Lake 2010: Wetlands, Biodiversity and Climate Change

Ecological Characteristics of Benthic Diatom Communities in Assessment of Lake Trophic Status

Alakananda, B1,2. Supriya Guruprasad1. Mahesh M.K2 and Ramachandra T.V1

1 Energy and Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, , 2 Department of Botany, Yuvaraja’s College, Mysore, India

The ecology of benthic diatoms was investigated in 15 lakes which are in the fringe of urbanization impacts. The aim of this study was to examine the community composition and diversity of benthic diatoms in different microhabitats viz. epilithic, episammic and epiphytic. This study also contributed to the understanding of whether environmental factors control the species composition? Water and benthic diatom samples were collected from different habitats and sampling sites during February – May 2009. Results showed that physical and chemical variables of water varied spatially. The water quality of lakes which were contaminated with sewage and/or industrial discharge was influenced by pH, electric conductivity, chemical oxygen demand, and biological oxygen demand and nutrient concentrations. This was also evident by principal component analysis (PCA). The cluster analysis groups the lake sampling sites which are categorized into different water quality classes. Total diatom data consisted of 122 taxa and varied with change in habitat. The dominance of Gomphonema parvulum, Nitzshia umbonata, N. linearis, N. palea conveyed the eutrophic to hypertrophic lake trophic condition. The genus Achnanthidium had a wide range for water quality parameters and was found abundance across all the sites. The high nutrient filled inflow was confirmed by the ecological preferences and tolerance of benthic diatoms to sustain in such pollution. The diatom indices (TDI, GDI, and SPI) are used to classify mesotrophic from eutrophic lakes and thus monitoring strategies including benthic diatoms can also aid in conservation of urban diversity.

INTRODUCTION

Aquatic ecosystem and its ecology have been the major concern during last century owing to rapid urbanization, intensification of agriculture and anthropogenic changes with impacts on the physical, chemical and biological shifts. These changes in any aquatic ecosystem will affect the species uniqueness and ecological characteristics of biotic community composition with loss of biotic integrity. The environment and its habitat are considered as a niche, when it is apt for biotic community composition with precise ecological preferences to inhabit. Thus, the requisite understanding of the biotic ecological

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Lake 2010: Wetlands, Biodiversity and Climate Change characteristics portrays varying environmental conditions, emphasizing for measure of the extent of degradation and restoration of the environment in these habitats. Amongst all the biotic community, benthic diatoms provide a representative group of indicative species, thus the community composition as a whole changes in response to changes in environmental conditions.

Benthic diatoms are ubiquitous and diverse components of aquatic biodiversity in ponds, lakes (Flower 2005), rivers, streams (Taylor et al., 2007b) and so on. Benthic diatoms in particular are patchily distributed and hence extremely vary in community composition at different spatial scales (Pan et al., 1999, Soinien, 2004). Such Heterogeneity in diatom composition at various scales could be due to multiple factors such as light, grazing, chemical variables and habitat availability (Sommer 2000). Thus benthic diatoms are being increasingly established as bioindicators because of their strong response to environmental change and biotic integrity of the ecosystem (Whitton et al., 1991; Potapova and Charles, 2002; Yellop and Kelly, 2006). Several pollution assessment methods developed using benthic diatom community composition and autecological indices aided in evaluating the changes in the diatom assemblages due to sensitivity and tolerance of the species to environmental variables (Sgro et al., 2006). Juttner et al., 2003; Taylor et al., 2007; Soininen & Weckström 2009 studied diatom community and diatom indices in relationships with environmental conditions, biodiversity and to monitor pollution in streams. Many of these indices have been developed and applied in European countries, especially in France, Belgium and Luxemburg (Prygiel & Coste, 1995). The diatom index IBD (Indice Biologique Diatomees; Prygiel & Coste, 1998) has recently been tested in France for routine monitoring. The tropical diatom indices- TDI in South Africa (Taylor et a., 2007b), Pollution sensitivity indices- IPS, Generic diatom indices (Kelly et al., 1998, Brabecz and Szoszkiewicz, 2006), Trophic diatom indices for lakes- TDIL (Stenger-Kovács et al., 2007) and so on have been discussed for water quality in rivers and streams. However, investigations of diatom based monitoring specific to an eco-region and specific for urban lakes are very scare or do not yet exist for Indian lakes. The urban lake represents altered ecosystems and hence research studies are particularly needed for both ecosystem restoration and management.

