 showed‘ significant 111 positive correlation and 3 having significant negative correlation with the occurrence and abundance of this species (Table 6.l2 ). Habitat Suitability Index models 9 habitat variables identified as critical in deciding the occurrence of this species were further subjected to simple regression analysis to bring out the influence of each parameter on the occurrence of Mesonemacheilus remadeviensis individually (Table 6.15). Subsequently a single multiple regression model was developed for Mesonemacheilus remadeviensis using 9 habitat variables (Table 6.23) which can be represented as follows. Y=1.95-0.08B+0.07BE-0.04C-0.l2D+3.05DI+0.2lG+0.24LWD+0.21R-0.29SWD Where Y-Species abundance, B- Bare ground,BE-Bedrock, C-Cobbles, DE-Depth, DI Dissolved oxygen,G-glide,LWD-large woody debris,R-Riffle,SWD-Small woody debris The regression model so developed showed a significant correlation with the occurrence of M. remadeviensis (R2 =0.86 P_ 6.3.9. Homoletera pillai(Indira and Remadevi, l98l)(Plate 6.9) Order: Cypriniformes Family: Balitoridae Subfamily:Balitorinae This is an endemic species to Kerala and is recorded only fi'om the headwaters (Silent valley) of Kunthi river. It is commonly known as Silent valley loach and is locally known as Kallepatti.The distribution range extended between Valiyawalald(ad(l l08’4lN and 76°25’l8E ele.995m) in the upstream and Puchappara (1l°06’5lN and 76°25’50E ele.945m) in the downstream. The maximum recorded size of this species is ll2 7.5cm(Menon, 1999) and in the present study specimens upto 6.2 cm were collected. The utilization status is only as an ornamental fish and as per the IUCN categorization conducted in the present study this species included under CRBI (critically endangered, extent of occurrence estimated to be less than l00km2 and severely fragmented) category. Relationship between habitat variables and species Out of the 27 locations studied occurrence of H.piilaz' was recorded only from 2 locations and the maximum population size recorded was six.Among the 54 habitat parameters, six habitat variables showed significant positive correlation with the occurrence of H.pillai while one variable have significant negative correlation with the availability of the species(Table 6.14). Habitat Suitability Index models The relationship between H.pz'llai and variables such as Bedrock (B), cobbles(C), dissolved oxygen (DO), glide (G), large woody debris (LWD), shrub cover (SC) and small woody debris (SWD) were fiirther examined using simple regression analysis to bring out the influence of each parameter individually (Table 6.15) .The single multiple regression model so developed (R2=0.9 P_<2.464)8) (Table 6.24) can be expressed as follows: Y=-0.136+0.076B-0.003C+|0.05D0+0.08G+0.1l9LWD+0.059SC+0.4l8SWD Where Y=Species abundance 6.3.10. Garra menoni(Remadevi and Indira,l984)(Plate 6.10) Order: Cypriniformes Family: Cyprinidae Subfamily:Ganinae t ll3 This species is strictly endemic to Kerala and in the present study it is recorded from the headwaters (Silent valley) of Kunthi river system. The distribution range extended from Valiya Walakkad (1 l"8’4lN and 76°25’l8E ele.995m) in the upstream and Synendri(l l°5’49N and 76°26’44E ele.lO0lm) m the downstream. The maximum recorded size of this species was 6.9m(SL) while in the present study specimens upto 7.4.cm TL were collected. This species is an ornamental fish. Menon (1999) treated this species under rare category while according to Biju et al. (2000) this species coming under endangered category. As per the IUCN categorization conducted in the present study this species is coming under EN, Bl (endangered, extent of occurrence estimated to be less than 500010112 and severely fragmented population) category. Relationship between habitat variables and species Among the 27 locations studied, this species was recorded only from 4 locations and the maximum recorded population size was thirty six. Out of the 54 habitat parameters studied occurrence and abundance of G.men0ni showed significant correlation with 6 habitat variables (Table 6.14). Habitat Suitability Index models The 6 habitat variables such as bedrock (B), dissolved oxygen (DO), glide (G), large woody debris (LWD), shrub cover (SC) and small woody debris (SWD) were found important in developing habitat assessment value in the stream reaches where abundance of G. menoni (Y) was observed (Table 6.15). The multiple regression model so developed (Table 6.25) can be expressed as follows: ll4 Y=-0.5+0.056B+0.62DO-0.008G+0.204LW-0.04SC+0.99SWD The regression model showed a significant correlation with the abundance of G. menoni (R2=0.92, P-<8.98"°). 6.4. Discussion Populations of many endemic and rare fishes in the Westem ghats streams occur as fragmented populations isolated in headwater tributaries. Understanding the factors that determine why they persist in some areas and not in others is a major challenge for conservation research (Rieman and Dunham, 2000). Studies on the microhabitat of some critically endangered species should reflect those habitat conditions, which are most critical for preserving fish populations Results of the present study showed that some of the physico-chemical habitat parameters like nature and distribution of different channel geographical units, instream cover, substrate, riparian cover, etc. are acting as critical parameters on the occurrence and abundance of these endangered species and this finding is complementary to that of Sreevastava and Sarkar(l997)that in freshwater lotic ecosystems , physical habitat plays major role in species assemblage than chemical variables. According to Hubert and Rahel(l989), physical habitat or abiotic habitat variables are believed to influence both the occurrence and biomass of fishes in stream systems, but these relations are not well understood for majority of the fish species. The present study revealed that L. typus tolerate only a narrow range of environmental conditions and is found as a highly habitat specific species. Abundance of L.typus showed a positive correlation with amount of bed rock substrate, chute type channel geographical unit, overhanging boulders, overhanging vegetation, total shade and tree cover and negative correlation with light intensity and slope. The affinity of the species to I15 bedrock type substratum is identical with the findings of Ziller(l992) who recorded a positive correlation between abundance of bull trout and larger substrates. The positive correlation of the species to overhanging stream boulders indicates that they are using overhanging stream boulders as hiding structures, which is in agreement with the findings of McPhail and Murray (1979), Ptolemy (1979) and Shepard er al. (1984) who recorded that occurrence of bull trout showing positive correlation to undercut banks. Hubert and Rahel(l989) found that abundance of Longnose dace is positively correlated to the overhead cover which is in complaince with the positive correlation of L.zypus with overhanging vegetation. The penchant of Ltypus to total shade is identical with the findings of McMohan(l982) who reported a positive correlation between creek chub and total cover in the streams. The positive correlation between tree cover and the abundance of L. typus is corroborating with the observation in bull trout with tree cover (Watson and Hillman, 1997). The negative correlation of L. typus with slope is in well agreement with the findings of Moshenko and Gee (1973) who reported a negative correlation between stream gradient and abundance of creek chub. Optimum habitat of H.micr0p0g0n periyarensis was found as midchannel pools with moderate depth, overhanging vegetation, less slope and excellent shade. The negative correlation of H.micr0p0g0n periyarensis with depth and positive correlation with midcharmel pools clearly indicate that this species prefer only pools in flowing water ecosystems and there is no preference towards deep dammed pools which is corollary with the findings of Minckley(l963) and Scott and Crossman( 1973) who reported that white sucker occur most frequently in pools, backwaters and slow sections of streams. The present finding also unravel the complexity that why this species is not showing 116 distribution in the Periyar lake even though it is abundant in the associated streams. The affinity of H. micropogon periyarensis with midchannel pools is in well agreement with the finding s of Watson and Hillman (I997) who observed that abundance of bull trout is positively correlated with the frequency of pools in streams. The direct proportionality between total shaded area of the riparian zone and the abundance of Hmicropogon periyarensis is identical with the findings of Hubert and Rahel(l989) who established a positive correlation between standing stock of white sucker and total shaded area of the stream. The negative correlation of H. micropogon periyarensis with the slope is similar to the findings of Hocutt and Stauffer (I975) who observed that creek chub is very abundant in low gradient streams. C. periyarensis is most abundant in scour out pools with enough woody debris, overhanging vegetation and tree cover. The positive correlation of C.periyrensz's with scour out pools is identical with the strong positive correlation between the abundance of bull trout and scour out pools (Watson and Hillman, 1997). Dare et al. (2002) reported that biomass of cutthroat trout and brown trout showed a strong positive correlation with the presence of pools. The strong positive correlation between C.periyarensis and large woody debris is in complaince with the findings of Hubert and Rahel(l989) who observed a positive correlation between biomass of white sucker and large woody debris. The positive correlation between the abundance of C.periyarensz's and overhanging vegetation is corroborating with the findings of Hubert and Rahel (1989) who observed a positive correlation between the biomass of longnose dace and overhanging cover. Talmage er al. (2002) reported that woody debris and overhanging vegetation provide fish communities with cover, temperature stabilization, food source and reduced fine ll7 sediment. Angermeier and Karr (1984) revealed that in spite of contributing shelter and food woody debris contributes to the local physical complexity of the stream and can form pools in stream channels. The affinity of C.periyarensz's with riparian zone with good tree cover is in well agreement with the findings of Buckman et al. (1992) who observed a positive correlation between riparian tree cover and occurrence of bull trout. S. wyndensis can tolerates only a narrow range of habitat parameters and was found as a highly habitat specific species. Biomass of S. wyndensis showed a positive correlation with total instream cover, trench pool, water temperature, and overhanging stream boulders which is strongly concur with the findings of Kavaliers (1982) who reported that biomass of white sucker showed a strong positive correlation with total instream cover in its natural habitats. The relationship between instream cover and species distribution seen in the Habitat Suitability Index models of S. wynadensis is in compliance with the findings of Copes and Tubbs (1966) who observed that there exist a strong positive correlation with instream cover and the distribution of creek chub. Distribution and abundance of S. wynadensis showed negative correlation with temperature, channel width and flow velocity. The negative correlation seen in S. wynadensis with flow velocity corroborated with that of creek chub in the horse creek drainage of United States (Hubert and Rahel, 1989). The relationship between channel width and distribution of S. vgynadensis also showed agreement with that of common shiner whose abundance was more in small streams having 7-10m width. Nevertheless, this attempt being a pioneer in this line, there is no scope to compare the present HSI with previous findings of any fish species of Western ghat streams. The present study revealed that the high degree of habitat specificity shown by the fishes studied poses one of the major reasons for the 118 endangerment of this species and any severe alteration in these critical parameters in future would leads to their extermination from the universe. The results revealed that the optimum habitat of N. wynadensis was lateral and plunge pools with less channel width, low alkalinity and hardness conditions. The affinity of N.wynadensiS towards the presence of plunge pool conform with that of creek chub whose distribution and abundance showed a strong correlation with the presence of riffles and plunge pools (McMohan, 1982; Hubert and Rahel, l989;Barber and Minkley, 1971 and Moshenko and Gee, 1973). The strong positive correlation between Nwynadensis and small sized stream is identical with the strong positive correlation between the biomass of common shiner and small to medium sized streams by Lee et al. (1980) and Trial et al. (1983). It is interesting to note that the distribution of O.longidorsalis was positively correlated with abandoned channel, backwater pools, emergent vegetation, glide and overhanging stream boulders and is negatively correlated with channel width. Talmage et al. (2002) reported that overhanging vegetation provide fish communities with cover, temperature stabilization, food source and reduced fine sediment. A positive correlation was observed between the distribution of O.longidorsalis and emergent vegetation and these findings are very much in agreement with that of Moyle (1973) in common shiner at Minnesota lake where the species abundance showed strong positive correlation with aquatic vegetation. In the present study, a positive correlation between the distribution of O.longidorsalis with backwater pools was established and these findings is concurring with that of Hubert and Rahel(l989)in longnose dace and Dare et al. (2002) in culthroat trout and brown trout. 119 P. jerdoni was found in abandoned channels of Ill order streams with good channel width and rocky substratum and its abundance was negatively correlated with alkalinity and cascade type instream habitat. The positive correlation shown P.jerdom' and channel width is similar to the finding s of Rich et al. (2003) in Bull trout. Moreover, the positive correlation reported in bull trout with large substrate and slow water habitat(Watson and Hillman ,l997)is in conformity with that of Pjerdoni with rocky substratum and negative correlation with cascade type instream habitat Among the three species studied, M.remadevi can tolerates only a narrow range of habitat parameters and is found that out of the 54 habitat parameters studied occurrence of M. remadevi showed negative correlation with bare ground (river banks without vegetation), cobbles type substratum and depth. On the contrary, the species showed positive correlation with bedrock type substratum, dissolved oxygen, riffle and glide type microhabitats, large and small woody debris. The negative correlation of M. remadevi with bare ground is in concurring with the findings of Thompson and Hunt (l930) and Kavaliers(l982)who reported a positive correlation between shaded area and the occurrence of white sucker. Moreover, the positive correlation reported in bull trout with large substrate (Watson and Hillman, 1997) is in conformity with that of Mremadevi with rocky substratum and negative correlation with cobbles. The strong positive correlation shown by M. remadevi with that of woody debris is identical with the positive correlation shown by bull trout (Rich et al. 2003) and white sucker (Propst, 1982b) to woody debris. The positive correlation of Mremadevi with that of dissolved oxygen level is in well agreement with the that of Salmo salar which showed reduced sustainable swirmning speed when dissolved oxygen concentration falls between 4 and 5 mgl'l I20 (Cowx and Welcomme,l998). The positive correlation shown by Mremadevi to riffle and glide type of channel geographical units is showing resemblance with that of creek chub which are showing a positive correlation with streams with altemating pools and riffle —-run areas (Moshenko and Gee, 1973). This indicates that the optimum habitat of Mremadevi was flowing water with altemating riffle and glide type of microhabitats, bedrock type substratum, good dissolved oxygen concentration, moderate depth, good riparian vegetation and instream cover with good strength of large and small woody debris. As a result of the dam construction there should a loss of riverbank vegetation and it may converted to bare ground, which will badly affect the species. The formula developed as part of this HSI model also reveals that with the increase of depth there are also chances for the decrease in the population size of this species. The strong positive correlation with bedrock and negative correlation with cobbles indicate the species abundance will decline with the reduction in the size of the riverbed material and with the construction of dam the substratum may entirely change into muddy type which will adversely affect the species. The level of dissolved oxygen, the most important parameter affecting this species, will drastically reduces with the construction of the dam. The typical microhabitats in flowing water ecosystems such as riffle and glide, which are having strong influence on the species will completely vanish as a result of dam construction. The typical hiding places such as large woody debris and small woody debris will loss as a result of dam construction. All these results lend support the fact that with the construction of dam, M. remadevi would disappear from Silent valley national park. I21 Occurrence of H. pillai showed positive correlation with Bedrock, dissolved oxygen level, glide type microhabitat, large woody debris, small woody debris and shrub cover and negative correlation with cobbles type substratum. The positive correlation shown by H.pi1lai to Bedrock type substratum and negative correlation to cobbles are in well agreement with the findings of Fontaine (1987) who found that rock structures with greatest number of crevices held the highest winter densities of salmon. The positive correlation shown by H.pillai to that of small and large woody debris is concuning with the findings of Tschaplinski and Hartman (1983) who reported a strong positive relationship between the volume of woody debris and the number of juvenile coho salmon Onchorhynchus kisutch during winter season in sections of Camation Creek, British Coloumbia. The positive correlation of H. Pillai to the level of dissolved oxygen is in compliance with the findings of Cowx and Welcomme(l998) who reported that the overall dissolved oxygen concentration required for salmon is at least 9mg/l.The positive correlation shown by H.pillai to glide type of channel geographical unit is in well agreement with the findings of Scott and Crossman(l973) who reported that the VVhite sucker prefer the slow sections of streams. The positive relationship of H. Pillai to shrub cover is identical with that of Watson and Hillman (1997) who reported a positive correlation between the abundance of bull trout and shrub cover. As a result of dam construction the bottom material will definitely converted to fines (mud) and other variables such as glide, shrub cover, large woody debris, small woody debris etc. will completely vanish from the aquatic system. On the other hand, the level of dissolved oxygen will decreases as a result of dam construction. 122 The occurrence of G.men0m' showed positive correlation with bedrock, dissolved oxygen level, large woody debris and small woody debris and negative correlation with glide type microhabitat. The positive correlation of G.men0m' with bedrock type substratum is in compliance with the findings of Huber and Rahel(l989)who observed a positive relationship between white sucker abundance and bedrock type substratum .The positive correlation between the occurrence of G.men0m' and dissolved oxygen level is identical with the strong positive correlation established between the biomass of Leuciscus cephalus and dissolved oxygen level (Cowx and Welcomme,l998).The negative correlation of G.menoni to glide type channel geographical unit indicated its affinity to fast flowing channel geographical units which is in well agreement with the high water velocity requirement of Chondrostoma nasus(50-1 l0ms-l) reported by Cowx and Welcomme(l998). The positive correlation of G.men0nz' with woody debris is in complaince with Watson and Hillman (1997) who reported a positive correlation between woody debris and the relative density of Bull trout. Goetz (1989) and Martin et al. (1992) reported that woody debris provide concealment cover and possibly increasing the carrying capacities. But after dam construction the level of bedrock type substratum, dissolved oxygen level, large woody debris, small woody debris and shrub cover showed a reduction which became a malediction to this species. The multiple regression models presented here are the first quantitative descriptions of the relationship between abiotic habitat features and the distribution and abundance of L. typus, Hmicropogon periyarensis and Cperiyarensis in the headwaters of Periyar river system,Silums wynadensis and N. wynadensis in the head waters of Kabbini river system, 0.l0ngidorsalz's in the headwaters of Chalakudy and Pooyamkutty river systems, 123 P.jerd0m' in the headwaters of Chalakudy river system and Mremadevi, H.Pz'llai and G.men0m' in the headwaters of Bharathapuzha river system. The multiple regression models also revealed that along with community structure, habitat also plays a crucial role in the distribution and abundance of each species. This study also identified the critical stream habitats necessary for the persistence of these species. Freeman er al. (1997) reported that although fishes respond simultaneously to multiple habitat variables, it is also likely that some variables can strongly influence the microhabitat use than others. But it is also important to identify and protect the processes that ultimately generate and maintain these features (hnhoff et al., 1996; Roni et al., 2002). Similarly, though this study focuses on habitat, it is equally important to recognize that there are critical non habitat factors such as illegal fishing activities and invasion by exotic species which were also strongly influencing species persistence. Dyer er al. (I998) reported that anthropogenic activities brought about changes in the physical conditions of the streams, thus leading to the degradation of fish communities, which is magnified by reduced species richness and decreased biotic integrity. If knowledge on critical habitat issues of each species is deficient, research efforts need to be directed at defining less ambiguous habitat suitability criteria. Hence management on fish and wildlife remains centered on an accurate understanding of habitat requirements as supported by Rosenfeld (2003). Another very significant implication of this study is on the National Policy of river linking. The results indicate that the linking of rivers will permanently alter the HSI indices of fish species, which are now protected by the individuality of the rivers. Any such interlinking would bring about severe alterations of habitat parameters such as flow velocity, nature of substratum, type of microhabitat and vegetation governing the 124 presence of these fishes and consequently there is every possibility of extinction of these species from the universe. No attempt has made to find out the reason of endemism in fishes related with HSI in the Indian context and therefore this subject was never surfaced while taking policy decisions on the fate of Indian rivers. The present information may dissuade the policy makers from interlinking rivers with such endemic fish habitat with other river systems, which would potentially damage such HSI factors and interalia the extermination of these species. The result of the present study also revealed that the construction of the proposed Pathrakadavu dam will adversely affect the aquatic ecosystem of Silent valley National park and many endemic species will vanish from Silent valley. Even though the dam is coming 500m away from the boundary of the Silent Valley National park, the proposed place and the silent valley is coming under the same class such as High hill zone (600 1200), based on the distribution of fish species in Western ghat streams (Manojkumar and Kunip, 2004) which indicate that the distribution of the above said rare and endangered species may extend upto Pathrakadavu region. There are numerous evidences in the history for the direct impact of dams on the aquatic ecosystem. Osborne (2000) reported that the Aswan high dam on Nile valley downstream constructed on 1964 with a view to ensure regular water supply to the fertile Nile valley downstream and to generate electricity for the industries in Egypt. But after dam construction the water supply was not increased as much as hoped and on the other hand the dam acts as a sediment trap, and the sediments that previously built up the rich, alluvial soils of the Nile valley now accumulates in the reservoir and the productive sardine fishery in the Mediterranean, off shore from the Nile delta, has been fully collapsed. Kanehl et.al. (1997) studied the 125 changes in the habitat and fish community of the Milwaukee fiver, Wisconsin, following the removal of the Woolen mills dam and found that construction of Woolen mills dam in the Milwaukee river in United states leads to the habitat quality loss, poor biotic integrity, reduction in the population of endemics such as small mouth bass Micropterus dolomieu. and a rampant increase of exotics such as Cyprinus carpio was noted after the commissioning of the dam. While the dam was removed during 1988 and five years after that habitat quality was excellent, small mouth bass abundance and biomass had increased substantially, on the contrary, common carp abundance and biomass had declined drastically, and biotic integrity was good. Kurup et al. (2004) reported similar situation from the Periyar lake in Kerala, where the endemic critically endangered species like Lepdopygopsis typus,G0n0prkt0pterus micropogon periyarensis and Crossocheilus periyarensis were completely disappeared from the lake region and now only limited to the head water streams. While in the lake, more than 66%(2003) of the fishery is contributed by two exotics such as Cyprinus carpio and Oreochromis mossambicus. So before the construction of the proposed Pathrakadavu dam its impacts on the economic and ecological environment begs the question: what price for development? This question can only be answered by carrying a detailed environmental impact assessment programme. 126 Table 6.l.Physical and chemical variables measured at 30 stream sites in 777 Periyarriver during the period from January 2001-January 2004. 7 Habitatirariables 5 V Range _Reach descriptions 77 77 77 7 77 7777 Sinuosity 7 7 7 77 1-1.47 7 _77 Entrenchment ratio 77 77 11-2 77 777777 IslopeW/d ratio 7 _5 70.5-5.7 0.01-0.15 Biparian 10110 so o 7 _ 5 1 7Shrub cover along ban!<7(7‘@77 77-93 Iree cover along bank(%)7 7 7 3-72 L, 18816lSubstrates _ 9101“! . ,_,@0091 ba0*<<%>'7 ,, t_ 4 1°-725 __ _ 'Fines(%)7 7 770-89 1 %57ra7ve7lfl1/<1)Qobbles (°/o)77 7 7_ or7707-32 170-425" Rock(%)Boulders(%) 77 7 _ 7770-39 10-82 _7Bedrock(°@LInstream cover 77 7 7 7 0-770 u »7'[urb7uIance(%7) 7 7 77 O-25 7 _D°Flth(%) 1 , 77‘a5'33 >4 ‘ 05:! 1SmaIlwooo_;Lgebr7ig%) 70-1 it 4-L 1__argewoodydebri$(%) 77 10-5 5 7Oy7erhangin7g vegetation7(%) 7 77 7 0'5 77 {Submerged vegetation(%) 77 7 70-10 — -—+ *7 Emergent ve7geta7tion§%) 7 Q-5 HF|oat7ingvegetation(%) 7 77 77 77 '0-5 )1 tTurbu7l7ant white water boulders(f’/3L 7 L0-10 .$°°"'°"*E°°|§(%>)t 1 1 77 f0-10 bverhanging streamibouloers(°7/0) 77 77 70-55 77 1 177U7ndercut7ban7k(%L 7 77 7 7 0-5 1101-1 000*-11"/g) 1 1 11-00 77Channel ggograghieal units 1 7 77 ?Fa11s<‘i/<1 1 1 _' 0-80 7_Cascadg%) 77 7 70-1779.6 5 'HBapids(%L 0-61.88 *7Ri7ffle(%)_7 7 7 77 10-378.5 Z 51 17000100/=> o 7_ *0-6.2 Sheet(%) A 0-2.64 Edd>4%>~Run<%> 00-55-011 0 __ 00” 0 0_Trench(%) T 0-1 1 H MidchanneI(%) 0 0-77.2 ; Pocket water p00ls(%) 0-0 ___ ¢Cinvergence(%) L0-0—v—————'77———7 7-T 77 — _G|idl__$ _ _ 0____ 00-0 Lateral p00ls(%) 1‘0-1 1.7 * Pwn9e(°/<>) 0-32-i_,-0 Debris(%l _ ___ J0-00 K K K K i Landslide(%) \ 0-100 Backwater(%) 0-0 L Abandened channels(%) 0-30.9 Water qualitiparameters 0-0 Air temperature(OC) 2633 F pHWater te1111> O O O O O (D O O CD Q O O Q C O O O O Q M C Sheet(%) -0 Run(%) ¢ 100 EddyL(%) _ % j -01 Trenph(%) _ %__ - 52.4 Midchanne|(%) __%? U _ 84.9 Pocket water poc{!§(°k) - 55-2 J Cinvergence(??‘4>L M :0 Glide(%)___? - 32.1 -60 Latefaj pools(%) E J L B|U"9e(%) ?Debris(%) _ % %Landslide?(?%) j W < 1 Backwat§_[§%) _ \_ W I Abandene<_ichannels(%) M 6 [1 Water qgality 0 §Airtemp<-:1-rature( C) %_ _ 20.5 -632.6 VV?a1er temperatu_[e§0 WC) M H 18.2 - 32 _EH 1 _ 6__1 6.9 - 7,6 Disso|ve?q_ox1gen(mgfl) ml 7 566-161 §Tota| hard[1ess(mgl|) W H9-20 Total alkaljnitylmgfl) { M LL 2-10 Flowjvelocatflm/s § _L :[_ 0 - 0:66 6.1 Mean .channel )widtljm) \ > ‘ { % 166 Mean chanel dep?th(m) M 1 1.04 - 16 C3 O CD CD o Q Q O O C O O O O | | | @ Q @ CD 9° <0 Table-6'.3.Physica| and chemical variables measured at 20 stream sites in ‘IA _{ * _Ch_ala1gud1 "— * * river *7 gluring_t_he V ‘ * period "* fromW January *** 2001-January ‘** ' W’ Z004, *_ _M ‘\ ul*‘!'liF°F'@'i=b'°$e it _' e £ _ Raves __ _ ear HsinuosimHRea<=h qesgripgiops *‘ i '_ eW " _ -111-5 e t _ _ __ K _i _ _ _ _ Q__ ,4 r_\EKn_trenchrner;1tratio _ ii _{O.7f6?-;I.9i ______{J-\ =e~—sFS|Q_pewid ratio L~ i _ as- _ _ t E” aw9.001-9.1? so.5-35.75 e as I _— _ _— ___ -_ Ww ” EFF-'i=!"1°"~= 7 w, _ 1 i _ _ _ _ are r_$hfUPC0V8f_alQ"lb8I1K(%) Q -30 ______Tree cpver al9ng_ba_r1k(‘j/31 1 _75 - 95 i » *§ar@ wound ame b§"k(‘Z=»L -,t_ _ ° -2° ~ Substrates» _ — — _ — —J -. AG'aY?'$§%LaT r_ _ e a _ K ;25 A gouldesczg)9°°e°e'°$lf’/"2 a _ _ ae 7 ”_*7 i°1 l e -Ya e iR°°'<(f/0) e K ‘i e _ _'§8 _ _ _ _ W4 B@9w<;I<fl1c%; I L T at-_98_ 1 _ _ _ 1 _ “ ;$ma"w<>Qd1d,¢bfi§(‘ZQ as I _-141*» 1 _ _ _ _ _ Hiarge g¢oo;dyiciebris§fA>l_ __ H W L s_-114.4 ______% _ hi @v§rhanginQveQetatiorl%) _ %fi% _ _ _'9§5.2__ 1 _ _ _ _ L 1*SubmeLge:dveg§tation§%l_ _ _H _ _ -0_ f % __ _ L {Emerqent\;e@tat|og_f/0) _ l ( f _-s5?6_.5__ M __ _ _ W i,F{|oatinQ_vege?tjatiQn(f%)f _ _ i _ i ?__ _ ~i f f _W 0 _ _ __ _\ »eTq_rbuIanfv1hite v@1erb<>uIder§(%] _ _ 153-6 W ______“$,<> OOCDO O COO OOOCJOCDOQCD COO (DOC ea} e I L4 ~$"9°*§%l_ _ _ _ 14%,1_ _ _ i.. 0 7 7 7 j l MR}1"i%L ______,_ _j ‘i 1 ;-13-8( 1 _ 1 1] \*E¢d¥! l W _ _ H 0/0 ‘ 2 - 17.1 [fre|jch(%l______w [F -0 ‘ \1Mid¢"a""e'(i4>> W _ _ "-100 ‘ ‘ ‘ ‘ 1 q A‘iCinvergence(%l _ _ _ __ -0 ‘éiGlide(%) _ _ _ _ _ f ,, ,; ; i -*62; ;~ _ _ : _ _ i — F Pocket wate_r(°[3) _ _ __ _ Z “-100 __ % l_ateralpoo_|s(‘f/<>)______T _'9*» __4 y_\%P|unge(%) i _ - 13.8 ;Debris(%l _ K _ _ _ _ -0 i % {LandsIide(%) 1 H _ _ f0 {K A_Backwater(°/0) _ _ _ _ _ **1-4 7 _ *_ _ W__ _ 5bandened ch;ann_eIs§°/oi __ { " ~16-5 _ \*1Nat9r qua!ity__Ea|:am_ete_rs _ ‘Air temperature(°C) \ 26 ' 37.4 _ Wgateg temperature(°C) @319, _ __ _ _ \ PH K K 1 K _ 6~1f§;92_ _ _ _ _ T\Di§so|_veq _ oxygerjmgfll_ _ {_ W 4~51‘§~1": f {_ _ __ _ ‘ Total harqne_ss§_@g_/_|l _ M _ ‘@1751 i _ _ _ I iTota|alk§linily_@g11) T3.Q8 -_8 ______f|owvelocit1(m/sl _ __ __ [ _ __ __O-0.7 _ _ Mean cl_1Lan{nelwidthQn)f i _1%3-140.5 ______' [Mean c;haqel_dep§hQfn)__ { 3.25 f_5Q_ __ _ _ _,7 T GO O Q o '~o O O O‘O QC O C) iii L Table6' .4.Physical and chemical variables measured at 30 stream sites in _ Bharathayuzha river during the [Leriod from January 20701-January 20074. 7 Habitat variables ';Re=?