Fish community structure in accordance with environmental signatures in tropical river ecosystem, Eastern Himalayan eco-region

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This study examined the relationship between fish community structure and ecological characteristics in the Dhansiri River, a tropical river within the Eastern Himalaya eco-region. Sampling was conducted across three seasons (monsoon, pre-monsoon and post-monsoon) at four stations representative of the whole river stretch. Highest number of species was recorded along upper stretch S1 (54), followed by S2 (45), S3 (41) and least in S4 (37). Seasonally, the number of species peaked during monsoon (64), decreased in post-monsoon (59) and was lowest in pre-monsoon (54). Shannon diversity index (H') ranged from 3.327 to 3.750, with higher values upstream and gradually declining downstream. Species diversity was lowest at S4, likely due to poor environmental conditions and high anthropogenic pressure. Cyprinids emerged as the most dominant fish group, with relative family abundance varying from 0-5.63%. Non-metric dimensional scaling indicated a distinct separation of S4 from S1, S2 and S3. Analysis of water quality revealed a pristine nature at S1, with gradual deterioration downstream. Significant relationships were identified between most water quality variables and fish community structure. Principal component analysis showed that pH (20.96%), total alkalinity (13.80%), specific conductivity (9.92%), NO 2 (12.19%), and TDS (6.22%) contributed significantly to Dim1, while NO 3 (53.43%) and water temperature (6.05%) influenced Dim2. BIO-ENV analysis reflected that NH 3 , NO 3 , CO 2 , TDS, total alkalinity, pH, specific conductivity, DO and water temperature significantly correlated with fish abundance and community composition. This study provides critical insights into the role of environmental parameters in shaping the fish community structure in a less-explored tropical river of the Eastern Himalayan and offers valuable information for the sustainable management of riverine fish diversity. Fish assemblage Ecology Spatio-temporal diversity Himalayan River Sustainable fisheries Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Tropical rivers are among the most diverse and dynamic ecosystems on Earth, serving as very important habitats for both local and global biodiversity (Dudgeon 2000 ). These ecosystems are very important due to their role in supporting an extensive range of species, many of which are endemic and play critical roles in maintaining ecological stability (Vörösmarty et al. 2010 ). They also provided essential ecosystem services, including riverine fisheries, which serve as a source of food and income for millions of individuals worldwide. Fish community structure refers to composition, abundance, diversity, and interactions among fish species within a particular aquatic ecosystem. They provide key insights into the health and functioning of tropical biodiversity hotspots, such as the rivers of the Eastern Himalaya region. Fish occupy central roles in aquatic food webs as primary consumers, predators and prey, thereby driving energy flow within these ecosystems (Allan and Castillo 2007; Kumari 2024). However, despite their ecological importance, tropical rivers face increasing natural and anthropogenic pressures, jeopardizing their health and the services they provide. The composition and structure of fish communities are highly sensitive to a wide range of environmental variables, including changes in water temperature, hydrological regimes, water quality, nutrient concentrations, habitat structure and land-use pattern (Reid et al. 2019 ). Climate change, habitat alteration, introduction of non-native species, pollution, and rising human activities are contributing to the rapid degradation of tropical rivers, threatening the balance of their aquatic communities (Dudgeon et al. 2006 ). The combined effects of these factors are severely threatening the biodiversity and ecological balance of tropical rivers, putting both the ecosystems and the human populations that depend on them at risk. Of particular concern is the impact of climate change, which alters water temperatures and hydrological patterns, disrupting the natural balance of these ecosystems. Temperature plays a critical role in regulating fish physiology, affecting metabolism, reproduction, and migration, which can lead to shifts in community structure (Comte et al. 2013 ). Adequate dissolved oxygen (DO) is essential for sustaining metabolic activities, and oxygen depletion significantly stresses fish, impacting growth and survival. Most fish thrive within a pH range of 6.5 to 8.5, with deviations causing stress, impaired gill function, and increased toxicity of compounds like ammonia (Moyle and Light 1996 ). Stable alkalinity supports these conditions by buffering against sudden pH changes (Palmer et al. 2008 ). Nutrient concentrations such as nitrite, nitrate, and ammonia influence water quality, and excessive nutrients from agricultural runoff lead to eutrophication, depleting oxygen and causing harmful algal blooms. Elevated carbon dioxide (CO₂) from organic decomposition and pollution reduces oxygen availability, increasing fish stress (Rahel and Olden, 2008 ). Environmental parameters like specific conductivity and total dissolved solids (TDS) reflect pollution levels, affecting fish osmoregulation and reducing biodiversity in sensitive species (Dudgeon et al. 2006 ). Additionally, reduced transparency from sedimentation or algal blooms decreases primary productivity and disrupts visual predators, while limited depth affects habitat availability for certain species (Reid et al. 2019 ). The introduction of non-native species, either through human activity or as a result of changing environmental conditions, poses another significant threat to the integrity of tropical river ecosystems (Palmer et al. 2008 ). These invasive species often outcompete native species for resources, leading to declines in biodiversity and alterations in ecosystem function (Dudgeon et al. 2006 ). Therefore, monitoring and assessing fish community structures provide valuable information for fisheries management, conservation efforts, and ecosystem health assessments. The structure of fish communities is a reliable indicator of environmental stress (Barrella and Petrere 2003 ), and specific community compositions can reflect the degree of habitat degradation (Wichert and Rapport 1998 ). Environmental and anthropogenic factors (Mondal and Bhat 2020 ), biotic factors (Robinson and Tonn 1989 ), abiotic factors (Debnath et al. 2022 ), trophic interactions and life-history traits have significantly influenced fish and other biotic community structures in aquatic systems worldwide. Anthropogenic influences have altered water flow and habitat quality for many freshwater fish species, considerably contributing to decline in freshwater biodiversity (Wilkinson et al. 2018 ; Zeng et al. 2022 ). Northeast India covers an ecologically diverse region, encompassing the seven states of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura. This region is located within Eastern Himalayan biodiversity hotspot and shares borders with Bhutan, Myanmar, and Bangladesh. Its unique geographical location, combined with varied topography, has resulted in creation of numerous distinct ecosystems. Rivers and water bodies in Northeast India are crucial components of its biodiversity. The mighty Brahmaputra River and its tributaries, including the Dhansiri River, play a vital role in supporting aquatic life, such as endangered Ganges river dolphin, freshwater turtles and numerous fish species. The Dhansiri River, a significant waterway of the Brahmaputra basin, flows through Nagaland and Assam. It originates from Laisong Peak in Wokha district of Nagaland and traverses various regions before joining Brahmaputra at Golaghat