Bangalore lakes were investigated for the better perceptive of urban lakes and pollution impacts on ecological characteristics of benthic diatoms. Advancement of urbanization in Bangalore has led to decline in the number of lakes due to immense agriculture, encroachment, nutrient inflow (sewage and industrial waste) and so on. In the past study physical and chemical analysis of several lakes such as , , Rachenahalli, Amruthalli, and were monitored and documented while it lack the ecological characteristic investigation of key indicator organisms primarily benthic diatoms. The objective of the current study was to investigate the relationship between diatom composition and the

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Lake 2010: Wetlands, Biodiversity and Climate Change impacts of environmental variables on its ecological characteristics at 15 lakes of Bangalore to comparatively assess the lake trophic status. STUDY AREA

BANGALORE

Figure 1: Map of Bangalore presenting lakes selected for study

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Lake 2010: Wetlands, Biodiversity and Climate Change

Bangalore lies at 77°37’19.54’’ E longitude and 12°59’09.76’’ N latitude with an area of 751 sq. km. Bangalore is located at an altitude of 920 metres above mean sea level, delineating four watersheds: Hebbal, , Challaghatta and Vrishabhavathi watersheds (Sudhira et al., 2007). The city harbors many man-made lakes facilitating the domestic and agricultural needs. Bangalore has grown spatially more than ten times since 1949 (69 square kilometres) and is a part of both the Bangalore urban and rural districts. Lakes of Bangalore occupy about 4.8% of the total geographic area covering both urban and non-urban regions. Among several lakes of Bangalore 15 were selected covering a range of environmental conditions and across sampling sites. The lake names and code are mentioned in Annexure 1.

METHOD

Water quality analysis

Water samples were collected from all possible sampling sites (at least more than 2 sampling sites at each lake) covering the inlets and outlets and also depending on the lake size during February 2009 and February 2010. Samples were stored in polythene bottles and were carried to laboratory for further analysis. Dissolved oxygen was analyzed on site using 125ml BOD bottles. On site parameters viz., pH, water temperature (°C); total dissolved solids (mgL-1); salinity (mgL-1) and electric conductivity (µScm-1) were measured using EXTECH EC500 Probe immediately after collection. Other water chemistry variables like chloride, hardness, magnesium, calcium, sodium, potassium and phosphates were analyzed in laboratory and analyses were carried out as per standard methods for the examination of water quality as mentioned in Trivedy and Goel (1986) and American Public Health Association (APHA, 1998). Diatom sampling

Diatom sampling along with water sampling was carried out and collected in polythene bottles from all available habitats such as plants (epiphytic), stones or boulders (epilithic) and sediments (episammic) following Taylor et al., 2007a and Karthick et al., 2010. Epiphytic diatoms were collected from crushing the submerged stems and leaves in a polythene cover. Epilithic diatoms from stones were brushed slightly with a toothbrush in a tray. The fine 5 mm upper layer of the soil containing diatoms was carefully collected excluding soil particles. All the samples were transferred to 125 sampling bottles separately with labels on it. Live samples were observed immediately after collection and then ethanol was added to preserve it. The diatom samples were processed for cleaning following KMnO4 and Conc HCl method. The cleaned samples were then centrifuged at 2500 rpm and slides were prepared using Pleurax mountant. The cleaning, processing and slide preparation was followed as per Taylor et al., 2007a. At least 400 valves

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were counted in each slide and species were recorded along with its abundance. The individuals were identified using identification guides and literatures of Krammer and lange- Bertalot 1986; 1988, Taylor et al., 2007b and Karthick et al., 2009.