-¢hd¢=*-criptions nah T is-iW9$“Y - 0 "H1-1.63 7 0 \ LEntrenchment ratio 0.7-5.1 , 1_ i0.001- 0.25 W fslqge 7 ,0 0 K aw/0 ratio 0 "1| 0.48 - 83.3 Rijlarian zon_e 7 7 T30-‘Eb ¢°Y0e' a'9"9 Pa'?'<(%!l '3-80 0-97 -%'_ree7cover alog bank(°/9717 7 77 Ba-‘e.00%°"'ld *-'="0°0'J9 ‘?a"k(%L 59-38 H \ 7§ubstrate 7 77 7 _.-! @77Fines(%l 7 0-75 G'3Ve'§£%)m - 0 ; 0- 978 10C°bb'e$(%L K0-023 70-60 iBo~Iders<%>’R07ck(%) *0 - 52 ]Bedrock(°/pl 77 _ i0-94_ Instream cover T~rbu'a"<=eL%)0 0 _,i 0-75 . 1. iP2Bth(‘?/5) - 0 0-100 i §ma||7w00dy debris§%) 7 770-17.6 _ -'—?[9° W°°dE3°bfi_$(%L- _ L0 -14.3 W l_ A0-71.4 HOve_rhanging vegetation QA) _$ubme§ed7vege_tati70n(%L 7 7“0-0 [Emergent ve_getati7on§%>) 7 70-90 7 i 7Turbu|an7t white water bou|ders(f’4>) 0-25 I 01 LScour 0utBools$%)7 _ L0-30.8 J 1 Overhanging stream bouIders(°/07) _T70-5.1 , Tlndercut ba7r71k(°L) 7 I 0-16 _ i_ 17Totaic0ver(ii) 7 7 0 io-100 1I ‘L§hannel7Jge707gra7[;hisaI units 77 7Riffle(‘_’/Q 7 77 7 7 L0-68.9 L7Rur!(%7L 0-100 .5dd1§° / 0L7 r’0_Oa 0 iTren0lK°A>L 77 77 0-227.7 -M*d°ha"0"'3'(%l 0 0-100 I éP°°k¢t W319’ P°°'fl°/Q, 0 0-100 G|i Flqyy velocitlgn/s) % K _ 01% _ “T Mean channel \fvic_ij:h(m) __% j 10-250 7 Megp chaneI?deptl%1%(n1L L1 .5-25 Table 6.5. Co-efficient of correlation between habitat variables and abundance 7 9”-°P"d9BZ9°Bs"$lYP"s " "T lPar7ameter$7 7777 77 V7 7 P L§edrock *_ 7 7 77 ,_7 77 0.531 07.034 L -F7Chute - 0 ~ K —— if 7 it 0 -~ 7'77 l’ 77~ 0-52‘ 0.039 7 tux 77 7 77 7 777 7 0.503. 0.047“ lOverhanging§tream boulders 77 7 77 7 l 7 0.8719‘ 7 oi .7Ov7er7hanQingvegetation 77 7 T77 0.67716 ! 0.0117 TTotal cover 7. 0.s4sJ 0.0720} .1S'°Pe_ 77 77. _ 77. Le07~7593L 0.016l__' l_l ‘IFee77cove7r 7 77 77 77 Q77 77 77 0.54§,_ 0.029 Table 6.6. Co-enfficientibf correlation between habitat variables and abundance 77 °§ G°?'2P'9kt‘.?B‘°'9s mi°'°P9£°"P°"}’a'°"5'3 a _7Peremetere 7 . 7 7 \_.r7 77 7 .9 ”.D%P"" 7 77 [email protected] 0.78. 0*. TMidehannelP2<>Ie7 7 0.612.e A 0.01200 roverherws veseletiee T 7 0.7881717 7 7 7 0 ‘Shaded cover 77 7 7 7 l__ 77 0.69§l. 0.003l islel__P7 e 7 71 77. _e _7—- 0 7 77 77,- __1L- 0 Q52? 07033} ;7Totalco7ver77 77 7 7 77 7 77? 77 77 0.533} 0-03%.’ ?7Treecover 0* 0 0 H 0‘ U 77 0.677 7 770.0147; Table 6.7. ‘Co-efficient of correlationjbehneen habitat variableé and abundance 7 77 <>f7Cr0$s<>¢heiIus neriyarensie 7 7 7 TP=r=meteI'e 7 Tr W jp 77 Z7 "7 itateraelpobl 77 7 7 710.529 "7 77 was legqéweedy debrie07 07 7 7 Y J7 00.7801} 0 77 01“ ,7OverhanQng7vegetation 7 it 0 0* 7 07701650107 I 7 0.00817 i7ScouroutlJools 0 7 7 7 if 7 007.6376“ 77 000.008] Jreec0ver077 0* 7 0‘ 7 if 7 7. 77 it 0.52:-YT 0.03§f Table 6? .8. Col-efficient of correlation between habiatat variables and abundance T 7 77 77 7770f Silyrus wyaadensis 7 _7ParameteI$ 77 7 77 7 0 0 ‘tr 0 7 T "‘l 77 7 7 l | leirteme-t~re 2 =LRegress1on equanon i I’ 7 P lepidopygopsis (ypus ;0.7l56+0.l946 Bedtock substratum _ 7 0.327 0.0206 _2.6038+1.6959 Chute habitat 7 0.1944 W 0.0873 111.0622-0.00931.11>; 1 '71 0.2001 770.0823 0.3 542+4,2083 7Overhanging streamboulders . 0.6151 0.0003 -0.371 1+3 .2891 Ovethang7ingvegetation 7 777 0.501 0.0022 i ‘1-4.236+0.8532 Total shaded area _ 0.5033 0.00Q2L -6.2094+146.069s1Qp¢ 7 717 0.391 %___Q.0095 i-3.3725+0.24Tota.l tree 881781 %%%_ 7777“ 0.3702 77770.01241_i Gonoproktopterus micropogon perivarensis 1-1.16399-98877949111 1 0.76088‘ 0.00041 -0.2727+0.043s Midchannel pools _11 0.37397? 0.0118 -0.3 789+0.5 1 7 Overhanging veg7e7ta7tion 0-7.77 0.2031 1 -1.078+0.l7l2 Total shaded area { A 0.4871 7 0.0026 _ 0.2712 0.038617 ;%1.l4+24.778 Slope i777 71' T-1.4834+0.0543 Total 1118118881 cover K 0.2844 0.0334 7-0.907+0.0482 Total tree cover 77 _ 0.3596" 0.01411 Crossocheilus perivarensis _? “0.267s+0.2927_La1er;1J>o01s1 _ 7 70.279877 0.035? 10.333+1.333 Large woody debris j __NH0.641 9.-90021 -0.2344%+_0.656 _C_)%verI1angin5yegetationN H 7 0.424 0.006; 4-0.0537+0.3782 Scout out pools % 0.40441 0.0081 j-0.7289+0H.0447 Totalwtree cover __fi 0.2734 1 0.0377._ Silurus wynadensis 1-0 15§2s+0 1559179 Aiitem 181303183 0.0030587 0.8448081_ __,_____ 0.286572+ -0.17101 Channel width 3 0.202746T 0.092135 _.Q-031909?-0-06732 F_|QWvBlQ¢iIL_. 7 0.027343‘ 0.018662. 70.07628 11- -0.2{6k_12_11Ov%efl1anging streamjboulders 0136861 0.016384 10.076182+ -0.00792 Totai cover 7 7 0.9680551 0.0001281 770.06816+ -0.03964 T1'enci_1pool7 % 7_ 7 7 0.710039% 0.010989. 3 _-_0.8667+ 0.768532 Water te[@_erature{{ h_ _ 0.23610 0.106079 Neolissochilus wynadensis 0 "0 l0.68356+ M-0.74708 Alkalinity ll 22 0.288995L 0.047805 J 0.584608+ -0.34504 Channel width 0.2812481 0.041986 l 2.161612+ W-1.83322 Hardriess 0.484887 0.0089542 H“-0.00464+ 0.24.3849 Lateral pools 0.512289 0.0028942 l0.1255424-2 -0.42645 Overhangir1g2 stream Boulders 2 3 0.884747 0.028040 .6.0828099-f-26.82332 pH l l2 0.194292, 0.1259471 Osteochilichthys longidorsalis I 22* I’ 0.0823l58—5 0.405413lab2andened channel 0.840898 0.006926; _0.o98884+ 5.175708 Backwater 300010 0.42552 0.001828 l0.044195+0.217195 Emergentvegetation , l 0.282884 0.015791 _0.0863l2¥0.22794l3 Glide l 2 2 9 l 2 _ 0.198097. 0.050542 ‘0.050142+_0.222576 Ovemanging stream boulders ._ 0.199581 0.048818 L10-5724+0-41.1587Chaflflelwidlh 2 2 _ 7 _ 22 9-21011651, 0.04208. Puntiusjerdoni 0.0166324-+ 0.398499 Abandened channel 7 20.721127 .9. 0.038849-P 0.2323483 Cascéae 2 2 22 2 70.21133 0.04 -0.01521+ 0.127599Rag0s 2 7 02.290124 0.014274 ~0.56822{0.899533 Total alkalinity _ 0.207529 0.048588 -0.50128+ 0.3321286 Chaflnelwidth 2 2 l 0.297856 0.012804 Nemacheilus remadevi 0.315 - 0._1_84999lBarelground ll 0.245807. 0.008543 0.289842-0.18195 Bedrock -0.181849 7 0.028778 -0.00703 + 0.210778 Cobbles 0.247982 0.008209. 10.428247-0.21218 00-pm 2 f l 2 0.1599571 0.038733 -3.00512+4.41024l5 Dissolved oxlggn 2 l 0.447758 0.000185. 10.041 1128+0.3166822 Glide 72 l 0.4715451 2 20.00007 i _20.0422118+0.316682 Lage woody debr2is l 0.871888 0.000788, i0.087787+0.033783 Rifflel 2 2 0.1885721 l 0.0888991 L0.099799+0.553623 Srnall woodydebris 0.209107 0.009528 Homaleptera pillai Kl l 0.006552+0.13218 Bedrock 0.187981 0.0288841 i i-0.022222-l+0.096669 2C0bbl2eS -2 2 l2 2 0.181835 l 0.026553 2-1 .17‘-561 +1 712174 Dls8olved20x1gen W 0.285259L 0.010888 1.-0.005724-0.18288 Glidef in 0.488521” 0.000189‘ g0.00429+0.4148114Large woody debris L 0.7884891 01 l 0.294278-0. 19175 Shrub cover 0.152528 0.04 100038914-0.548568 Small woodydebris I 0.8207141 . 0 Garra menoni i0.02893+0.39831 1 Bedrock _ l 7 i 0.42. 0.0002l -3.07786l+4,4760l6 Dissolved oxy_gen l 0.8247 20.002; i*0.000983-1-0.361469. Glide ' 1 0.43 A .- -0-0002.1 0.741 040O3409+1 - 002687 LaLqe woody debris 0.. 0725298-0.47071snru0 cover 0.185265» . _" ‘Ii 0.02511 _l0.017747-ll-1 278555 Small wood! debris l 0.898679 °i Table 6.16. Multiple regression habitat suitability index model of Lepidopygopsis typus Regrassion§_t_atistics Multiple R 0.9299101 R Square 0.8647329 Adjusted R2 0.7101418 Standard Error 5.1676291 Obsewagtigns 16 ANOVA g __ “L. 95 g MS F Significance F Regression 3 1 195006765 7149 5.5937 0.017523454 Residual 7 1 86.930735 26.7 Total 0 15 1 381 .9375 g Coefiicientsg Standard Error tStat: P-vahieii Lower 95% 0gpeT955%il_ower 95.10% tlgper 595. 019611 Intercept 0.6130779 4462044087 0.14 0.8937 -9.93297217 1 1.16913 -9.9329722 1 1 .16'£fi28G6 X1 Variable 1 0.0904756 0. 06786462 1 .33 0.2242 -0.06999859 0.25095 -0.0699936 0.250949833 X2 Variable 2 0.733442 0.71 2273221 1 .03 0.3374 -095081534 2.417699 -0.9506153 2.41769931 X3 Variable 3 -0.00054 0.004645859 -0.12 0.9108 -0.01152532 0.010446 -0.01 15253 0.010446088 X4 Variable 4 3.0016543 1 .604727732 1 .87 0.1036 -0.79292109 6.79623 -0.792921 1 6.796229707 X5 Variable 5 2.767946 1 .328 705672 2.08 0.0757 -0.37394145 5.909833 -0.3739414 5909833367 X6 Variable 6 0.0576039 0.348801 6 0.17 0.8735 -076717523 0.882393 -0.7671752 0882393032 X7 Variable 7 -46.06336 59.32 04836 -0.81 0.4443 -188.353912 92.1872 -166.35391 92.18719531 X8Variable 8 -0.096239 0. 1 28478968 -0.75 0.4782 -040004288 0.207566 -04000429 0207565656 Table 6.17. Multiple regression habitat suitability index model of mGonoproktopterus micropogon periyarensis Regression Statistics f Multiple R5 ' 0.9341761 R Square 0.8726849 Adjusted R2 0.7612843 Standard Error 0.9560765 Observations it 16 f§NOVA 5 1 i_ g g_ MS F Significance F Regressiondf 7 65012484133 ss 7.16‘ 7.6337 0004717067 Residual 8 7312658669 0.91 Total _g g 15 57-4375 Coefficients Standéifl Error t Stat P-value guliower 951%’? UQpergg9g5%il_ower 95. O96 fiper 95.0% Intercept 0.4269966 0735152342 0.58 0.5773 -1.26826887 2.122262 -1 .2682689 2.122262009 X1 Variable 1 -0.087415 0.071967456 -1.21 0.2591 -0.25337261 0.078542 -0.2533726 0076542105 X2 Variable 2 0.0275387 0.014557943 1 .89 0.0952 —0.00603196 0.061109 -0.006032 0.061 109433 X3 Variable 3 0.83743 021332422 3.93 0.0044 0.345503118 1.329357 0.34550312 1.329356321 X4 Variable 4 0.0657968 0075703559 0.37 0.4101 -0.10677603 0.24037 -0.106776 0240369641 X5Variable 5 -8.177745 9.254726137 -0.66 0.4027 -295191957 13.16371 -29.519196 1316370535 X6 Variable 6 0.0123387 0021405569 0.53 0.5602 -0.0370227 0.0617 -0.0370227 006170002 X 7Variable 7 —0.024745 001324674 -1.36 0.2121 -006662675 0.017337 -0.0663267 0017336647 Table 6.18. Multiple regression habitat suitability index model of Crossocheiius periyarensis H Regression Statistics _ g Multiple R 0.8852412 R Square 0.783652 Adjusted R2 0.675478 Standard Error 1.1858593 Observations - 16 ANQVA . dr SS MS? *F Significance F Regression 7 V 5 50.9373779 10.2 7.244-4 0.004128515 Residual 10 14.0626221 1.41 Total _ 1.5 _g 4_ 65 Coeflicients Standard Error tStat P-value gl_ower9u5%” Upper 95_%Lower_9g5.0% Upper? 95.0% Intercept S-0.526797 0.648506135 -0.81 0.4355 -1.97174932 0.918175 -1.9717493 0.918174614 X Variable 1 -0.007023 0.12238944 -0.06 0.9554 -0.27972405 0.265677 -0.279724 0.265677384 X Variable 2 0.9596924 0.4445-14045 1.93 0.0819 -0.13081363 1.850198 ~0.1308136 1 .850198427 X Variable 3 0.2547349 0290490057 0.91 0.3851 -0.37023605 0.879706 -0.3702361 0.879705755 X Variable 4 0.139941 1 0.1 14299997 1.22 0.2492 -0.1 148328 0.394515 -0.1148328 0.394514919 X Variable 5 0.010297 0022599603 0.46 0._6_583 3004003579 0.06063 -0.0400358 0.060629772 . 9' Table 5.19.lVlultiple regression habitat suitability index model of Silurus wynadensis Regression Statistips Multiiale R 0.8688504 R Square 0.754901 1 Adjusted R2 0.5098021 Standard Error 0.1175416 Observations 15 ANOVA 9;» 0 (ssh MS??? F Significance F Regression 7 7 0.297871978 0.04 3.08 0.080451014 Residual 7 0.096712154 0.01 Total g H _g14 0394584132 Coefficients Standard Error tSr‘at P-value Lower 95% Upper 95%Lower 95.0%? Qgper 95. 0% g Intercept -0.204037 0.869446656 -0.23 0.8212 -2.25994987 1.851876 -2.2599499 1 .851876485 X Variable 1 -1 .01 1653 1 .091943094 -0.93 0.385 -359368582 1 .570381 -3.5936858 1 .570380729 X Variable 2 -0.1 10378 0.082694513 -1.33 0.2237 -0.30591 91 0.085164 -0.3059191 0.08516352 X Variable 3 -0.052794 0.098803512 -0.53 0.6097 -0.28642705 0.180839 -0.286427 0.180838978 X Variable 4 -0.329165 O.133023172 -2.47 0.0426 -0.64371442 -0.01462 -0.6437144 -0.014615232 X Variable 5 0.0450205 0.139702342 0.32 0.7567 -029532279 0.375364 -0.2953229 0375963935 X Variable 6 0.1255285 0124497821 1.01 0.3469 -0.16996191 0.419919 -0.1699619 0419919909 0774731459 X Variable? 1.293925 1.67 0.1399555 -053912244 g3.1_25713 -0.5391224 312577253 Table 6.20. Multiple regression habitat suitability index model of Neolissochilus wynadensis Regression Statistics Multiple R 0.9041198 R Square 0.8174326 Adjusted R2 0.5505071 Standard Error 0.162566 0bs9r~4ati¢>_r1§ 15 ANOVA 3 3 dr 75-3” ss MS F Significance F Regression 5 0.946625713 0.16 5.9699 00121667297 Residual 5 0.21 1421664 0.03 Total ..14 1.158047377 Coefiicients Standard Error I $F.Q_E#\/Biue Lower 95% Upper%Q5%gLovy_er 95.0% UQpergQ5.0% A Intercept 7.6158597 3.269604709 2.33 0.0482 0.076132799 15.15559 0.0761 328 15.15558651 X Variable 1 -0.382961 0.309881429 -1.24 0.2516 -1 .09754974 0.331527 1 .0975497 0.331626898 X Variable 2 0.0072828 0.146665853 0.05 0.9616 -0.3309294? 0.345495 -0.3309295 0.345495095 X Variable 3 -0.510353 0. 751 634268 -0.68 0.5163 -2.24362594 1.22292 2.2435259 1.222919764 X Variable 4 0.0956303 0. 1 03414365 0.92 0.3822 -0.14284382 0.334104 0.1429433 0.334104399 X Variable 5 -0.265312 0.143196386 -1.85 0.101 -0.595524 0.054099 -0.595524 0.06489935 8 X Variable 6 -7.663966 4;1_15§§137Z 1 -1.86 0.0996 -17-15452922] 25507 -17.15452 L826587369 Table 6.21. Multiple regression habitat suitability index model of Osteochiiichthys longidorsaiis __R3gression Statistics Multiple R 0.9456048 R Square 0.8941685 Adjusted R2 0.9453232 Standard Error 0.1019625 Ql_>_servations 20 AN OVA ? df 3 SS MS F Significance F_ Regression 5 1141902394 0.19 19.305 1.20217Ei05 TotalResidual 19 13 01351526061.277055 0.01 Coefficients Standard Enor tStat P-value WW?’ 95% --_UBP°’.95?5!-.°_W?f .95-9% . UBPW 9.5-£92 Intercept 0.1039469 0.1 65234327 0.63 0.5402 -025302009 0.460914 1072530201 0.460913894 X Variable 1 0.1486036 0.095663891 1.55 0.1443 -0.05806563 0.355273 -0.0580656 0.355272834 X Variable 2 4.8169324 1 .030878929 4.67 0.0004 2.589854305 7.04401“ 2.58985431 7.044010499 X Variable 3 0.1791773 0.05631 068 3.18 0.0072 0.057525486 0.300829 0.05752549 0.300829097 X Variable 4 0.12481 16 0.063838493 1.96 0.0724 -0.01310306 0.262726 -0.0131031 0.26272625 X Variable 5 0.0878536 0.049409034 1.78 0.0988 -0.01888812 0.194595 -0.0188881 0.194595298 X Variable 6 "9-P9995’ _9+1Q_1.95°112 -0.89 0.3916 -0-31062845 9-129914 .-0.3195284 0-129911329 Table 6.22.Multiple regression habitat suitability index model of Puntius jerdoni Regressiorr_Statr'stics M Multiple R 0.8867863 R Square 0-7863899 Adjusted R2 0.7101006 Standard Error 0.0944899 Observations 20 ANOVA M df ss MS_ F7 Significance F Regression 0.4601 66473 0.09 10.308 0.000264998 Residual 514 0. 1 24996758 0.01 _Total m g 19 05851632315 an 5 Coeflicients Standard Error tStat P-value gower 95% M L/Qper 95% l,ower 95. 0% g (leper 95.0% 5 Intercept -0.381776 0.231 627-1 99 -1.65 0.1216 -0.87856744 0.115015 -0.8785674 0.1 1501531 X Variable 1 0.3352807 0.0704061 1 1 4.76 0.0003 0.184274437 0.486287 018427444 0.486286884 X Variable 2 -0.044133 0. 1 1 7981458 -0.37 0.714 -029717835 0.208912 -0.2971783 0.208912224 X Variable 3 0.029003 0.042840374 0.68 0.5094 -006288053 0.120887 -0.0628805 0.120886559 X Variable 4 0.4536832 0 .305335483 1.49 0.1595 -020119688 1.108563 -0.2011969 1 .108563243 X Variable 5 0.0421351 0.1 08390595 0.39 0.7033 ii ¢0.1903398§ 8 0.274618-0.1903399 0.274609974 ‘ . Table 6.23. Multiple regression habitat suitability index model of Nemacheilus remadevi Rgressr'on_Statr'str'cs g Multiple R 0.9274424 R Square 0.8601494 Adjusted R2 0.7861109 Standard Error 0.1490631 Observations _fl g 27 ANOVA 4? df SS MS f H Sr'@r'fioance F Regression 9 2.323265565 0.26 11.618 1.184-32E-05 Residual 17 0.377736775 0.02 Total _ A26 2.70100234 Coefficients Standard Error Mtg Stat Pg-value Lower 95%? UBQer95%l.ovyer 95.0% Qpper 95.0% intercept 5’ -1.951782 0.593951594 -3.29 0.0044 —3.2049123 -0.69865 —3.2049123 -0698652146 X Variable 1 -0.076154 0044435793 -1.71 0.1047 -016990593 0.017597 -0.1699059 0.017596988 X Variable 2 0.0655076 0.047478683 1.38 0.1855 -003466385 0.165679 -0.0346638 0.165678962 X Variable 3 -0.0448 0.066462981 -0.67 0.5093 -0.1850246 0.095425 -0.1850246 0.095425056 X Variable 4 -0.1 17601 0.062793797 -1.87 0.0784 -025008413 0.014883 -0.2500841 0.014882902 X Variable 5 3.0539744 0818102151 3.76 0.0016 1.338476438 4.769472 133847644 4.769472397 X Variable 6 0.21 1938 0.071777601 2.95 0.0089 0.060500325 0.363376 006050032 0.363375751 X Variable 7 0.242479 0.223183774 1.09 0.2924 -022839826 0.713358 -0.2283983 071335626 X Variable 8 0.2050327 0.0571 13208 3.59 0.0023 0.084534205 0.325531 0.0845342 0325531213 X Variable 9 —0.286504 0.200662149 7-1.43 g0.1715g_g -070986481 0.135857 -0.7098648 0.136856624 Table 6.24. Multiple regression habitat suitability index model of Homoioptera pillar‘ Regression Statistics Multiple R 0.9501 121 R Square 0.9027129 Adjusted R Squ 0.8668703 Standard Error 0.0629864 Observations 27 A.N_Q_\/A... - . -5- df SS i _F HSignificance F ResidualRegression 719 0.699426006 0.07537846 0.1 25.185 0 2.46025E-08 Total 26 0774804465 _.-Q°9*759"90!$..§§60 Table 6.25. Multiple regression habitat suitability index model of Garra menoni Regression Statistics Multiple R 0.9574902 R Square 0.9167874 Adjusted R Squ 0.8918236 Standard Error 0.1264614 §i .__T .—I _—_'_‘__“__“ ANOVA ___ _ 6 g 5 SS MS F g g g Significance F Regression 0 76 3523913423 0.59 36.725 6.977075-10 Residual 20 0. 31 984954 0.02 Total 5 :..____-.-. . .26 3.843762963 60900990 Standard Engr tStat P-value Lower 95% Upper 95'5_6gl,_o_iii/er 95.0% Qper 95. 096 M Intercept -0.523212 04690376697-1.12 0.2779 -150160696 0.455163 7-1.501607“ 0455182998 X Variable 1 0.0564754 o.057765054 0.96 0.3401 -0.o6406201 0.177013 -0.064062 0.177012897 X Variable 2 0.6151394 0.63503991 0.97 0.6443 -0.70953 1.939609 -0.70953 1 .939808853 X Variable 3 -0.007503 0056500053 -0.13 0.6957 -012536032 0.110354 -0.1253603 0.1 10353663 X Variable 4 0.2037551 017336061 1.16 0.2537 -015791037 0.565421 -0.1579104 0.565420523 X Variable 5 0.0641 16 0066023633 0.75 0.4647 -0.11532544 0-243557 -0.1153254 0.243557452 X Variable 6 0.9908693 0190246404 5.21 4E-05 0594016257 1.36772 0.59401626 1 .387720322 Plate 6.1 Lepidopygopsis typus (Raj,1941 b) Typical habitat of Lepidopygopsis typus Plate 6.2 Gonoprokloplerus micropogon periyarensis Raj, 1941 a Typical habitat of Gonoprokloplerus micropogon periyarensis Plate 6.3 Crossocheilus periyarensis (Menon & Jacob, \996) Typical habitat of Crossocheillls periyarensis Plate 6.4 Siturus wynaadensis Day, 1868 Typical habitat of Sitllrlls wynaadensis Plate 6.5 Neolissochilus wynaadensis (Day,1873) Typical habitat of Neolissochilus wynaadensis Plate 6.6 Osteochilichthys longidorsalis Pethiyagoda &Kottlet, 1994 Typical habitat of Osteochilichthys longidorsalis Plate 6.7 Puntius jerdoni Day, 1876 Typical habitat of Puntius jerdoni Plate 6.8 Mesonemacheilus remadev; Shaji, 2002 Typical habitat of Mesonemacheilus remadev; Plate 6.9 Homaloptera pi/laii Indira &Remadevi,1984 Typical habitat of Homaloptera pil/ai Plate 6.10 Garra menoni Remadevi & Indrira,I984 Typical habitat of Garra menoni Section II Life history traits and resource characteristics of Puntius carnaticus(Jerd0n,1849) Chapter 7 Systematics of Puntius carnaticus(Jerd0n,l849) 7.1. Introduction Kerala is a land of rivers, which harbours a rich and diversified fish fauna characterized by many rare and emdemic fish species. According to Kurup(2002) of the 170 freshwater fish species collected from the rivers and streams of Kerala 66 species belong to potential food fish category, while 104 species can be considered as potential omamental species. The state abounds extensive inland water bodies, which are suitable for fish culture, including 0.3 lakh ha. of reservoirs, 0.03 lakh ha. of tanks and ponds and 0.85 lakh ha. of rivers. In spite of having immense scope and potential for the development of freshwater fish culture as well as capture fisheries in the state, the yield from these water bodies are far below optimal. However, with the increasing demand for fish as a source to cater the ever-increasing demand for protein requirements of the human being, extension of aquaculture activities to more areas and utilization of indigenous fish germplasm resources are the way outs. An effort in this direction was attempted by investigating the life history traits of P. carnaticus an endemic threatened fish species of Western ghats . 7.2. Description of the species P.carnaticus is a cyprinid fish, which is commonly known as ‘carnatic carp’ and is locally known as ‘Pachilavetti’ (Plate 7.1) Systematic position Phylum Chordata Sub-Phylum Veitebrata Super-class Gnathostomata Grade Pisces Class Osteichthyes I27 Sub-class Actinopterygii Sub-Division Teleostei Order Cypriniformes Sub-order Cyprinoidei Family Cyprinidae Sub-Family Cyprininae Genus Puntius Species Carnaticus \ P. carnaticus can be diagnosed with the help of following characteristics Div8;Aii-iii5;Pi l4;Vi8 Body elongate its depth 2.5 to 3.4 times in standard length. Mouth slightly subterminal; lips moderately fleshy. Barbles two pairs; maxillary pair as long as orbit, rostral ones much shorter. Dorsal fin inserted slightly nearer to tip of snout than to base of caudal fin; its last unbranched ray is osseous, strong and smooth. Scales fairly large. Lateral line complete, with 28-32 scales; lateral transverse scale rows 51/2 /31/2; predorsal scales 10 to 12. Colour is olivaceous green on back, fading to dull -~white glossed with gold on flanks and abdomen. Usually a faded band is seen above the lateral line. 7.3. Earlier reports Available literature revealed that P. carnaticus was diagnosed and described by J erdon (1849). 128 Barbus carnaticus Jerdon, 1849, Madras J.Lit.& Sci.,15:31l(type —locality:Cauvery river). The previous reports of P. carnaticus shown below: -_'_—_~—— ? _ __ _ Barbus carnaticus Day, 1878.Fishes of India: 563,pi.l37, fig.3; Day l889.Fauna Br.India, Fishes, 1:305 1 Mukeiji, 193 7J.B0mbay nat.Hist.S0c. ,3 5(2): 164 Barbodes carnaticus Yazdani, 1992. Proc.J.Nat.Synp. Env. Hydraulics,Pune: 134-147 Menon and Remadevi, l995,J.§0mbay nat.Hz'st.S0c.,92:389-393 Pun tius carrziitiugus Jayaram,(Kottayam, 1981. Handbook of freshwater Kerala) fish, India, p.113 § Talwar and J hingran, 1991 .In]and fishes of India and adjacent 1 countries, 1; 262(Kerala) 1 Easa and Basha, 1995. A sun/ey of the habitat and distribution of 1 stream fishes in Kerala part of Nilgiri Biosphere Reserve.KFRI Research report No.104. Jayaram, 1999. The freshwater fishes of the Indian region,p.101 1 Ajithkumar et a1., 2000.Ec0l0gy of hill streams of Westem Ghats with special reference to fish community, Final report, pp.203, Bombay Nat.Hist.Soc.Mumbai. Gopi, 2000. Endemic fish diversity of Westem Ghats, NBFGR NATP publication No.1, Lucknow.p.62. Shaji et a1., 2000.Endemic fish diversity of Western Ghats,NB FGR-NATP publication No.1,Lucknow.p.62. Shaji and Easa, 200l.Field Guide. Freshwater fishes of the Western Ghats, p.101 .KFRI, Kerala and NBFGR, Lucknow.p. 108. 129 The genus Puntius is represented by 55 species, of which 44 species are available in India (J ayaram, 1999). Many of the species coming under this genus are small fishes and have no fishery potential while some species have good omamental value. On the contrary P.carnatz'cus attains big size and the maximum size recorded is l2 kg (Talwar and Jhingran, 1991). According to the earlier reports this carp provide a minor fishery in the Mettur reservoir area. However, the catch of this carp have significantly declined in recent years. In the present study specimens upto 1.75 kg were collected and specimens in the wild range 0.25kg to l.5kg were very common. In Kerala P. carnaticus is available in five river systems such as Chalakudy, Kabbini, Achenkoil, Pambar and Chinnar. Among these river systems except Chalakudy and Kabbini, the occurrence of this species was sparse and sporadic. This species contributes a fishery in the Peringalkuthu reservoir and the adjacent areas of Chalakudy river system and Muthanga,Ponl-ruzhy, Begur and Baveli regions of Kabbini river system almost year round. Even since the description of P.camaticus in 1849 by Jerdon as Barbus carnaticus, virtually nothing has been added to our knowledge on this species other than the very few references came across in general surveys. This paucity of information on this valuable fish germplasm prompted to undertake studies on life history traits and resource characteristics of this species. During the period of study from April 2001 to March 2003, the following aspects were studied 1. Food and feeding habits to provide information on basic components of diet as well as season and size related variability in feeding behaviour. 2. Reproductive biology to observe spawning season, sex ratio, fecundity and other related aspects for asserting the rate of reproductive potential of this species. I30 3. Length-weight relationship and condition factor to ascertain the relationship between length and weight and the general well being of the fish 4.Age and growth to understand the age composition of the exploited stock, age at maturation and life span of the species, growth rate and its comparison with other species. 5.Population dynamics to estimate mortality rates, exploitation ratio, exploitation rate, relative yield per recruit etc. so as to bring out the level at which the exploitation of the stock is presently carried out which is essential for examining whether the present exploitation rate is at judicious level or not '? I31 Plate 7.1 Puntius carnaticus (Jerdon, 1849) Systematic position Phylum : Chordata Sub-Phylum : Vertebrata Superclass : Gnathostomata Grade : Pisces Class : Osteichthyes Su b-c1ass : Actinopterygii Sub-Division : Teleostei Order :Cypriniformes Sub-Order : Cyprinoidei Family : Cyprinidae Sub-family : Cyprininae Genus : Puntius Species : carnaticus Chapter 8 Food and Feeding 8.1. Introduction All living organisms depend on food for a regular supply of energy to keep working and so stay alive. Food is an important factor influencing the growth pattern, distribution and abundance of stock and migratory habits of fishes. Information on natural diet of fish is a necessity for understanding its nutritional requirements, its ‘interaction with other organisms and evaluation for aquaculture (Royce, 1987). Assessment of the food items and feeding habits are helpful in defining the trophic relationship of fish in the food web of the ecosystem. Once the food preference of a species is ascertained, an evaluation on the trophic relationship of the species such as the overlapping of the food spectrum with other co-existing species, competition from other species, selectivity or flexibility in feeding on the food items, etc. can be made. Based on this information, compatibility of different fish species with least inter-specific competition for natural food can be ascertained for fanning purposes. It would also be useful in developing proper supplementary feed. The food and feeding habits of the same species differ in time, space as well as at different stages of growth (Hardy, 1924) and this would, in turn, pinpoint the importance of detailed study on this aspect. The age related information on feeding habit is invaluable in nursery and hatchery operations. Feeding habit is an important factor to be considered while transplanting a species to a new ecosystem so as to leave the native fauna in their natural habitat with least disturbance. The applicability of food and feeding habits of fishes becomes apparent while examining their role in controlling water-bom diseases (Menon and Chacko, 1958). Many fishes have been successfully used in biological control of mosquito laivae and molluscs, which serve as intermediate hosts of many helminth parasites and algal blooms. Investigations of the feeding ecology of a 132 species can also throw light upon how the organisms have evolved ecologically to meet the pressure (Grossman er al., 1990). Studies on the dietary habits of freshwater fishes are available from different parts of India. The important contributions are those of Mookhe1jee(l944); Chacko and Kuriyan(1949); Das and Moitra (1955, 1956, l958, I963); Chacko and Kuriyan(l949) Menon and Chacko(l957,l958);Natarajan and Jhingran(l96l); Bhatnagar(l963); Qayyum and Qasim(l964); Rajan( 1965); Pandian(l966); Chakrabarthy and Singh(l967); Sinha(l972);David and Rajagopal(l975); Pathak(l975); Badola and Singh(l980); Gupta(198l); Vinci and Sugunan(l98l); Nautiyal and Lal(l984); Biswas(l985,l986); Dasgupta(l988,l990,l99l);Sha1-ma et al.(l992); Nath(l994), Kohli and Goswami(l996), Kishore et al.(l998), Basuda and Viswanath(1999) and Singh and Subbaraj(2000). Nevertheless, reports on the feeding habits of fishes inhabiting the rivers and streams of Kerala are very few. Ritakumari(l977) studied the diets of loaches, Lepidocephalus thermalis and Noemacheilus triangularis. The food preference, seasonal and lengthwise fluctuations in the food items and variations in the feeding intensity of Puntius sarana subnasutus were analysed in detail by Nair and Shobana(l980). Sheila (1981) recorded the food and feeding habits of Aplocheilus lineatus and Macropodus cupanus. A detailed illustrative account on the morphological adaptations of the digestive system of Puntius vittatus in relation to its mode of life in the environment was fumished by Geetha et al.(l990) along with the food and feeding habits of the species. Besides providing information on the diet preferences and seasonal and lengthwise variations in the gut contents of Labeo dussumieri, Kump (1993) extended his work to the study of the food of 133 spawn, fry, fingerlings and juveniles which helped in identifying this species as a cultivable fish. Studies on food and feeding of animals are of great importance in understanding growth, migration, reproduction, seasonal variation in body condition, etc. (Sureshkumar, l998). Assessment on the food and feeding habit of the fish helps us determining its habitats and its preferred food items. Moreover, observations on food and feeding along with the species assemblage structure will help us to understand the extent of competition for food among different populations. Basic knowledge on the food preference and feeding habits of a species are of primary necessity for ascertaining its suitability for aquaculture because it will helps to determining the desirable species combinations in culture systems with minimum interspecies competition for the natural food (Anon, 2001). It also provides vital clues in developing supplementary feed for the species. Puntius carnaticus attains more than l2kg.(Talwar and Jhingran, 1991) and the large size it could attain in the wild call for assessing its suitability for aquaculture. Knowledge on the food and feeding habit is a prerequisite for taking decisions in respect of its candidature for farming purpose and therefore an attempt in this direction was made as part of the present study. 