district, Assam. Its diverse habitats provide favourable conditions for numerous fish species to thrive. The Nagaland Pollution Control Board (NPCB) has designated lower stretch of the Dhansiri (near Dimapur town) as highly polluted and categorized it under Priority I due to high BOD levels (30 mg/l) (Anon 2019 ). This part of the river has been severely stressed by immense anthropogenic pressures in recent years due to domestic and municipal sewage dumping. Dhansiri is one of many rivers in the biodiversity hotspot of North East India that has yet to receive much scientific attention regarding its fish diversity and ecology. Previously, several studies have been conducted on the Dhansiri River, mostly focusing on land use, land cover changes and geomorphological aspects, such as channel sinuosity, erosion and sediment dynamics using remote sensing and geographical information system (GIS) techniques (Kotoky et al. 2012; Mili and Acharjee 2014 ; Barman and Goswami 2015). However, research on the fish community has been limited. Acharjee et al. ( 2012 ) reported 34 species under 5 orders, 25 families and 24 genera from the Dimapur stretch of Dhansiri River. A study by Daimari ( 2020 ) identified 15 fish species from the river, representing 4 orders and 8 families. These studies primarily focused on species composition and abundance, lacking a comprehensive understanding of how environmental factors influence fish communities. Understanding fish assemblage structure in relation to environmental variables in rivers remains a challenge due to limited knowledge on the subject (Mondal and Bhat 2020 ). This study aims to investigate how specific environmental factors influence fish community structures in the Eastern Himalayan tropical river ecosystem, seeking to identify patterns in species distribution and biodiversity linked to distinct environmental signatures. The present study holds significance as it addresses these knowledge gaps, providing valuable insights into ecosystem functioning and conservation needs, which will aid in the sustainable riverine fisheries management. Additionally, the research helps address the impacts of climate change on fish communities, providing valuable insights for adaptation strategies. The study also contributes to protecting endangered species, ensuring their survival amid growing environmental challenges. Preserving fish community structure can ensure long-term health and sustainability of our riverine ecosystems in context of changing scenarios and ever-increasing stressors. Materials and methods Study area and sampling station description The study was conducted on the Dhansiri River, one of the largest tributaries of the Brahmaputra. Dhansiri is a perennial river with a total length of 352 km (Long: 25°54’45” N, 93°44’30” E and Lat: 25°91’25” N, 93°74’16” E). It originates from Laishong Peak in the Barail range of Nagaland and flows from south to north before joining Brahmaputra at Dhansirimukh, Assam. Samples were collected during 2020-21 from four designated sampling stations, each representing different stretches of the river. The stations were selected based on their ecological significance and geographic distribution along the river’s course. Intangki National Park (INP) (S1; upper stretch, 25°43'19.5" N and 93°32'35.4" E), is situated within a protected forest area and characterized by minimal anthropogenic disturbance. Mangalmukh (S2; middle stretch, 25°43'19.3" N and 93°32'35.7" E), is characterized by a mixed forested landscape with moderate human activities. Doyapur (S3; middle stretch, 25°46'9.4" N and 93°35'54.3" E), lies further downstream with increasing agricultural and human activities. Domukhia (S4; lower stretch, 25°57'26" N and 93°46'10" E), is influenced by urbanization and agricultural runoff (Fig. 1 ). Samples were collected across three distinct seasons viz. , post-monsoon (POM), pre-monsoon (PRM) and monsoon (MON) to account for seasonal variations in fish community structure and environmental conditions. Fish diversity Experimental fishing was carried out at each station using various gear types, including gill nets (2 no.; 10 m in length; 1m width; 25 mm and 30 mm mesh size), cast nets (3 no.; 2.4 m length and 3 m width; 10 mm and 20 mm mesh size), scoop nets, hooks and lines, and traditional bamboo traps, to assess fish diversity. Gill nets were set along the current in deeper pools and kept overnight. Other fishing gear was operated during early morning hours for approximately 2–3 hours. Fish samples collected were cleaned, labeled and preserved in 8–10% formalin and transported to laboratory for identification. Identification of fish was done following Talwar and Jhingran ( 1991 ) and Jayaram ( 1999 ). Taxonomic status and systematic position of fishes were cross-verified using the Catalog of Fishes (Fricke et al. 2023 ). Conservation status of fish species was assessed based on the IUCN Red List of Threatened Species (IUCN 2023 ). Environmental parameters A total of 12 environmental variables viz. water temperature (WT), depth, transparency, pH, dissolved oxygen (DO), total dissolved solids (TDS), CO 2 , specific conductivity, total alkalinity (TA), nitrate (NO 3 ), nitrite (NO 2 ) and ammonia (NH 3 ) was systematically measured to assess water quality. Water samples were collected from surface and sub-surface (up to 0.5 m depth), homogenized and immediately transferred to pre-rinsed polyethylene bottles (1 L capacity). WT, pH, DO and specific conductivity were measured in field using a multi-parameter water quality meter ((Model 9829, HANNA, Romania) to ensure immediate and accurate in-situ readings. All the other remaining water quality parameters were analyzed in the laboratory following standard procedures (APHA 2017). Transparency was measured with a Seechi disc, following the method of Strickland and Parsons ( 1972 ). Depth measurements were taken manually to ensure precision. Statistical analysis The assessment of fish community structure and diversity employed a range of indices calculated from species abundance data. These indices included the Shannon-Wiener index (H′), the Margalef richness index (d), Pielou’s evenness index (J’), Simpson’s dominance (λ) and Simpson’s diversity (D) (Table 1 ). All indices were calculated using Primer (Ver. 7.0). Cumulative dominance was also assessed using Primer (Ver. 7.0) (Clarke and Gorley 2015 ). Relative abundance was calculated for each family across seasons and stations in MS Excel, using the following formula: Relative abundance = (Abundance (no.) in each family/Total abundance (no.)) × 100. To analyse species composition patterns, non-metric dimensional scaling (NMDS) was employed. NMDS particularly effective in visualizing community structure by reducing high-dimensional datasets, was applied to explore dissimilarity patterns within the dataset. Conducted in Primer (Ver. 7.0), this ordination technique facilitated the visualization of seasonal and spatial patterns in species distribution along the river gradient (Clarke and Gorley 2015 ). Principal component analysis (PCA), another statistical technique for dimensional reduction and inter-variable data exploration, was conducted in R (Ver. 4.3.0) (R Development Core Team 2019 ). This approach transformed interrelated water quality variables into uncorrelated principal components, aiding in elucidating the key environmental gradients that influences species distribution across the sampling stations. To examine spatial variability in water quality parameters, one-way analysis of variance (ANOVA) was performed, with post-hoc comparisons using Duncan’s multiple range tests to distinguish significant difference among stations, using SPSS (Ver. 23.0) (Das et al. 2022 ). The BIO − ENV (Biota and/or Environment matching) method was executed using the vegan-package in R (R Development Core Team, 2019 ) to identify and quantify the environmental variables most strongly correlated with observed variations in fish community structure. Table 1 Description and formulas used for the calculation of diversity indices Sl no. Diversity indices Significance Formula Description of the formula 1 Shannon diversity index (H′) provides information about community composition H′= i log e P i H′= species diversity in bits of information per individual. n i = proportion of the samples belonging to the i th species 2 Margalef richness index (d) weighs number of species in the community d = (S-1) / log N S = total number of species and N = total number of individuals in the collection. 