Statistical analysis Statistical analyses comprising Principal Component Analysis (PCA) was performed using PAST 2.04 version software to explain the water quality variation. Detrended correspondence analysis (DCA), a multivariate statistical technique for analyzing ecological data of a community (using PAST 2.04 version) and is used to study the major patterns of community composition and maximum amount of variation in the diatom distribution across lakes.

RESULTS AND DISCUSSION

Water quality analysis The physico chemical analysis of 15 lakes across 39 sampling sites has been listed in table 1. The water chemistry differed across sampling sites. pH, electric conductivity, biological oxygen demand (BOD), chemical oxygen demand (COD) and alkalinity were the parameters showed marked difference among lakes. The pH ranged from 7.25 to 10.30, highest being 10.30 at Mallathally inlet reflecting alkaline pH and exceeding the permissible limit. Water temperature had a wide range, 24.95 to 35.50 (mean=29.72, sd 2.15) which mainly dependent on the time of sampling. Electric conductivity was varying much (mean = 1210.98, sd 1902.39) having low at Hoskere outlet (335 ppm) and high at Anchepalya inlet (9220 ppm) which is beyond the permissible limits. High electric conductivity was mainly due to high ionic concentrations. Dissolved oxygen was below permissible limit (<5 mgL-1) at few inlets like Hoskere, Komghatta, and outlet site of Jakkur. Low dissolved oxygen level reduces the diversity of fish. Nutrients such as nitrates and phosphates varied from 0.01-0.84 ppm and 0.01-0.44 ppm respectively within the permissible limits. The alkalinity ranged from 95 mgL-1 at venkateshpura outlet to 1100.67 at ramsandra (rb). Both COD and BOD values were high at Anchepalya inlet (197 mgL-1, 60 mgL-1) and low at Hoskere outlet (5.33 mgL-1, 1.64 mgL-1) respectively. Among the lake sampling sites, Anchepalya and sites reflected high ionic concentrations while low values within the permissible limit was recorded in Hoskere lake.

PCA analysis PCA indicated significant difference in water chemistry across lakes explaining 49.844 % and 16.744% of the variance from 1st and 2nd axis respectively (Figure 2). PCA bi plot formed 2 groups of highly polluted and moderately or slightly polluted among sampling sites. Sampling sites Jakkur, Hulimavu, Mallathally and thalghattapura were grouped to the right side along the component 1, characterized by

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Lake 2010: Wetlands, Biodiversity and Climate Change higher concentrations of electrical conductivity, total hardness, chlorides, Alkalinity and COD. Ramsandra, hoskere, venkateshpura, konsandra and sompura were grouped along the component 2 with no or minimum influence of water chemistry. Anchepalya, Madiwala and Kothur were grouped separately showed effects of nitrates, phosphates and biological oxygen demand and can be said as highly polluted (table 1).