8.2. Materials and methods A total of 904 specimens comprising of 262 males (232-430mm TL), 150 females (270 472mm TL) and 480 indetenninates (52-227. lmmTL) were examined. The samples were collected from the commercial landings at Peringal region of Chalakudy river and were preserved in 8%formalin after making some perforation in the vent region for better preservation of the intemal organs. After taking the morphometric measurements such as 134 total length, standard length, total weight, etc., the stomach was dissected out. The fullness, length, weight and volume of the gut were examined. The extent of feeding can be judged by the degree of fullness of stomach or from the amount of food contained in it. The food item in general showed a high degree of mutilation as they were already subjected to the strong action of digestive juices. Therefore, the gut contents could only be identified up to generic level or group depending on the state of digestion. Feeding intensity was also assessed by classifying the stomach as nil, trace, 1/4full, 1/2fu1l, 3/4full and full depending on the state of distention and amount of total food in the stomach.. Depending upon the degree of fullness of the gut, points, 0, 5, 7.10.15 and 20 were given to nil, trace, l/4full,l/2full,3/4full,and full gut respectively (Anon, 2001). The feeding intensity was also estimated by calculating the gastrosomatic index (GSI) by applying the formula Weight of the gut GSI = ------ Total weight of the fish Monthly as well as size-wise variations in gastro-somatic indices were worked out. The relative length of gut (RLG) was estimated by dividing the gut length by total length of the body (Al-Hussaini, 1949). Length of the gut RLG = ------ Total length of the body The contents of the intestinal bulb and intestine proper were taken out separately for the analysis of food components. Because of the occurrence of different types of food items such as macro vegetation, animal matter, filamentous algae, diatoms etc. in the diet, the 135 percentage composition of the diet was detennined following the occurrence method as described by Hynes (1950). The points (volumetric) method, as described by Pillay(l952) was used for estimating the volume index. The points gained by each food item altered proportionally to the total points allocated for the stomach. The Index of Preponderance’ (Natarajan and Jhingran, 1961) was worked out to assess the food preference of males, females and indeterminates. This index accounts for both the frequency of occurrence of food items (occurrence index) as well as its size (volume index). The Index of Preponderance was resolved by the formula: ViOi I = ------x100 EViOi Where I = Index of preponderance of the food item Vi= Percentage of volume index of the food item Oi= Percentage of occurrence index of the food item. 8.3. Results Alimentary canal comprises of mouth, buccal cavity, oesophagus, stomach, intestine and rectum. Mouth is sub terminal in position. Gill rakes are moderately long. Stomach is well distinguishable from the intestine. This species appear to be a voracious feeder as in most of the occasions the gut was found completely full. The gut of this species has been found to be comparatively large with the relative gut length varying between 2.1 to 4. The relative gut length of different length groups of P. carnaticus, ranged from 2.1 to 3.2 in indeterminates, 3.1 to 3.8 in males and 3.3 to 4 in 136 females (Fig.8.l). The stomach is well developed and can accommodate bigger sized particles. 8.3.lGeneral diet composition of P. carnaticus Analysis of gut contents showed that food items could be assorted into 7 groups. Semi digested plant matter was the most predominant dietary item recorded from the gut of the fish almost round the year. It was represented by leaves, roots and parts of stem. During the field observations it was observed that this species showed very good affinity towards fecal matter of elephants. Filamentous algae were regularly encountered in the gut of the fish species. Spirogyra, Ulothrix, Shizogonium, Pleurodiscus, Uronema and Hormidium were regularly present in the gut. Bacillaiophyceae also present as an important food item represented by Dinophysis, Navicula, Clostrium, Calothrix, Bulbocheate, Pinnularia, Fragillaria, Nitzchia and Rhizosolenia, among them. Dinophysis was the dominant diatom (42%) followed by Navicula(27%). Semi digested animal matter, which was also found in the food spectrum of P. camaticus. Insects (50-60%) were the predominant group under this category and was represented by Diptera(Chironomus larve and pupae,Tanypus and Ablabesmiya larvae), Hemiptera (Corixa and Micronecta),Ephemeroptera(Mayfly nymphs), Coleoptera(Hydrophilus larvae) and Odonata(dragonfly nymph).Semidigested and mutilated parts of other small fishes and crustaceans were also encountered in the gut contents. l37 Seeds of plants along the riparian zone were observed in the gut contents of P. carnaticus. Presence of sand was encountered in some samples and was separated by continuous washing 8.3.2. Variation in the diet composition of indeterminates , males and females The food of indeterminates, males and females were analyzed separately to find out the differences, if any. The percentage composition of different food items of indetemiinates, males and females are given in Fig.8.2a, 8.2b and 8.2c respectively. The index of preponderance of different food items of P. camaticus is presented in Table 8.1.The food preferences of males, females and indeterminates were similar with variations in the magnitude of different food items consumed. Semidigested plant matter, filamentous algae, diatoms, semidigested animal matter and seeds were the order of preference in all groups. Semidigested plant matter contributed to 31.1% in indeterminates, 32.3% in males and 30.7% in females. While filamentous algae formed 17.16% in the diet of indetenninates, 17.2% in males and 18.6% in females. The preference for diatoms was found to be higher in indeterminates (16.5%) than to males( 14%) and fema1es(l l.6%).Semi digested animal matter fonned 26.5% in indeterminates followed by 19.1% in females and 18.2% in males. While the occurrence of seeds of some plants found at the river banks were observed in the gut of some specimens and it contributed to 3.3% in indetenninates, 12.5% in males and 12.2% in females. Miscellaneous matter including the sand formed 5% of the diet in indeterminates, 5.8% in males and 7.8% in females. 138 8.3.3. Seasonal variations in the diet of males and females The monthly fluctuations in the diet composition of males and females, based on index of preponderance, for the year 2001-02 and 2002-03 are given in Tables 7.2, 7.3.7.4 and 7.5. During 2001-02, semi digested plant matter formed the dominant food item throughout the year in males with highest occurrence in March with an index value of 71.4 while it was minimum in September with 64.3(Table 8.2). Filamentous algae and diatoms formed the second and third dominant food items respectively. The index value of semi digested animal matter ranged between 4.5 in October and 8.4 in May. Seeds of plants growing in the riparian zone fonned a minor portion of the diet during all months and its contribution varied from 2.9 in March to 5.8 in June. Miscellaneous matter varied from 0.3 in October to 3.4 in June. The pattern of variation was more or less on a similar line during 2002-03 with slight difference (Table 8.3). The quantity of semidigested plant matter, filamentous algae, diatoms and semidigested animal matter followed similar trend during both the years. While the occurrence of seeds in the gut content was not observed during July, November, January and March in 2002-03. Presence of miscellaneous matter showed a decreasing trend and its contribution varied from 1.5 in September, November and March while it was higher in May with 3.5. Semidigested plant matter was the dominant food item of females in all the months during 2002-03(Table 8.4). The highest contribution was observed during May (70.3) and October (69.3). Filamentous algae which formed the second dominant food item varied its contribution from 11.1 during June to 15.1 in October. Diatoms showed their peak occurrence during November (9.3) and declined to 7.9 during May. Semidigested animal matter showed its highest occurrence during August (7.7) and reduced to 4.2 during May. I39 Seeds of plants growing in the riparian zone contributed to substantial quantity during some months while it was totally absent in the diet during May, July, August and March. Presence of miscellaneous matter varied from 0.6 during January to 7.3 in July. Similar trend was observed during 2002-03 with slight variations (Table 7.5). In males, a decrease in the proportion of semidigested plant matter was discernible during May, September and December in 2001 and May and September in 2002.111 females also similar trend was observed during July in 2001 and October in 2002.Index of prepondarence value of indeterminates of P. carnaticus from April 2001-March 2003 are given in Table 8.6.Among the different food items semidigested plant matter (71.9%) was the dominant food item followed by filamentous algae (l4.7%),Bacil11ariophyceae(9.1%), semidigested animal matter(3.3%) and seeds(0.9%) in the order of their dominance. Miscellaneous items formed 0.1% of the diet. 8.3.4. Feeding intensity Guts in different degrees of fullness The data on the percentage occurrence of guts in different degrees of fullness in males and females of P.carnaticus during the years 2001-02 and 2002-03 are depicted in Figs 8.3, 8.4, 8.5 and 8.6 respectively. 1n males, full gut was present during all the months. During June, September, November and January the guts of all the fishes were full. The lowest representation for full guts was observed during April and only 21.4% individuals showed the full gut condition. Individuals with 3/4 '1‘ full gut showed maximum occurrence during December followed by April, October, March and February. 1/2 full individuals was maximum (33.3%)during July, followed by August (16.7%), May (12.5%) and October (11.1%). 1/4 full 140 Q individuals showed their occurrence only during March (22.2%) and May (21.4%). Individuals with only trace amount of food materials in the gut were observed during March (22.2%) and April (7.1%), while empty guts were observed only during August (16.7%). During 2002-03 the gut of all fishes collected during most of the months was full.3/4 full guts were observed only during July, August, October, December and February.1/2fu1l guts formed 40% during August and 11.1% during September. In Females, during 2001-02 full gut was encountered only during June, September and February. While % full gut was highest during December (58.4%) followed by March (30.8%), April (25%), October (20%), January (20%) and November (12.8%). During 2002-03, full gut was observed in May, June, September, January and F6bI'Ll3.l'y.II1dlVIdL13.lS with 3/4 full gut were observed during April, July, November, December and March with a maximum of 66.6%during April and December. During August 100% individuals have ‘/2 full guts whereas in July fishes with ‘/2 full guts contributed to only 25%. During October 66.6% of the specimens were having empty guts. 8.3.5. Gastrosomatic index Monthly variations in gastrosomatic index of male and female P. carnaticus during 2001 02 and 2002-03 are shown in Fi gs 8.7 and 8.8 respectively. In males during 2001-02 there was a sharp increase in GSI from September onwards and registered the peak value of 7.2 in December. Thereafter the GSI showed a decreasing trend in the proceeding months and reached the lowest value of 4.5 during August. During 2002-03 also the GSI showed the similar trend but for the highest GSI of 7.5 registered in October and December. In females, during 2001-02, the GSI gradually increased from 4.5 during August and 141 reached the highest of 7.4 during September. From December onwards the GSI declined and reached to 4.6 during August. During 2002-03 also the GSI showed the similar trend except that the peak GSI was recorded during October and not in September as in 2001 02 Lengthwise variation in GSI of males, females and indeterminates is depicted in Fig.8.9.In males from a higher value of 5.7 in 220-240mm size group the GSI showed a gradually declining trend and declined to 4.3 in 420-440mm size group. ln females also the GSI showed the similar trend. From a higher value of 5.7 in 260-280mm size group, the GSI showed a gradually declining trend and touched 4 in 460-480mm size group. In indeterminates the highest value of 4.8 was recorded in 100-120mm size group. Thereafter, the GSI showed a gradually declining trend and touched to 4.1 in 140-160mm size group. The GSI increased to 4.3 in 160-180mm size group and declined to the lowest value of 3.9 in 180-200mm size group. Generally GSI values of females were found higher than their male counterparts and among the three groups studied females showed the higher GSI values when compared to males and indeterminates. It is worth reporting that Males, Females and indeterminates follow almost similar trends in feeding intensity as manifested by gastro-somatic index during both the two years with minor variations (Fig.8.10 and 8.11). 8.4. Discussion The alimentary canal of fishes is well adapted and modified in accordance with their nature of diet and mode of feeding habits. The variation in the position, shape and size of the mouth can be correlated to the dietary habits of fishes. The subterminal mouth seen in I42 P. carnaticus is well adapted to suit its column feeding habit. According to Gupta er al. (1999), the column feeders are characterized by sub-tenninal mouth. The coiling of intestine is regarded as a specific feature of herbivores and omnivores. In P. carnaticus , the intestine is somewhat elongated which represents the omnivores nature of this fish with more affinity towards plant matter. According to Suyehiro(l942), the lack of space in the body cavity for accommodating the full length of the intestinal coils leads to coiling of the intestinal tract. Generally any change in gut length is believed to be closely related to the nature of diet of fishes. Khanna (1961) supported this view and stated that the guts of predatory and carnivores fishes are generally short, on the other hand, that of omnivores are comparatively longer, whereas in herbivores, it is still longer. According to Nikolsky(1963), in cyprinids, gut length less than lO0%of body length indicate camivory while more than 100% indicates herbivory. Low relative gut length (RLG) is indicative of camivory while greater RLG of herbivory. An intermediate value indicates omnivorous mode of feeding (Das and Moitra, 1956a; Das and Nath, 1965; Gupta er al., I999). While studying cyprinid gut morphology, Junger et al.(l989)observed that fishes with RLG ranging between 0.776 and 0.869 showed carnivorous tendencies while those with values from 0.913 to 1.254 were onmivores whereas RLG value of 2.053 was recorded in a herbivorous species. The results of the gut analysis of P. carnaticus revealed that there exists a strong preference towards plant materials in indeterminates, males and females. Plant matter formed the most preferred category of food which is regularly consumed by all fishes irrespective of sex and size, followed by filamentous algae. Diatoms and animal matter 143 appeared as respectively of 3rd and 4"‘ preferential food groups of P. carnaticus. According to Nikolsky(1963), based on the importance of food items in the diet of fishes, 4 categories of food can be recognized. 1) Basic food-normally eaten by fish and comprise of most of the gut contents. 2) Secondary food-frequently found in the gut, but in small quantities. 3) Incidental food-found rarely in the gut. 4) Obligatory food- found in the absence of basic food. In accordance with the above categorization, semidigested plant matter, filamentous algae and diatoms could be discerned as the basic food in all groups of P.carnaticus while semidigested animal matter coming under the category of secondary food item whereas the seeds can be adjudged as an incidental food item. According to the diversity in the types of food consumed, Nikolsky(l963)classified fishes as l)euryphagic — feeding on a variety of food 2)stenophagic-feeding on a few different type 3)monophagic- feeding on only one type of food. Based on this classification all size and sexes of P. carnaticus including indeterminates can be categorized as stenophagic feeders. On the basis of the nature of food consumed and the percentage of ingested food stuff as the criterion, Das and Moitra(l955,1956,l958,1963)classified the freshwater teleosts into 3 primary groups: l)Herbivores- more than 80% of food plant material 2)Omnivores approximately 50% of both plant and animal food, usually with variation in their percentage 3)Carnivores-more than 80% of animal matter. Later two more categories were added: 1) Herbi-omnivore-greater amount of plant matter 2) Cami-omnivore-greater amount of animal matter. While evaluating P. camaticus in the light of above categorization, it appears that this species belonged to herbi-omnivore group because in 144 males 91.95% of the food spectrum was comprised of materials from plant origin while in females and indeterminates it was respectively 90.95% and 96.6%. While analyzing the food preferences of indeterminates and both the sexes, it is worth noticing that though the dietary items of the three groups were more or less same, there was conspicuous variation in the percentage of occurrence of different food items. hideterminates showed more affinity towards animal matter than both the sexes. While in both male and female the affinity towards the plant matter was almost same. Monthly variation in the gut contents COI1filTl‘l6d that indetenninates and both the sexes have identical feeding habits, more or less consuming the same food items, but the extent to which each dietary item consumed was different. It was very glaring that the greater portion of the diet consisted of plant matter during all the months of the year. It appeared that among the three major groups of food items such as semidigested plant matter, filamentous algae and diatoms, a decrease in any of the category was duly compensated by another group. The feeding intensity of the fish was found to be very high. During few months in both the years studied full gut was found as the dominant category in both sexes, which indicates the voracious feeding nature of this species. Gastrosomatic index showed an inverse relationship with the occurrence of empty guts. Feeding intensity of fish was related to maturity, spawning and the availability of food items (Malhotra, l967;Khan et al., l988;Gowda et al.,1988;Keshava er al.,l988;Geetha er al.,l990;Das and Goswami,l997; Rao et al.,1998;Kiran and Waghray,l998;Pandian and Rahrnan,l999).It appears that in P. carnaticus the rate of feeding was very much influenced by the reproductive cycle. Feeding intensity was found to be less during the pre-spawning and 145 spawning periods in females as indicated by the low gastro-somatic index and low degrees of gut fullness. Higher feeding intensity observed during the periods of May-June and September, might be attributed to the occurrence of (a) spent fishes which tried to make good the loss caused by the reduced rate of pre-spawning feeding and (b) presence of immature individuals which require a rigorous feeding for the ensuing vitellogenesis for the subsequent breeding season. When compared to females the feeding intensity of males didn’t show much variation during pre-spawning and spawning periods. The low pre-spawning feeding intensity seen in females might be due to the pressure exerted on the alimentary canal by the voluminous ovary whereas in males, the testes do not grow much in size. But it appears that there exists a feeding rhythm in both males and females. A period of high feeding activity was found to altemate with a period of low feeding. Lagler et al. (1952) had suggested that feeding pattem of fishes is influenced by a number of factors such as light intensity, time of day, season, temperature, salinity, pH and any internal rhythm that may exist. Perhaps there might be an intemal rhythm that acts in someway to bring about the alternate high and low feeding pattem shown by P. carnaticus. Gastro-somatic index indicated higher percentage of feeding among females than males and indetenninates. Generally females consumed more food than their male counterpart. Higher feeding intensity in females when compared to males had been reported by Pandian and Rahman(1999) in Etroplus suratensis. Influence of feeding intensity on condition factor was clearly evident during some of the months in both the sexes of P. carnaticus. (This aspect has been dealt within detail in Chapter 9 on ‘Length —Weight relationship and condition factor’). l46 The present study revealed that Puntius carnaticus is an omnivore, showing more preference towards plant materials as food. Presence of sand and detritus in the gut content indicates the bottom feeding habit of the species. Based on the results of the present study it can be concluded that it would be possible to develop P.carnaticus as a substitute for grass carp in composite culture since this species is having the rare distinction of voracious feeding on vegetation, other plant matters, leaves, stem, roots, fruits and seeds mostly seen in the fi'inges of the rivers. Since this species is categorized under endangered category, its germplasm needs to be protected and conserved by utilizing in the culture basket so easily and rehabilitation of streams through aquaranching. 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Q { A_¢_N! Bo Q“ mumowf O06WIN N: 2 AAGNA ‘do AL: 1 6? V2 __Jm_m iqw J_‘_N ‘M NOEL age _mE_=m U0Hmg__U_Eow mg_|i\ I‘ In | 1‘ ‘V F‘ F Kw _@N Nd‘ we g No ‘Mm E am 0m8\E&__w___omm W09 %}v_NA_NA of W$_ 5_ MN“? g. m_A¢_% }_ n____N%_A Ahmg gm_%mgoEmEm__M ‘So MN_®®yLgm qom gm _2_ Sp ‘Ego Q8 P56 N8“ so ElmmtmgEmE\_§$m__O_Eow wmcobouco ma __° __%___ wE8:U°°1_L__l H“ __‘ V‘: _|_Y IL‘ I: h‘: ‘I ‘Al. |‘ 1- 1| ‘l 4| _gmSN “S ____ 4.5 1 • j 3.5 3 .... 2.5 "'" 0.5 ';0 1 r , 0 0 0 0 0 0 0 0 0 0 N ., 0 ., N 0 ., N • N N .., ill <--- <- <- <- <- <- <- ;r; ~ ;r; 0 ., N ., ..,0 ;l; ., N ., • N N .., • • ~~MmiMI~ 1 - - - L.engtI1 groupo(mm) • Male [ DFema~ I .. ._ _.. I .S.2.Diet composrtlon of indetenninates,males and females of Puntius camaticu5 ______,,(P -'oo=led=fo:::r:..:2:.:00:=-':4_2 ~ ncl2~2_03) ______ Indetenninatas I [] Semidigesled plant-matter • Filamentous algae o Bacillariophyceae o Semidfgested animal matter . Seeds C Miscellaneous Males 6% 32% C Semidigested plant matter • Filamentous algae o Bacillariophyceae o Semidigested animal matter . Seeds C Miscellaneous Females 8% 1 2~ [] Semidiges1ed plant m-. • Filamentous algae ,~~ o Bacillariophyceae o Semidigested animal matter , 12% . Seeds 1_ C Miscellaneous Fig.8.3.Percentage occurrence of guts in different degrees of fullness in females of Puntius camaticus during April 2001 to March 2002 ------ •co i! i ~ ~ ~ ~ Ofull ~ 1;; ~ ~ • •c, ,-3 , .!! .!! .!! .!! 1! _314 full ~ , co E E E ,• •2 '" , c .c • " < • g ~ , 0 112 full j 0 • ...• Z R " 0 114 full Months'" . Trace I D Nit Fig.8.4.Percentage occurrence of guts in dtfferent degrees of fullness in males of Puntius camatJcus during April 2001 to March 2002 100% 90% IW% •co 70% 60% i! 50% 40% 30% i 20% 10% III 0% o full ~ ~ ~ ~ ~ c 1;; ~ ~ ~ • ,• , , .!! .!! .!! .!! .314 full , , co 0 , 1! <'" '"' , E E E •c •2 • " < • g ~ , .c 0 112 full 1S. 0 • • • z R ... " 0114 full '" . Trace - D Nil Flg.8.S.Percentage occurrence of guts in different degrees of fullness in females of Punt/us clImaticus during April 2002 to March 2003 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% ~ DfuH i;' G ~ ~ ~ ~ ~ Q. c 3' ~ . 314 full ,. ~ , 1: 1: 1: .. .. 11 « , E ~ E ~ 2 .. " "~ c «'" G i ,. 0 112 full a 8 ,.. "G I ell z~ ~ "- 0114 full I • Trace I 11 Nil 1.--- - Fig.8.6.Percentage occurrence of guts in different degrees of fullness in makts of Punt/us cllmat/cus during April 2002 to March 2003 . I 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% +-LL,JL...L,-L...l~ ~ Dfull ~ .. ~ ~ ~ ~ ~ ~ ~ C Q. .. ~ ~ .314 full ,. ~ , 0> 1: 1: 1: 1: .. 11 ~ .. «'" , 0 ~ E E E 2 .. " c ,. 0 112 full « ~ ,.. ~ 8 0 § "-".. .. z 0 0 114 full ! Cl) Months . Trace L eNil FIg.8.7.Monthly variation in gutrosomatie Index of males of Puntius camaticus Flg.8.8.Monthly variaHon In gastrosomatie Index of femal.. of Puntius camaticus 9 8 7 6 '" 5 " .3 2 1 o ~ ~ ;; ~ ~ ~ ~ .,. .,. Q. ~ 0 ,• ,~ , 11 11 11 11 ~ ~ ~ "< ,. , 0 , m ,.. E E E 0 2 < • ! ,m .0 ,. 15. 8 0 u.• Jl z R mon"'" I : 2001 ] 1__ - - = Fig.8.9.Lengthwise vanatlon in gastrosomatic Index of Puntius camllflcus Fig.8.9.Lengthwise variation In gastrosomatic: index of Puntiu$ camllflcu$ 6 , 5 -- • - ~ ;;; 3 " 2 1 0 1 , , , , , , , , , , , , . 0 0 0 0 0 0 0 lil 0 ... 0 .. M'" l!! --'"0 0 .,'" 0 0'" '" 0 0 0 6 -+-Indetemlinates 0 ...... ,0 ,; ...., _ Male - '" '" - - leng1II(nwn) -+-FemaIe Fig.8.10.Monthty variation In gaatrosomatic index of Puntiu$ camllflcu$ during April 2OO1-Mlrch 2002 ------, 8 , 7 6 5 ~ 4 3 2 1 j o +--1~~-~ ____~ - - __~ 'E ~ ~ ~ ~ Co •c , , " " " • , , a .!i ! ! , 1! i , ", E ~ E E •c •2 • '" '" ~ , D ! Il 0 • • '" • z ~ "- '" '" -+- F~ J IIorIIt. ---..... l__ -a- I~~ Ftg.8.11.Monthty variltion in gastrosomatic index of Puntius camaticus during April 2OO2-March 2003 9 , 8 7 8 .. 5 " .3 2 ~ +--J~ ~~~ -~~-_~~~~ ,~ , !" " !" !" "a, E E E ! j • '" • ~ -'" ~ Chapter 9 Maturation and Spawning 9.1. Introduction Every living organism has immense power of reproduction and recruitment. Under favorable conditions tremendous increase in their number may lead to population explosion. However, this does not happen in nature because right from the beginning of gameto genesis to the attainment of maturity, there are several factors adversely affecting organism in different stages of reproduction and growth and majority of the off-springs perishes before reaching maturity. During recent past, the natural and antropogenic stresses have been bringing about drastic reduction in the population of many fish species, even leading to the endangerment of some of them. If any fish species is to be managed, conserved and exploited scientifically, a thorough knowledge on the various intricacies of reproduction is of paramount importance. Qasim(l973), while explaining the importance of studying the maturation and spawning of fishes, has stated that the main purpose of such studies is to understand and predict the biological changes undergone by the population as a whole during the year. Information on related aspects such as ecological conditions which lead to the synchronization of maturity and breeding activity in males and females, size at first maturity, breeding migration, sex ratios, sexual dimorphism, fecundity, etc, are having immense application for the conservation and management of fish stocks and also for developing captive breeding techniques and undertaking aquaculture programmes. Size at first maturity is the prime factor in detennining the size at first capture of the natural population. Each fish should be given a chance to contribute to the population by breeding at least once in their lifetime. So also, the over exploitation of immature juveniles will reduce the size of breeding population which would, in turn, lead to the decline of population size in the near future. A precise knowledge on the maturity stage, breeding period, fecundity in relation to size/ age is of 148 great practical utility in fish culture programmes for proper plamiing of successful hatching and nursery operations. The number and size of broodstock to be maintained for achieving a certain set target of fish seed production calls for a knowledge of the fecundity of the species in question (Varghese, 1973). Fecundity studies have been considered useful in tracing the different stocks or populations of the same species of fish in different areas (Gupta, 1968). Extreme variations in all aspects of breeding are exhibited by fishes and hence species-wise information is ineludible before venturing into seed production in aquaculture or conservation of natural fauna. The knowledge on the maturing time, breeding migration, breeding grounds and aggregation assume importance in various fishery regulation and conservation progrannnes. Infonnation on breeding habitats and breeding migration helps in identifying habitats that require conservation and declaring them as aquatic sanctuaries (Anon, 2001). Reproductive capacity provides the rate of replenishment of the stock, which is very essential for the sustenance of fish species and its abundance. The reproductive capacity is an adaptation, which ensures the survival of the species under the conditions in which it is originated and survives. A study on fecundity is essential from the viewpoints of regeneration, stock recruitment relationships and stock assessment in any water body (Nautiyal and Lal, 1985). In recent decades much attention has been given by research workers on the gonadal cycle, reproductive physiology and induced breeding of many species of freshwater fishes from Indian waters (Simpson, 1951; Pillay, l958;Begenal, l957,1978;Sarojini, l957;Das, l964;Varghese, l973,1976;Ch0ndaI, l977;Nautiyal and Lal, 1982 ;Kurup and Kuriakose,l994). 149 A review of literature showed that hitherto no infonnation is available on the reproductive biology of P. carnaticus. Hence, a pioneer attempt was done in this direction to delineate various aspects related to the maturation and spawning of P. carnaticus such as size at first maturity, breeding season, breeding migration, sex ratios, fecundity, etc. 9.2. Materials and methods The study was based on 508 specimens of B.carnatz'cus, 262 males and 150 females ranging in total length from 232mm to 430 mm and 270 to 472mm respectively and weight between 292g to ll20g and 348g to 1'/50g in males and females respectively. Fortnightly sampling of fishes were done from the commercial landings at Peringalkuthu region of Chalakudy river system (Kerala, S.lndia) during April 2001 to March 2003. The specimens were preserved in 8%formalin after making some perforation in the vent region and brought to the laboratory for further investigation. After removing the excess water by blotting, total length, standard length, total weight and colour of the fishes were recorded. Fishes were then dissected out to identify the sex and the condition of the gonad. Gonads were taken out and their length and weight were recorded to the nearest millimeter and milligram respectively following Kurup and Kuriakose (1994). After assessing the stage of maturation, the ovary was preserved in 4% formalin for ova diameter and fecundity studies. The spawning season was delineated on the basis of: (1) quantification of maturity stages, (2) the monthly percentage occurrence of fish with gonads in different stages of maturity, (3) pattem of progression of ova during different months and (4) variation in gonadosomatic index. Based on the scheme proposed by Qayyum and Qasim (1964 a,b,c) and Qasim(l973), the testis and ovary were grouped under five maturity stages. Quantification of maturity stages was done following 150 morphological characteristics of the gonad such as appearance, colour, degree of distension, relative space occupied in the body cavity and ova diameter measurement. To trace the development of ova, ova diameter was measured from ovaries belonging to all the five stages of maturity, following the method of Clark (1934). A total of 150 ovaries in different stages of maturation were examined. Altogether 300 ova with 100 each from the anterior, middle and posterior region of each ovary were taken for ova diameter study. Measurements of ova diameter were taken by an ocular micrometer, which was calibrated using stage micrometer. Each ocular micrometer division was equal to 0.014 mm. Ova measurements were classified into groups of 0.1mm intervals and the monthly percentage frequency of each size group was calculated and the prominent mode recorded. Immature oocytes (0.5 to 0.8mm) were present in varying proportions all the year round and they were not considered while preparing the percentage frequencies. Gonadosomatic index (GSI) was calculated month-wise, applying the formula of June(l953) and Yuen(l955) Weight of gonad GSI = ------x 100 Weight of fish The percentage occurrence of males and females in 3 to 5 stages of maturity in different length groups of the fishes examined was plotted to calculate the length at first matmity. The length at which 50% of the fishes attained maturity was taken as the minimum length at first maturity (Kagwade, 1968; Geevarghese and John, 1983; Kurup, 1994). Sex-ratio data was analyzed month wise and size-wise. Chi-square formula (Snedecor and 151 Cochran, 1967) was employed to test whether the observed ratio between males and females deviated from the expected 1:1 ratio for the two sexes using the fonnula: X2 = (O-E) 2 E Fecundity was estimated on the basis of 35 ripe ovaries of P. carnaticus in the length range of 274mm to 472 mm. Sub samples from the anterior, middle and posterior regions of the ovary were weighed and the number of ova in each sub-sample was counted manually. F ecundity was estimated by the gravimetric method, applying the formula: F= NG/ g where F= Fecundity N= number of eggs in the sub-sample G=Total weight of the ovary G: weight of the subsample Fecundity indices such as the number of ova produced per gram weight of the body or relative fecundity (Bagenal, 1963), the number of ova produced per gram ovarian weight, the ovarian weight as percentage of total fish weight or the coefficient of maturity (Bagenal and Braum, 1968) and the gonadosomtic index or the ovarian weight in relation to the fish weight excluding the ovary weight (Somavanshi, 1985) were worked out. Regression analysis was employed to find out the correlation between fecundity and various body parameters such as total body length, total body weight, ovary length and 152 ovary weight and also between ovary weight and parameters such as total body length and total body weight. 