3 Pielou’s evenness index (J’) refers to the degree of species abundance in an ecosystem. J′ = H'/ln(S) H' is Shannon Weiner diversity and S is the total number of species in a sample 4 Simpson dominance index (λ) measure of community diversity D = Σp i 2 p i is the proportion of individuals in the i th species. Results Species composition and diversity This study documented 3399 individual fish, representing 69 species across 20 families and 46 genera from the Dhansiri River. A systematic checklist of fish and their IUCN conservation status are illustrated in Table 2 . The Cyprinidae family was the most diverse group, represented by 22 species, followed by Danionidae (14 species), Sisoridae (6 species), Bagridae (5 species) and Channidae (5 species). Families such as Botiidae and Nemacheilidae were represented by 2 species each, while single species were identified in the families Siluridae, Erethistidae, Schilbeidae, Cobitidae, Gobiidae, Ambassidae, Osphronemidae, Mastacembelidae, Psilorhynchidae, Belonidae, Badidae, Balitoridae and Notopteridae. In terms of abundance, Cabdio morar , Salmostoma acinaces , Pethia ticto , P. conchonius , Puntius chola , Opsarius tileo and Acanthocobitis botia were dominant. Number of species was highest at S1 during monsoon season with 52 species, followed by 47 species in the post-monsoon and 37 species in the pre-monsoon season. At station S2, number of species was highest in the pre-monsoon (40), while both monsoon and post-monsoon recorded 38 species. For station S3, species numbers peaked during monsoon (39), followed by pre-monsoon (37) and post-monsoon (36). Station S4 showed similar trend, with 38 species recorded in the monsoon, 36 species in the pre-monsoon and 33 species in the post-monsoon. Overall, the highest number of species was recorded along the upper stretch of the river at S1 (54), followed by S2 (45), S3 (41 species) and lowest at S4 (37). Seasonal analysis showed that highest number of species was recorded in monsoon (64), followed by post-monsoon (59) and pre-monsoon (54). An assessment of the conservation status of fish species revealed that 57 species (82.61% of total) were classified as Least Concern (LC), 5 species (7.25%) as Near Threatened (NT), 3 species (4.35%) as Vulnerable (VU), 2 species (2.90%) as Data Deficient (DD). Schistura fasciata has not been evaluated and is grouped under Not Evaluated (NE). A single exotic species, Cyprinus carpio was also recorded from the river. Biodiversity indices are depicted in Fig. 2 . Shannon index (H') values ranged from 3.327 at station S4 (post-monsson) to 3.750 at station S1 (monsoon). Along the upper stretch (S1), value of H' peaked in the monsoon period, with slightly lower value observed during post-monsoon (3.664) and pre-monsoon (3.465) periods. In case of station S2 (middle stretch), the highest H' value was noted in pre-monsoon at 3.496, while post-monsoon at 3.431 and monsoon recorded the lowest at 3.385. Similarly, at station S3 (middle stretch), H' values were highest in pre-monsoon (3.414), followed closely by the monsoon (3.409) and post-monsoon (3.391). Along lower stretch (S4), H' reached its maximum during the pre-monsoon (3.427), with a slight decrease in the monsoon (3.361) and lowest in post-monsoon (3.327). The Margalef richness index (d) varied across stations and seasons, with values ranging from 6.544 (S4, post-monsoon) to 9.875 (S1, monsoon). In case of station S1, the richness index (d) was highest in the monsoon, with slightly lower values observed during post-monsoon (8.626) and pre-monsoon (8.624). For the middle stretch at station S2, the richness index reached its maximum in pre-monsoon (8.544), while monsoon values were moderately lower (7.715) and the post-monsoon had the lowest index (7.601). At station S3, monsoon again recorded the highest richness index (7.924), followed closely by pre-monsoon (7.767) and then post-monsoon (7.135). At station S4, lowest value of ‘d’ was observed in post-monsoon, highest during monsoon (7.742) and intermediate in pre-monsoon (7.722). Generally, the value of ‘d’ was found to be higher during monsoon at all stations, except for S2, where highest species richness appeared in the pre-monsoon and the lowest in the post-monsoon. Pielou’s eveness index (J') ranged from 0.924 (S4, monsoon) to 0.9596 (S1, pre-monsoon). The J' values were lower during the monsoon across all stations and higher during pre-monsoon, except for station S3, where it was higher during post-monsoon (0.9463). The mean values of J' were highest at station S1 (0.9535), followed by S4 (0.9440) and lowest at S2 (0.9410). Simpson dominance index (D) ranged from 0.027 (S1, monsoon) to 0.045 (S4, monsoon). Values of D were found to be on the lower side at S1 (0.027–0.037) and increased downstream, with highest values at S4 (0.37–0.45). Values of D were intermediate in middle stretch, ranging from 0.037–0.042 at S2 and from 0.038–0.040 at S3. The cumulative dominance curve ( k -dominance) extracted for different stations showed that fish species dominance in S1, S2 and S3 did not differ significantly. However, station S4 exhibited a significantly different dominance pattern compared to other three stations. A higher curve in the cumulative dominance plot and more quickly the curve reaches 100% value, indicates lower fish species richness. S4 had the lowest species richness, while S1 showed the highest species richness, as evident in the k -dominance plot (Fig. 3 ). Spatio-temporal variation in the relative abundance of different fish families is given in Fig. 4 . Relative abundance of most families was higher at S1 and progressively decreased downstream. The proportion of fish families observed across the stations varied between 0% and 5.63%. Cyprinidae family was the most abundant, with its relative abundance varying between 1.81% (S1, pre-monsoon) and 5.63% (S1, post-monsoon), followed by Danionidae family, with values ranging from 0.87% (S1, pre-monsoon) to 3.02% (S1, post-monsoon). Relative abundance of all other fish families was found to be < 1%, except for Channidae family, which reached 1.27% at S1 during post-monsoon. Cobitidae followed by Botiidae were the least abundant families in terms of number of specimens reported during the study. Non-metric multidimensional scaling reflected that samples from S4 were distinctively separated from those collected at S1, S2 and S3. Further, S1 post-monsoon sample also demonstrated distinct separation from the remaining samples. A stress value of 0.07 portrayed a good ordination pattern for the observed data (Fig. 5 ). Table 2 Systematic checklist of fishes recorded from Dhansiri River along with their IUCN conservation status Family Species Conservation status Site 1 Site 2 Site 3 Site 4 POM PRM MON POM PRM MON POM PRM MON POM PRM MON Notopteridae Notopterus notopterus (Pallas, 1769) LC + - + + + + - + + + - + Cyprinidae Bangana dero (Hamilton, 1822) LC + + + + + + - - - - - - Chagunius chagunio (Hamilton, 1822) LC + + + + + + + + + - - - C. nicholsi (Myers, 1924) LC + + + + + + + + + - - - Cirrhinus reba (Hamilton, 1822) LC - - + - - - - - - - - - C. cirrhosus (Bloch, 1795 ) VU + - + + - + - - - - - - Cyprinus carpio (Linnaeus, 1758) Exotic - - - - - - + + + + + + Hypsibarbus wetmorei (Smith, 1931) LC + - + - - - - - - - - - Labeo dyocheilus (McClelland, 