Diatom analysis The study represents a total of 96 species belonging to 40 genera with wide range of community composition and species distribution across 15 lakes (refer Annexure 1 for list of species and codes used in the study). Among all species (relative abundance >10% of all sites), Achnanthidium Kützing, Cyclotella meneghiniana Kützing ex Brébisson, Aulocoseira granulata (Ehr.) Simonsen, Diadesmis confervaceae Kützing, Gomphonema Ehrenberg and Gomphonema parvulum Kützing var. parvulum f. parvulum, Nitzschia palea (Kützing) W. Smith were the most abundance species occurred. These species were cosmopolitan which is reported from North America (Stevenson and Pan, 1999) Europe (Bella et al., 2007) & Africa (Facca and Sfriso, 2007) and well documented across continents inhabiting moderate to highly polluted lakes. Cyclotella meneghiniana, a pollution tolerant species, was abundant at Jakkur (Ji1, Ji2), Rachenahalli (Ro), Madiwala (Mde, Mdo) lake representing water quality as eutrophic and rich with ionic concentration. Aulocoseira granulata and Gyrosigma accuminatum (Kützing) Rabenhorst were present in thallghattapura (Ti) and venkateshpura (vi) sites respectively. These species prefers eutrophic waters and are tolerant to high organic pollution. Hulimavu inlet comprised of Diadesmis confervaceae whereas Nitzschia palea occupied Hulimavu inlet. Water quality analysis also evidences the ionic status of these lakes. Eolimna subminiscula (Manguin) Lange-Bertalot, Gomphonema parvulum and Nitzschia Hassall with ecological characteristics of highly tolerant to nutrients and ions was abundant at Anchepalya, which is having the highest COD, BOD, EC and ionic concentrations (Table 1). However Hoskere, unlike from rest of the lakes (low ionic level, BOD and COD) was dominated by only Cymbella tumida (Brebisson) Van Heurck and Achnanthidium sp which occurs in slightly to moderate eutrophic waters. This justifies that Hoskere lake is comparatively oligo to slightly mesotrophic with less electrolyte concentrations from former lakes. Achnanthidium sp. has a wide range of ecological preference of occurring in oligotrophic waters with tolerance to mesotrophic conditions. It was noted as abundant group in most of the sites such as rachenahalli (Ri1,Ri2), Komghatta (Kgi1, Kgi2), Mallathally (Mo, Mi), (Uo, Ui), (Ktos, Ktop), Thallghattapura (Ti1, Ti2, To), Sompura (Si, Sost, Sos), Konsandra (Kf, Kis, Ko), ramsandra (rl, ri, rost, rop) and Hoskere (Hist, His, Host). Since the ecology of Achnanthidium sp. is not properly understood, further work on this genus aids in comprehending

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DCA analysis The Detrended Correspondence Analysis (DCA) for diatom data indicated that communities differed clearly between the sampling stations. This plot shows diatom community composition and its relationship with varying environmental variables across sampling sites. The eigen values of the first two axes for diatom DCA analysis were 0.6294 and 0.5665. The first DCA axis summarized the distribution of the diatom communities throughout the conductivity and nutrient gradient, with clustering of the moderately pollutes sites at the bottom of the plot. The Highly polluted sites were clustered on the right side of the axis with dominant tolerant taxa and corresponded to those sites located in densely populated and highly industrialized areas (Anchepalya, Hulimavu, Jakkur and Madiwala). Diatom taxa showing maximum abundance in these samples were C. meneghiniana, D. confervaceae, Eiolimna subminiscula, N.palea and N. umbonanta. Sites on the upper left side of the axis 2 corresponded to communities in oligo to slightly mesotrophic site, Hoskere (located in less populate, remote area) (Figure 3). Diatom taxa abundant in these samples were Cymbella tumida, Achnanthidium sp. and Discotella sp.

CONCLUSION The ecological characteristic of each diatom taxa in occurrence and distribution as community composition was significant at each sampling site. This thoroughly corresponded with those observed in other geographical areas. The relevance of water quality variation among the sampling sites was expressed in PCA gradient. The highly polluted lakes were markedly separated from rest of the data. The site specific indicator taxa either as a community or a single species were relevant to classify sites based on its ecological preference (DCA plot). Anchepalya, Madiwala, Hulimavu and Jakkur lakes were grouped as hyper or eutrophic lakes while oligo to mesotrophic status was characterized by the different indicative diatom community of Hoskere lake. Benthic diatom assemblages are controlled by multiple factors reflecting land use and site-specific conditions at various temporal and spatial scales (DeNicola et al. 2004, Pan et al. 2004). This study provides reason for difference in community composition as the site specific ecological characteristics, thus the sensitivity and tolerance level of each species occurs at a particular site. Further the development and implementation of diatom indices using the ecological preferences, specific to urban context elaborates need of long term monitoring the water quality, restoration and management of urban lakes.

REFERENCES 1. APHA, 1998. Standard Methods for the Examination of Water and Wastewater. American Public Health Assoc., (American Waterworks Assoc., Water Pollution Control Federation), Washington, DC.