9.3. Results As in most teleosts, the gonads in the males and females of P.carnatz'cus are paired, elongated structures lying on the side of the air bladder ventral to kidneys. The ovary is attached to the dorsal wall of the body cavity by the mesovarium and the testes by means of mesoarchium. Posteriorly, the two lobes of the ovary unite to form a short oviduct, which opens to the exterior by the genital aperture. The testes communicate to the exterior through the genital aperture via the sperm duct. Stages of maturation The following stages of maturation were identified in the males and females of P. carnaticus Degree of Description Maturation Immature virgins Ovaries: Slender, elongated jelly-like, flesh coloured, occupy a little more than ‘/1 of the body cavity. Ova invisible to the naked eye. Testes: Extremely thin, thread-like, translucent, occupy nearly 1/5 of the body cavity Maturing virginsl Recovered spents Ovaries: Somewhat flattened pale yellow, occupy ‘/2 of the body cavity 153 Testes: Opaque, firm, white, occupy nearly 1/3 of the body cavity. Ripening Ovaries: Slightly cylindrical, yellow. Opaque, occupy 3/1 of the body cavity, the inner side slightly depressed to accommodate the gut. Usually asymmetry observed between the two lobes of ovary. Testes: Creamy white, lobulated with irregular outer margin, occupy ‘/2 of the body cavity. Ripe Ovaries: Considerably enlarged, occupy nearly the entire length of the body cavity, golden yellow in colour, distended outer membrane, loosely arranged and clearly visible mature and ripe ova having a diameter ranging from 1.4-1 .8.The ovary is highly vasculated with rich blood supply. Testes: Very soft, cream coloured, occupy more than % of the body cavity Spent Ovaries: Shrunken, flaccid, blood shot, translucent, occupy a little more than ‘A of the body cavity. Few residual eggs, which are in different stages of maturity were observed. Testes: Shrunken, flabby, partly opaque and partly semitransparent occupy less than % of the body cavity. 154 9.3.1. Monthly percentage occurrence of fish with gonads in different stages of maturity The monthly percentage occurrence of males and females in different stages of maturity during 2001-02 and 2002-03 are shown in Fig.9.land 9.2 respectively. In males the immature individuals (Stage I) appeared from August onwards and reached the maximum in October and were contributed 95.7% in 2001-02 and 100% during 2002-03.After October the stage I individuals showed a sharp decline and after December their presence in the catch was not observed. Recovering spent (Stage ll) fishes started to appear in the catch from November onwards and reached a peak during December with a contribution of 72.7% during 2001-02 and 77.4% in 2002-03.From January onwards the recovering spent individuals showed a sharp decline. Fishes with gonads in stage III or ripening individuals appeared in the catch from December onwards and reached the peak during February and contributed to 51.6% in the catch during 2001-02 and 48.3% during 2002 03. Ripe (stage IV) individuals were available in the catch from March onwards and reached the peak during May in 2001-02 and July in 2002-03, contributed to 81.6% and 75.3% respectively. Spent (stage V) fishes were present from May onwards and reached the peak during August and showed their presence in the catch upto September. In females the immature (stage I) individuals appeared in the catch from August to December and reached the peak during October with a contribution of 90.1% in 2001-02 and 92.8% during 2002-03.Maturing virgins or fishes with gonads in Stage II appeared in the catch from October onwards and reached the peak during December with a contribution of 72.5% during 2001-02 and 69.4% during 2002-03 .After March, maturing 155 virgins were not observed in the catch. Ripening (Stage III) fishes appeared in the catch from December onwards and reached the peak during February with a contribution of 88.2% during 2001-02 and 85.5% in 2002-03.Fishes with gonads in stage III condition showed their presence in the catch till June. Ripe (Stage IV) fishes appeared in the catch from March to August and reached its peak during March with a contribution of 75.8% during 2001-02 and 83.2% in 2002-03. From April onwards the ripe females showed a decline and reached the second minor peak during July with a contribution of 74.9% during 2001-02 and 74.6% in 2002-03.Spent (stage V) fishes appeared in the catch from March to September and reached the peak during August with a contribution of 92. l%during 2001 -02 and 94.9% in 2002-03 9.3.2. Pattern of progression of ova during different months The pattem of progression of ova during November to August is depicted in Fig.9.3.All the ova less than 0.8mm diameter were immature. The next group of ova between 08 l.00mm was identified as maturing ones. The ova in the range between 1.00-l.39mm were belonged to the ripening eggs. Ova measuring 1.4mm and abovewere in fiilly ripe condition. The development of ova during different months showed the preponderance of immature and maturing ova during November and December. Oocytes up to l.l'7mm were appeared in January with a major mode at 0.8-0.9rmn.Thereafter; the progression of ova was very rapid with the result that ripening oocytes were very prominent with the mode shitting to 1.00-l.lmm in February. In March the ova diameter ranged between 0.8-1.6 with a major mode at 1.4-1.5mm and minor mode at 1.00-l.lmm ova diameter. During April and May the ova diameter ranged between 0.9-1.8mm size class and the ripe ova contributed to 75% and 70% respectively during both the months. During June 156 and July only ripening and ripe eggs having a diameter ranged between 1.14-l.77mm were observed in the ovary. In August only ripe eggs having a diameter of 1.42-l.78mm were identified from the ovary. During January to August wide range of ripening and ripe eggs having 1.04-1.78mm diameter were observed in the ovaries in varying proportions. Largest oocytes having the diameter ranged between 1.7-1.8mm were encountered during the months of April, May, June and August. While ripening oocytes were dominated only in February. 9.3.3. Gonadosomatic index The mean monthly variation of gonadosomatic index (GSI) values of males and females during April 2001 to March 2003 are depicted in Fig.9.4 and 9.5respectively.During 2001-02, the testicular weight started increasing from September (0.72) and attained the peak in July (3.9). Thereafter the GSI showed a drastically declining trend. The trend was more or less the same during 2002-03 except for the variation in the values. Females showed distinct seasonality in GSI values similar to those of males. Index values which were lowest in September (1.26) steadily increased and attained peak in July (7.1) during 2001-02.The GSI value showed a declining trend from August onwards and reached the lowest level during September. During 2002-03 also, the females exhibited similar trend but for the highest GSI recorded in March. 9.3.4. Length at first maturity Occurrence of males and females at different stages of maturity in various size groups are shown in Table 9.1 and 9.2 respectively. Fig.9.6. represents the relation between maturity and length of the male and female B. camaticus. It appeared that in females, specimens up to 270mm total length and in males specimens up to 231mm were belonged to immature 157 and maturing fishes. The percentage of ripening fishes increased rapidly up to 290mm TL in males and 3l0mm TL in females beyond which there was a sudden increase in the occurrence of fishes with ripe gonads. The smallest ripe male belonged to the 231 250mm TL size group while the smallest ripe female belonged to 271-290mm TL group. The length at which 50% of the specimens attained maturity, taken as the mean length at which maturity is attained (Kagwade, 1968), were 280mm and 318mm for males and females respectively. Thus males were found to mature at a lower size than their female counterpart. 9.3.5. Sex ratio Altogether 882 specimens were examined in the laboratory to determine the sex-ratio. Due to the absence of sexual dimorphism in Rcarnaticus, the fishes were sexed by internal examination. Out of the 508 specimens examined, 262 were males, 150 females and the remaining 470 indeterminates. The month wise distribution of the two sexes (Table 9.3) revealed that the sexes were disproportionate in the population. Males outnumbered the females in almost all months during 2001-02.Chi~square test confirmed the significant dominance of males during 2001-02(Table 9.3). During 2002-03, the preponderance of males in all months except March was glaringly evident from the chi square values. During March the females showed significant dominance in the population (Table 9.3). Though there was considerable variation in the distribution of the sexes in some of the months of both the years, the overall sex ratio showed significant dominance of males (P<0.003). The mean ratio of males to females was l:0.6lfor the year 2001-02 and l:0.7 for 2002-03 and the respective chi-square values of 104.42 and 86.18 lend to 158 support to the above observation that the sex ratio significantly skewed from the expected 1:1 ratio (P<0.0l). Table 9.4 shows the variation in sex ratio among the various size groups. Males were predominating up to 310mm TL and thereafter the percentage occurrences of males were reduced and females showed much higher contribution in the fishery. Beyond the 390mm TL, females dominated in the fishery. Chi-square values indicated that there was significant variation from l:l ratio in the size groups between 271 and 430mm TL. The chi-square value of 59.02 for the overall sex ratio showed that the variation was highly significant (p<0.0l). 9.3.6. Fecundity The average values of fecundity indices of P.carnaticus are given in Table. 9.5. Relationship of fecundity with total body length, body weight, ovary length and ovary weight were worked out by regression analysis and the results are depicted in Fig.9.7 — 9.10. Fig.9. l land 9. l2.represent the regression of ovary weight on total body length and body weight. 9.3.6.1. Fecundity indices The absolute fecundity varied from 2763-14071 eggs in specimens ranging from 216.83 — 445mm in total length and the average was worked out to be 5806 ova. The relative fecundity was estimated to be vary between 4(38l.9mm TL) and 27(338.2mm TL) with an average of 17, while the number of ova per gram ovarian weight varied between l44(367mm TL) and 329(278.lmm TL), with the average 222. The co-efficient of maturity showed higher values up to 331—350mm length group, thereafter a decreasing trend was noticed. Similarly, gonosomatic values also showed an increasing trend upto l59 311-330mm length group, thereafter a diminishing trend was observed. The coefficient of maturity and gonosomatic values varied between 3.6(37l-3901mn size group) and 5.8(33l-350mm size group) and between 3.8(37l-390mm TL) and 7(25l-270mm TL) respectively. 8.3.6.2. Relationship between fecundity and body parameters The relationship between total length (x) and number of ova (y) was calculated and the result is depicted in Fig.8.7. The regression equation after logaritamatic transfonnation of the variables can be expressed as follows: Log F= 0.4266+1.304s log TL; 1-’ = 0.22 The degree of correlation indicates that the number of ova produced have a direct relationship with the length of the fish. The logarithamatic relationship between fecundity and fish weight (Fig.9.8) was found to be Log F=2.7l32+0.3639 log w; 1-’ = 0.11 which shows a linear relationship between them Fecundity was related to the measurements of ovary, the ovary length (OL)(Fig.9.9) and ovary weight (OW)(Fig.9. 1 0) which can be expressed as follows: Log F =0.9366+1.340 log OL; r2 = 0.4 Log F = 2.s16+0.ss32 log ow; r’=0.62 The results indicate a direct proportional increase in fecundity with increase in length and weight of the ovary. 160 The regression equation of ovarian weight (OW) on body weight (TL)(Fig.9.ll) and body length (W)(Fig.9.l2) are given below. Log ow = -0.s09s+0."/011 log W; r’ = 0.49 Log ow = -3.21+1.s317 log TL; r2 = 0.51 The results indicate a direct proportional increase in ovary weight with increase in total length and weight. 9.4. Discussion The male and female reproductive organs of P. carnaticus are built on the general telestean pattem as observed in other teleosts. The paired testes in teleost fishes are either fused along the entire length or completely separate or fused posteriorly. In P. carnaticus, the testes are united at the posterior region to fonn a spermatic duct as reported in Channa gachua(Sanwal and Khanna, l 972a). Breeding season of fishes was ascertained by applying indirect methods such as quantification of maturity stages, monthly occurrence of gonads in different stages of maturity, monthly progression of ova towards maturity and seasonal variations in the gonadosomatic index. Results of the two years data have shown that as far as occurrence of gonads in different stages of maturity is concerned, females mature slightly earlier than males. During September, all fishes collected belonged to immature and maturing stages. Thenceforth, majority of the fishes underwent ripening rapidly and by the end of December majority of the males and females were in the maturing virigin stage. At the end of February, most of males and females reached the ripening stage. From February onwards the maturation in males was a slow process and from the end of April onwards ripe males appeared in the population. While maximum number of ripe males appeared in 161 the population during May. In the case of females, ripe fishes were observed in the population from March to August with a peak during March. Females showed strong oscillations in their occurrence from March to July. Though ripe individuals appeared in insignificant numbers during March, the presence of spent fishes was observed only by the end of April in females, which would suggest that actual spawning might have commenced in April. The fish might have completed its spawning by the end of August, as manifested by the total absence of spent fishes during October and November. Based on the results of the present study, it can well be concluded that P. carnaticus inhabiting Chalakudy river has a prolonged spawning period extending from April to August with a distinct peak during July —August. It is well known that ova diameter measurements can give reliable evidence about the time of spawning and spawning periodicity of fishes. Clark (1934) made the first attempt to study the maturity of Califomia sardine (Sardina caerulea) based on the size frequency of ova in the ripe ovary. This method has been successfully applied for delineating the spawning period of many Indian fishes by several authors (Prabhu, l956;Qasim and Qayyum, l96l;Sathyanesa.n, l962;Annigen', l963;Bhatnagar, l967;Desai and Karamchandani, 1967;Qasim, l973;Murthy, l975;James and Baragi, 1980;Jayaprakash and Nair, 1981;Thakre and Bapat, l981;Geeevarghese and John, l983;Kun1p, 1994). In P. carnaticus, all the ova measuring l.4m1n and above were fully ripe while the group having diameter between 1-1.4mm were the ripening ones. Those falling below lmm were adjudged as maturing and immature categories. From the appearance of largest oocytes of l.75mm in fully ripe conditions in April, 1.73 in July and August, it can be reasonably concluded that this species starts spawning during April and this is in close 162 agreement with the spawning season delineated for P. carnaticus in the present study. From the pattern of ova diameter frequencies arrived at different months, a distinct mode of 1.4-1.5mm size class were observed during March, April and May while during June, July and August, 1.5-1.6mm size class dominated in the ovary. During November and December the immature oocytes of 0.5-0.6mm size class showed their dominance in the ovary. While in January the predominance of 0.8-0.9mm size class was noteworthy whereas in February size classl.00- l . lmm showed their dominance. The results revealed that P. carnaticus has a prolonged spawning season with two peaks with former in April May while the second one during July —August. The prolonged spawning may be atonement against the low fecundity of this species. The present finding is in corroboration with the findings of Nikolskii(l96l) and Wootton(l984) who opined that multiple spawning is helpful in increasing the fecundity of fishes. A relatively long lasting spawning readiness which could explain the continuous presence of mature females has been previously reported by Alkins-koo(2000)while studying the reproductive timing of fishes in a tropical intermittent stream in West Indies. Ova diameter of Rcarnaticus indicated the presence of oocytes in varying maturity stages in the ovaries. The wide size range of mature ova with indistinct minor modes within the group of these mature ova would manifest the tendency of the fish for fractional spawning within the season. According to Nikolskii(l963), fractional spawning and prolonged spawning are characteristic of tropical and subtropical fishes and may not only be just an adaptation to increased food supplies, besides they also ensure the survival of the species under unfavorable spawning conditions. Fulton (1899) stated that the occurrence of large number of ova of different sizes between immature and ripe ones 163 in mature fishes can be considered as an evidence of its prolonged spawning period. Norman (1931) reported that the actual rate of extrusion of ova will vary in different species. While in some species, majority of the eggs become ripe more or less at the same time whereas in others the process is comparatively slow and only a part of the ova ripen and are getting released at a time. According to Hickling and Rutenberg(l936), a single group of ova will get differentiated when the spawning is short and definite while in the case of long and indefenite spawning, no distinct separation exists between the general stock of eggs and the maturing eggs. Marza (1938) described three categories of rhythm in the maturation of oocytes.(l)Total synchronism- all oocytes in the ovary develop synchronously as in Onchorhyncus mas0u(Yamamoto et al.,1959) (2) Group or partial synchronism-two groups of oocytes are distinguished indicating spawning once a year within a short and definite period as in Clarius batrachus(Lehri,l968).(3) Asynchronism —oocytes in different stages of development are present indicating a long spawning season with several spawning within the season as in Schizothorax richards0m'i(Bisht and Joshi,l975).In P. carnaticus, different batches of oocytes continuously passing from one stage to other were observed and hence the fish exhibited asynchronism in oocyte maturation. As far as the duration of breeding season is concerned, Kramer (1978) suggested that it ranges from extremely brief (l-2 days) through moderately long (2-4 months) to continuous spawning. Prabhu(l956) treated the duration of 2-3 months as prolonged breeding season. Qasim and Qayyum(l96l)stated that the breeding season is short when it lasts for about 2-4 months and relatively long when it lasts for 4-5 months and non-seasonal occurring over a greater part of the year. In P. carnaticus, breeding season lasts for 4-5 months and 164 therefore, this species can be categorized under ‘relatively long’ following Qasim and Qayyum(196l). The timing of annual spawning for each species inhabiting a particular niche has evolved to ensure that the young hatch and commence feeding in a season which is most conducive to their survival (Bye, I984). Stancey(l984) reported that ovulation in most teleosts occurs rapidly in response to specific exogenous factors relevant to reproductive success. These factors include photoperiod, temperature, spawning substrate, visual and chemical stimuli, pH, turbidity of water and availability of food items. In Indian subcontinent, most of the freshwater fishes are reported to be monsoon breeders (Jhingran, 1982). The earlier reports of Khan (1945), Kulkami(l950,l97l), Khanna (1958), David(1959), Karamchandani(l961), Belsare(l962),Bhatnagar(l967), Parameswaran et al.(1972), Rao and Rao(1972), Khan and Jhingran(l975), Murty(l975), Sidiqui et al.(l976), Pathak and .Thingran(l977), Somavanshi(l980), Vinci and Sugunan( 1981), Badola and Singh(l984), Shreshtha(l986), and Kurup(l994) lend support the above observation. Most of the factors triggering spawning in tropical fishes are supposed to be associated with onset of monsoon and flooding. Fishes are thought to be sensitive to the rising water levels (Alikunchi and Rao, 1951; Khanna, 1958; Kulkarni, 1971; Shreshtha, 1986). Habitat expansion in the rainy season leads to decreased crowding and predation pressure (Alkins-koo, 2000). Improved productivity and food availability (Hails and Abdullah, 1982) and optimum temperature (Qasim and Qayyum, 1961) during rainy season are the other reported factors influencing the spawning of freshwater fishes. Qasim and Qayyum(l96l) stated that the breeding seasons in freshwater fishes are adapted to provide optimum conditions of temperature and shelter 165 for the newly hatched fishes. The results of the present study indicate that the beginning of spawning in P. carnaticus coincided with the pre-monsoon showers; however, the juveniles would be present in the population at the time of peak flooding. The maturation of genn cells in fish gonads is associated with an increase in the weight of gonad and this increase is expressed by the gonadosomatic index (GSI). However, the process of maturation is not exactly identical in males and females. In ovary, as the oocytes grow, they accumulate metabolites leading to an increase in their weight (Nagahama, 1983). GSI is indicative of fish spawning in temperate and tropical regions (Bouain and Sian, 1983; Biswas et al., 1984; Phukon and Biswas, 2002). GSI values of both males and females followed more or less the same trend. Low GSI values in September and October is concomitant with a period of early development of gonads and occurrence of spent fishes. The slightly high values observed from November to February reflected a diversity of gonad stages including a large number of maturing (II stage) and ripening (Ill stage) gonads. Comparatively high GSI values were encountered from March to August in both the sexes. The peak GSI values encountered during March and July in females while in males the peak GSI was registered during May and July. During spawning season, the GSI show a plummeting due to the release of the gonadal products. Hence breeding season ensues the months with maximal GSI. Reduced GSI in females is a consequence of release of ova from the ovary while in males, it may result from the combined effect of elimination of residual body followed by initiation of spermiation (Stoumboudi et al., l993).In P. carnaticus , the sudden drop in the values in April and August is indicative of the onset of spawning season. The conclusion drawn earlier that l66 P. carnaticus spawns twice a year can be further be substantiated by the two peaks of GSI, the former in March and the latter in July. Based on the occurrence of large number of ripe fishes and ripening individuals with advanced stages of oocytes in the ovary, the appearance of spent individuals, the presence of ripe ova and the high GSI values, it can reasonably be inferred that this species is reproductively active for 4-5 months (April~August) with the onset of premonsoon showers and towards the end of south west monsoon. Nath(l994) studied the spawning ecology of fishes in J ammu Province and observed that the cyprinids , Labeo rohitha, L. calbasu and Cirrhinus mrigala became ripe in May , however, spawning commenced only from the begimiing of July with the onset of monsoon. Similarly, other related fishes such as Chela, Salmostoma, Barilius, Dania, Chanda and Puntius were reported to breed during the early part of the monsoon on the margins of ponds, lakes and rivers. Prabhu(l956) classified fishes into 4 distinct groups on the basis of the spawning pattem. Type A: Spawning taking place only once in a year during a definite short period. 2 batches of ova, mature and immature, are found in mature ovaries. Type B: spawning taking place only once in a year but with a longer duration. The range in size of the mature ova will be nearly half of the total ranges in the size of the whole intra—ovarian eggs. Type C: Spawning twice a year. Ovaries contain distinct ripe as well as maturing ova. Type D: Spawning throughout the year but intermittently. Ovaries contain different batches of eggs which are not sharply differentiated fi"om one another. Qasim and Qayyum (1961), on the basis of ova diameter frequencies, classified fishes into 3 categories. 167 Category I: Fishes with a well-marked single batch of maturing eggs in their ovaries. Breeding occurs only once a year. Category II: Fishes with more than one group of maturing oocytes. The breeding season is long. Category Ill: Fishes with oocytes of all sizes ranging from the smallest to the largest without well-marked batches. They have non-seasonal breeding. It would thus appear that P. carnaticus fits into Type ‘C’ of Prabhu(l956) and category II of Qasim and Qayyum(l96l).P.camaticus was found to breed twice in an year in the Chalakudy river with ovaries containing more than one group of maturing oocytes. The breeding season was observed to be moderately long. Usually fishes attain maturity at a particular length of the individuals. The onset of maturity differs considerably inter-specifically as well as intraspecifically (Nikolskii, 1963). Information on the size of maturation is essential for avoiding over exploitation of immature juveniles and ensuring the spawning of the individual fishes at least once in life. The minimum size of maturity has been estimated earlier by several workers (Qayyum and Qasim, 1964a; Parameswaran et al., 1972; Selvaraj et al., 1972; Sobhana and Nair, 1974; Somavanshi, 1980: Nautiyal, 1984; Sunder, 1986; Kurup, 1994; Agarwal, 1996). In P. carnaricus, the males and females were found to be mature at 232 and 270mm respectively. Thus, males attain sexual maturity at a smaller length than the females. Similar observations had been reported in many freshwater fishes such as Cyprinus carpz'0(Parameswaran er al.,1972),Labe0 b0ggut(Selvaraj et al.,l972)Barbus sarana(Murthy,l975), Tor t0r(Chaturvedi,1976), Labeo g0m'us(Siddiqui et al.,1976a), Labeo bata(Siddiqui et al., l976b), Noemacheilus triangularis(Ritakumari and 168 Nair,l979), Schizothorax l0ngzpinm's(Sunder,l986) and Labeo dussumieri(Kurup,l994). The first appearance of ripe and spent individuals in 230-250mm size group in males and 270-290mm size group in females of P. carnaticus suggest that this roughly corresponds to the minimum size group at which the females and males attain ripeness and start spawning. lt is a generalized fact that among fishes, males usually grow to a smaller size than females (Sivakami, 1982). In P.carnaticus also, females are larger in size. The maximum size of the males and females encountered during the present investigation is 430mm and 472mm respectively. The difference in the size at first maturity and the maximum size attained in the two sexes may be due to differential growth rate or due to the fact that females live longer and hence attain a larger size (Murthy, 1975). A proper knowledge of sex ratio is important in the management of fishery. It indicates features such as the movement of sexes in relation to season, strength of spawning stock, catch composition, etc. Considerable variation was observed in the ratio of males and females of P. carnaticus in some of the months of two years. Murthy (1975) reported similar condition in Barbus sarana and opined that the contradictory values of the two years could be due to sampling variation or may reflect actual situation of sex ratio, which shows variation from year to year. However there, was a preponderance of males during almost all the months. This observation closely agreed with the findings of David (1954), Qayyum and Qasim(l964a) and Singh(l99'7) in Hilsa ilisha, Channa punctatus and Schizothorax plagiostomus respectively. The ideal sex-ratio in natural population is close to l:l(Nikolskii, 1980). A definite ratio of males and females during the spawning season is a prerequisite for most effective fertilization of eggs deposited by spawning females. The deviation in sex ratio from the 169 ideal one during the spawning season encountered during both the years with a distinct predominance of males may be a contributing factor to the endangerment of P. carnaticus. Nautiyal(l994) and Singh(l997) reported that spawning migration of fishes can lead to alterations in sex ratio drastically. The changing sex ratios may be associated with the shoaling habits of fishes, which might be a contributing factor for the dominance of either of the sex in the catch composition of different days. Differential mortality may be another cause of skewness in sex ratio (Bhatnagar, l972). The higher occurrence of males in lower and females in higher size groups as observed in P. carnaticus are corroborating with the findings in a number of fish species (Bennet, 1962; Bailey, 1963; Bhatnagar, 1972; Chaturvedi, 1976; Siddiqui et al., 1976a; Somavanshi, 1980, Vinci and Sugunan, 1981; Kurup, 1994). According to Makeeva and Nikolskii(l965), variation in sex ratio at different sizes and age groups exists even in species with an overall 1:1 ratio. Nikolskii( 1980) assigned the dominance of males in smaller size groups to the tendency of males to mature earlier and live less longer. Siddiqui et al. (1976b) stated that the increase in contribution of females in higher groups might be due to heavy mortality of males in smaller size groups either due to natural death or fishing pressure as they were more active and caught more easily or more exposed to predation. According to Qasim(l966), the disparity in growth rate between sexes led to the preponderance of one sex and the preponderant sex attains a bigger size. This is at variance with the present observation in P. carnaticus in which the males were dominant in the sample population, although the minimum size at maturity and the maximum size of the individual was found to be higher in females. I70 Lowe-McCom1ell (1975) defined the fecundity as the number of eggs produced by an individual fish in its lifetime. Bagena](1978) considered it as the number of ripening eggs found in female prior to spawning and termed it as individual or absolute fecundity. Fecundity is generally regarded as the number of ova in an organism, which has the potential to give rise to the offsprings. Thus, the reproductive potential is a function of the fecundity of fishes. Fecundity varies both within and between fish populations and numerous factors such as nutritional state (Scott, 1962; McFadden et al., I965; Stauffer, 1976), time of sampling and maturity stage (Healey, 1971), racial characteristics (Bagenal, 1966) and enviromnental conditions such as rainfall and salinity (Joshi and Khanna, 1980). Fecundity in teleosts range from a few hundreds to several lakhs. The fecundity estimates of important freshwater cyprinids have been reported by several authors.Fishes such as Labeo calbasu(Khan,l934;Rao and Rao,I972;Vinci and Sugunan,l98l), L.r0hita(Khan,l934;Varghese,1973), Cirrhinus mrigala(Khan,l934; Chakrabarty and Singh,1967), L.dero(Bhatnagar,l967), Cyprinus carpi0(Parameswaran et al.,1972),Lfimbriatus(Bhatnagar,l972),L. g0m'us(Joshi and Khanna,l980) and L.dussumz'eri(Kurup,l994) are highly fecund fishes with several lakhs of eggs. Puntius vittatus(lbrahim,1957)with 26 to 302 ova, Barilius bendelisis var. chedra (Desai and Karamchandani,l967)with 305-1168 ova, Glyptothorax kashmirensis(Kaul,l994) with 692-1392 ova and Noemacheilus triangularis (Ritakmnari and Nair, 1979) with 800-2126 ova are some freshwater fish species with less number of ova in their mature ovaries. The fecundity of other cyprinids are 2368-8590 ova in Puntius tz'ct0(Ibrahim,l957),1700-6259 ova in Garra mullya(Somvanshi,l985), 3340-6160 in Crossocheilus latius dz'plocheilus(Kaul,1994),34l6-53139 in P.stigma(Ibrahim,l957)l4245-58330 ova in 171 P.d0rsalis (Sivakami,l982) and 58327-139934 ova in P.sarana(Sinha,l975). In P.carnaticus the fecundity ranged from 2820-1407l.Comparitively bigger sizes of the eggs may be identified as one of the reasons for the low fecundity of P.carnaticus. Bulkley (1976) discussed the influence of egg size on fecundity in steel head trout, Salmo gairdneri and stated that it is possible that a fish producing fewer eggs could produce larger eggs within limits than if it were producing numerous eggs. Fecundity is higher in those fishes in which eggs are smaller in size than those in which the eggs are larger (Kaul, 1994). The reproductive potential of fishes of different size groups had been expressed as the number of ova produced per gram body weight called relative fecundity. (Bagenal, l963;De Silva, 1973b) or comparative fecundity (Das, 1964). Relative fecundity provides a better comparison of fecundities and eliminates the alteration in absolute fecundity with fish age and size (Sheila and Nair, 1983). The present study revealed that the average relative fecundity of P. carnaticus was ll.This value is very low when compared to a relative fecundity of 252 in L.caIbasu(Pathak and Jhingran,l977),256 in L.r0hita(Varghese,l973),285 in L.bata(Alikunchi,l956), 275 in Barilus bendelisis (Dobriyal and Singh,l987), 271 in L.g0m'us (Joshi and Khanna,l980), 228 in P.vittatus (Ibrahim,l957),227 in P.sarana sunasutus (Sobhana and Nair,1974),20l in L.calbasu (Vinci and Sugunan, 198 l) and 180 eggs in Ldussumieri (Kurup, l994).It can therefore be concluded that the very low relative fecundity of P. carnaticus when compared to other species is a major reason for the endangerment of this species in the natural waters. 