1839) LC + + + + + + + + + + + + L. rohita (Hamilton, 1822) LC - - - + + + + + + + + + L. pangusia (Hamilton, 1822) NT + - + + + + - - - - - - L. gonius (Hamilton, 1822) LC - - - + + + + + + + + + Neolissochilus hexagonolepis (McClelland, 1839) NT + - + + + + + - + - - - Puntius chola (Hamilton, 1822) LC + + + + + + + + + + + + P. sophore (Hamilton, 1822) LC + + + + + + + + + + + + Pethia conchonius (Hamilton, 1822) LC + + + + + + + + + + + + P. ticto (Hamilton, 1822) LC + + + + + + + + + + + + Systomus sarana (Hamilton, 1822) LC + - + - - - - - - - - - Tor tor (Hamilton, 1822) DD + + + - - - + - + - - - Tariqilabeo latius (Hamilton, 1822) LC + + + + + + + + + + + + Garra gotyla (Gray, 1832) LC + + + + + + + + + + + + G. nasuta (McClelland, 1839 ) LC - + + + + + - + + - - - G. rupecula (McClelland, 1839) NT + + + + + + + + + + + + Danionidae Salmostoma acinaces (Valenciennes, 1842) LC + + + + + + + + + + + + S. bacaila (Hamilton, 1822) LC - - + - - + - - - - - - Amblypharyngodon mola (Hamilton, 1822) LC - - - + + + + + + + + + Barilius barila (Hamilton,1822) LC + + + + + + + + + - - - Opsarius bendelisis (Hamilton,1822) LC + + + - - - - - - - - - O. dogarsinghi (Hora, 1921) VU + + + + + - - + + - - - O. tileo (Hamilton,1822) LC + + + + + + + + + + + + O. barna (Hamilton,1822) LC + + + + + + + + + + + + Danio rerio (Hamilton, 1822) LC + + + - - - - - - + + + Cabdio morar (Hamilton, 1822) LC + + + + + + + + + + + + Devario devario (Hamilton, 1822) LC + + + - - - + + + - + + D. aequipinnatus (Hamilton, 1822) LC + - + - - - + + - + + + Esomus danrica (Hamilton, 1822) LC - - - - - - + + + + + + Rasbora rasbora (Hamilton, 1822) LC + - + - - - - - - + + + Psilorhynchidae Psilorhynchus sucatio (Hamilton, 1822) LC + + + + + + - - - - + - Balitoridae Balitora brucei (Gray, 1830) NT + + + - - - - - - - - - Nemacheilidae Acanthocobitis botia (Hamilton, 1822) LC + + + + + + + + + + + + Schistura fasciata (McClelland,1838) NE + + + - - - - - - - - - Cobitidae Canthophrys gongota (Hamilton, 1822) LC - - - - + - - - - - - - Botiidae Botia dario (Hamilton, 1822) LC - - - - - - - - - - - + B. rostrata (Grunther, 1868) VU + - - - - - - - - - - - Bagridae Sperata seenghala (Hamilton,1822) LC - - - - - - - - - + - + Olyra longicaudata (McClelland, 1842) LC - - - - + - - - - - + + Mystus tengara (Hamilton, 1822) LC + + + + + + + + + + + + M. bleekeri (Day, 1877) LC + + + + + + + + + + + + M. dibrugarensis (Chaudhuri, 1913) LC - - - - - - + + + - + + Erethistidae Hara jerdoni (Day, 1870) LC - + + - - - - - - - - - Siluridae Ompok bimaculatus (Bloch, 1797) NT + - + - - - - - - - - - Schilbeidae Clupisoma garua (Hamilton, 1822) LC + - + + - + + - + - - - Sisoridae Bagarius lica (Volz, 1903) LC - - + - - - + - - - - - Gagata cenia (Hamilton, 1822) LC - - + - - - - - - - - - Glyptothorax telchitta (Hamilton, 1822) LC - + + + + - - + + + + + G. trilineatus (Blyth, 1861) LC + + + - - - - - - - - - G. platypogonoides (Bleeker, 1855) LC + + - - - - - - - - - - Sisor rabdophorus (Hamilton, 1822) LC + - - - - - - - - - - - Belonidae Xenentodon cancila (Hamilton, 1822) LC + + + + + + + + + + + + Ambassidae Parambassis baculis (Hamilton, 1822) LC - - - - + - - - - - - - Badidae Badis badis (Hamilton, 1822) LC - - - + + + + + + + + + Gobiidae Glossogobius giuris (Hamilton,1822) LC + + + + + + + + + + + + Channidae Channa barca (Hamilton, 1822 DD - - + - - - - - - - - - C. marulius (Hamilton, 1822) LC + - + - - - - - - - - - C. gachua (Hamilton, 1822) LC - - - + + + - - - + + + C. punctata (Bloch, 1793) LC + + + + + + + + + + + + C. striata (Bloch, 1793) LC + + + + + + + + + + + + Osphronemidae Trichogaster fasciata (Bloch and Schneider, 1801) LC - - - - + + - + + 0 + + Mastacembelidae Mastacembelus armatus (Lacepede, 1800) LC + + + + + + + + + + + + +, Present; -,Absent Environmental parameters Mean values of environmental parameters for the Dhansiri River, Nagaland, across seasons and stations are given in Table 3 . It was observed that water temperature was lower at S1 and increased downstream of river. Maximum value of DO was observed at S1 during post-monsoon (12 mg/l), while minimum value was observed at S4 during monsoon (8 mg/l). Water pH was observed to range from 7-8.5. NH 3 was not detected at S1, S2 and S3, while at S4 it was found to range from 1–3 mg/l. NO 2 and NO 3 were not detected in water samples at S1, while at S2 and S3, nitrate and nitrite respectively were found to range from 0.1–0.2 mg/l and 0.1–0.16 mg/l, and were observed during pre-monsoon and monsoon. Values of CO 2 were found to range from 1.7–3.2 mg/l, with higher values recorded at S4. TA was found to range from 95–160 mg/l, with a higher mean values observed during monsoon season at all stations except for S1, where higher mean value was observed in pre-monsoon. Spatial analysis showed that mean values of TA were reportedly higher at S1 and lowest at S2. TDS was observed to range from 76–125 mg/l, with S1 showing the highest mean values and S4 the lowest. Across seasons, higher mean values of TDS were observed in monsoon at all stations. Specific conductivity was observed to range from 116–174 µS/cm in the Dhansiri River. Higher mean values of specific conductivity were observed at S1 and lowest at S2. Specific conductivity did not show any particular trend across seasons in the river. Table 3 Mean values of physico-chemical parameters of Dhansiri River STATION S 1 S2 S3 S4 SEASON POM PRM MON AVG POM PRM MON AVG POM PRM MON AVG POM PRM MON AVG Temperature (°C) 15.5 ± 0.5 21.75 ± 1.8 28 ± 0.5 21.88 ± 1.92 16.5 ± 0.5 23.25 ± 1.75 28.5 ± 0.5 22.88 ± 1.81 16.5 ± 0.71 23.5 ± 1.7 29.5 ± 0.5 23.25 ± 1.92 16.75 ± 0.3 24.25 ± 1.8 31.2 ± 1.2 24.11 ± 2.1 DO (mg/l) 11.75 ± 0.3 10.75 ± 2.5 9.5 ± 0.5 10.69 ± .34 a 11.5 ± 0.5 10 ± 0.41 8.85 ± 0.15 10.09 ± 0.41 ab 11.65 ± 0.49 9.75 ± 0.25 8.8 ± 0.2 9.99 ± 0.42 ab 11.35 ± 0.4 9.12 ± 0.31 8.15 ± 0.2 9.44 ± 0.47 b pH 7.75 ± 0.25 8.25 ± 0.14 8.25 ± 0.25 8.12 ± 0.13 a 7.5 ± 0.5 7.87 ± 0.13 7.75 ± 0.25 7.75 ± 0.13 ab 7.6 ± 0.14 8.12 ± 0.12 8.25 ± 0.25 8.03 ± 0.12 a 7.1 ± 0.1 7.5 ± 0.2 7.75 ± 0.3 7.46 ± 0.14 b TA (mg/l) 141 ± 1.0 151.25 ± 4.73 147.5 ± 2.5 147.83 ± 2.76 a 120.5 ± 0.5 133.7 ± 8.98 152.5 ± 2.5 135.13 ± 6.01 a 125 ± 7.07 141.2 ± 1.3 142.5 ± 2.5 137.5 ± 2.99 a 102.5 ± 7.5 126.25 ± 3.8 131 ± 1.0 121.5 ± 4.77 b Nitrite (mg/l) ND ND ND 0.0 ND 0.03 ± 0.025 0.15 ± 0.05 0.05 ± 0.03 a ND 0.03 ± 0.02 0.1 ± 0.05 0.04 ± 0.02 a 0.045 ± 0.005 0.16 ± 0.11 0.45 ± 0.05 0.20 ± 0.08 b Nitrate (mg/l) ND ND ND 0.0 ND 0.03 ± 0.025 0.13 ± 0.025 0.04 ± 0.02 a ND 0.03 ± 0.02 0.13 ± 0.03 0.04 ± 0.02 a 4.5 ± 0.5 4.75 ± 0.3 5.5 ± 0.5 4.88 ± 0.23 b Ammonia (mg/l) ND ND ND 0.0 ND ND ND 0.0 ND ND ND 0.0 1.1 ± 0.1 2.25 ± 0.3 2.75 ± 0.3 2.09 ± 0.26 CO 2 (mg/l) 1.85 ± 0.05 2.25 ± 0.16 1.9 ± 0.1 2.06 ± 0.11 a 1.75 ± 0.05 2.58 ± 0.09 2.45 ± 0.1 2.34 ± 0.13 a 2.65 ± 0.21 2.53 ± 0.17 2.05 ± 0.1 2.44 ± 0.12 a 2.25 ± 0.05 2.93 ± 0.15 3.2 ± 0.05 2.81 ± 0.15 b Specific conductivity (uS/cm) 132.5 ± 12.5 160.5 ± 5.12 159 ± 1.0 153.13 ± 5.62 a 131 ± 1.0 129 ± 5.0 119 ± 1.0 127 ± 2.93 b 138.5 ± 30.41 128.7 ± 5.06 117 ± 1.0 128.25 ± 5.51 b 148 ± 12 140 ± 11.53 131 ± 1.0 139.75 ± 6.23 ab TDS (mg/l) 109 ± 4.0 103 ± 3.14 117.5 ± 2.5 108.12 ± 2.82 a 82.5 ± 1.5 88.25 ± 1.18 106 ± 4.0 91.25 ± 3.48 b 88.5 ± 7.8 84.25 ± 3.8 120 ± 5.0 94.25 ± 6.08 ab 86 ± 4.0 94.25 ± 7.02 118 ± 2.0 98.12 ± 5.63 ab Transparency (cm) 27.5 ± 2.5 20.75 ± 1.49 19.5 ± 0.5 22.13 ± 1.46 a 35.5 ± 1.0 28 ± 1.78 23.5 ± 1.5 28.75 ± 1.84 b 36 ± 1.41 31.75 ± 2.36 25.5 ± 0.5 31.25 ± 1.80 b 33 ± 1.0 30 ± 2.04 25.5 ± 0.5 29.63 ± 1.4 b Depth (ft) 2.75 ± 0.3 3.5 ± 0.35 5.25 ± 0.25 3.75 ± 0.39 1.5 ± 0.5 2.25 ± 0.52 4.75 ± 0.3 2.69 ± 0.53 1.75 ± 0.0.36 2 ± 0.54 5.3 ± 0.25 2.75 ± 0.61 2.9 ± 0.1 3.25 ± 0.48 5.75 ± 0.3 3.78 ± 0.49 Values with different superscript are significantly different (p < 0.05); ND = Not detected PCA plot of water quality parameters is shown in Fig. 6 . The first principal component (Dim1), with an eigenvalue of 5.29 