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2. Bella, V.D. Puccinelli, C. Marcheggiani, S and Mancini, L. 2007. Benthic diatom communities and their relationship to water chemistry in wetlands of central Italy. Ann. Limnol. - Int. J. Lim. 43(2): 89- 99. 3. Brabecz, K. and Szoszkiewicz, K. 2006. Macrophytes and diatoms – major results and conclusions from the STAR project. Hydrobiologia 566: 175–178.DeNicola, D.M. Eyto, E.D. Wemaere, A and Irvine, K. 2004. Using epilithic algal communities to assess trophic status in Irish lakes. J. Phycol. 40: 481-495. 4. Eloranta, P and Soininen, J. 2002. Ecological status of some Finnish rivers evaluated using benthic diatom communities. Journal of Applied Phycology. 14: 1–7. 5. Facca, C and Sfriso, A. 2007. Epipelic diatom spatial and temporal distribution and relationship with the main environmental parameters in coastal waters, Estuarine, Coastal and Shelf Science. 75: 35–49 6. Flower, R. 2005. A taxonomic and ecological study of diatoms from freshwater habitats in the Falkland Islands, South Atlantic. Diatom Res 20:23–96. 7. Jüttner, I. Sharma, S. Dahal, B.M. Ormerod, S.J. Chimonidex, P.J and Cox, E.J. 2003. Diatoms as indicators of stream quality in the Kathmandu Valley and Middle Hills of Nepal and India. Freshwater Biol. 48: 2065-2084. 8. Karthick, B. Alakananda, B and Ramachandra, T. V. 2009. Diatom Based Pollution Monitoring in Urban Wetlands of Coimbatore, Tamil Nadu. ENVIS Technical Report: 31. Environmental information System, Centre for Ecological Sciences, Indian Institute of Science, Bangalore. 9. Karthick, B. Taylor, J.C. Mahesh, M. K and Ramachandra, T. V. 2010. Protocols for collection, Preservation and Enumeration of Diatoms from Aquatic Habitats for Water Quality Monitoring in India. The IUP Journal of Soil and Water Sciences, 3(1): 25-60. 10. Kelly, M. G. and Whitton, B. A. (1998). Biological monitoring of eutrophication in rivers. Hydrobiol., 384: 55-67. 11. Krammer, K and Lange-Bertalot, H. 1986-1991. Bacillariophyceae. In: Süßwasserflora von Mitteleuropa, Band 2, (eds Ettl, H., Gerloff, J., Heynig, H. and Mollenhauer, D.). Spektrum Akademischer Verlag, Heidelberg, Berlin, 1–4. 12. Pan, Y. Stevenson, R.J. Hill, B.H. Kaufmann, P.R and Herlihy, A. T. 1999. Spatial patterns and ecological determinants of benthic algal assemblages in Mid-Atlantic streams, USA. J. Phycol. 35: 460–468. 13. Pan, Y. Herlihy, A. Kaufmann, M. Wigington, J. van Sickle, J and Moser, T. 2004. Linkages among land-use, water quality, physical habitat conditions and lotic diatom assemblages: a multi-spatial scale assessment. Hydrobiologia. 515: 59-73.