172 The number of ova per gram ovarian weight was ranged from 46-630.Sivakami (1982) estimated the average number of ova per gram of ovarian weight in P.d0rsalis as 3319, which is comparatively very high when compared to that of P. carnaticus. Even though the coefficient of maturity showed some oscillations in different size groups, it showed a decreasing trend after 890g size. According to Hochman(l967), a declining trend in the coefficient of maturity after reaching a particular size could be a manifestation of beginning of aging , connected with decreasing reproductive capacities. Gonadosomatic index and relative fecundity also followed similar trends. As reported in Garra mullya by Somavanshi( 1985) and Ldussumieri by Ku1up(l994), the initiation of aging in P. carnaticus is marked by changes not only associated with maturity index but also with gonadosomatic index and relative fecundity. Fecundity is often correlated with length, weight and age of fish and also with the length, weight and volume of ovary. The relationship between total length and fecundity differ in different species of fishes. Clark (1934) opined that the fectmdity of a fish increased in proportion to the square of its length. Simpson (1951) established that the fecundity of plaice was related to the cube of its length and was thus directly proportional to fish weight. Many authors have supported Simpson’s view of fecundity being related to fish length by a factor closer to the cube (Bagenal, 1957; Sarojini, 1957; Pillay, 1958; Pantalau, 1963; Varghese, 1973, 1976; Kurup, 1994). After surveying 62 fish species, Wooton(l979) concluded that the exponent value varied from l to 5 with most of the values lying between 3.25 and 3.75 and invariably higher values were reported in marine species than in freshwater forms. Jhingran(l96l) and Qasim and QayyLun(1963) have reported the exponential value to range around 3. In the present study, the exponential 173 value of P.carnaticus was observed to be 1.3048 which showed significant difference from the value of ‘3’ and this finding is in total agreement with the above reports. The value of exponent in the length - weight relationship of female was found to be 2.4575 (Chapter 9). Since the exponential value in the length — fecundity relation (l.3048) was observed to be lower than that in length-weight relationship (2.4575), it appears that the fecundity in the species increased at a rate lesser than than the rate of increase of body weight in relation to length. Fecundity was found to have a linear relationship to body weight. The ‘b’ values of 0.3639 showed that body weight have very low influence on fecundity. The coefficient of determination (r2) indicated that only 22% of the variation in fecundity was associated with body length. The correlation of fecundity on body weight indicated that only 11% of the variation in egg production was explained by the changes in weight. Linear relationship between fecundity and body weight has been reported in L.fimbriatus(Bhatnagar,1972), P.sarana(Sinha,l975), L.r0hita(Khan and Jhingran, l975),L.bata (Siddiqui et al.,l976b), L.der0 (Raina and Bali, 1982) and L. Dussumierz'(Kurup,1994). The observations of some early workers (Bagenal, 1957; Sarojini, 1957; Gupta, 1968; Varghese, I973) also lend support to the linear relationship between fecundity and body weight. The coefficient of correlation of the various statistical relationships derived between fecundity, body length, body weight, ovary length and ovary weight revealed significant relation between fecundity and the body parameters. The highest degree of correlation was seen between fecundity and ovary weight. This is in agreement with the observations of Chathurvedi(l976) in Tor t0r,Joshi and Khanna(1980) in L.g0nius, Qadri et al.(l983) 174 in Schizothorax richardsonii, Sunder(l986) in S. longipinnis and Kurup(l994) in Ldussumieri. It is well known that the weight of ovaries of a fish is mainly influenced by the ova contained in them. The ‘r’ value between ovary weight and body length and ovary weight and body weight exhibited a fair correlation between the variables. From the study on the relationship between fecundity and various body parameters it can be concluded that ovary weight was identified as the most appropriate predictor of ovarian egg count, 61.4% of the variation in fecundity being explained by the changes in ovarian weight. I75 TableMaturity 9.1.Percentage Maturity stages in different length stages groups of male Puntius camaticus L°F?9§l‘.9L°E.E(.'F'T') -'. . all III IV V 231-250 - -29-.59 3.92 13.64 4.76 251-270 25.49 23.81 il 9.3.0.1 9.09. Ll 271-290 9.80 37.25 9.09-1 if 7.69 l 291-310 15.69 13.73 18.18! 14.29 31 12-7330 y H M____ 17.65 11.76 4.551 7.69 192.905 331 -350 7 A 13.73 7.84 4.55 7.69 9.52 351-370 3.92 g_ 31.82 7.69.. 19.05 371-390 1.96 3.92 39.09.- 23-08 9.52 391 -410 1.96 7 3.92 . 146-15 ____.. Table 9.2.Percentage Maturity stages in different length groups of female yf_>_r_:_ntr'us camatfcus lllaturity stages gLengthgr9u231-250 yylll IV =V Ll 251-270 6.25 12.50 6.32l _..3.-.23 271-290 12.50 11.36 12.90 291-310 12.50 37.50 4.55! 9.68 31 1-330 ___ __ M______1g8.75 12.50; 12.50 20.45 16.13 331-350 12.50 25.00; 12.50 22.73 12.90 351-370 12.50 9.09 29.03 25.00 l 371-390 25.00 187 289 _. . __.__.,i_ ___.1.. _ l 391-410 37.50 2.27 3.23 12.50]? L 411-430 g____g 312.501 4.55 12.90 Table 9.3.Sex ratio of Puntius camaticus during different months of 2001-02 and 2002-03 Months Total H W §Mg:_Fg Chi square Probability April 722 14 1 110.6 8.50 P<0.05 15 1 1 :0.9 8.87 P<0.05 May 2 1 17“ 8 i June '77 1 15 121 y 1 :0.3 9.37 P<0.05 July 13 9 1 1 :0.4 3.49“P<0.05 /-\u9vS1 9 5 I V 1 10.8 3 3.46 P<0.05. _$9P!?_r!199.r. - . 20 1 11023.17 if 8.76 P<0.05 9919*‘ 14 9 W 1 10.6 I 8.98 P<0.05 November 1 __.31 23 81 :0.4 8.51 P<0.05 y. December 1 if 911—i 28 17 11110.7 8.73 P<0.05 January y W 35 24 11 1.0.5" 3.72 P<0.05 February fig" "N 34 24 “10_1:0,“H4 8.50 ‘ P<0.05 March __H 30 13 12 .170.7 8.53 i P<0.05 Total 266 1747 92 1=0.6 1 04.422 P<0.05 2002-0371 April9M 9 1 :0.6 7.13 P<9.9§ if 27.7173 May 131 .2.. 1:1 I B59-°§ 1 June 131 A 1 10.7 7.09 jP<0.05 -1 :05 7.11 P<0.05 July 8= 1 30.7 August 1 12! _ L1 .39 P<0-05 12 l 1 :0.4 77:85 Sepiember . . _._r_l _ P<0.05 October i M W712 .11 3:03 7.13_P<0.05 T November L fig M7 15l 1Z1 ; 7.12 l P<0.05 Decem ber M 15 M V 1 :0.4 7.13 . P<0.05 4January 12 1 :0.5 7-1.3 . P<0.05 February“ W H 14 1 120.4‘ M775“ “W .. .7-.11 §P<0.05 March __y I 11 y 1.21257" _ 7.10lP<0.05 Total W W 7 140” 1150173 36.131 P<0.05 Q _\ Q Q \1 (O @ CO (D \I (Q01 -P9 O) OJ OJ U1 O‘) -I8 O1 O’) (.0 O1 (O -IS -b 8 \l *9-Le. 9? ‘*7. 5'. °.°__ K8‘_ Am no 7PNo \ N NON‘ M ‘ E 5 LI L ‘A A Iomr IIF AA Im‘I““""‘H‘I‘ Omig@moVQM(mg % W lb ( & QM ’ §\_m_| in; %;_‘_8 Emw QR o®m__Nm“@3©3%tum ‘mg i_gmm %é : E8 [l§_l $__A kw” imfiw 8% I Kg“ Av_o_ mm N_mm_mN ®'oNml7%%Nm_mmm H Em- Bmmomm_FWm% ©®©@L onF; ¢ Pg“ L_Nm_N_ %_;Ni ’B_mt‘ J3; O8 _ 3©®NVNdmg %N_w_N *2: 6 62 Q8“ __mNAi%%‘ pmwiva»%N©22"YL@w_o Lmd an Q8 ? 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FIg.'.''-''-'-__ ot __ ot ___ In d_, ...... 01 -rIIJ durIng_-2002 ._ - - _._--- 'DO 00 ..00 20 • 1-"","'" J I t ~ J j I !I f I I ~ tiliL t J I t ~ J j I I I I I I [,: loo :.f: ...... "'*- ...... 00 70 00 ..50 3D 20,. • .... '20 'DO 00 ..00 20 • -- -~ ...... "'*- -- ,_._-- - ~ FIg .'.2~-'-_of~of""_._. In _t ... of nmurtty during 2M2·zon 100 80 ..60 20 ...... -.-.., .... , , i ~ } JJ I I I I ~ , ' t ~ } J J I I I I ~ 100 eo ..60 20 • ~ !, b, , .. ~ :i ~ ~ I ~ .,"!r :i j J I I ~ I 120 100 eo 60.. 20 , , . . • ~ b 1I . ~ , .. ! , ! .. .. ~ ,.• ~ I ~ ~ ,.• 1 i I ~ I ~. I I FIg.9.3.Monthty validon In ova diameter percentage frequency of Puntlus camMlcus April , , , • , " • ~- ~ ~ ~ ~ ~ 3 Ova diameter(mm) Ova diameter(mm) December Moy i'l.30 40 iC20 1 , , , , , , 0 , , , ~ , ~, , CLi~ l oh~ ..:. cA " ...:. CL oh ..:. cl cl cl ..; cl cl - Ova diameter(mm) Ova diameter(mm) January .. June f~ +l~~,~,~, ~,~,~,~,~, ~,-,~,~,~, a. .. o '" .. Ova diameter(mm) Ova diameter(mm)-- .. July C> ~ @: 0 1 , , , , , ~ , ~ .. , .. .. 0 ~ ~ - " Ova dia..-.jmm) Ova diameter(mm) "arch Auguot .. 40 1 , o , , , , , , 0 , I~ -I--~' ~,~, ~~-. _, , ~.,~ ~~~,~, , ..o - - Ova diameter(mm) "- Ova diameter ~ ~ ~ ~ Gon~dooomatlcIn:.x(G~;1i 1-Gonadooomatlc Indox(GSII ~ ~-:",~W"Ulo)~~~ ; ... ~;.. OIQ) ....HD ~ ...... oC ' oC ~ < ~ R < "~ ~ .~ May' I~ May ' ~ ~ J g June E7? So June ! So C ~ c July ' ;j, g July , g & ~ a. Augusl I August Jii'- ~ OCtober IiiiiiI. it October a. •M M• November ~ 5' November 5' ~ ~ ~ December R § December ~ § ~ ~ ~ g. January 0 ~ January ~ ri . ~ . February D i! February R i ~ 4 g. March R fA March 0 fA -' CL .J Cl. C C ~ 3:; 1, c6 ~•3 mCl et"T1S' "m mI:I " ,,,IS ]8 ~IS, 8 ..- ~ ~ 7' Ng Ng W N Fig.9.S.Percentage occurrence of mature males and females in Puntius camBtlcus 150 ••COu :I c 100 c! • • • • -+- Male . ~ 50 _ Female e u &8 0 I::ae:,·, , , , , Length class Fig.9.7.Relationship between fecundity and total length of Puntius camaticus 1>5 ;; 4 ,...... • § 3 • • .. . ¥ 2 -go 1 -'O +----~---~----~--~ 2.3 2.4 2.5 2.6 2.7 Log totallength(mm) Log F =0 .4266+1 .3048log TL;" =0.22 Flg.9.S.Relationship between fecundity and total weight of Puntius camaticus i;' j : 1+-______r-____-. ___ .._ 7_:-:__ r· ______~ J 0 1 2 3 4 Log fish w.lgh~ g) Log F = 2.71 32+0.3639Iog W;" = 0.11 Fig.9.9.Relationship between fecundity and ovary I weight of Puntius camaticus 1> 5 '0 4 .. § 3 •• cHt .... •• ~ 2 8' 1 -' 0 +-----.----~-----r------, o 0.5 1 1.5 2 Log ova'Y w.lgh~g) Log F = 2.516 + 0.8532 log OW; ,. = 0.62 Fig.9.1 0.Relationshlp between fecundity and ovary ______-" ie"n"gth of Punt/us camaticus ~ 5 .c JP- 4 ; 3 - •~ 2 ~ 1 0 " 3 0 0.5 1 1.5 2 2.5 Log ov.ry lengttt(mm) '------' ~ioQ ' F ;' 0.9366+1.340I;,gc:OC"L-;".,..="::0-=.4------' Fig.9.11 .Relationship between total length and ovary weight of Punt/us camaticus ~ .c- 2 .. 1 5 • 1 . ... . I".. .,~ - ~ 1 • • • ~ 0.5 o 3 0 2.3 2.4 2.5 2.6 2.7 Log body weight(g) Log OW= -4.5098+0.7011 log W;,.. = 0.49 Fig.9.1 2.Relationship between body weight and ovary .-______--' W".,,!ght of Puntfus camatfcus ~ 2 • -&1- .5 .. . A1 ·.r - -; 1 • • ....• . '". -. ~O . 5 > 0 0 ...... 0 2.3 2.35 2.4 2.45 2.5 2.55 2.6 2.65 2.7 Log total iength(mm) Log OW ~.21+1.8317Iog TL; r2 - 0.51 Chapter 10 Length- Weight relationship and Condition factor 10.1. Introduction Growth is defined as the change in size with reference to time. Weight of a fish is expressed as a function of length. Knowledge of length - weigh relationship is of paramount importance in fishery biology as it serves several practical purposes. The general length-weight relation equation provides a mathematical relationship between the two variables, length and weight, so that the unknown variable can be easily calculated from the known variable. This expression had been extensively used in the study of fish population dynamics for estimating the unknown weights from known lengths in yield assessments (Pauly, 1993), in setting up yield equation for estimating population strength (Beverton and Holt, 1957; Ricker, 1958), in estimating the number of fish landed and in comparing the populations over space and time (Sekharan, 1968; Chanchal et al., 1978). It also yields infonnation on the growth, gonadal development and general well being of the fish (Le Cren, 1951) and therefore, is useful for the comparison of body forms of different groups of fishes. The length —weight relationship also has a biological basis as it depicts the pattern of growth of fishes. According to the general cube law goveming length-weight relationship, the weight of the fish would vary as the cube of length. However, all fish species do not strictly obey the cube law and deviations from the law are measured by condition factor (Ponderal index or K factor). Le Cren(l95l) proposed relative condition factor(Kn)in preference to K as the former considers all the variations like those associated with food and feeding , sexual maturity, etc., while the latter does so only if the exponenent value is equal to 3. Thus ‘K’ factor measures the variations from an ideal fish, which holds the cube law while Kn measures the individual deviations from the expected weight derived from the length- weight relationship. 176 The leng1h- weight relationship of cyprinids from India has been subjected to detailed studies, notably by Jhingran(l952), Bhatnagar(l963), Natrajan and Jhingran(l963), Sinha(l972), Pathak (l975),Chatte1ji (1980), Chatterji et al.(l980),Vinci and Sugunan(l98l), Sivakami(l982), Choudary er al.(l982), Malhotra(l982, 1985), Mohan and Sankaran(l988), Kurup(l990), Reddy and Rao(l992), Biswas(l993), Pandey and Sharma(l998), Sarkar et al.(l999), Sunil(2000) and Kurup et al.(2002) . However, no information is available on the length-weight relationship and condition factor of P. carnaticus and therefore, the present study was undertaken to establish the pattern of growth and general well-being of this fish species. 10.2. Materials and Methods 882 specimens of Rcarnaticus comprising 262 males, 150 females and 470 indeterminates were collected from Peringalkuthu region of Chalalcudy river (Kerala) using gill nets of varying mesh sizes during March 2001 to February 2003.The specimens were preserved in 8% formalin. After blotting the specimens to remove excess water, the total length to the nearest millimeter and weight to the nearest 0.01 gram were recorded. Total length was measured from the tip of the snout to tip of the longest ray in the caudal fin(Jayaram,l999). Total length of male, female and indeterminates varied between 232 to 430 mm, 270 to 472mm and 52 to 228 mm respectively and the weight from 150 to 1 120g in males, 300 to l750g in females and l5.2to 314g in indeterminates. The data so generated was subjected to statistical analysis by fitting length-weight relationship following Le Cren(l95 1). Length- weight relationship can be expressed as: W=aLb, the logarithamatic transformation of which gives the linear equation: 177 log W = a+ blogl where w= weight in gram, l= length in mm, a= a constant being the initial growth index and b= growth coefficient. Constant ‘a’ represents the point at which the regression line intercepts the y-axis and ‘b’ the shape of the regression line. The relationship between length and weight was determined for males, females and indeterminates separately by transforming the values of both variables to logarithamatic values and fitting a straight line by the method of least squares. The data was processed in EXCEL soflware. The significance of regression was tested by ANOVA. The regression coefficients of the sexes and indeterminates were compared by analysis of covariences (ANACOVA) (Snedecor and Cochran, 1967) to establish the variations in the ‘b’ values, if any, between them. Bailey’s t-test (Snedecor and Cochran, 1967) was employed to find out whether ‘b’ value significantly deviated from the expected cube value of 3(t=(b-3)/Sb where b= regression coefficent , Sb = Standard error of ‘b’. The t test (Snedecor and Cochran, 1967) on ‘r’ values reveals whether significant correlation exists between length and weight. Relative condition factor (Kn) as per Le Cren(l95 l) is expressed as follows: Kn =W/ “W Where W =observed weight “W = calculated weight derived from length-weight relationship 10.3. Results Length — weight relationship of males, females and indeterminates of P. carnaticus can be expressed as follows: 178 Logarthamatic equation parabolic equation Males log W = -4.1567 + 2.7148log l W=-4.1567 l N148 Females log W = -4.5089 + 2.8618log 1 w=-4.5089 1186'“ Indetemiinates : logW = -0.961 l+l.4243 logl W=-0.9611 1 M243 The 95% confidence limits of ‘b’ values were: Male = 2.4705 - 2.959 Female = 2.5386 — 3.1850 Indeterminates = 1.3117 — 1.537 The logarithmic relationship between length and weight of males, females and indetenninates of P. carnaticus together with con'elation coefficient is depicted in Figs.l0.l, 10.2 and 10.3 respectively. The correlation coefficient ‘r’ between log length and log weight was found to be 0.872 in males, 0.8658 in females and 0.9302 in indeterminates. The‘t’ test on ‘r’ values (Table 10.1) showed the existence of very good relationship between length and weight (P<0.0l). The results of ANOVA on regression of males, females and indetenninates are presented in Tables 10.2, 10.3 and 10.4 179 respectively. The length-weight regressions were found to be highly significant in both the sexes as well as indetenninates(P<0.00l).Based on the coefficient of determination (r2)(Croxton, l953),76% of the variation in weight in males,75% in females and 86.5% in indeterminates were found to be associated with the change in the length of the fish. The results of the analysis of covariance (ANACOVA) (Table 10.5) revealed significant difference in the regression coefficient of males, females and indeterminates(F value = 69.04, df: 2,1102) thereby indicating heterogeneity of the samples. Hence, pair wise comparison between males and females, males and indeterminates, females and indetenninates were carried out using students‘t’ test (Zar, 1974). The results (Table 10.6) show that ‘b’ values are significantly different (P<0.01) in all except males and females. The comparison of elevations disclosed significant difference among the three groups (P<0.0l). Hence, pooling of data to provide a single equation expressing the length weight relationship of P. camaticus will not be justifiable, thus necessitating fitting up of separate equations for males, females and indeterminates. The value of the regression coefficient in males was 2.7148 while in females it was 2.8618 whereas in indeterminates, the same was 1.4243. ‘The‘t’ test arrived at, 2.3(df: 152) in males manifested the significant departure of ‘b’ value from 3(P<0.05). In females‘t’ value (0.8. df: 103) was found as non-significant. In the case of indeterminates the‘t’ value was 27.7(df: 98) which was significantly different from ‘b’ value of 3(P<0.0l). The fluctuations noticed in Kn values of males and females during 2001-02 and 2002-03 are represented in Figs 10.4 and 10.5 respectively. In 2001-02 the Kn values of males 180 showed 2 peaks (April and August) and 1 trough (December). In 2002-03 also the relative condition factor (Kn) of males showed the same pattem. In the case of females, during 2001-02 lowest Kn value of 0.64 was observed during December. An increase in Kn value was observed in April while it decreased in May- June followed by a gradual increase in the values upto August. After August the Kn gradually decreased and reached the lowest level in December. In 2002-03 also females followed more or less the same trend. The average values of relative condition factor in respect of indetenninates and sexes belonging to different size groups are plotted in Figs 10.6 and 10.7 respectively. hi males, higher Kn value of 1.08 was reported in 240-260mm length group, followed by a decreasing trend in 260-280 and 280-300mm size group. In 300-320mm length group the Kn value increased up to 1.1 and plummeted upto 0.94 in 340-360mm length group. Thereafter, the Kn value increased and reached the highest value of 1.2 in 360-380mm size class followed by a diminishing trend. In females, after reaching a Kn value of 1.06 in 280-300mm size class the relative condition factor gradually decreased and attained the lowest value of 0.98 in 320-340mm size class. Thereafter, the Kn increased to a peak in 380-400mm length class followed by a gradual decline in the succeeding classes. In the case of indeterminates the Kn gradually increased from 0.73 in 40-60mm length class and showed a comparatively good condition of 1.03 in 120-140mm length class. Thereafter the Kn decreased to 0.96 in 140-160mm length class and reached the peak of 1.08 in 160-180mm length class. Beyond 160-180mm length class the Kn showed a declining trend and plummeted to 0.85 in 200-220mm length group. 181 10.4. Discussion Length-weight relationship was expressed by the cube formula W=aL3 by the earlier workers (Brody, 1945; Lagler, 1952; Brown, 1957). Allen (1938) supported this law and declared that for an ideal fish, which exhibits isomeric growth, the value of regression coefficient should not be different from 3.The cube law confers a constancy of form and specific gravity to an ideal fish. However, adverting the inadequacy of the cubic law in explaining the length-weight relationships in fishes, many researchers adopted the general formula in the form W=aLb. LeCren(l951)suggested that the deviations from the cube law might be contributed to the condition of the fish, reproductive activities, taxonomic differences or environmental factors. Ricker (1958) explained that due to changes in body proportions during the various life stages of fishes, their body fonn and specific gravity can vaiy and hence cube law does not hold true for them. According to Rounsefell and Everhart (1953), generally the value of ‘b’ is 3 in fishes but the cube law need not always hold good. In the present study, the highest ‘b’ value was arrived at in females of Rcarnaticus followed by males. The exponential value of 2.8618 implies that the females gain weight at a faster rate in relation to its length whereas the low exponential value [.4243 observed in indeterminates indicates their low growth rate. The exponential value of 2.7148 of males indicates that the growth rate of males doesn’t show much variation from females. It may be concluded that during the early stages of life, the growth rate was very less in this fish while after attaining a length above 200mm the growth rate suddenly increases and after attaining sexual maturity the females grows isometrically, more or less obeying 182 cube law. While the low ‘b’ value of males indicate negative allometry, which indicates that, the increase in length is not in accordance with a three time increase in weight. Reports on the length-weight relationship of cyprinid fishes showed that many of them strictly follow cube law while there are many in which the weights of fishes either tend to increase or decrease in proportion to the cube of length. Isometric growth pattern has been reported in Cirrhinus mrigala and Labeo r0hita(Jhingran,l952), Labeo calbasu(Pathak,1975), Puntius sarana(Sultan and Shamsi,l981), Puntius d0rsalis(Sivakami, 1982), Catla catla(Choudhury et al.,l982; Kartha and Rao, 1990) and Schizothorax plagi0st0mus(Bhagat and Sunder, l983).All these earlier reports are in compliance with the present findings on the length-weight relationship in females of P. carnaticus in which the ‘b’va1ue was very close to the isometric value of 3. Deviations from cube law has been observed in Indian major carps by many authors (Jhingran, l952;Nataraj an and Ihingran, 1963; Shrivastava and Pandey, 1981; Choudhury et al., 1982; Mohan and Sankaran, I988;Pandey and Sharma, l998;Sarkar et al., l999).The slope value of less than ‘3’ has been reported in Tor t0r(Malhotra,l982), Labeo der0(Ma1hotra and Chauhan,l984), Labeo dy0cheilus(Malhotra,l985), Puntius ticto and Barilius bendelesis(Gairola et al.,l990) and Cyprinus carpio communis and Cteno pharyngodon idella(Dhanze and Dhanze,l997) and Rasbora dam'c0m'us(Sunil, 2000).All these earlier reports corroborate with the present findings on the length-weight relationship in P. carnaticus in which significant departure of ‘b’ value from the isometric value of 3 was noticed in respect of both males and indetenninates. Females of P. carnaticus were found to surpass males in weight in relation to length as evidenced from the disparity in ‘b’ values. Similar trend has been observed in other 183 cyprinids too viz., Puntius k0lus(hatnagar,l963) Labeo fimbritus(Bhatnagar,l972) L.der0(Malhotra and Chauhan,l984) R.danic0m'us(Thakre and Bapat,l984) and L.dussumierz'(Kurup,l99O).But in the present study even though the weight at same length range was higher in females when compared to males there was no significant difference between the ‘b’ values of males and females. On the other hand, the ‘b’ value of both males and females showed significant difference from that of indeterminates. This indicated that in indeterminates of Rcarnaticus, the weight of the fish was not increased in proportionate with their length. The present finding is supported by the low feeding intensity, gut fullness and relative gut length of indetenninates( refer Chapter 7). Le Cren(l95l) reported that females are heavier than the males of the same length probably because of the difference in fatness and gonadal development. While discussing the seasonal effect on length-weight relationship of Clarias batrachus, Mitra and Naser(l987)found that higher metabolic activity with spawning season lowered the ‘b’ value while less metabolic activities, accumulation of fat, weight of gonad, etc. during the pre-spawning period increased the values. The higher regression coefficients in female P. carnaticus may be attributed to the higher fat accumulation and more gonadal weight when compared to their male counterpart. Beverton and Holt (1957) opined that since ‘a’ and ‘b’ of allometric formula might vary within a wide range for very similar data and are very sensitive to even the tmimportant variations in various factors, allometric formula worked better than cubic formula. Any indication in biological events could be recorded by allometric law. The significant departure of regression coefficients from the isometric growth value in male and indeterminates of P. carnaticus indicates that the general parabolic equation W=aLb 184 expresses the length-weight relationship in these groups better than the cubic law while the cube law W=aL3 holds good for the females of this species. Fluctuations in the condition of the fish is related to reproductive cycle (Le Cren, l95l;Sarojini, l957;Pantalu 1963; Qayyum and Qasim, l964a,b,c;Chatterji, l980;Neelakantan and Pai, l985;Gairola er al, l990;Narejo et al., 2002), feeding rhythms (Hile, 1948; Qasim, 1957; Bal and Jones, l960;Blackburn, l960;Bhatt, 1970,1977; Shrivastava and Pandey, 1981; Das gupta, 1991; Pandey and Shanna I997) or physico chemical factors of enviromnent, age, physiological state of fish or some other unknown factors(Brown l957;Kumar et al.,1979:Kurup and Samuel,l987;Kurup,l990;Ka1ita and Jayabalan,1997).In P. carnaticus the higher Kn values recorded in March-April and July — August in females and April-May and July- August in males coincided with the occurrence of high gonadosomatic index (GSI)in both males and females. The Kn values in males showed a decreasing trend during June and from September to December in males. While in females the relative condition factor decreased during May-June and September to December. This may be attributed to the increased spawning strain in them, as opined by Menon(l950).Thus it appears that reproductive cycle in P. carnaticus is related to the variations in the condition factor. Sex-wise analysis of Kn values revealed that the mean Kn values in females (0.96) was higher than that of males (0.91). In indetenninates, the mean value was 0.77. According to Le Cren(l95l), Kn values greater than 1 indicated good general condition of the fish whereas values less than 1 denotes reverse condition. Vinci and Sugunan (1981) and Biswas (1993) reported higher Kn values in females of L.calbasu and Lpangusia respectively. Pandey and Shanna (1997) studied the condition of four exotic carps and 185 only the common carp, Cyprinus carpio communis was found to have values above l(l.0lO9). High Kn values were recorded in Labeo r0hita(l.0l29) and Carla catla(l.0O07)and low values in Cirrhinus mrigala(O.9967) by Pandey and Sharma(l998). In the present study even though the Kn values of all the groups were below ‘ 1’ females showed the highest value (0.96) when compared to males (0.91) and indeterminates(0.77). This indicates that females are in better condition when compared to males and indeterminates. Influence of feeding intensity, as indicated by the gastro-somatic index, on condition factor was apparent during certain months of the year in both the sexes. In females even though the gonad was in far advanced condition dining May, low Kn value and comparatively low gastrosomatic index were observed. Similarly in both males and females during June Kn value was less when the GSI was comparatively higher and gastrosomatic index was less. In September the relative condition factor was comparatively good when the GSI was less and gastrosomatic index was high. From these observations it can be concluded that in P. carnaticus, though the condition of the fish is more related to gonadosomatic index, there exists some relationship between relative condition factor and gastrosomatic index and other environmental and physiological factors. 