explains 44.13% of total variation. The second principal component (Dim2), with an eigenvalue of 3.86 explains an additional 32.23% of the variation. First principal component (Dim1) is mainly influenced by variables, such as pH (20.96%), total alkalinity (13.80%), specific conductivity (9.92%), NO 2 (12.19%), and TDS (6.22%). These variables contribute significantly to the observed variation in Dim1. On the other hand, second principal component (Dim2) is primarily influenced by NO 3 (53.43%) and water temperature (6.05%). Influence of environmental parameters on fish community structure The BIO-ENV analysis indicated significant correlations between fish abundance and composition and environmental variables, including NH 3 , NO 3 , CO 2 , TDS, TA, pH, specific conductivity (Sp. Con.), DO and WT. The strongest correlation ( ρ = 0.6203) was observed with the combination of NO 3 , CO 2 , TDS. This was followed by the combination of pH, NO 3 , NH 3 , CO 2 , Sp. Con. and TDS ( ρ = 0.6134) and by the combination of pH, NO 3 , CO 2 , Sp. Con., TDS ( ρ = 0.6073). Details of correlation of environmental parameters with fish abundance are given in Table 4 . Table 4 BIO-ENV analysis of fish assemblage compared with environmental variables (pooled data) No. of variables Correlation selection Spearman correlation ( p < 0.01) 1 NH 3 0.5093 2 NO 3 , CO 2 0.5711 3 NO 3 , CO 2 , TDS 0.6203 4 TA,NO 3 , CO 2 ,TDS 0.6066 5 pH,NO 3 , CO 2 , Sp. Con., TDS 0.6073 6 pH,NO 3 , NH 3 ,CO 2 , Sp. Con., TDS 0.6134 7 pH,TA,NO 3 , NH 3 ,CO 2 , Sp. Con., TDS 0.6031 8 DO, pH,TA,NO 3 , NH 3 ,CO 2 , Sp. Con., TDS 0.5964 9 WT, DO, pH, TA,NO 3 , NH 3 ,CO 2 , Sp. Con., TDS 0.5441 10 WT,DO, pH, TA,NO 3 , NH 3 ,CO 2 , Sp. Con., TDS, Depth 0.4910 11 WT,DO, pH, TA,NO 3 , NH 3 ,CO 2 , Sp. Con., TDS, Trans, Depth 0.4360 12 WT,DO, pH, TA,NO 2 , NO 3 , NH 3 ,CO 2 , Sp. Con., TDS, Trans, Depth 0.3739 Discussion The present study investigated alterations in the structure, diversity and richness of fish species communities during three different seasons, while also comparing physico-chemical characteristics of the Dhansiri River, one of the largest tributaries of Brahmaputra. Spatio-temporal changes in environmental factors are key determinants of freshwater fish assemblages, influencing habitat structure and species composition (Fischer and Paukert 2008; Elías et al. 2020). This study offers valuable insights into ecological shifts within the river, enhancing the understanding of the intricate interrelationships between fish populations and their habitat. The Dhansiri River is characterized by high DO levels, high total alkalinity and an alkaline pH, which are comparable to other hilly rivers in the region (Gurumayum et al. 2014; Sarmah et al. 2020; Lkr et al. 2020). Spatial analysis of water quality parameters revealed that the upper stretch (S1) reflects a relatively pristine habitat with minimal human impact. On the contrary, a slight deterioration in water quality was noticed downstream, with comparatively poorest condition at S4 near Dimapur town. This stretch of the river is characterized by low DO levels, high CO 2 and presence of NH 3 , NO 2 and NO 3 . Stretch of the Dhansiri near Dimapur town has been listed as polluted and placed under Priority I category due to high BOD load (Anon 2019). Poor downstream environment quality may be attributed to increased human habitation, high anthropogenic discharge, agricultural runoff and changes in land use patterns (Premke et al. 2020; Ji et al. 2021). Pristine nature of water at S1 may be explained by its location within INP, where human interference is restricted. Distinct seasonal changes in current patterns, discharge rates, and temperature bring about unique alterations in the physico-chemical properties of riverine ecosystems (Pradhan et al. 2009). These seasonal changes affect the distribution of nutrients and dissolved gases, which in turn influence biological productivity and the species composition of the river. PCA analysis indicated the importance of water chemistry, such as pH and total alkalinity in determining primary axis of water quality variation (Saalidong et al. 2022). The dominance of these parameters suggests that river’s buffering capacity and its ability to neutralize acidic inputs are critical to maintaining its ecological balance. Additionally, the significant presence of NO 2 , NO 3 and TDS as influential contributors highlights the role of nitrogen compounds (Vorobyeva et al. 2021) and dissolved solids in shaping water quality profile and its biological productivity. Excess nitrogen in aquatic ecosystems can lead to eutrophication, which disrupts aquatic food webs and reduce biodiversity (Dodds and Smith 2016). Furthermore, water temperature also emerged as a critical abiotic factor influencing Dim2. Relatively smaller contributions of other variables to Dim2 indicate their secondary importance in explaining water quality variation. The study revealed a total of 69 fish species, distributed across 20 families and 46 genera, indicating significant diversity of freshwater fishes comparable to other major river systems in India (Sarkar et al. 2010; Shukla and Bhat 2017). Highest number of species was recorded along the upper stretch of river at S1 (54), while the least was observed along the lower stretch at S4 (37). The upper stretch (S1) is located within the Intangki National Park, an authorized biodiversity conservation area. This site is restricted from anthropogenic interference and features a pristine ecosystem with high diversity, contributing to the observed richness and diversity of fish species. Conversely, the lower stretch (S4) near Dimapur town showed significant declines in fish diversity. This decline can be attributed to the deterioration of environmental variables, as recorded in the study (Table 3), along with the decline in structural habitat complexity, and the increased human habitation and activities observed during downstream sampling. Poor environmental parameters (lower DO, higher NH₃ and higher CO₂) (Anon 2019) along with increased anthropogenic pressure (e.g. pollution, over exploitation etc.) may have negatively impacted fish species richness, diversity, distribution and relative abundance. These findings are consistent with previous studies showing that degraded water quality and habitat deterioration adversely affect freshwater fish populations (Anon 2019; Dudgeon et al. 2006). Typically, in riverine systems species richness, diversity, and abundance increase from upper to lower stretches due to broad range of habitats and resources available (Weber and Peter 2007). However, the Dhansiri River exhibited an opposite trend, with species numbers declining from upstream to downstream. The observed spatial variation in diversity, number, and distribution of fish species is attributed to several factors, including natural topography, environmental influencers (Hashemi et al. 2015), pollution (Anon 2019), habitat complexity (Smokorowski and Pratt 2007), reduced water quality and increased anthropogenic pressures, which limit the suitability of downstream habitats for diverse fish communities (Table. 