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14. Potapova, M. and Charles, D. 2002. Benthic diatoms in USA rivers: distributions along spatial and environmental gradients. J. Biogeogr. 29: 67–187. 15. Prygiel, J and Coste, M. 1993. The assessment of water quality in the Artois-Picardie water basin (France) by the use of diatom indices. Hydrobiol. 269/270: 343–349. 16. Prygiel, J and Coste, M. 1999. Progress in the use of diatoms for monitoring rivers in France. In: Use of Algae for Monitoring Rivers III, (eds Prygiel, J., Whitton, B. A. and Bukowska, J.). Douai, Agence de l’Eau Artois-Picardie. 165–179. 17. Sgro, G.V. Ketterer, M.E. and Johansen, J.R. 2006. Ecology and Assessment of the Benthic Diatom Communities of Four Lake Erie Estuaries using Lange-Bertalot Tolerance Values. Hydrobiologia. 561(1). 239-249. 18. Soininen, J. 2004. Benthic Diatom Community Structure in Boreal Streams; Distribution Patterns along Environmental and Spatial Gradients. Academic Dissertation in Limnology, University of Helsinki, Finland. 19. Sommer, U. 2000. Benthic microalgal diversity enhanced by spatial heterogeneity of grazing. Oecologia. 122: 284-287. 20. Stenger-Kovács, C.S. Buczkó, K. Hajnal, E and Padisák, J. 2007. Epiphytic, littoral diatoms as bioindicators of shallow lake trophic status: Trophic Diatom Index for Lakes (TDIL) developed in Hungary. Hydrobiologia 589:141–154 21. Stevenson, R. and Pan, Y. 1999. Assessing environmental conditions in rivers and streams with diatoms. In: The Diatoms: Applications for the Environmental and Earth Sciences. Cambridge University Press, Cambridge, (eds Stoermer, E. F. and Smol, J. P.). 11-40. 22. Sudhira, H. S. Ramachandra, T. V and Bala Subrahmanya, M. H. 2007. City Profile Bangalore, Cities, 24(5): 379–390. 23. Taylor, J. C. Archibald, C. G. M and Harding, W. R. 2007a. A Methods Manual for the Collection, Preparation and Analysis of Diatom Samples. WRC Report No TT 281/07. Water Research Commission, Pretoria. South Africa. 24. Taylor, J. C. Prygiel, J. Vosloo, A. de la Rey, P. A and van Rensburg, L 2007b. Can diatom-based pollution indices be used for biomonitoring in South Africa? A case study of the Crocodile West and Marico water management area. Hydrobiol. 592: 455–464. 25. Trivedy, R. K and Goel, P. K. 1986. Chemical and Biological Methods for Water Pollution Studies, (Environmental Publications), Karad, 1-29. 26. Whitton, B.A.E. Rott and Friedrich, G. (eds.) 1991. Use of algae for monitoring rivers. Institüt für Botanik, Universität Innsbruck, Innsbruck.

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Table 1: List of water quality variables of 15 lakes of Bangalore