186 Table 10.1 .StatisticaI details showing number of fish studied(n),intercept(log a),regression coefficient(b), standard6 6 error 6'6 of b(sbl loga and results 6666 of6bailey's t-testisb on 6'b' ti and t-test66 on Peicorrelation rf coefficient 6P" r 6 Males 6 6 262 66-4.1567 2.7146 0.616236 66 2.3 P<0.05 0.67605 22.65 P<0.061 Females 8* 150 i -4-5069 2.6616 0.163 0.6 " 8 0.6649 20.1 P<0.01 6 lndetenninates 470 -60.9611 1.443 0.0566 627.7 P6<0.01* 0.9311 24.35 |§><0.061 66_ Table 10.2.Analysis of varience on the regression of the length weight relationship in5 males ssh of Puntius 5 camaticusM86 6; 6P6-value6Fcrlt_ R6g6Le_ssi0nr_6Residual 6 0.73123_66 6.475527 M1 0.7631236 360 0.025663 28.47112 2E-07 6 3.8698 6 1091 5 9.2661656 951 5 is 6 5 Table 10.3.Analysis of varience on the regression of the length weight relationship in females of Puntius camaticus E 6 'ss6 it _ Ms 66 " 5 it P-value Fm‘: Regression 6 2.046917 1 2.046917 94.61046 66E-19 _6 330 Residual 6 6 4.664009 226 0.021611 6 Total i6_ 6 6.932926 6_ 227 86 '6 Table 10.4.Analysis of varience on tl1e regression of the length weight relationship in indeterminate; of Puntius camaticgs _ 6 6 ss 1 df MS 116 F__ [P-value LE crit _1' Regression 6 29.62695 _1_. 29.62695 203.7711 6412-30 3.90166 1636616061 Y1_622.66062“ 616 15 610.145369!@ _ 8* 6 Y1 116191kTotal ‘ 61'52.3o756fl 10.054141 155% 6 1631 J! 6 7, L1 1 ‘,11 __ _|i_. 1 1 1 I 1 Edy“ mow‘ as $fiEEh20_E_Xm'_m__wEm“_ B_OVn_ N8 Q6 mo_mEm"_xwm_m_)_ NWN NdWQ_NEO“_XWO_@_)_ $0: u____g gO_aE______O g____=& __° 8_g_§2%___ U: O_G_____2__Q_fi______O $565000 __O_$9_m9_ ___°O___2_E°O 3; Ea *0 “___gN__o_2 O___£ I Ir k \\\| ‘‘A6 ON kq _ W1 % E 22 '~wm‘nNHwgm©W_lO1 ; |“_ co__m>m_3o C026 E8 _o>®_nx_:mHC§_cm_w"_ __ 33 Aogwviwoommwflo um m8o_mho c8__mQE0ofi $86R8 FN\_2_3i $83 “ “NM6_m_a% mom %_w§1 2 ©©ON O :23 W_ 2$_>___2| ‘U i I‘ \ I‘GO @@ ®gO H: Y H ubwmoo $80pogkwag”:0“;_| li1W0§ gm myjmW vNNQ:Q_&V__‘8;” O2 $@‘_E_®$Uc_% 2&6go? W®N©®NMg|E©mNNl_O mg mm_mEm“_W WmawM32“?QQKNO©N©d SF mm_m_>_W N; 3| %U|A» flWH%?%Q”_ N9 A S fi M L V 3 5 AHA H?¢1% _w W _imp ‘Y ZO_®wmMOmE _)_O”_“_ WZO_P<_>mO ‘ _‘ ‘IAVIIM _|‘H'_f ‘>_P: Nil“ “"‘Hh‘|"‘J|>H:l‘|| Q 3.5 -* ._ se 3 2.5 .... ,...... ~ ~"'t.'?-·'·'. f 2 ~ 1.5 1 0.5 0 2.4 2.45 2.5 2.55 2.6 2.65 2.7 log TL(mm) FIg.10.2.length - weight relationship in males of Puntius camatJcu. 3.5 3 •• ... 2.5 \t ••• ,,, ..Jt' ...... -.-.4''-·-.11' • , "ii 2 • ~ • ~ 1.5 1 0.5 0 2.35 2.4 2.45 2.5 2.55 2.6 2.65 log TL(mm) Fig.i0.3.Length - weight relaUonship In IndetennlNlt.. of PuntJus c.m etlcus 3 2.5 2 "ii i" 1.5 f 1 • 0.5 0 0 0.5 1 1.5 2 2.5 log TL(mm) Fig.10.4.Selaor1ll vlrIItion in relative condition factor (Kn) of mII'" of Puntiua um.tkua 1.4 1.2 1 c: 0.8 0.6 " 0.4 0.2 0 ~ ;f~I I'l 2001 ___ 2002 I: 1 Ftg.10.S.SeaaonII variation In rellttve condition factor (Kn) of lema ... of Puntius carnaticus 1.4 1.2 1 c: 0.8 " 0.6 0.4 0.2 0 11 I'l Fig.10.6.Lengthwise variation In relative condition factor{Kn) ~ ______~ o~f ~lnd~~~nn~l~n~.u.~~o~fP~u~n~~~u~s~c~.m~~~c~u~s~ ______ 1.2 A. 1 .A- ~ 0.8 c .. 0.6 " 0.4 0.2 0 R ~ ~ ~ ~ ~ ~ # ~ I I .§I ~ ~ ~ ~ ~ ~ ~ 'V~'" Longth group(mml Flg.10.7.Lengthwlae v.ri.tIon In relative condition factor{Kn) of Punt/us canuJtlcus 1.4 1.2 1 c 0.8 " 0.6 0.4 0.2 Chapter 11 Age and Growth 11.1. Introduction Age and growth of fishes are very closely interrelated. As age increases, there will be a change in size. Studies on age and growth are important in fisheries research. Besides being of biological interest, the determination of age has significant practical utility. It helps in the study of dynamics of fish populations. Most of the methods employed for assessing the state of exploited fish stocks rely on the availability of age composition data (Ricker, 1975a). Information on growth rate, natural and fishing mortality, age at maturity and spawning, age composition of the exploited population, etc. can be evolved from age data of fish populations. Such information provide essential tools for scientific interpretation of the fluctuations in fish populations over space and time and also in formulating scientific and economic management policies for the fisheries in question (Seshappa, 1999). The growth process is species specific, however , it can differ in the same fish inhabiting different geographical locations and is easily influenced by several biotic and abiotic factors. Growth is an adaptive property, ensured by the unity of the species and its environment (Nikolsky, 1963). A comparison of rate of growth from different localities may help in identifying suitable environmental conditions for the sustenance of a stock. The purpose of growth studies in any fish species is to determine the amount of fish that can be produced with respect to time (Qasim, 1973b). The age and growth rate of fishes are determined by both direct and indirect methods. The direct methods include rearing fishes in captivity under controlled conditions and observing their growth and also by using mark recapture method (tagging programmes). 187 Dissection of annual rings laid down on scales, otoliths and other hard parts of the body and length frequency analysis are the indirect methods mostly relied upon. As the direct methods have limited scope due to practical difficulties, biologists prefer the indirect methods for age and growth studies. The annular rings on scales and other hard parts of the body are effectively used in temperate regions where, during winter seasons, slow growth leaves clear rings of closely placed circuli. On the other hand, in tropics, the age determination based on direct counting of check marks is difficult because the growth rings do not necessarily represent year marks. The length frequency analysis method of Petersen (1895, 1903) is well known, in which, peaks of length distribution are assumed to represent the different age groups. The method is very good for younger fish (2-4 years life). However, in older fishes, there are possibilities of over lapping of length frequencies in individuals of different age groups, as the growth rates slow down. Furthermore, age determination by length frequency analysis does not hold good to fishes with prolonged breeding season also. Length frequency method is widely used by fishery biologists in fishes inhabiting tropical waters. A computer based method for the analysis of length frequency data, ELEFAN (Electronic Length Frequency Analysis) (Gayanilo er al., 1988), has been effectively used to separate the composite length frequency into peaks and troughs and the best growth curve passing through maximum number of peaks is selected using a goodness of fit ratio of ESP(Explained sum of peaks)/ASP(Accumulated sum of peaks)(Rn)(Pauly and David, 198 l ;Gayalin0 er al.,l988). The peaks are believed to represent individual cohorts. The module is incorporated into the FISAT (FAO-ICLARM Fish stock assessment tools) Software (Gayanilo and Pauly, 1997). 188 The age and growth of freshwater fishes of India were studied by several scientists (Jhingran,l959;Qasim and Bhatt,l964; Bhatt,l969; Kamal,l969; Khan and Siddiqui,l973; Murty,1973; Chattelji et al.,l979; Pathani,198l; Reddy, l98l;Mathew and Zacharia,l982;Tandom and Johal,l983; Shree Prakash and Gupta,l986; Desai and Shrivastava,l990; Devi er al.,l990; Johal and Tand0n,l992). Qasim(1973b) made a critical evaluation on the various methods used for age and growth studies in India and described the difficulties encountered in determining the age in tropical fishes. Some of the recent works on age and growth include those of Kurup(l997) in Labeo dussumieri, Singh et al. (1998) in L. rohita, Karnal et al.(2002)in Lcalbasu, Nautiyal(2002) in Tor Putitora and Narayani and Tamot(2002) in Tor tor. No attempt was made to study the age and growth of Puntius carnaticus, and hence a pioneer study is attempted in this direction. 11.2. Materials and methods 882 specimens of P.carnaticus comprising of 262 males and 150 females and 470 indeterminates collected from Peringalkuthu region of Chalakudy river system were used for the present study. All specimens were measured to the nearest mm in total length (TL). Length frequency data were grouped into 20mm class interval. Growth was estimated separately for males and females while the pooled population comprised of males,females and indeterminates. The von Bertalanffy growth fonnula (VBGF) (Bertalanffy, 1938) was used to describe the growth. The equation in growth in length is given by: L, =La[l -exp"“‘*‘°>] Where L, = length at age t. 189 La = asymptotic length or the maximum attainable length if the organism is allowed to grow. K = growth coefficient to = age at which length equals 0, i.e. the theoretical age at zero length The growth parameters for both the sexes were estimated separately using the ELEFAN l programme of FISAT software (Gayanilo and Pauly, 1997). Powell- Wetherall Method is used to estimate asymptotic length and the ratio of the coefficients of growth (Z/K) using length-frequency data based on Beverton and Holt (1956) Z= K [ (Lot - L)/ L, - L’)] It estimates the total instantaneous mortality coefficient (Z) in a steady state population with constant exponential mortality and von- Bertalanffy growth, from mean length (L) of a random sample of fish above cut off length (L’). The mean length of the selected fish (L) is a linear function of the knife edge selection length L’ given by L= Lot {l/ {1+(Z+K)]} + L’{l/{1+(Z+K)]} For a series of arbitrary cut off lengths, we can construct a corresponding series of partially overlapping sub samples. If the mean lengths for sub samples are plotted against the cut off lengths, it results in a positive linear relationship as given by the above equation. If the intercept of the straight line is considered as a and slope as b, a= Lot [l+ (Z+K)]} b = (_Z/K)/ [l+ (Z+K)] From this, La and Z/ K can be computed as 190 Lot = a/(1-b) Z/K: b/ (1-b) In FiSAT, the modified form of Wetherall method as proposed by Pauly (1986) is incorporated. Lt’= a + bLt Where La = a +b Lt and Z/K= (l+b)/ -b Estimation of to Age length key at 3 months interval was prepared from ELEFAN 1. Estimate of to was done using von Bertalanffy (1934) plot in which the results of the regression of - ln (1 Lt/La) against t was used to calculate t0_ to = -a/b Since ELEFAN curves showed the existence of only one brood in P. carnaticus, estimation of growth parameters was restricted on one cohort only. Growth performance of this single cohort in both male and female was compared by Munro’s PHI prime index, ¢> (Munro and Pauly, 1983) which was computed from the equation: ¢ = log 10 K +2 log 10 La where K and Lu are Von Bertalanffy’s growth parameters. According to Pauly (1982 b), the structure of a set of length frequency data is dependant on the recruitment pattem into a population and hence it is possible to derive some information on the seasonality of recruitment from the length frequency data. FISAT applies this inverse approach, thereby identifying the number of recruitment pulses per year and evaluating the relative importance of these pulses when compared to each other. 191 The recruitment pattems of both male and female P. carnaticus were obtained from FISAT programme. 11.3. Results 11.3.1. Distribution of length The lengths of males of P.carnaricus ranged from 232 to 467mm in total length. The modal length of males during 2001-02 was estimated to be 294mm, which belonged to the class 280-300mm TL whereas the same during 2002-03 was estimated as 303.07mm in the class 300-320mm TL. The length of female population ranged from 270 to 472mm in total length. During 2001 02 the modal length was 344.62mm belonging to the size class 340-360mm TL. While during 2002-03 the modal length showed a slight increase with 372mm which comes in the size group 360-380mm TL. The length of the smallest fish recorded was 52mm TL and belonged to immature class. In the case of immature fishes the highest length class observed was 100-120mm TL during 2001-02 while it was l20—l40mm during 2002-O3. 11.3.2. Estimation of growth parameters 11.3.2.1. Males: In males, La computed following Powell-Wetherall plot was 479.033 mm and Z/K =0.904(Fig.l 1.1). The data used for estimation of Lot and Z/K for male P.carnatz'cus is shown in Table 11.1. ELEFAN 1 growth curve (Fig.1 1.2) showed that the male population of P. carnaticus was composed of a single cohort aimually, generated by only one recruitment during August-September. The growth parameters estimated by ELEFAN l along with the growth performance index, ¢ are given in Table ll.4.The Lot 192 estimated from ELEFAN 1 with highest Rn value (0.181) was 493.5 aha 1< =0.5 yr‘ (Fig.ll.4) The growth performance value obtained by ELEFAN 1 was 5.08 . Based on the values so obtained through ELEFAN I, the von Bertalanffy growth equation (VBGF) of males of P. camaticus(Fig. 1 1.4) can be express as: Males: Lt = 493.5(1-exp'0'5(t+m8) On applying the average growth co-efficients estimated by ELEFAN l, the males will be attaining an average length of 286.9, 368.2, 417.6, 447.6 and 477mm at the end of I, II, III, IV“ and Vm years respectively (Table 11.5). 11.3.2.2. Females: In females Lot derived using Powell-Wetherall method was 504.6l2mm and Z/K was 3.l73(Fig.l 1.3). The data used for the estimation of Lot and Z/K for female P. carnaticus is shown in Table ll.2.ELEFAN 1 growth curves (Fig.ll.4) showed that the female population of P.carnaticus was composed of a single cohort annually generated during August-September. The growth parameters estimated by ELEFAN l along with the growth performance index, <1) are given in Table 11.4. The Lot computed from ELEFAN I with highest Rh value (0.162) was 504 and K =0.65 yr" (Fig.1 1.5). The growth performance value obtained by ELEFAN 1 was 5.2. Based on the values obtained from ELEFAN I, the von Bertalanffy growth equation (VBGF) of females of P. carnaticus(Fig.l 1.5 ) can be express as: Females: Lt = 504(1-exp'”-‘5“*-’*°” 193 When compared to males, females attained a higher length during different years with 345.l8mm, 42l.l2mm, 460.85mm and 48l.7mm respectively at the end of I, I1, I11 and IVyears (Table 11.5). 11.3.2.3. Estimation of growth parameters of pooled category In the pooled category which includes male, female and indeterminates the Lot derived using Powell-Wetherall method was 500.83 and Z/K=2.073(Fig.ll.5). The data for estimation of Lot and Z/K for male Rcarnaticus is shown in Table 11.3. ELEFAN I growth curves (Fig.1 1.6) showed that the whole population of P. carnaticus comprised of a single cohort originated during April-May. The growth parameters estimated by ELEFAN 1 along with the growth performance index, rb are given in Table 11.4. The Lo. obtained from EIEFAN I with highest Rn value (0.131) was 500.83 and K =0.97 yr'l (Fig.1l.6).The growth performance values computed using ELEFAN 1 was 5.5. Based on the values arrived at through ELEFAN 1, the von Bertalanffy growth equation (VBGF) of females of P. carnaticus (Fig.11.6) can be express as: Pooled (male + female + indeterminates) : Lt = 500.83(l-exp'°'97“+3°65) l 1.3.3. Analysis of recruitment pattern The recruitment pattem obtained for males, females and pooled category through F ISAT is given in Figs. 11.7, 11.8 and 11.9 respectively. The occurrence of a long recruitment pulse every year is quite discernible from the recruitment pattem of both male and females. In male P. carnaticus, the recruitment period extended from May to October. The major recruit was identified from May to July with a peak of 15.28% in June. The 194 minor mode was appeared in October-November with a peak of 11.95% in October. In the case of females, the recruitment season extended from April to October with two peaks. The major peak extended from August to October with a peak in August (17.97%). Thereafter, it gradually declined and continued till February. The minor peak extended from April to June with a marginal peak in April (16.48%). 11.4. Discussion In the present study, Lot computed by ELEFAN I and Powell-Weaterall method were almost comparable in both the sexes and also in the pooled category. Among the three groups females showed the highest Lo of 504.612,followed by pooled category(500.83) and males(479.033).While the ‘K’ value and growth performance index ((1)) were 0.5 and 5.08 in males,0.65 and 5.2 in females and 0.97 and 5.5 in pooled category. The higher values of growth co-efficients in females indicated that females attained asymptotic length at a faster rate than the males. While the much higher <1» and K values in the pooled category indicated that the growth rate was very high before attaining the sexual maturity. In the present study, the largest size of male P.camaticus was recorded as 467mm and that of female as 472mm.The length of males at the end of first, second, third, fourth and fifth years of life were estimated to be 286.9, 368.2, 417.6, 447.6 and 465.9mm respectively. Females attained a length of 345.18 at the end of I year, 421.1 at the end of II year, 460.85 at the end of third year and 481.65 at the end of IV year. Based on the results of the present study, it can reasonably be inferred that the longevity of P.carnat_icus is around four to five years. Since majority of the males fall in the length class 280-300mm and females in 340-360mm, it can be postulated that the exploited 195 stock of males and females invariably belonged to one year age group. Accordingly representation of male and female individuals belonging to age group three and above was sparse and sporadic in the exploited stock. Puntius carnaticus has been listed under vulnerable category of fishes based on its biodiversity status following IUCN (Walker and Molur, I997). The basic principle of fishery resource conservation and sustenance of the fish stock is by allowing a fish to breed at least once its life time for ensuring the natural recruitment and regeneration. In P. carnaticus, the length at first maturity has been estimated to be 232mm in males and 270mm in females (refer: Chapter 9). It would thus appear that both male and female are getting a chance to complete the maturation and spawning before completing one year of their life cycle. Johal and Tandon(l987 a) found that the Indian Major Carps attains sexual maturity only above 30cm TL during the second or third year of their life span.Singh et al.(l998) reported that L.r0hita attained sexual maturity at a length of 46cmTL after the third year of their life span. Based on the results of the present study, it can be well recormnended that both males and females of P.carnaticus can be exploited before attaining one year in their life and the growth rate of both the sexes of P. carnaticus was perceptably higher than any of the Indian Major Carps of the country. The Length-weight relationship studies (Chapter ll) also revealed that the ‘b’ values of males (2.7148) and females were (2.86l8) comparatively higher in Rcarnaticus when compared to other cyprinids like Tor t0r(Malhotra,l982),Labe0 der0(Malhotra and Chauhan,1984) and Labeo dycheilus(Malhotra, 1985). 196 P. carnaticus was found to exhibit fastest increment in length during the first year of its life history and it was relatively higher in females when compared to its male counterpart. A drastic reduction in the growth rate was observed in the second, third and fourth years of age in both the sexes, while males performed better than females during this period. Similar pattern of faster growth rate during the first year and subsequent decline in the succeeding years have been reported in many cyprinids such as Cirrhinus mrigala(Kama],l969; Desai and Shrivastava,l990), Labeo caIbasu(Gupta and Jhingran,l973;Kamal er al.,2002), L. dussumieri(Kurup,l997), L.r0hita(Singh,et al.,l998) and Torputit0ra(Nautiyal,2002). The growth co-efficient (K) of C.catla(0.l044),L.r0hita(0.255l) and C.mrigala(0.275) reported by Mathew and Zacharia(l982) are relatively less than that of P.carnatz'cus. While Haroon, er al.(2002) recorded higher values of 0.8 in L.r0hita, 0.73 in C. catla,0.7 in Cmrigala and 0.76 in Lcalbasu collected from bheels. The growth co-efficient of Ldussumieri was estimated as 0.64 for males and 0.81 in females by Kurup(1997) is in compliance with the present finding that females showing a better growth rate than their male counterpart. Pauly(l984 a) reported that species having shorter life span have higher ‘K’ value and therefore can reach their La within one or two years. Conversely, those having flat growth rates are characterized by a lower ‘K’ values and takes more years to reach their La .In P.carnaticus, the moderate ‘K’ value in both the sexes support a moderate life span of the 4-5 years, which shows a strong corroboration with the established relations between is in general agreement with the relationship between ‘K’ values and Lot as reported (Pauly, 1984 a). l97 Recruitment to the fishery was discernible during May to November in males with the major pulse in May-July and the minor in October-November. In females, the recruitment period extended from April to October with the major pulse from August to October and the minor in April May. This finding is very much in agreement with the results of maturation and spawning studies ( see Chapter IX), which could identify an extended spawning season in P.carnaticus viz., April to August. The growth curves obtained using ELEFAN I also strongly corroborate the possible existence of a single brood in a year. The present study revealed that P. carnaticus is a fast growing fish which attains marketable size by the end of the first year of its life. The growth co-efficient of P. carnaticus (male= 0.5; female = 0.650) was comparable with other freshwater fish species used for aquaculture. Moreover, the extended recruitment period (Male: May October ; Female: April — October) revealed the long term availability of brooders and fingerlings in the wild. So the present findings are supportive of utilizing P. carnaticus as a prime an effective aquaculture species. P.carnaticus,is having the status of vulnerable species. Non-availability of sufficient numbers of specimens belonging to all groups at regular intervals had been identified as one of the major limiting factor in pursuing the studies on length frequency using more refined methods. Since there is total lack of knowledge on the age and growth of P. carnaticus, the results of this pioneer work on these parameters would definitely advance our knowledge on the biology of this species and immensely help in fonnulating relevant conservation and management programmes for the protection and preservation of this species. 198 Table 11.1.Data for estimation of La and ZIK for male Puntius camaticus using the method of Wetherall (1986 as modified by D. Pauly,1986 Limei")-L_ both in Fishlgyte- 0. Vol.4(1):12-14 \:N(¢0_mulalive) and 18-20 I I 320 7061 000 7 9 1 1616251 _ 1 300.706. 1_ 20,0000. 13162510 260.706 40.000! 131625 260.706 j 60.000}f 1316251 240.706] 80.000 0“ 1316251‘ j _1 220.706 _ 100.0001 131 625 200.706 _ 120.000» 1316251 180.7061 140.000 131625 160.706 100.0009 _ 131625 140.706” 780.0001 0' aw 1316251 ii" 120.706 200.0001 13162s L 100.706 9.220.000 __ j 1316251 63.3921 240.000 _. 127653 66.711 _260.000 119197. 1 56.472 0 0 260.000 _105279i19___? 7 45.495: . 300.0001 88162 7 69.3541 K 320.-000 __0634051_f _% 33421 1 640.000 43162 9 331237 3601000 230811 36.492. 6" 360.000; 11536‘ fiifi 41.0361 400-0001 5988 32.265‘ 420.000 4397| 19.651 440.000 6.3302 11 ._._.10.000 1 0 1160.000. 1593 *** regressionfline is fitted fgom this p0i11t_*999t >>|i; Y= 251.55 jl-0.s25)*x Ly}!-.997 _ 1 Estimate of Lo: = 47 9 . 033mm A Estimate 6rz1K=0.904| 9 ii 4-—-1 Table 11.2.Data for estimation of L01 and ZIK for female Puntius camaticus using the method of Wetherall (1986 as modifled by D. Pauly,1986 __ 9 both in Fishbyte Vo|.4(1L1N2-14 and 18-20 Hmjean)-L M 7 L’ 0‘ N@q_nj|%ulative) 344.598 9 0.000 131 626 324.598 20.000 131 626 1 304.596 40.000 "T...\ 131626 284.598!‘ 60,-.000. 1316261 2641596] __ 80.000 E . 1316261 244.598 ;_ W7 100.0001? 131626‘ 1 224.596 0' ‘ 120.000 131626 204.596 140.000 131626; 104.-5931’ 160.000_ 1 31.62.03 164.596 160000| F 131626 144.-599 200.000 13162.6; 124.596 2201000 1316261 0 1 1 1 104.5981 240.000. 131626 1 K 260.0001 131626 64.596 1' _ 68.925 _f 280.000 124409 54.095 .300-000. 114675. iii 46.020 ;_1 0 7320.-.0001 W 90028; 37.422 340,000 663621. 33.179 360.000‘ 43427. 28.430 330.-.000| 1 251 9.5; 1 26.153 11 9 400.000 12653; 22.943 420.000 0* 69.72% 1 24.259 2440.000 I _2634 10.000 0' 460.009 0 1878 1 '*"?'regressi_qn+??line is fittedrfrom this piqint [email protected])*x, r =?_-.960 _ t_ _. Estimate of L01 = 504 . 612mm Estimatettofz/K =39.1;73| 7 _ Table 11.3.Data for estimation of L0: and ZIK for pooled category of Puntius camaticus using the method of Wetherall (1986 as modified by D. Pauly,1986 both in Fishbyte Vol._4(1):1 2-14 and 18”-2Q_M Hmean) -L - 1"- N(¢u"w'a11v¢) 222.431!__ Q 161627 ' 7 7.___ 202.43—1 _,_ 3° 1.31627 i ' 162.431 40 131627 -. 175-224. 60 1 22535 170-557 112129 §! 8.9 L 1 163.216. 100 103933 1 j 161.7371 1 -1 120 92726 i 163.577 7140» & 61059 U 155.642 W160 75155 1 33133.11 160 73113 it 1247211 200 7066711 106.661 _ 220 69059 240 66059 A _ 7 91.2597_—1-:_ -"7Y1 1 75.996 Z50 62420 55969 7 763.603 230 U % % 52.331 300 46132 L Q 447-741 Q1‘ 320 31221 1 1 E _ P_37.1961 340 27399 j j 34.646 360 1 6655 330 9704 1 71 V i =0 32.336 *i'k 7 32.4327 400 E 5119 “26.479 420 9 3148 _ H 22.768‘ 44° . 1583_ 10' 2.460. 21.0.1 1 7 1 “* 33923353133 line fitted from this point ‘ Y= 162.98 +(-O.325)*X, r = -.972 Estimate of Lo = 500.827mm Estmate of Z/K = 2.073 TableSex 11.41‘.-irowth Cohort parameters L== estimated b ELEFAN(mm) jl for maleK and to female Rn Puntius <0 %carnat1'egs Males _ Augost-September 493.51 %0.5 -0.7448 1311* 5.08_ Females _ Aqfisto-September% _% 504.612 0.65 _ -0.7802 _162 75.22 Table 115.Length arrived at various ages in males and females estimated b Elefan I method éggYears) {j Male 1 Female ; 266.91 346.1? 7 W 7 I1 368.2 421.12 417.6 460.851 1v 9 447.62 9 1 461.65 iv 465.67 476.95 Y1. 1 1 %§U__\Q=_~QU §_:5£ MO _s=_“__a2_ 2&5 HO VS Ea H: wHE_“Em_8 he __E2__8>> | __9$OA___._ 3: _> _; uzcihczam zoiwwmmwmm _ vam Q H x\N “O UFMEMFWM M EE fim®_mfiv u OOH Ufiflfimgmm fimm_‘Hh x*H mNm_®‘ + mm_HmN“ w_ __MWN_M%*MM_w__WM_MF__|kHl' I Him‘ “Hy A ‘H;lH|l‘ 1|lH‘lVH‘|“‘| fi££“_4V ;pm=w_ muousu W; mg OWN mw m ‘ ‘l II __I I; III |___|‘_\|HH_|!!‘_||d|__ J W 1 L m‘i O 0 HI‘ C U L0"U (U __Q jG _0 N _wWU" __ WQ_ W1_0 _Z MW‘ _MI mmC "W"H" H_r_ _*"U MW ( Mhttv zpmcmfiimz mfiq aw“ GH fi=\LHEAH‘W€hFI#+*m1T?¢¢£f¢&%Jm ID "0F 3PM J"U WaW"U : 1UQ IJ __O)HQ xTI QFY VW 2% ("H“L MM lkwm fimm _WH64“ Aqammxhmz Agmzom ML t E “G gmA____£_ ‘U __:_w_:~ :o_§U W 3"‘ gm QI H|“lHm‘ _ llA“iI‘|‘l‘ lI“'|I“‘I' iiilz WM _lh' "““‘_H|“‘ I ‘\ ‘ Y V fiazstcb §_:§Q_ “Q __$_“____§ gwse HO EN Ea "5 w__=_EE8 he BE ___“__2__§> | __m;gH_ N__ __w_H_ x\N MO Uyfifiwywm DOA 3_H____"_£ T ‘uh x*H ®¢N_®- H + Nm_®NH“ “N _:Q_Hc=Gm =O_wwmm@mm ‘_ l‘Il \ ‘\\|\T} ' I‘ It‘ “ Atty zfimcwfifimx GP” Sq“‘N SM Hniggg Q Rhi‘ I“ N IN‘ M ‘_il_é_v\ H\ é&||é ‘H E‘ Nilu _____r____ HO“; __Efl____”mEH_m§ AAHIQAW TI\U 1“H“fig _"Nu AI _CCI _F“ __nu“ _O0QFI "UH,“‘I % la ‘MM t 1‘ ?“|\““‘|H ‘|‘HW“|l‘:| ““| é l‘*1I §_Q_:s:8 _§_:S£ HO __O=_W__a2_ E_O2_ “O V_\_N E; ad w___§___m_8 he Ba __E2_z>) I __m_;$_.m___.wE x\N MD Upfifimpwm DOA MU DfifiEmFWm Nhm_l"h _ x*H mNm_Qi H + Wm_NmHH F “=Q_H¢=Gm zm_mmH=wm: I“_ WmN®_N; Ea Nmmfioem i _Q A££“_AV :*m:w_ “kouzu W wamv mm“ G A. 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Q.-__ _I.._-i_--I--,.¢__,_,,_-__ 1, .- -5- — ¢u-w-~¢- _._. -._.- -4-—U"'-QII -¢-\.¢-.-Z_-- ._ up» --- --In [email protected].\IIw _.-_ -__{, Q -_ .~_,, _._.‘ 1.‘...-_____ .- _.-I---I_v-.—--¢-¢- -1- --111 A P _ _ _:":. -.1 2 ': ‘Z Q-Iaiq-I-10¢ -_-a a_-In -. -w -ha_n -_¢ Q-— I-1; -—-I *1. luvw I‘-—$ -‘Q a~—-.. .\|-_— -II‘; Ilzl anq-v titan I‘-I-QI -|na- nI_I-_ -i-ltrv Ih "—— -1:‘ -1 »\_..Q .-in _- -1- w—.n- -nu-1 -In.-1.li um-ppm ._-__ -M-I $1..-_ -—v- -1.-_ -aj -Gui -5-pant-— _ ._.I..._-_._ . _ , ,,,____..._...-I--.I------.--I--. Fig.l1.9.Recruitment pattern of pooled population of Puntius carnaticus Chapter 12 Population Dynamics 12.1. Introduction The fish population is highly dynamic due to various types of forces acting on it such as fishing and other fishery independent factors (Banerji, 1967). Successful management of this living resource is required for maintaining the balance of the stock between additive and destructive forces acting on the population. Fish exploitation has been increasing at a rapid rate to meet the growing demands of the rapidly multiplying human population which in tum has lead to a drastic decline in the abundance of many fish stocks. This situation calls for the development of suitable management strategies for the conservation of fishery resources for their rational use. Studies on population dynamics are essential to formulate fishing strategy to obtain the maximum sustainable yield without disturbing the equilibrium of fish stock. These studies help in evaluating both natural and human forces acting upon a population and fitting them into yield models so as to moderate the dynamic forces through management practices and thereby sustain benefits from the fish population on a long term basis (Bal and Rao, 1984). Some of the important contributions on fish stock assessment in the tropics were those of Pauly(1980a, b; l982a,b;1983 a,b; l984a,b; 1987), Baneiji and Chakraborthy(l973), Pauly and David( 1981), Devraj(l983b), Sparre and Venema(l992) and Gayanilo and Pauly(1997). Miah et al. (1997) estimated the growth and mortality parameters of Hilsa from Bangladesh. Some of the recent works on the population dynamics of carps include those of Haroon et al. (1999, 2002) on major carps, Alain et al. (2000) on Labeo calbasu, Haroon et al. (2001) on L. rohitha, L. calbasu and L. gonius and Nurulamin et al.(200l) on ,»/:“/99/ L.r0hitha.WA ,9/,('7;-*., '1 . .7‘.“i 159;? Several studies on population dynamics of fishes from Indian waters are available, however, most of them pertain to marine fishes. Bane|ji(l967)highlighted the importance of fish population studies and reviewed the various methods available for such studies. The work of Sekharan(l974)on Oil Sardine and Mackerel, Krishnamoo1thi(l976) on Nemzpterus japonicus, Yohannan(l983) on Mackeral, Annigeri(l989)on Sardinella gibbosa, Karthikeyan et al.(l989) on Leiognathus spp.,Khan(l989)on Harpodon nehereus, Khan and Nandakumaran(l993) on Cynoglossus sp.,Reuben et al.(l994) on Upeneus spp., Philip and Mathew(l996) on Priacanthus hamur, and Jaiswar er al.(200l) on Decapterus russelli are worth reporting. Goswami and Devaraj(l993)estimated the potential yield of L. rohita from a flood plain lake in Assam. Optimum yield assessment of L. rohitha and Wallago artu was carried out by Goswami and Devaraj(l994).The total mortality estimates of W. attu was done by the above authors(l996) from Bhramaputra basin of Assam region. Kurup (1998) studied the growth parameters, mortality, biomass recruitment pattern and exploitation rate of an indigenous endangered carp, Labeo dussumieri of river Pamba of Kerala (S. India). P. carnaricus is an endemic vulnerable species of Kerala which requires protection and judicious exploitation of stock. Virtually, no information is available on any aspect of population dynamics of this endemic species. Therefore, present study is aimed at providing information on the mortality parameters and exploitation rate of P. carnaricus inhabiting Chalakudy river. 