3) (Lakra et al. 2010; Pandey and Radhakrishnan 2022). Seasonally, a higher number of fish species was observed in the Dhansiri River during monsoon at all stations, with the exception of S2 (pre-monsoon). Water discharge has been identified as the single most important factor driving fish species richness in Himalayan rivers (Bhat et al. 2012). Increased water discharge during monsoon creates new habitats and improves connectivity between different habitats and sections of the river, facilitating fish migration and colonization of new areas, thereby increasing likelihood of encountering higher number of species. Higher number of fish species observed at S2 during pre-monsoon may be attributed to increased natural food availability (Acharjee and Barat 2014). Previous studies across rivers in south and Southeast Asia have consistently reported cyprinids as most dominant group of fishes (Bhat 2003). The results of this study, which observed that cyprinids exhibit the highest relative abundance compared to other groups is a testimony to this statement. Cyprinids dominate fish community structure in tropical Indian rivers owing to their high adaptive variability and ability to occupy heterogeneous habitats (Johnson and Arunachalam 2009). Diversity indices in general are functions of different species available in an ecosystem and relative abundance of each species. Shannon diversity index is widely used to quantify diversity or richness of species in a specific ecological community and is one of the most commonly employed indices for comparing species diversity across habitats (Clarke and Warwick 2001). Margalef richness index is a biodiversity metric used to assess species richness in an ecological community (Margalef 1958). Simpson dominance index assesses the dominance or evenness of species abundances within an ecological community (Simpson 1949). On a spatial scale, values of ‘H′’ and ‘d’ were highest in pristine upper stretch (S1) with a gradual decline downstream. Conversely, values of ‘D’ increased from upstream to downstream, indicating a higher dominance of fewer species. Highest values of ‘H′’ (3.750) and ‘d’ (9.875) and lowest value of ‘D’ were observed during monsoon at S1, highlighting a high level of species richness and uneven distribution. This aligns with established ecological principles, as fish typically migrate, spawn and recruit during monsoon, leading to increased diversity and abundance in the ecosystem (Sreekanth et al. 2016). Restricted human interference by virtue of location and congenial habitat might be major factors for migration and breeding of fish during monsoon, leading to higher fish diversity and low dominance at S1. Pielou's evenness index quantifies the distribution of species within a community, providing a measure of how evenly individuals are spread across species. The index ranges from 0 to 1, where 0 represents maximum species dominance (only one species present), and 1 represents maximum evenness (all species are equally abundant) (Pielou 1966). In this study, it was observed that upper stretch (S1) has an even distribution of fish species, followed by S4. It should be noted that instances of high abundance in certain species may result in a deviation from evenness in overall species diversity (Saha et al. 2022), which might be one of the possible reasons for lower evenness in S2 and S3. Cumulative dominance curve ( k -dominance), which ranks fish species based on their abundance and the proportion of individuals per species, plotted against the logarithmic rank of species (Clarke 1990). The curved showed S4 as least diverse site, with a steep dominance curve indicating a few species dominating the community. Concept of species richness is commonly utilized as an indicator of environmental quality, as it tends to rise in presence of healthy ecosystems and minimal anthropogenic impairment (Roth et al. 2000; Kirk and Rahel 2022). Conversely, a decrease in species richness accompanied by proliferation of a few dominant species indicates a progressively deteriorating environment (Jacinto et al. 2023). It is important to note that freshwater assemblages are not solely affected by species zonation or spatial arrangement, but also shaped by physical disturbances, and habitat modifications (Daufresne and Boet 2007; Perkin et al. 2015). NMDS is an ordination technique used to visualize the similarity between samples based on ecological data. In the present study NMDS analysis revealed a clear separation of S4 from the other three stations. As per guidelines forwarded by Clarke (1993) stress values < 0.05 are considered excellent; < 0.10, good; 0.20, not reliable. Lower the stress value, better the fitting in ordination plot. In the present study, a stress value of 0.07 indicates a good fit for the distances/dissimilarities in the spatial ordination plot. Environmental factors play a crucial role in maintaining fundamental habitat characteristics and ecosystem functions, and they are known to significantly influence fish community structure in aquatic systems (Mondal and Bhat 2020; Debnath et al. 2022). Understanding the impact of environmental influencers on fish communities is essential for elucidating fish-habitat relationships, which can contribute to more effective ecosystem management and preservation (Gillooly et al. 2001; Wang and Lyons 2003; Li et al. 2018). BIO-ENV analysis found strong correlations between environmental parameters, fish abundance and composition, with NH 3 , NO 3 , CO 2 , TDS, TA, pH, specific conductivity, DO and WT being the most influential factors. Highest degree of correlation with fish abundance was observed in the combinations of NO 3 , CO 2 and TDS. Environmental variables affects fish abundance and composition both directly or indirectly by influencing dynamics of fish food organisms such as plankton (Gogoi et al. 2019) and aquatic invertebrates (Das et al. 2022). WT is one of the critical influencers that affect distribution of fishes, both directly by influencing their metabolic and physiological processes (Gillooly et al. 2001) and indirectly by affecting biological productivity and food matter availability (Sarkar et al. 2021). Additionally, TDS, TA and pH have been shown to reportedly influence chlorophyll contents in rivers (Sarkar et al. 2021), which are closely associated with productivity and the availability of food sources, thereby affects fish distribution. Similarly, NH 3 , NO 3 , CO 2 are also associated with biological productivity of aquatic ecosystems (Galloway et al. 1994; Sigman and Hain 2012) and can directly influence fish community structure. Parameters like pH, WT, TDS, NO 3 , DO are known to influence dynamics of fish food organisms (Gogoi et al. 2019; Das e al. 2022), which in turn affects distribution of fishes. Furthermore, DO, pH, NH 3 , NO 3 , CO 2 , TA have direct effects on fish metabolism, which may influence their distribution and abundance (Boyd and Tucker 1998). It is to be noted that, DO is the single most critical parameter for the survival of all forms of aquatic life (Keke et al. 2016) and it therefore exerts influence on fish communities. Managing adequate DO levels is essential for sustaining healthy fish populations and preserving the overall balance of aquatic ecosystems. The present study highlighted the impact of human activities, particularly at S4 near Dimapur town, as evidenced by reduced species richness, higher dominance of fewer species, and poorer water quality parameters. The presence of higher concentration of NH₃, NO₃ and CO₂ at S4 reflects inputs from agricultural runoff, urban wastewater and industrial discharges, all of which contribute to the degradation of Dhansiri River ecosystem. The finding of this study underscore the need for implementation of effective regulation and management measures to protect this Dhansiri River’s biodiversity, particularly in downstream areas. Establishing buffer zones, improving wastewater treatment and controlling agricultural runoff are critical steps towards mitigating the negative impact of anthropogenic activities (Hughes et al. 2018). Additionally, the presence of several species listed as Near Threatened and Vulnerable highlights the importance of targeted conservation efforts. Protecting critical habitats, especially in the upper stretches of the river, is essential for maintaining the ecological integrity of the entire system. Further research on the population dynamics of these threatened species is necessary to inform conservation strategies and ensure their long-term survival. As previously mentioned, environmental aspects participate crucially in shaping fish communities. Given the current state of rapid urbanization and climate change, it