pH WT EC TDS DO BOD COD N P TH CaH MgH CHL ALK Ji1 8.02 27.80 1240.33 870.67 4.67 14.20 79.31 0.016 0.026 326.67 93.33 56.93 286.84 163.33 Ji2 8.07 28.77 1325.67 947.00 6.91 13.60 48.72 0.015 0.030 346.67 100.00 60.19 295.36 163.33 Jo 7.89 28.60 1236.33 869.33 4.76 8.20 65.08 0.016 0.027 325.33 85.33 58.56 267.91 160.00 Ri1 9.22 30.33 871.33 625.00 6.12 2.90 11.71 0.018 0.026 221.33 84.67 33.35 195.96 126.67 Ri2 9.10 30.07 885.67 620.00 7.75 4.05 77.55 0.018 0.023 221.33 72.67 36.27 191.23 120.00 Ro 9.05 31.33 854.33 609.33 7.32 3.22 35.91 0.020 0.023 222.67 80.00 34.81 208.27 120.00 Vi 8.54 28.15 342.00 239.00 8.13 3.11 26.88 0.020 0.022 122.00 63.33 14.31 45.44 100.00 Vo 8.21 24.95 361.50 247.50 6.18 5.22 83.45 0.020 0.027 152.00 56.00 23.42 44.02 95.00 Kgi1 9.32 28.05 812.00 594.00 5.98 2.96 24.00 0.049 0.038 264.00 24.05 58.55 121.41 276.00 Kgi2 9.01 29.05 782.00 558.00 4.55 5.30 84.00 0.056 0.020 298.00 15.23 69.00 109.48 248.00 Kgo 8.98 28.70 764.50 548.50 6.14 3.71 48.00 0.066 0.022 286.00 32.87 61.76 119.42 170.00 Mi 10.30 26.65 1160.00 807.00 9.39 25.80 110.00 0.072 0.064 278.00 32.87 59.81 214.42 252.00 Mo 9.28 31.45 1105.00 803.00 7.44 18.00 69.00 0.062 0.046 302.00 24.05 67.82 106.50 301.00 Ui 8.80 28.75 747.50 514.00 7.03 6.50 106.00 0.092 0.037 298.00 23.25 67.04 80.94 315.00 Uo 8.97 26.05 587.00 416.50 6.59 4.91 82.00 0.078 0.041 224.00 20.04 49.77 80.94 210.00 Ti1 8.98 30.10 779.00 536.00 11.54 14.35 70.00 0.048 0.045 178.00 36.87 34.43 185.31 252.00 Ti2 8.92 29.20 788.50 548.00 11.18 13.26 34.00 0.058 0.054 190.00 29.66 39.12 187.44 293.00 To 8.45 29.55 790.50 670.00 5.61 2.67 30.00 0.043 0.049 180.00 36.87 34.92 184.60 163.00 Si 8.77 29.47 1020.67 708.67 6.69 2.88 36.00 0.078 0.044 112.67 31.00 19.93 120.70 265.33 So 8.72 30.20 1024.67 709.67 6.29 2.31 26.67 0.075 0.046 109.33 33.67 18.46 82.36 286.67 Kti 9.13 30.05 681.00 472.00 6.91 20.58 31.00 0.068 0.056 82.50 25.05 14.02 142.00 194.00 Kto 9.12 29.15 653.00 467.00 7.56 23.50 12.00 0.079 0.056 67.50 23.05 10.85 139.16 192.00 Kf 8.80 33.43 792.00 551.33 6.37 2.63 38.67 0.067 0.015 88.67 22.98 16.03 69.20 406.00 Kl 8.80 31.47 718.00 548.00 6.41 2.35 30.67 0.067 0.006 86.00 22.98 15.38 57.46 334.67 Ki 8.97 32.43 766.00 537.67 7.28 13.44 49.33 0.058 0.005 80.00 23.99 13.67 41.75 327.33 Ko 8.69 31.67 825.67 582.00 6.11 13.75 26.67 0.070 0.007 85.33 24.90 14.74 71.95 398.00 ri 8.85 31.00 490.00 343.00 6.67 2.88 44.89 0.051 0.001 113.33 30.73 20.16 59.92 1088.67 ra 8.96 31.10 466.00 369.33 6.05 1.92 19.11 0.067 0.004 129.33 33.13 23.47 61.53 788.67 ro 8.60 31.10 496.00 356.00 7.06 3.33 58.67 0.039 0.020 164.00 41.28 29.94 100.82 744.00 rl 8.88 28.97 516.67 357.67 6.21 2.68 36.44 0.047 0.014 112.67 34.20 19.15 65.13 974.00 rb 8.86 30.07 503.33 353.67 6.37 4.59 17.79 0.027 0.006 107.33 33.67 17.97 64.94 1100.67 Ai 8.70 33.60 9220.00 6500.00 10.60 60.00 197.00 0.438 0.375 632.00 531.92 129.79 451.56 580.00 Ao 8.73 35.50 9210.00 6410.00 10.38 58.00 160.87 0.511 0.438 400.00 307.93 75.13 508.36 520.00 Hi 7.25 30.00 401.00 260.00 7.50 3.32 10.67 0.246 0.004 116.00 79.97 19.51 42.60 180.00 Ho 7.58 30.50 335.00 233.00 8.20 1.64 5.33 0.842 0.083 96.00 55.97 13.66 45.44 180.00 Mde 8.41 27.50 775.00 538.00 8.37 20.64 100.67 0.585 0.023 201.20 131.54 32.10 130.64 246.00 Mdo 8.35 25.30 759.00 532.00 8.13 14.66 53.33 0.486 0.120 194.00 102.73 25.07 143.42 240.00 Hui 8.23 28.70 1070.00 759.00 2.39 24.70 58.67 0.05 0.17 232 123.91 30.23 232.88 520

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Huo 8.53 30.20 1072.00 753.00 7.2 20.93 80.00 0.01 0.21 240 91.88 22.42 261.28 380

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Figure 2: Bi-plot of Principal component analysis for variation in water chemistry across lakes

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Figure 3: Detrended correspondence analysis for species distribution across lakes