12.2. Materials and methods 882 specimens, comprising 262 males, 150 females and 470 indeterminates collected from Chalakudy river during April 2001 to March 2003 were used for the stock 200 assessment study. Assuming that the growth of this species follows von Bertalanffy growth formula (VBGF), growth parameters were estimated using FISAT (PAO ICLARM Stock Assessment Tools) computer software package (Gayanilo and Pauly, 1997) as mentioned in Chapter ll and results were used for the computation of various parameters given below: 12.2.1. Total mortality coefficient (Z) Total mortality coefficient or instantaneous rate of total mortality expressed by Z, includes both natural mortality coefficient (M) and fishing mortality coefficient (F). Total mortality estimate was done by the methods of Beverton and Holt (1956), the cumulative catch curve method of Jones and Van Zalinge (1981), Ssentongo and Larkin method (1973), Pauly’s pile up method (1983) and length converted catch curve method of Gayanilo et al. (1996). 12.2.1.1. Beverton and Holt method Z was calculated from the mean length L, La and K derived from the von Bertalanffy growth parameters. Z=K La-II... ‘ in where L = Mean length of fish II = Lower limit of the size group from which length upwards all lengths are under full exploitation. 12.2.1.2. Ssentongo and Larkin method (1973) 201 “Klil [£1] Y= -ln(l — 1/la) Yc= -ln (l-lc/la) v = 2 fy/ zf where n =Ef,n+l =Zf+l Yc = Corresponding to lc value n = Number of fish caught from Yc onwards. 1 = Mid length 12.2.1.3. Pauly’s pile up method log . (Nt/t) = a - b ¢* Z = -(-b), t* = t1+ 1/1 t t = Time taken to grow from lower limit of the length class to upper limit. i: 1/K108 e(La — L1) / (La * L2) t1= 1/K loge (1-l/La) l = Lower limit of length class. t1 = Relative age corresponding to lower limit of length class. t* = Relative age corresponding to the mid length of length-class. Nt = Number of individual caught at time ‘t’. 12.2.1.4. Jones and van Zalinge method (1981) Jones and van Zalinge found a linear relationship between catch and survivors. Following formula is applied: 202 III (Ci, (1) = 21 -I-{Q X III (Lq— L1) where Ci, Q = Cumulative catch corresponding to a given length. i = Lower limit of that length class. ot = Indicates that the catch refers to a range from L1 to all larger size. 12.2.1.5. Length converted catch curve method (Gayanilo et al., 1996) The length converted catch curve was computed using the following formula: ln(Ni/ti)=a+bti where Ni = Number of specimens in length class i ti = Relative age corresponding to length class i 12.2.2. Natural mortality coefficient The methods of Sekharan (1974), Rikhter and Efanov (1976) and Pauly’s empirical formula (Pauly, 1980 b) were used for calculating natural mortality coefficient. 12.2.2.1. Sekharan’s method This method is based on the assumption that 99% of fish would die if there was no exploitation when they reach tmax, which corresponds to Lmax. Lmax is the maximum observed length in the catch. M = - (log, 0.01/tmax) where tmax = Age at Lmax calculated from VBGF equation. 203 12.2.2.2. Rikhter and Efanov method (1976) This method used the following formula: tun M = (1.521 / '" )- 0.155 where tm = Age at which 50% of the population is mature. 12.2.2.3. Pauly’s empirical formula (1980) Natural mortality is given by the following empirical formula: L0g10 M = - 10g 10 La-|' l0g|0 K+0.4634 l0g1() T where M = Natural mortality La and K = Growth parameters of VBGF T = Annual mean temperature ( OC ) of the water in which the fishes lives. In the present study, T was taken as 25°C. 12.2.3. Probabilities of capture The probability of capture by length (Pauly, 1984b) of P. carnaticus was calculated by the ratio between the points of the extrapolated descending arm of the length —converted catch curve using the FISAT software. 12.2.4. Fishing Mortality Coefficient Instantaneous rate of fishing mortality (F) was computed by subtracting natural mortality (M) from total mortality (Z). F = Z —M 204 12.2.5. Exploitation rate (U) The rate of exploitation is defined as the fraction of fish present at the start of a year that is caught during the year (Ricker, 1975). This is estimated by the equation given by Beverton and Holt (1957) and Ricker (1975) as: U =_F (1- e") z 12.2.6. Exploitation ratio (E) It refers to the ratio between fish caught and the total mortality (Ricker, 1975) or the exploitation rate or fraction of death caused by fishing ( Sparre and Venema (1992). It is estimated by the equation: E =I = _F_ Z M + F The ratio gives an indication of the state of exploitation of a stock under the assumption that the optimal value of E equals 0.5 (E ~ 0.5). This, in turn, is under the assumption that the sustainable yield is optimised when F w M (Gulland, 1971). 12.2.7. Virtual population analysis-VPA (Gulland, 1965) The term virtual population means the part, by number, of a fish stock that is alive at a given time and which will be caught in future. In virtual population analysis the annual catch obtained from a single cohort during the exploited phase is used to calculate the abundance and fishing mortality rates of the cohort in each year. Managing a fishery by 205 limiting effort requires estimates of annual abundance and total catch at different levels of fishing effort. VPA is a suitable method in such situations. The basic equations used in this analysis are: F (i,t+1) l.C (I, t, t+l) = N (i, t) ------exp [M+F (i,t,t+l)] M+F(i,t,t+l) C (i, t, t+l) F (i, t, t+l) 2. ------= ------{exp [M+F9i, t,t+l)]-1} N (i+l ,t+ l) M+F(i,t,t+ 1) 3. N (i,t) = N(i+l,t+l) exp[M+F(I,t,t+l)] (the notation exp (x) used in place of ex) The terms used in these equations have the following meanings: C (I, t, t+l): Catch in number for year I with ages between t and t+l N (i, t) : Number of fish (survivors) of age t in the sea at the begimiing of year i F (i, t, t+l): Instantaneous rate of fishing mortality during the year i for those between ages t and t+l M : Instantaneous rate of natural mortality which is assumed to be the same for all age groups Z (i, t, t+l) = M+F (I, t, t+l): Instantaneous rate of total mortality during year I for those between ages t and t+1. The calculation for VPA starts from the bottom (highest age class in the catch, also known as the terminal class). With an initial guess of the fishing mortality for the terminal class (terminal F value), knowing the estimate of natural mortality M and catch for the terminal class, it is possible to estimate the number of survivors at the beginning of the year for this class from the first equation as: M+F (i, t, t+l) c (i, t, t+l) 206 N (I, t) = ------ F (i, t,t+l) exp[M+F(i,t,t+1)] Since the number of survivors at the beginning of a year is same as the number of survivors at the end of the previous year, the estimation of the fishing mortality is also possible for the immediate previous age class from the second equation in which the only unknown factor will be F (i, t, t+l). The number of survivors for this class can be estimated using the third equation. This procedure can be repeated in this fashion starting from the last age class to estimate fishing mortality and number of survivors for each of the age classes. 12.2.8. Length based cohort analysis (Jones, 1984) Cohort analysis is employed to estimate stock sizes and fishing mortalities. In this analysis, the number of fishes in the river that attain L, is given by N (Ll) = [N (L2) S (L1, L2) + C (Lb I-12)] S (Lb L2) Where s (L1, L2) = [(L., -L.) / (L, 4.2)] W2“ The exploitation rate is detennined from the relationship F/Z = C (Lb L2)/ lN (L1) — N (L2)l The fishing mortality was calculated using the formula, F = M (F/Z)/ (1-F/Z). In the above expressions, La and K are growth parameters of VBGF. L1 and L2 are the lower and upper limits of a length group considered, N is the stock number, C is the number caught, F and M are the fishing and natural mortality coefficients respectively. 12.2.9. Relative yield per recruit (Y/R) and relative biomass per recruit (B/R) 207 Y/R and B/R values were determined as a function of Lc/La and M/K (Pauly and Soriano, i986). The estimates were made using the FISAT software. 12.3. Results The growth parameters used for the stock assessment studies were estimated using ELEFAN I programme of FISAT software (see chapter ll). Lot, K and to computed in respect of males and females of P.carnaticus are 493.5,0.5 and —O.7448 and 504,0.65 and —0.7802 respectively. 12.3.1. Total mortality coefficient (Z) Total mortality (Z) of males and females of P.carnaticus, estimated following different methods, are presented in Table l2.l.There exists variation in the values of Z calculated by different methods and therefore, further analysis was carried out based on the average values arrived at from various methods. The total mortality values calculated for males ranged from l.9(Ssentongo and Larkin Method, 1973) to 3.64(Jones and Van Zalinge method, 1981). The average of the estimates by various methods was 2.01. In female population, the values of Z varied between l.97(Pauly’s pile up method, 1983) to 3.46(Jones and Van Zalinge method, 1981), the average being 2.78. The results of the catch curve analysis for male and female P. carnaticus are depicted in Figs.l2.l and 12.2 respectively.Fig.l2.3 and Fig.l2.4 represents the Jones and Van Zalinge plot for the estimation of total mortality of P. camaticus in Chalakudy river. 12.3.2. Natural mortality coefficient (M) The values of natural mortality coefficient worked out by different methods in males and females of P.carnaticus are given in Table 12.2.In males, the values of M were found to be 1.37 by Rikhter and Efanov method, 0.77 by Sekharan’s method and 0.45 by Pauly’s 208 empirical formula. In the case of females, the natural mortality was estimated to be 1.37 by Rikhter and Efanov method, 0.99 by Sekharan’s method and 0.54 by Pauly’s empirical formula. 12.3.3. Probabilities of capture and length at first capture (lc) The results of the length converted catch curve method were used for the estimation of probabilities of capture and lc .The values obtained by the probability of capture were L 25=278.19 mm, L-50=30l.1mm and L-75 = 324.0lmm in males (Table 12.3) and L 25=3l0.6nm1,L-50= 334.15mm and L-75 = 357.7mm in females (Table 12.4) respectively. 12.3.4. Fishing mortality coefficient (F), exploitation rate (U) and Exploitation ratio (E) Fishing mortality coefficient worked out for males and females were 1.15 and 1.81 respectively. The exploitation ratio (E) in male and female of P. carnaticus was 0.57 and 0.65 respectively. Similarly, the exploitation rate (U) was found to be 0.52 in males and 0.36 in females. 12.3.5. Virtual population analysis (VPA) Results of the virtual population analysis of males and females are shown in Table 12.5 and 12.6 respectively. The F value increases to a maximum of 1.15 at 460-480mm and the maximum number of fishes were caught in the size group 300-320mm. In the case of females the maximum F value of 1.81 was observed in the 460-480mm size class and maximum numbers were caught in the size group 340-3601mn.The average F value was 0.159 in males and 0.098 in females. The mean numbers, the length-wise catch and the steady state biomass pertaining to each length class of males (Table 12.7) show that the 209 maximum catch (41l6.6t) was obtained in the size class 300—320mm (Fig.l2.5). Catch constituted mainly of 260-380mm length groups. The mean numbers, the length-wise catch and the steady state biomass pertaining to each length class of females is shown in Table 12.8. The maximum catch (96ll t) was observed in the size class 340-360mm (Fig.l2.6). In the case of females the catch was mainly constituted by 300-400mm size groups. In males, the biomass increased from 116.4 t in the size group 40-60 to the maximum of 6887.5t in 300-320mm length group and thereafter gradually declined to 712.9 in 460 480mm size group. In females, the biomass increased from 82.4t in 40-60mm size group to 8596.8t in 300-320mm length group. Thereafter, the biomass decreased to 930t in 460 480mm length class. The mean E was 0.103 in males and 0.14 in females. 12.3.6. Length based cohort analysis The results of the length based cohort analysis of male population (Fig. 12.7) revealed that the exploitation started at 200mm and increased up to 340mm and thereafter decreased. In females (Fig.l2.8) the exploitation began from 240mm and gradually increased up to 380mm size, thenceforth a decline was noticed. 12.3.7. Relative yield per recruit model (Y ’/R) The relative yield per recruit (Y’/R) and biomass per recruit (B/R) of male and female populations of Rcarnaticus are given in Table 12.9 and 12.10 respectively. In males the LQ/Loo and M/K used for the Y’/R analysis were 0.3 and 1.73 respectively. The yield per recruit reaches a maximum at an exploitation rate of 0.53 and as the exploitation rate increases the Y’/R decreases. Fig. 12.9 depicts the relationship between present exploitation rate, relative yield per recruit and relative biomass per recruit, which 210 revealed the present exploitation rate, E (0.52) was almost reached to the optimum exploitation rate(Emax =0.53). The E.0.i Was estimated as 0.45 and E415 as 0.3. In females the LC/L00 and M/K used for the Y’/R analysis were 0.3 and 1.48 respectively. The yield per recruit reaches a maximum at an exploitation rate of 0.52 and as the exploitation rate increases the Y’/R decreases. The relationship between present exploitation rate, relative yield per recruit and relative biomass per recruit are shown in Fi g.l2.10.The results revealed that the present exploitation rate, E (0.36) is below the optimum exploitation rate (Ema, =0.52). The Em was estimated as 0.46 and E415 as 0.31. 12.4. Discussion Progress on studies on fish population dynamics in tropical waters has been slow even though great strides have been made in temperate regions since 19"‘ century. The main hindrance in the study of population dynamics of tropical fishes are due to the well known problems such as the difficulty in the determination of age of fishes from their hard parts owing to the absence of clear cut armual markings on them and also due to the existence of large number of species supporting the fishery and variety of gears used for harvest. The stock assessment investigations from tropical waters gained momentum in the eighties due to the introduction of length based methods and models and also by the development of suitable computer sofi wares like ELEFAN, LFSA and FISAT. In India most of the studies on population dynamics pertain to marine fishes. Non availability of required number of specimens belonging to different size classes has been the major factor hindering the progress of such studies in freshwater fishes in general and threatened fishes in particular. Rcarnaticus is a vulnerable endemic fish of Westem 211 ghats. Virtually no information is available on the population dynamics of this species and hence the urgency of such a study was felt. Mortality is caused by natural factors like diseases, predation, environmental change, senility etc. in the unexploited stock while in exploited stocks, in addition to natural causes, fishing is the major cause for mortality: Therefore total mortality of exploited stock comprises both natural and fishing mortalities. For estimating total mortality, five methods viz.,Beverton and Holt method(l956), Jones and Van Zalinge method(l981), Ssentongo and Larkin method(l973), Pauly’s pile up method(l983)and length converted catch curve method(Gayanilo et al.,l996) were used. In male Rcarnaticus , Z value was lowest in Ssentongo and Larkin method (1973) and highest in Jones and Van Zalinge method(198l). The estimate of Z was comparable in Pau1y’s pile up method and Ssentongo and Larkin method. The average value of mortality coefficient found from the five methods were 2.01 which was very close to the one estimated from catch curve method and Beverton and Holt method. In females, the values arrived at Ssentongo and Larkin method (i973) and catch curve method (1996) were almost comparable. Pauly’s pile up method (1983) showed the lowest value while it was highest in Jone and Van Zalinge method (1981). For estimating natural mortality coefficient (M), several simple methods are available and the best and easy method is regressing Z against effort (Sparre and Venema 1992). However, in the tropical multi-species system, apportioning of effort for a single species is difficult. Hence this method could not be attempted in this study. Moreover, as natural mortality is influenced by several biological and environmental factors, it is difficult to get an accurate estimate (Pauly, 1980b; Cushing 1981; Liu and Cheng, 1999). Further, it 212 is also related to other growth parameters like La(Sparre and Venema, 1992), maturity (Rikhter and Efanov, I976) and gonad weight (Gunderson and Dygert, 1988). The empirical equation of Pauly(1980b), Sekharan’s method(1974) and the method of Rikhter and Efanov(1976) were used to derive natural mortality in the present study. In the case of males Pauly’s empirical formula gave the lowest value while it was highest in Rikhter and Efanov method (1976). In females also, Pauly’s empirical formula was the lowest while Rikhter and Efanov method showed the highest value. The low natural mortality arrived at in both the sexes of P. carnaticus was in compliance with the observation of Cushing(l98l) who reported that the natural mortality is closely related to age and size and is low in larger fishes due to low predation rate. Therefore, M can be correlated to longevity of the fish and which in turn is correlated to growth coefficient K. M/K ratio can be used as an index for checking the validity of M and K values and the ratio usually ranged from I to 2.5 (Beverton and Holt, 1959). In the present study, the M/K ratios computed were 0.9(Pauly,s empirical formula,1980),l.54(Sekharan’s method,l974) and 2.74(Rikhter and Efanov method,1976) in males and the same in females were 0.83,l.52 and 2.11 respectively. It was found that M/K ratio calculated using the M values estimated by all the three methods calculated in males except that using Rikhter and Efanov method falls under the limits proposed by Beverton and Holt (1959). The average M/K ratio obtained for male P. carnaticus was 1.72 while it was 1.5 in females. M/K ratio is found constant among closely related species and sometimes within the similar taxonomic groups (Beverton and Holt, 1959; Baneiji, 1973). In the present study, the M/K ratios calculated in both males and females of P. camaticus using three different 213 methods were in compliance with that of L.dussumieri(Ku1up,l998),L.calbasu(Alarm,et al.,2000)and L. r0hitha(N urulamin et al.,200 1) Estimation of the probabilities of capture showed that in males the exploitation starts at a lower size than in females. In males 25% of the total catch was less than 278.2 mm size, 50% was less than 301. lmm size and 75% of the total individuals were less than 324mm size. Whereas in females, the L-25, L-50 and L-75 were estimated to be 3l0.6mm, 334.2rmn and 357.7rmn respectively. The fishing mortality co-efficient of females (1.81) was comparatively higher than in males (1.15) which justified the high exploitation ratio. Virtual population analysis showed the highest ‘F’ value of 1.15 in the 460-480 mm size class in males and the fishery was dominated by 300-320mm size class. While in females the highest ‘F’ value of 1.81 was also observed in 460-480mm length class and the maximum fishery was contributed by 340-360mm size group. Higher the average ‘F’ value in males, in contrast to females, revealed that males are more exploited in lower size group than females. This finding is also supported by the results of the length based cohort analysis which revealed that in males exploitation starts at 200mm and intensified up to 340mm followed by a decline. While in females exploitation begins from 240mm and gradually increased up to 380mm and thereafter showed a decrease. In males, the present exploitation rate is 0.52, which is lesser than the Emu (0.53). In females, the exploitation rate and the Em were 0.36 and 0.52 respectively. This implies that the stocks of P.carnatz'cus are not under excess fishing pressure and are well within the optimal level of exploitation. The higher exploitation of males of P. carnaticus may be attributed to three reasons l) Due to the preponderance of males in the population (Sex 214 ratio between males and females = l:0.6), there is a possibility of its hiher exploitation.2) The commercial catch coming from the Peringalkuthu reservoir is mainly contributed by gill nets. Since males of this species are agile and inhabits in surface water in contrast to females which is characterised by a subsurface habitat preference, the former is more vulnerable to gillnet fisher}/.3) As evinced in the results of length based cohort analysis, in males, the exploitation starts in the lower length classes when compared to its female counterpart. The result of the present study revealed that harvest of P. carnaticus could be kept at sustainable level by maintaining the present exploitation rate of male population. Even though this species belonged to vulnerable category, in Chalakudy river system, based on the present findings, it can be recommended that the fishing pressure of female can be improved by increasing the exploitation rate from 0.36 to 0.52 by way of excreting selective gillnet fishing effectively so that the production of Rcarnaticus can be improved substantially. 215 Table 12.1 .Estimation of total mortality coefficient(Z) of Puntius camaticus collected from Chalakudy river system by different methods _ HSl.no. { {Method { 0 0\TotaImortality0oo-efficient@‘ _ ‘ 7 A Males Females K 't— ‘ * *" 3 " ~ P ‘ - -as - " ~ 9 -é I _ 1 Beverton and holtfimethod 2.09; { 2.99‘ i 0 Ssentongo and Larkin 0! 0 7 ! M _2method 7 9 W Q 3 _ 19.9\ 2.76 f 9 34 Pauyjs gile ugmethod { 01.921 1.971‘ it AJones and van Zalinge . 0 \ it 4 method 3.641 3.40 Length converted catch * A Scurvemethod 1 H W 2.15 2.71a 0. 0.. Ayerage 7.-. -. ._ 0 -. 0 ..7 .-_0 2-3.41 0‘ 0 - . -8.27 Table 12.2.Estimation of notal mortality coefficientlllll) of Puntius camaticus W collected fromMCha|akudy river system Bydifierent methods j M j %_$ \|S|.no. Method Natural mortality co-efficient(M) 070v ' 09‘.- * _ 9- 7 v=fMa|es -7| ti-' "Females " * 1 Sekharan's method 4 9 0.77% 9 0.99{ ’A Rikhter ?2methodd and Efanov H 1.37; _t 1.37 1 39 Pauly's empirical formula 0.45 0.541] 0 0 _ ‘Avergge 0 it 1] 3 it 0-86* 3 0.9; Table 12.3.ProbabiIities of captureof males of Puntius camaticus collected from Perlngalkuthu region of Qhalakudy river ‘yIid|eQgtn(mmj Probabilities or selection fSmootM)r0babilily_,§ 230" 0 0.0288 0 0.o3200L if 250; 0 0.0886 0.07940 A U - . 2791 10.197 0.18371. _ j 290;. 0.3477 0.3099? '- - 3.107 1.0000 0.60509 , 33_0\ f 1 .0000 0.79992] _ -350}-.. 1.0000 0.91252 1 1 0370” 1 .0000 0.96450 390 J1___ 1 .0000 0.900121 P - 004101 1 ,000Q 0.99465- L. { 4370 . 1 .0000 0.997943 45Q 1.0000 0.999291 L . .. -470? .. "1 .0000 0.999709 L-25 =27s.1 Li-?= 493.500 (I.-50 i=9 301.1 K=0.50 0 - 1. L- 75% = 334.010, = -0.75 '71 t_slope%= 0.048 K 0 L Table 12.4.Probabilities of captureof femals of Puntius camaticus collected from 3e"m1=" YTL257=310.601 7 7 FL" =504.612 11 7|.-50 =334.151*K7 =0.657 0 17 1 1 7 AL-75 =357.700 15 540.73 1sI0Q1e-H1 1__. _ 1 -.50-04711. 1 - - 1, Table 12.5.FlSAT output of results of the length-structured VPA results for Punt|'us ca1rnatiqus1 colle¢te1d1frQm P3ring1q1Ikuthu 1re1?i1onof1Chalakq§l_y1f§yer,1Ke|f3Ia, S. lnqia 1 1 TLengthclass(mn“11L§atchesQ~Q1 1 PopuIation§N 10 3jFishing1morta|ity 1.0 -20 ' 0.001 23406108511 1 1 1 0.0000 V20 -40 7 L 7 7 7 0.00” 2179843“ °-°°°9. K40 -60 0.00 1202318941131 1 0.00100 1 160-30 1' 1 1 0.001 18728210.3§ 11_ 01.100001 160-100 .1 1 0.00" 17266636311 1 o.000@1 “T100-120 9 1 7 0.001 1585574953111 11 0.001001 120-140 1 0.001 14494818.38]1.11 0.00001‘ "5140-160 1 1/ 1 0.100‘ 1313574631_ __ _ _ 1 1 _0.0000 _ J 1160U .. -180 . 2.-. _J 7 0.001 1192888251 0.0000 1780 -200 . 1?. 0.00"" 10721515251 0.000011 12047-220 - 1 0.00‘ 957548.56‘”7 0.00001 11220 -240 1 L11 1 6853011 .011 0 7 _ 848089“ 01.057101 1240 -260 158200.00“ 7137811321311 1 0.114151 1260 -280 - T _254860.00 L 625849.19 0.25071 0.3476‘ 2s0»300 1 312390.001 51.2953-3.11 _ . 7300 -3?-0 451780.00 404.473-.15. 1 - 7 7 0.1597617 @1320-340 1 11 369100.001 204231.06‘ 1 ‘ 1 0.609911’ 1.340 .-360 L 365970.0 0.1 20153020911 11 71 1 0.79761 1311610-31801 _ 1 200620.00 “ 129243.17 7 0.63021 1.380.-400-7 . 7. 100620.001 796765311 71 0.411361 1400 420 . 1 26570.00; 487629.76;-.31 7 1 W11 11 1 0.15431 "420 1-440 J_ 20000.00 293451 11 11 1 0.1426 “£40 @460 30960.00T1 .‘15736.2211 11460 -4810 1 1 29°90 (Ct). 12- .5°84~43 (NI) 1 1.-15? (F9 0.350% Table 12.6.FISAT ou ut of results of the len th-structured VPA results for female Puntius camaticus Fqollected from11PeringalI Table 12.7.FISAT output of results of the length-structU red VPA ll results for male Puntius camaticus 1;91llected frog;1PefingaIkufl1u region 01f1Chalakud_y_1§iver, Kerala, S. India _ 111/PA || 11 !1FEMALE11 1 I A SteadyI state ML(F!10!) DELTA T(y0ar$) . _ Mean N Ca_t§;H(tonnes)1bi0m1ass 11 1_ 1 110 0.083= 1009005001 . 0-Q01 2688.91 '1 :4 - 1 30 -0-03001 1 1 81 13315952 0.00 011007.04 1 501 1?'§65720°i 0.00 1 110420.004 4. 1 701 7 0.094 1 699263111001 1 1 0.00 2766 1101.72 _1 11 90 0.099 154109392? __11 0.00 525200.00 1 110 Q-.1 Q4: 1 58211 0672 0.00 070021.10 1 Q 1 13012. 0.1111 71522253445 0.00 131 552110.38 . . _ -150 .1. 1 0.110 140140970 .0.-0° 1000455110 .1. 70 0.124 1 39968592 1110.00 25000075 A 7 1.90. 0.102 1000021521 0.00 0220*/741.75 0.141“ -2101 2 1 12727351113511 .0-00 1! 40022405 02301111 1 0-.1 52 120237088 1 277042.91 40740025 1 250. _. 0.1641. 111017000 004141.09 50007505 0-1.791 1596196.75 1 2701.-- . 1010004241 1 500511 1.5 1 2901; 07.197 8981 53041 207502050 68281451 68874575 1_ 1 1_*310 0.210 _75597024 4110012251 1__1 1 005049001 090500975 65346825 _ 3301 0.24511 77 -- . 3501 _ 0.279 I 7450001521 4004400100 501o024.5 _ 370 _ 0.325 33261348 3086566.00 4091590 1 1 3961 0.3881 240770201 1712501101 414075025 Table 1 2.8.FlSAT output of results of the length-structured VPA ll results for female Puntius camaticus collected f798m88Peringalku_t8hu region of Chalakudyriver, Kerala. S. India 4 ~l ML§mm) 8 108DELTA T(y(8e)zg65% _888 88 88 Mean88 1032764641 8 8Catcl1(ton|_]esqSteadystate 880.001 88 155898.411 biomase 30l -08086518’ 1' 8 101 196136 8 0.00 8 20700.63 50 0.0681‘ 9907094418 0.00" 88 88 62441.6 70 0.07118 96897448 0 00 207717.23 90 0.074 8 9467275288 0:008 413777.086 110 0-97897 8 92392512 80.00 714664.56 1301 8 0.062 90052616 0.00 1121381.38 .150‘ 0.087 67646720 88 0.001 164189988 170 0.09211 l 851 74560 0.00 22610665 190 00.098 l 888882623864 8 W 0.0081 3040856237 2101l______. 0.105 79989176 0.001 3918884595 2301 .0-1.128 88 8 5 ’ 772616561 0.008 749091355 7250 '0.1211 1 744313361 it 0.008 680027255 '1 8270 8 0.1321 70636208 13201'30.631 70992785 .290 0.144 65466664 2241615L 80872221 3810. 88 8 88 0.1598 5761 31 36 6626530 4‘.1 ”6596796 3301: it 0.177. 88 .8 4776718201 70329295 77 8527223 l 350 0-211.. it fill 37130396 l 9611792. 888 7840552 370 0.23 8 8 8 8268854784 7_764700.5l 6647942. 3901 0.271 8 8 7 18137770 ;787881028481.5 522000451 -5101 0.329. .37. 11333654. 3 317.7503-25 8 88 3929682 1 7_ 430 -041 311 8873366535 8380327418 82792090.5 450 _8]0.576*@ _ 88 8 84s01660.5*[§886189393.018 195122538 7470 8 0.933 8 169447525 1663252751 929973.94 Total %.. 8 it 7 3883904000 885051 3620.001 6596310400 Table 12.9.FlSAT output of yield! recruit from selection data for male Puntius carnaticus from Peringalkuthu region of Chalakudy river Parameters : L,,I_L_q_8&_ .304, MIK = 1.872883 Y’/R . _._._ 1 B'/ R .3 .7 l 0-.05. 0.00561853l 089076060 l 0.10 0.0110766 888 0819084800 9115; 0-01 511733 8_808.7344400 0.201 0.0199028 0.653946 _l 0.2885 002344291 0.5776970 0.30 0-026391171 0505632018 0.358 0.0267436 0.4364650 0.4.0; 0.0304987 _] 80.3757660l 0.45” 0.0316506, 0.3178540 0.50 003223591 0.2647940 0.55 0.0322425 8 0.2166940t 0.60. 0.0317036 0-1756140 0.65 0-0.3065367 0.1355630} 0.70 0.029130811"8" 010256108 0-75 0.0272216 n 0.7453500 0.808 0.0249797 7 0.0512970 0.6588 0.0225115 0.0326320 1 0.901 0.01993534% 0016195018 0.958 0.0173880 8 0.0075170 1.00‘ 0.0150161 0100000001 Table 12.10.FlSAT output of yield! recruit from selection data for female Puntius carnaticus from Peringalkuthu region of Chalakudy rlver lfarametere; LJLQ = .2916, IVIIK = 1.4995 TE 1 Y‘?/'R B‘/R] 0.05 i 70007234217 0.908536 ” 0.10 _L 0.0137944. 7 1 0.3206131 3 I 1 I Q-.15 E 0.0196603‘ 0.736402‘ I [ .__ 0.20 002481291 0.656047 0.25 0.0292345 1 0.5797157 '| 1. 0.30; 0.0329097 0.507572. 0.35 0.035826 0.4397863 1 0-46 ? 0.031975? 0.316513 0.45 L _ _Q.0393537L__ H 0.31 0.50 \ 0.039900? M 0.2_34%113 K . _ Q-.55 0.0398253 * j 0.215337 0.60 0.0339503? 0.171666 Q-65 0.0373986; A 0.133109 0.70 0.0352103 0. 0997461 v I 0.75 1 0.0324742. 0.715513 0.80 % 0.0292982 0.0434151. 0.35 002582541 9 0.030124 Q-90 0.0222344» U 0.01633’ 0.95 0.0187387 __ 0.006519 1.00 0.0155740 °L°°°°.QQ wa_s_E8 ___,__.=5___~ 22: __° £§_@_:“ 9:3 :83 2: 3 m____§____§_wE E5 @N ‘UNMW WW6_Q HNW_%OP @@_N H X %o _@w U_____:_U ‘DEED ED?“ N in Ah“ “MOO QHOU _ mmm_ mfi_N| Haw mmO_w @m_®H Adv Pmmuhu¥;m'* c fN“M {j /Imoflpwwpfigm commmmhmwm L” *11 ®@_®@I_®M Mhmfiwfifihfim ;¢3Dhw ma Q®_® x Ea ®m_mm¢ Q¥%N ‘M W Q / CooQ$ J4 A_ I,’/_’__ nu @ Amfldumv UM“ ~u=_°mAG w Q—|l}"||‘\““qh|\|\\ M ‘ I “_ H‘I‘||*'Ll_ ' _M“‘]r |‘\ WW:wm0 _0 ” L/fl ____kw‘J; Go IHmIU_)N/V,4(.__._ as Qmv _Nm:QMfi6:WUMfl° :#m=u_Moum=w= i F‘Ik‘W \ ‘l |hI|_‘ ’ |||\ ‘A|‘ AIL? __ : L @Hw:U_=§=__QU §._“=__H__ Q_flEU‘_ *9 mmm_h__Efl 02:0 H_UU_flO 0.: “Q m==mO~__N_N_.wW_ ___% EE om? iJ Ea fimw_‘N H UNMM mmfl_Q Q ‘& Hhwiflflafighuwao £¥m=U_ “O Hagan MHQHQN OF _m_m N mo _Qv % Hh_N U:fi5U ;U#flQ EBB“ fimm_iH A%w_“UDU _hhOU W Hm_N‘ Hp“ mmo_m fi fin_®H “fig ¥mUUhU#5mI* _ HF wuwamwgfifiw =DMmwmhmmm_; mfg ®mn_®1 H®@_® ma @o_® x ____;_m mm v® mhmQ®Eflh¢m&m¥1mLw!w§ ‘IllAmgfiflmv Wmfi 0*5~OM£c E m Hi hi WfiH~ WWi1!‘@Ly& fiLyN1l% fJ@ ____ 0 /Iz i_m ‘__/Ill I_w I J’®p_i,__§IIfWMWW[HNii% MHb %:wWk%V¢1? 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H‘ __|:“‘ +“*‘:"”|‘PI‘I‘v‘Fr“HL‘ ll I: ' “““_ “ WIN!’ N mama camamgmofimxm J ‘. __ ‘l iI. H_m 3' H_ _. F _H “K! LHI Hm 8M fix & LN_ I{ ._ : ._' W U_ D '_ ___ 0_ I. , __M f_ Jm_ qw '___ ‘_ Ww ___l A _____ V M J’ .1 0 my ¢ " (_____SW (__ WW L1 1 I_|_Lm_ U__ _I ‘I _O_ _W ,_ 5__.____ l_m. a NW _f kfi_ o{ MJ 'M ’___ m _.__ Wfiw ______M H@fJm _L: ( xi_ 3 nWW £3 {% m*mg =°M#fi*M°_mxw mm‘ mm fig 5'.I.EW MZ _1 _T *_M_m_fl_ ____W7 ___._.__ _1f é__~______\__ ’__f__ @'__.______x __~ /_ __\ “_ H, m7 ____‘_____‘ ____\___ i NWat .“‘|Fl’.l_.-_ I l iII M‘ “|‘l‘M!I'| ‘li|__! ’_ ‘M _¥ HH| }IHBIPIJBOJn_-__1')TBVZ(_' \ I‘ IIHWIYIHIM‘L‘|‘h‘H|H|h|q‘|'| i1 "'H“U“W||“|""‘ Hmam______Chapter 13 Summary and Recommendations 13.1. Summary Biodiversity refers to the variety within the living world. It manifests itself at all hierarchically related levels of biological organization from gene through cells, tissues, organs, individuals, populations, species, cormnunities and life forms of ecosystems. The loss of biodiversity is a natural process, which takes many forms, but at its most fundamental and irreversible outcome it involves in the extinction of species. The convention of biodiversity signed by 156 countries at the Earth Summit in June 1992 in Rio de Janeiro thus shows that conservation of biodiversity currently regarded as a problem of worldwide scope. Scientists estimate that over the next 25 years more than a million species of plants and animals will become extinct. There are many reasons why humans should be concerned with biodiversity conservation. Organisms provide a wealth of resources and ecological services that benefit humans. Biotic resources include food, building, materials, firewood and medicines. Many organisms bring significant pleasure and humans also have a moral and ethical responsibility to care for the environment and the variety of life it supports. The loss and impainnent of natural habitats as well as pollution are universally recognized as the prime causes of loss of biodiversity. The ever increasing demand for resources in terms of land area (agriculture, urbanization, industry, leisure), materials (food, construction materials) and energy from an ever increasing human population and the attendant array of harmful effects (pollution, degradation, fragmentation and disappearance of habitats) constitute the greatest threats to the integrity of ecosystems and, consequently to biodiversity. National Research Council outlined the five important and widespread human impacts on biodiversity and placed habitat loss and degradation as the prime factors responsible for biodiversity decline. 