is imperative that we gain critical insights into ecological mechanisms affecting fish communities in order to develop effective protection and conservation strategies. The present study, conducted in a least-explored tropical river from a globally significant biodiversity hotspot, contributes to our knowledge and understanding, providing cues for sustainable riverine fisheries management. Declarations Ethics approval Procedures and activities performed during the study period involving animals were in agreement with ethical standards of the institution. Sampling was performed after due approval from Institute Research Committee (IRC) of ICAR-Central Institute of Fisheries Education. Statement on ‘Authors contributions’ All authors contributed in preparing the manuscript through designing of study, sampling methodology, data collection, data analysis, drafting and revision of the manuscript. Authors’ contribution SO, major contribution in writing, data collection; ATL, overall guidance, supervision, manuscript writing and revision and facilitation; KR, data analysis, manuscript writing and methodology; SB, conceptualization, major contribution in writing, data analysis and methodology; JB, data collection, taxonomy; SKM, manuscript correction and facilitation; NC, Data analysis and graphs, contribution in manuscript writing and revising; BKD, overall guidance, manuscript correction and facilitation. Funding The authors are thankful to the Indian Council of Agricultural Research, New Delhi for financial support to carry out the research work. Declaration of competing interest Authors declare no conflicts of interest in the research activity and in data presented in the manuscript. Further the authors declare that they have no relevant financial or non-financial interests to disclose. Availability of data and materials The data generated in the present study have been submitted to ICAR-CIFE data repository and can be obtained from the Institute through proper channel and with due permission from competent authority. Conflict of interest The authors declare that the research was conducted in the absence of any commercial and financial relationships that could be construed as a potential conflict of interest. Acknowledgement Authors are grateful to the Director, ICAR-CIFE, Mumbai for providing necessary facilities to carry out the research work. The first author thankful to the Director, ICAR-CIFRI, Barrackpore, Kolkata for providing necessary laboratory facilities and valuable guidance for completing the research work. The authors also thankful to the fisher community of river Dhansiri River, Nagaland, India. 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R Foundation for Statistical Computing, Vienna, Austria Rahel FJ, Olden JD (2008) Assessing the effects of climate change on aquatic invasive species. Conserv Ecol 22(3):521-533. Reid AJ, Carlson AK, Creed IF, Eliason EJ, Gell PA, Johnson PT, Kidd KA, MacCormack TJ, Olden JD, Ormerod SJ, Cooke S J (2019) Emerging threats and persistent conservation challenges for freshwater biodiversity Biol Rev 94(3): 849-873. Robinson CLK, Tonn WM (1989) Influence of environmental factors and piscivory in structuring fish assemblages of small Aberta Lakes. Can J Fish Aquat Sci 46:81-89 Roth E, Rosenthal H, Burbridge P (2000) A discussion of the use of the sustainability index: ‘ecological footprint’ for aquaculture production. Aquat Living Resour 13(6):461-469 Roy PS, Ramachandran RM, Paul O, Thakur PK, Ravan S, Behera MD, Sarangi C, Kanawade VP (2022) Anthropogenic land use and land cover changes—A review on its environmental consequences and climate change. Journal of the Indian Society of Remote Sensing 50(8):1615-1640 Saalidong BM, Aram SA, Otu S, Lartey PO (2022) Examining the dynamics of the relationship between water pH and other water quality parameters in ground and surface water systems. PlOS One 17(1):0262117 Saha S, Chukwuka AV, Mukherjee D, Saha NC, Adeogun AO (2022) Hydrological connectivity, surface water quality and distribution of fish species within sub-locations of an urban oxbow lake, East India. Watershed Ecology and the Environment 4:44-58 Sarkar SD, Sarkar UK, Naskar M, Roy K, Bose AK, Nag SK, Karnatak G, Das BK (2021) Effect of climato-environmental parameters on chlorophyll a concentration in the lower Ganga basin, India. Revista de Biología Tropical 69(1):60-76 Sarkar UK, Gupta BK, Lakra WS (2010) Biodiversity, ecohydrology, threat status and conservation priority of the freshwater fishes of river Gomti, a tributary of river Ganga (India). The Environmentalist 30:3-17 Sarmah R, Dutta R, Bhagabati SK, Nath D, Mudoi LP, Pokhrel H, Ahmed AM (2020) Seasonal variation of water quality parameters of river Dikhow in Nagaland and Assam. Int J Chem Stud 8:1429-1434 Shukla R, Bhat A (2017) Environmental drivers of α-diversity patterns in monsoonal tropical stream fish assemblages: a case study from tributaries of Narmada basin, India. Environ Biol Fishes 100:749-761 Sigman DM, Hain MP (2012) The Biological Productivity of the Ocean. Nature Education Knowledge 3(10):21 Simpson EH (1949) Measurement of diversity. Nature 163:688 Smokorowski K E, Pratt TC (2007) Effect of a change in physical structure and cover on fish and fish habitat in freshwater ecosystems–a review and meta-analysis. Environ Rev 15:15-41 Sreekanth GB, Manju Lekshmi N, Chakraborty SK, Jaiswar AK, Zacharia PU, Vishnuradhan R, Singh NP, George D, Pazhayamadom G (2016) Effect of monsoon on coastal fish diversity of Goa: an example from the gillnet fishery. Indian J Fish 63(2):8-18 Srivastav AL, Patel N, Rani L, Kumar P, Dutt I, Maddodi BS, Chaudhary VK (2023) Sustainable options for fertilizer management in agriculture to prevent water contamination: a review. Environ Dev and Sustain. https://doi.org/10.1007/s10668-023-03117-z Strickland JDH, Parsons TR (1972) A practical handbook of seawater analysis, 2 nd edn. Fisheries Research Board of Canada, Ottawa Talwar PK, Jhingran AG (1991) Inland fishes of India and adjacent countries, Vol I and II. Oxford and IBH Publishing Co. Pvt. Ltd., New Delhi Vorobyeva T Y, Chupakova AA, Chupakov AV, Zabelina SA, Moreva OY, Pokrovsky OS (2021) Distribution of dissolved nitrogen compounds in the water column of a meromictic subarctic lake. Nitrogen 2(4):428-443 Vörösmarty CJ, McIntyre PB, Gessner MO, Dudgeon D, Prusevich A, Green P, Glidden S, Bunn SE, Sullivan CA, Liermann CR, Davies P (2010) Global threats to human water security and river biodiversity nature 467(7315): 555-561. Wang L, Lyons J, Rasmussen P, Seelbach P, Simon T, Wiley M, Kanehl P, Baker E, Niemela S, Stewart PM (2003) Watershed, reach, and riparian influences on stream fish assemblages in the Northern Lakes and Forest Ecoregion, USA. Can J Fish and Aquat 60(5):491-505 Weber C, Peter A, Zanini F (2007) Spatio-temporal analysis of fish and their habitat: a case study on a highly degraded Swiss river system prior to extensive rehabilitation. Aquat Sci 69:162-172 Wichert GA, Rapport DJ (1998) Fish community structure as a measure of degradation and rehabilitation of riparian systems in an agricultural drainage basin. Environ Manage 22:425–443 Wilkinson CL, Yeo DC, Tan HH, Fikri AH, Ewers RM (2018) Land-use change is associated with a significant loss of freshwater fish species and functional richness in Sabah, Malaysia. Biol Conserv 222:164-171 Zeng C, Wen Y, Liu X, Yu J, Jin B, Li D (2022) Impact of anthropogenic activities on changes of ichthyofauna in the middle and lower Xiang River. Aquac Fish 7(6): 693-702 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 05 Feb, 2025 Read the published version in Aquatic Sciences → Version 1 posted Editorial decision: Revision requested 03 Jan, 2025 Reviews received at journal 18 Nov, 2024 Reviewers agreed at journal 04 Nov, 2024 Reviewers agreed at journal 31 Oct, 2024 Reviewers invited by journal 30 Oct, 2024 Editor assigned by journal 28 Oct, 2024 Submission checks