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Annexure 1

List of sampling sites and code names

Jakkur Ji1 Ullalu Ui Ramasandra ri Jakkur Ji2 Ullalu Uo Ramasandra ra Jakkur Jo Thalghattapura Ti1 Ramasandra ro Rachenahalli Ri1 Thalghattapura Ti2 Ramasandra rl Rachenahalli Ri2 Thalghattapura To Ramasandra rb Rachenahalli Ro Somapura Si Anchepalya Ai Venkateshpura Vi Somapura So Anchepalya Ao Venkateshpura Vo Kothnur Kti Hoskere Hi Kommaghatta Kgi1 Kothnur Kto Hoskere Ho Kommaghatta Kgi2 Konasandra Kf Madiwala Mde Kommaghatta Kgo Konasandra Kl Madiwala Mdo Mallathally Mi Konasandra Ki Hulimavu Hi Mallathally Mo Konasandra Ko Hulimavu Ho

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Lake 2010: Wetlands, Biodiversity and Climate Change

List of species and code names

Achnanthidium exiguum AEHE Eunotia sp. EUNO Navicula viridula NVIR Amphora coffeaeformis ACAC Fragilaria biceps FBCP Nitzschia capitellata NCPL Amphora copulata ACOP Fallacia pygmea FPYG Navicula cryptotenella NCTE Achnanthidium eutrophilus AEUT Fragilaria tenera FTEN Navicula sp. NAVI Aulocoseira granulata AGCU Fragilaria ulna FUAC Navicula rostrata NROS Anomeoneis sphaerophora ASAN Fragilaria ulna v. acus FAUT Nedium productum NEPR Amphora veneta AVCA Fragilaria sp. FRAG Nitzschia intermedia NINT Achnanthidium sp. ACHD Gomphonema affine GAFF Nitzschia obtuse NOBT Brachysira Wygaschii BWYG Gomphonema gracile GGRA Nitzschia umbonata NUMB Brachysira sp. BRAC Gomphonema parvulum FPAR NItzschia sp. NITZ Craticula Accomodiformis CRAC Gomphonema pseudoaugur GPSA Pinnularia acrospheria PACR Craticula aequatorialis CRAE Gyrosigma accuminatum GRAU Pinnularia borealis PBOR Cyclotella meneghiniana CMEN Gomphonema spp. GOMP Pleurosigma elongatum PELO Cocconeis placentula CPLA Hantzschia amphioxys v. gracilis HAMP Planothidium frequentissimum PLER Cymbella tumida CTUM Lemnicola hungarica LHUN Pinnularia sp. PINU Craticula vixnegligenda CVIX Mastagloia smithii MSMI Placoneis sp. PLAC Caloneis sp. CALO Mastogloia elliptica MELL Pleurosigma sp. PLSG Craticula sp. CRAT Nitzschia amphibia NAAC Rophalodia gibba RGIB Cymbella cymbiformis CCYM Navicula antonii NANT Surirella angusta SANG Cymbella sp. CYMB NitzschIia clausii NCLA Surirella brebissonii SBKU Diadesmis confervaceae DCOF Nitzschia etoshensis NETO Sellaphora laevissima SELA Diploneis subovalis DSUB Nitzschia frustulum NFTU Surirella ovalis SOVI Diploneis oblongella DOBL Navicula gracilis NGLS Sellaphora pupula SPUP Discotella sp. DISC Navicula gregaria NGRE1 Sellaphora stroemii SSTM Epithemia sorex ESOR Nitzschia lancettula NLTL Seminavis sp. SMNA Eolimna sumbmiscula ESBM Nitzschia palea NPAL Staphanodiscus hantzschii SHAN Encyonema mesianum ENME Nizschia pura NIPR Staphanodiscus sp. STEP Encyonopsis sp. ENCP Nitzschia reversa NREV Surirella sp. SURI Eolinma sp. EOLI Nitzschia subacicularis NSUA Tabularia TABU Eunotia minor EMIN Navicula symmetrica NSYM Thalosiosira THAL Tryblionella TRYB

22nd-24th December 2010 Page 15