216 Seen from this perspective, scientists have a particular responsibility, a central role to play both in order to understand better the biodiversity phenomenon and to be able to draw up clear guidelines for careful resource management. In a review by WWF, IUCN and UNEP on the ways of conserving genetic diversity of freshwater fish it was recommended that the best way to conserve species diversity is to conserve habitats. ln comparison to population —based management, habitat has the advantages of being relatively stable through time and habitat is easily defined in intuitive physical terms and provide a tangle resource for negotiations and decision making. The habitat studies in freshwater ecosystems are very essential for the proper understanding and management of human impact on fish diversity, to study the relationship between habitat variables and fish species assemblage structure, quantification of ecosystem degradation, habitat quality and biotic integrity of the ecosystems, development of habitat suitability index (I-ISI) models and classification of river reaches based on their physico-chemical properties. Therefore in the present study an attempt was made to assess the biodiversity potential and the relationship between habitat variables and fish species assemblage structure in six major river systems of Kerala which would be very useful in impressing upon the seriousness of habitat degradation and biotic devastation undergone in the major river systems of Kerala. An attempt was also made to develop habitat suitability index models of 10 critically endangered and endemic freshwater fishes of Kerala, so enabling the administrations in adopting the relevant conservation and management plans for the sustenance of these fishes in our river systems for the years to come. Kerala the land of rivers is endowed with 41 west flowing and 3 east flowing rivers with a total length of 321 lkm and having a basin area of 37884km2.These rivers are 217 originating from different regions of Western Ghats, even from an elevation as high as 2800m MSL, and harbouring 170 fish species belong to 12 orders and 28 families. Among the total 44 river systems, six major river systems such as Periyar, Bharathapuzha, Pamba, Chalakudy, Kallada and Periyar together constituted a basin area of l6942km2 and supports 75% of the fish diversity known from Kerala rivers. Periyar, the largest river system in Kerala having a total length of 244km originating from the Sivagiri hills having an elevation of l830m from the mean sea level(MSL). One of its major tributary originating from the Anamalai hills, having an elevation of 2800m MSL. Fish gennplasm inventory conducted in this river system by various investigators so far identified a total of 76 species, among them 46 fish species were collected during the present study. Bharathapuzha river system has a total length of 209km, originating from the Anamalai hills is having an elevation of 1964m MSL. 63 fish species were reported by previous investigators while 58 species were collected now. Pamba river system has a total length of l76km originating from Pulachimalai having an elevation of l650m MSL. 54 species were reported so far from this river system while in the present study 30 fish species could be collected. Chalakudy river system with a total length of l30km is originating from Anamalai is having an elevation of l250m MSL. Earlier surveys reported 40 species of fishes while 40 species were collected and identified fi'om Chalakudy river system. Kallada river system with a length of l2lkm, originating from Karimalai is having an elevation of l524m MSL. 41 fish species were known from this river system while 23 species were identified from this water body now. Kabbini is one among the three east flowing river systems of Kerala is originating from Thondarmudi Malai having an elevation of l500m MSL. 51 fish species were known from this river 218 system. Whereas 54 fish species were collected from the Kerala part of Kabbini river system in the present study. In the present study, in Kabbini river system 15 locations encompassing between 721 946m above MSL were surveyed. In Bharathapuzha river system 27 locations were studied including the main stretch, tributaries such as Gayathripuzha, Kunthipuzha , Kanjirapuzha and Chitturpuzha and I order streams above Malampuzha, Mangalam dam and Meenvallam region.All the stations were located between 18.4 ~l001m above the MSL. In Kallada river system ll locations were surveyed including the main stretch, tributaries such as Kulathupuzha, Kazhuthuruty Ar and Chenthumny Ar. All the stations are located between 20.3 to 641m above MSL. In Pamba river system, 15 locations were surveyed from the main river stretch and tributaries such as Kakkiyar, Kochupamba and Azhutha. All the locations were situated 4.5-l000m MSL. In Chalakudy river system 20 locations encompassed between 40-996.4m above MSL were surveyed which include the main river stretch and major tributaries such as Sholayar, Parmbikulam and Karappara. In Periyar river system 29 locations embarking 20-l540m above MSL were surveyed which include the main river stretch and two major tributaries such as Neriyamangalampuzha and Pooyamkuttypuzha.57 habitat variables were collected from the selected locations in Periyar, Bharathapuzha, Chalakudy, Pamba, Kallada and Kabbini river systems following standard methods. For analyzing the species assemblage structure, sampling of fishes was done from all stations selected for habitat inventory. The fishing effort was made uniform at all the sampling stations. Based on the ratios such as sinuosity, entrenchment ratio, slope, width/depth ratio and dominant substrate the stream reaches were classified upto Ros gen’s II level. The physical habitat quality (HQ) scoring and index of biotic integrity 219 (IBI) scoring of selected locations in each river system were done following Lyons (1992). The fish diversity in each river system were studied based on four diversity indices such as Shanon-Weiner diversity index, Simpson index, Pieoleu’s evenness index and Margalefs index. The extent of ecosystem degradation undergone in each river system was studied by correlating Shamion- Weiner diversity index, index of biotic integrity score and fish abundance in each river system with the 57 habitat variables collected from each river system. The habitat suitability index (HSI) models of 10 endangered fishes were developed from the habitat parameters, which showed significant influence on the distribution and abundance of the respective species. In the configuration of channel geomorphic units run was the dominant type in Kabbini river system. Whereas in all other west flowing river systems midchannel pool was the dominant microhabitat. Among instream cover, overhanging vegetation was the dominant type in Kallada and Kabbini river systems while in other river systems such as Bharathapuzha, Pamba, Chalakudy and Periyar depth was the dominant microhabitat. In the case of riverbed materials gravels were the dominant type in Kabbini and Kallada river systems whereas in all other river systems bedrock was the dominant substrate. In Kabbini river system, among the l5 locations surveyed 1 location belonged to D4 class, 6 locations under A4 class, l location under DA6 class, 2 locations under n/a class, 1 location under A2 class, 3 locations under G6 class and 1 location under G5 class as per Rosgen’s classification. In Bharathapuzha river system n/a class accommodated 10 locations, Ala+class 6 locations, A3 class 4 locations, A2 class 2 locations and DA5,DA6,D6,B6,C2b classes have l location each. In Kallada river system 5 locations comes under n/a class, 3 locations under Ala+ class while A2, G5 and A3a+ 220 accommodated 1 location each. In Pamba river system, Al class accommodated 5 locations, n/a class 4 locations, A3 class 3 locations and A2 and Ala+ classes having 2 and I locations respectively. In Chalakudy river system, of the total 20 locations studied 9 locations are coming under n/a class, 5 locations under Al class, 2 locations under A2 class while Gle, Gde, Ala+ and Bl classes were represented by one location each. In Periyar river system ll locations were coming under Al class, 5 locations under n/a class, 3 locations under Ala+ class, 2 locations under Flb class. While classes such as C3, B5, A6, A4, B2, A2, G2e and A2a+ were represented by one location each. During the present study the Habitat Quality Score (HQ) developed by the Ohio EPA was applied for the first time in India. To comply with the conditions prevailing in our river systems appropriate modifications were made in the scoring criteria. The Habitat Quality score (HQ) was found as ideal to measure the physical habitat quality of the river systems of Kerala. In Kabbini river system the habitat quality score varied from I4 to 56 with an average value of 33.4. Habitat quality score varied between 14 to 63(mean 39.6) in Bharathapuzha and 12 to 70(mean 40) in Kallada river systems. In Pamba river system the habitat quality score varied from 20 to 66 with a mean value of 41.9. Chalakudy river system showed the highest average habitat quality score of 57 and the location wise habitat quality score varied between 24 to 75.Habitat quality score varied from I0 to 77 with a mean value of 49.1 in Periyar river system. Index of Biotic Integrity scoring (IBI), a technique used to study the biotic integrity and health of an ecosystem was applied for the first time in the rivers of Kerala. In U.S.A., Index of Biotic Integrity (IBI) is extensively used for bioassessment and biomonitoring programmes and interestingly, the Ohio EPA incorporated IBI scoring into Ohio water 221 quality standards. In Kabbini river system IBI varied from 5 to 65 with a mean value of 38.4.Index of biotic integrity score in Bharathapuzha river system was in the range 0 60(Mean 21.7) and Kallada river system from l5-45(Mean 27.3). Biotic integrity was maximum in Chalakudy river system with a mean value of 44.1 and the location wise IBI ranged between 25-64.In Periyar river system IBI ranged between 0-52 with a mean value of 34.1. The result of the present study revealed that, among various variables analysed, altitude has a very significant influence in deciding the fish diversity in six major river systems of Kerala. The fish diversity studied on the basis of Shanon-Weiner and Simpson diversity indices revealed that even though some minor variations occur with the suitability and complexity of habitats, the altitude showed inverse relationship with fish diversity. Shanon-Weiner diversity index showed maximum value in the 0-200m ranges in Bharathapuzha, Chalakudy and Periyar river systems. While in Kallada and Pamba river systems the maximum diversity recorded was in the range 200-400m and 400-600m. In Kabbini river system the survey was conducted only in the 600-l00Om MSL.The highest diversity was observed in the stretch 600-800m. Simpson diversity index was maximum in 200-400m in Chalakudy and Pamba river systems, in contrast, it was highest in the 0 200m in Periyar, 600-800m in Bharathapuzha and Kallada river systems and 800-l000m stretch in Kabbini . The species richness measured based on Margalef’ s index was highest at 0-200m in Bharathapuzha, Periyar, Chalakudy and Pamba river systems while in Kallada and Kabbini river systems it was respectively at 400-600m and 800-l000m. Species evemiess measured based on Pieolu’s evenness index was highest at 600-800m in Bharathapuzha, 222 Chalakudy and Kallada river systems,400-600m stretch in Periyar and Pamba river systems and 800-l000m stretches in Kabbini river system. The extent of ecosystem imbalance in each river system has been determined by comparing the fish species diversity, abundance and index of biotic integrity scores with the habitat variables in the respective locations in each river system. With the knowledge of these relationships, the stream restoration activities may successfully target on those features that are important to the stream fish community, which will helps to achieve the physical, chemical and biological integrity of our river systems. The study revealed that among the six river systems studied only Chalakudy river system showed the sign of a healthy ecosystem. On the other hand Bharathapuzha and Kallada river systems were prone to high degree of habitat degradationand if this ecosystem imbalance continues, there is every reason to anticipate that these river systems will become aqua deserts in the near future. The extent of relationship of habitat variables with fish abundance and tropic structure in Periyar and Pamba river systems revealed that even though the habitat alteration not severe as in the case of Bharathapuzha and Kallada river systems, habitat degradation were found very high in these river systems. In the present study habitat suitability index models for 10 endemic threatened species such as Lepidopygopsis typus,G0n0pr0kt0pterus micropogon periyarensils, Crossocheilus periyarensis, Neolissochilus wynadensis, Silurus Mg/nadensis, Osteocheilus longidorsalis, Puntiusjerdoni, Garra menoni, Homoleptera Pillai and Mesonemacheilus remadevi were developed. Abundance of Lepidopygopsis typus showed a positive correlation with amount of bed rock substrate, chute type channel geographical tmit, overhanging boulders, overhanging vegetation, total shade and tree cover and negative correlation 223 with light intensity and slope. Optimum habitat of Garra micropogon periyarensis was found as midchannel pools with moderate depth, overhanging vegetation, less slope and excellent shade. Crossocheilus periyarensis is most abundant in scour out pools with enough woody debris , overhanging vegetation and tree cover. Silurus wynadensis can tolerate only a narrow range of habitat parameters and was found as a highly habitat specific species. Biomass of Silurus wynadensis showed a positive correlation with total instream cover, trench pool,water temperature and overhanging stream boulders. Optimum habitat of Neolissocheilus uynadensis was found as lateral and plunge pools with less channel width, low alkalinity and hardness. Distribution of Osreocheilus longidorsalis is positively correlated with abandoned charmel, backwater pools, emergent vegetation, glide and overhanging stream boulders and is negatively correlated with charmel width. P. jerdoni was found in abandoned channels with good Cl’l8.I‘lIl6l width and rocky substratum and its abundance was negatively correlated with alkalinity and cascade type channel geomorphic unit. Occurrence of Mesonemacheilus remadevi showed negative correlation with bare ground, cobbles type substratum and depth. While the species showed positive correlation with bedrock type substratum, dissolved oxygen, riffle and glide type microhabitats, large and small woody debris. Occurrence of Homoleprera pillai showed positive correlation with bedrock, dissolved oxygen level, glide type microhabitat, large woody debris, small woody debris and slnub cover and negative correlation with cobble type substratum. Occurrence of Garra menoni showed positive correlation with bedrock, dissolved oxygen level, large woody debris and small woody debris and negative correlation with glide type microhabitat. The results of the present study were useful in forecasting the impact of proposed Pathrakadvu dam on the 224 fish fauna of Silent valley. The HSI models of the three endemic fish species such as Mesorzemacheilus remadevi,Hom0Zeptera pillai and Garra menoni from Silent valley revealed that the distribution of these species showed high degree of correlation with rocky substratum, flowing water channel geomorphic units such as riffle and glide, presence of woody debris, dissolved oxygen level and vegetation on the stream bank. But once, the dam is commissioned, the level of bedrock type substratum, dissolved oxygen level, riffle and glide type channel geomorphic units, woody debris and vegetation cover on the river bank may be obliterated and this will become a malediction to this species. Based on the results of the present study it can be inferred that the construction of the proposed dam across Kunthi river at Pathrakadavu would bring about serious alterations in the fish habitat and species assemblage structure at Silent valley and such ecological transformation would not only ends up with the extermination of the above mentioned endemic threatened fish species but also the proliferation of many exotic fish species in the transformed lotic ecosystem. Moreover, hitherto no attempt was made to find out the reason of endemism in fishes related with HSI in the Indian context and therefore this subject was never surfaced while taking policy decisions on the fate of Indian rivers. The present study revealed that the National Policy on the interlinking of rivers would permanently alter the HSI indices of the above mentioned fish species, which are now solely protected by the individuality of the rivers where their limited occurrence was noticed. Any such interlinking would bring about severe alterations of habitat parameters such as flow velocity, nature of substratum, type of microhabitat and vegetation governing the presence of these fishes and consequently there is every possibility of extinction of these species from the universe. The present finding may be useful for the 225 policy makers in dissuading from taking decisions in interlinking of those rivers which harbour such endemic fish habitat with other river systems, which would pennanently damage such HSI factors and interalia the extermination of these species. Puntius carnaticus(Jerdon), commonly known as Carnatic carp and locally known as Pachilavetti, belongs to the family Cyprinidae and subfamily Cypriniae. This species is endemic to Western Ghats and belongs to vulnerable category. P. carnaticus is a food fish with an excellent demand in local markets and fetches Rs.50-65 per kg at Peringalkuthu region of Chalakudy river basin. Besides being valued as a food fish, due to its voracious feeding nature on plant materials, prolonged breeding season and comparatively good growth rate when compared to other carps, this species has all the desirable traits of a candidate species for aquaculture, which can also substitute grass carp in polyculture. Hitherto, no information is available on the bionomics and resource characteristics of this species. Studies on detailed life history traits are indispensable for fishery management, captive breeding and conservation programmes. ln the present study, a pioneer attempt was made to investigate the life history traits and resource characteristics of P. camaricus. The qualitative and quantitative aspects of food composition in relation to sex, size and season, seasonal variation in feeding intensity as well as gastro-somatic index were studied. The index of preponderance was used to assess the food preference of males,females and indetenninates. The study indicated that basic food of P.camaticus was plant matter. The other major food items identified were filamentous algae, diatoms and animal matter in the order of their preference. Based on the feeding habitat males, females and indeterminates of Rcarnaticus are coming under herbi-omnivore category. 226 Feeding intensity was very high and was found to be influenced by the reproductive cycle. It appeared that there exist a cyclic feeding rhythm in both males and females showing a period of higher feeding activity followed by a phase of lower one. Based on the diversity of the types of food consumed, this species can be categorized as stenophagic fish. Relative gut length and feeding intensity was comparatively less in indeterminates when compared to both the sexes. Gastrosomatic index (GSI)showed higher rate of feeding among sexually mature individuals than in indeterminates. Length group data of GSI revealed that females consuming more food than their male counterpart. The various aspects of reproduction such as maturity stages of males and females, monthly percentage occurrence of fish with gonads in different stages of maturity, pattem of progression of ova during different months, gonado-somatic index, length at first maturity, sex ratio, fecundity and its relationship to various body parameters were studied in detail. The spawning season was delineated based on quantification of maturity stages, monthly percentage occurrence of fish with gonads in different stages of maturity, pattem of progression of ova during different months and the monthly variation of gonadosomatic index. The wide size range of ova with only one or two modes is the typical cyprinid character and is an indication of the prolonged spawning season with two distinct peaks. Males mature at a lower length (232 mm) than females (270mm).The spawning season of P.carnatz'cus is a prolonged one extending from April-August with a major peak during July-August in both the sexes and minor peak during April-May in females and May-June in males. The predominance of males were seen upto 3 l0mmTL and thereafter the percentage occurrence of males become insignificant, on the contrary, 227 females showed predominance in higher size groups in the fishery. Beyond 390mm TL, females dominated the fishery. Fecundity of P. carnaticus ranged from 2763(2l6.83mm TL) to l407l(445mm TL). Fecundity showed strong con'elation to the weight of the ovary than to the other body parameters. The length-weight relationship in males, females and indeterminates was established with the help of general linear equations. The value of regression co-efficient for indetenninates and males were 1.4243 and 2.7148 respectively, which showed significant departure from ‘3’ indicating that the growth followed negative allometric pattem. On the contrary, the exponent value of 2.8618 in females is indicative of an isometric pattern of growth. The general well-being of the fish was ascertained from the relative condition factor (Kn). Monthly variation in relative condition factor (Kn) were found influenced by reproductive cycle, feeding intensity as well as some other unknown physiological or inexplicable enviromnental factors. Size-wise variation in Kn values could be related to maturation and spawning. Age and growth of Rcarnaticus was studied in detail. The La of males is computed at 493.5mm and that of females at 504mm.The growth co-efficient (K) and Munro’s PHI prime index were 0.5 and 5.08 in males and 0.65 and 5.22 in females respectively. The life span of P.carnaticus is 4-6 years and the male attains a length of 286.9mm, 368.2mm, 4l7.6mm 447.6mm and 465.9mm in the I, II, III, IV and V years respectively, while female attains 345.8mm, 421.1mm, 460.85mm and 48l.7mm at the end of I, II, III and IV“‘ years respectively. The growth rate of P. carnaticus is moderately fast when compared to other carps and attains marketable size in the first year of its life span, itself. Studies on the recruitment pulse revealed that P. camaticus has a single long recruitment 228 period extended from May-October in males and April- October in females, which is indicative of the long-term availability of brooders and fingerlings in the wild. The results of the age and growth are invaluable in recommending this species for aquaculture. Total mortality, natural mortality, fishing mortality, exploitation rate, exploitation ratio, probabilities of capture and yield per recruitment were studied as part of resource charactrestics. The average total mortality co-efficient of males and females were 2.01 and 2.78 respectively. In males the average natural mortality was 0.86 and in females it was 0.97. Highest fishing mortality of 1.81 was recorded in the 460-480mm size group of females while it was 1.15 in males. Virtual population analysis revealed that the average ‘F’ value of different size classes were higher in males (0.16) when compared to females (0.098). In males exploitation starts at 200mm and fishery was dominated by 300-320mm length class. While in females exploitation starts at 240mm and fishery was dominated by 340-360mm length class. Studies on probabilities of capture also revealed that exploitation starts at a lower size in males and the L-25, L-50 and L-75 were 278.19mm, 301 . lmm and 324.0lmm respectively. While in females it was 3 10.6mm, 334.l5mm and 357.7n1m respectively. The exploitation rate and exploitation ratio of males and females were respectively 0.52 and 0.57 in males and 0.36 and 0.65 in females. Comparison of the present exploitation rate of males (0.52) with that of the Em,‘ (0.52) revealed that the harvest of P. carnaticus could be kept at sustainable level by maintaining the present exploitation rate of male population. While the comparison of females exploitation rate(0.36) with that of its E,m,(0.36) revealed that a slight increase in the fishing pressure through selective harvesting of female population up to an exploitation rate of 0.52 from the present 0.36 will help to increase the production without affecting the stock. 229 13.2. Recommendations l. The fish habitat studies will provide adequate inputs for the proper management and restoration activities of river systems and therefore detailed habitat inventory surveys should carried out in all river systems of Kerala. 2. Develop a new stream of classification system of fish habitats exclusively for the streams and rivers of Kerala is required urgently. 3. Implementation of various action plans are required to maintain the Habitat Quality (HQ) and Index of Biotic Integrity (IBI) above 40 in the entire stretch of all the river systems of Kerala by improving the water quality parameters, instream cover, microhabitat diversity and quality of substrates. 4. Instream and stream side cover can be improved by boulder placement, placements of stumps, roots or debris, artificial undercut banks formed by overhanging cover structure, tree planting in banks and stop the removal of overhanging vegetation 5. In view of the fact that the pool-riffle reaches can be identified as most diversified macrohabitat it can be achieved by current deflectors, stream narrowing deflectors, installation of low weirs and mechanical construction of pools. 6. Substrate reinstatement by replacing the sediments with well-sorted gravels, cobbles or even with crushed rocks which will helps to improve the fish and invertebrate habitat. 7. In braided reaches improvement of current speed diversity possible through the installation of rapids by the construction of different types of low weirs. The weirs shall be placed over the full or partial width and at different angles to the riverbank. It may be straight, ‘V’ shaped in the upstream or downstream direction or with an irregular crest form. The weirs can built with boulders, cobbles, stone filled gabions or with concrete. 230 But maximum height of these weirs should not exceed 1.5m or it should be completely submerged in water. 8.Keep the longitudinal connectivity of rivers as intact not only to permit passage of migratory fish species but also for the free movement of all species within the maximum range; obstructions presented by dams and weirs may be bypassed by fish passes but the influence of water quality barriers must also be considered. 9. To maintain the lateral connectivity between the channel and river margin or flood plains in the middle and lower stretches, should not convert the flood plain ponds and backwaters associated with the river system to agricultural lands. l0. The micro invertebrates which form a good source of food to stream fishes can be motivated by increasing the concentration of woody debris, wet land vegetation and restoration of riffle type microhabitats in streams. 1 1. Due to the immense fish diversity prevailing at Athirappally to Vettilappara region in Chalakudy river system, Kulathupuzha to Thenmala dam in Kallada river system,Pooyamkutty to Thandamankuthu in Periyar river system and Begur to Baveli region in Kabbini river system, these regions may be declared as aquatic sanctuaries. 12. Develop the habitat suitability index (HSI) models of all the threatened and endemic fish species of Kerala for their effective insitu conservation and transplantation to similar habitats. 13. Ban the illegal sand mining activity in the rivers of Kerala 14. It is felt that there is inadequacy of appropriate legislation to curb the unethical and unscientific fishing methods such as dynamiting, fish poisions, electrofishing etc. which are very rampant in the rivers and nivulets of Kerala. By totally conceiving this, 231 immediate enactment of Kerala Inland Fisheries Regulation Act (KIFRA) is found indispensable for the conservation of the unique fish germplasm resources of Kerala. l5. The mesh size proposed in the acts and legislation shall be strictly implemented in various gears used for fishing. 16. Government of Kerala shall set up fish hatcheries exclusively for the breeding and propagation of critically endangered and endemic freshwater fishes in suitable locations, where brood stocks are available. l7. Introduction of exotic species should be permitted only after studying its biology, habitat specificity and potential threats to native fish species and enviromnent. l8. It is mandatory to treat the effluents from the factories before its disposal to rivers. 19. The bionomics studies revealed that Rcarnaticus have the potential of a good aquaculture species and also can use as a more effective substitute for grass carp in polyculture operations. 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Length -Weight relationship of Deccan Mahseer-Tor Khudree(Sykes_, l839).In: Singh,S.P., Kapoor,D., Sarkar,U.K. and Basheer,V.S. (eds.),Proceedings of the National Symposium on Life history Traits of Fish Populations for its Utilization in Conservation. National Bureau of Fish Genetic Resources, Lucknow, India.AA7 Manojl Manojkumar,T.G. and Kurup,B.M.,2002. Food and Feeding Habits of Camatic Carp, Barbodes carnaticus(.lerd0n,l849)-An endangered endemic fish of Westem Ghats. In: Singh,S.P., Kapoor,D., Sarkar,U.K. and Basheer,V.S. (eds.), Proceedings of the National Symposium on Life history Traits of Fish Populations for its Utilization in Conservation.National Bureau of Fish Genetic Resources,Lucknow,India.AF7 Manojkumar,T.G. and I(u1up,B.M.,2002.Food and Feeding Habits of the Deccan Mahseer Tor Khudree(Sykes,l839). In: Singh,S.P., Kapoor,D., Sarkar,U.K. and Basheer,V.S. (eds.), Proceedings of the National Symposium on Life history Traits of Fish Populations for its Utilization in Conservation. National Bureau of Fish Genetic Resources, Lucknow, India.AFl Manojkumar,T.G. and Kun1p,B.M.,2005.Relationship between habitat variables and distribution and abundance of four critically endangered and endemic fishes: an investigation of habitat suitability index models, Journal of Fish Biology,U.K.(Communicated) Manojkumar,T.G. and Kuiup,B.M.,2005.Fish diversity vis-a-vis altitude, Journal of Freshwater Ecology ,Denmark( Communicated)QQQ Q QQO QQQQ‘ i Q Q Q QQQQ Q Q Q QQ Q Q QQ Q__QQ Q Q Q [E.Qv:'§latus_Q Q QQ Q Q Q QQQQQ [Y ‘Q Q_fiQ Q _i i ‘,0 F _ J-"""