completed at journal 27 Oct, 2024 First submitted to journal 27 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5340746","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":373883186,"identity":"adfdb555-1cbf-451a-b3d5-8adbf4b0ed55","order_by":0,"name":"Shamyung O Ongh","email":"","orcid":"","institution":"ICAR-Central Institute of Fisheries Education","correspondingAuthor":false,"prefix":"","firstName":"Shamyung","middleName":"O","lastName":"Ongh","suffix":""},{"id":373883187,"identity":"00e6a13b-be32-47b7-98bf-545a2650458b","order_by":1,"name":"Asha Taterao Landge","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYFACHgaGBwwMjA0MzAdAJJFaEsBa2BJI1sJjQJwW/v6zBz8k1NyRne/e803i5w4bOQb2w0c34NMicSMvWSLh2DPjjWfObpPsPZNmzMCTlnYDrzU3eAwkEtgOJ26ckbtNgrftcGKDBI8ZXi3y588Y/0j4B9Qy/80zyb/EaDE4kGMmkQhUOV+Ch02aKFsMb+SYWST2HTbewJNmbC3blmbMRsgvckCH3fjw7bDs/PbDD2++bbOR42c/fAy/9xEuZGCRADHYiFIOAvLAFPOBaNWjYBSMglEwogAAFO5SvZwKWdkAAAAASUVORK5CYII=","orcid":"","institution":"ICAR-Central Institute of Fisheries Education","correspondingAuthor":true,"prefix":"","firstName":"Asha","middleName":"Taterao","lastName":"Landge","suffix":""},{"id":373883188,"identity":"2e8a6d5b-66d0-4273-8f8e-3cf2d73f3336","order_by":2,"name":"Karankumar Ramteke","email":"","orcid":"","institution":"ICAR-Central Institute of Fisheries 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10:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5340746/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5340746/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00027-025-01169-z","type":"published","date":"2025-02-05T15:57:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68344833,"identity":"db91881f-ed65-4fea-87bc-b0bb00ca8b7a","added_by":"auto","created_at":"2024-11-06 09:31:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84002,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the study area and the sampling sites\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/4fd1e1bbce68c61829aa8d95.png"},{"id":68344837,"identity":"0f7a2d28-8d50-4407-880d-f8833bfc5242","added_by":"auto","created_at":"2024-11-06 09:31:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":11759,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial and temporal variation in speciesrichness, evenness, diversity and dominance of the Dhansiri River, Nagaland\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/91705178756e8912ad197eb5.png"},{"id":68344834,"identity":"ccfb924d-fb2a-4121-bcb6-ef7b4d00a805","added_by":"auto","created_at":"2024-11-06 09:31:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":31477,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative dominance curve depicting fish species abundance across stations\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/4e77e64ea8e51e13620eb7ac.png"},{"id":68344836,"identity":"843064b1-6765-4f6a-8b34-24926717e03d","added_by":"auto","created_at":"2024-11-06 09:31:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":139000,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance (%) of fish families across different seasons and stations\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/cba048ce9705a5a48905c99f.png"},{"id":68345804,"identity":"50a1e7c2-f7cc-40ce-bdab-ab3b807856ce","added_by":"auto","created_at":"2024-11-06 09:39:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":67300,"visible":true,"origin":"","legend":"\u003cp\u003eNMDS ordination plot based on Bray-Curtis similarity of samples in the Dhansiri River, Nagaland from different\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/31207f27e431d7719d70066b.png"},{"id":68344838,"identity":"482ad662-bdac-44aa-9c74-7dc3d867cc87","added_by":"auto","created_at":"2024-11-06 09:31:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":68841,"visible":true,"origin":"","legend":"\u003cp\u003ePCA plot of water quality parameters of the Dhansiri River\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/3fbe5f34e3b312d6f66555e4.png"},{"id":75931322,"identity":"f8f628ce-3657-4402-b91b-752f9363eafb","added_by":"auto","created_at":"2025-02-10 16:14:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2253360,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5340746/v1/76294325-6786-4cd0-94b2-ee59ed23f2f8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fish community structure in accordance with environmental signatures in tropical river ecosystem, Eastern Himalayan eco-region","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTropical rivers are among the most diverse and dynamic ecosystems on Earth, serving as very important habitats for both local and global biodiversity (Dudgeon \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). These ecosystems are very important due to their role in supporting an extensive range of species, many of which are endemic and play critical roles in maintaining ecological stability (V\u0026ouml;r\u0026ouml;smarty et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). They also provided essential ecosystem services, including riverine fisheries, which serve as a source of food and income for millions of individuals worldwide. Fish community structure refers to composition, abundance, diversity, and interactions among fish species within a particular aquatic ecosystem. They provide key insights into the health and functioning of tropical biodiversity hotspots, such as the rivers of the Eastern Himalaya region. Fish occupy central roles in aquatic food webs as primary consumers, predators and prey, thereby driving energy flow within these ecosystems (Allan and Castillo 2007; Kumari 2024). However, despite their ecological importance, tropical rivers face increasing natural and anthropogenic pressures, jeopardizing their health and the services they provide.\u003c/p\u003e \u003cp\u003eThe composition and structure of fish communities are highly sensitive to a wide range of environmental variables, including changes in water temperature, hydrological regimes, water quality, nutrient concentrations, habitat structure and land-use pattern (Reid et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Climate change, habitat alteration, introduction of non-native species, pollution, and rising human activities are contributing to the rapid degradation of tropical rivers, threatening the balance of their aquatic communities (Dudgeon et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The combined effects of these factors are severely threatening the biodiversity and ecological balance of tropical rivers, putting both the ecosystems and the human populations that depend on them at risk. Of particular concern is the impact of climate change, which alters water temperatures and hydrological patterns, disrupting the natural balance of these ecosystems. Temperature plays a critical role in regulating fish physiology, affecting metabolism, reproduction, and migration, which can lead to shifts in community structure (Comte et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Adequate dissolved oxygen (DO) is essential for sustaining metabolic activities, and oxygen depletion significantly stresses fish, impacting growth and survival. Most fish thrive within a pH range of 6.5 to 8.5, with deviations causing stress, impaired gill function, and increased toxicity of compounds like ammonia (Moyle and Light \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Stable alkalinity supports these conditions by buffering against sudden pH changes (Palmer et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Nutrient concentrations such as nitrite, nitrate, and ammonia influence water quality, and excessive nutrients from agricultural runoff lead to eutrophication, depleting oxygen and causing harmful algal blooms. Elevated carbon dioxide (CO₂) from organic decomposition and pollution reduces oxygen availability, increasing fish stress (Rahel and Olden, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEnvironmental parameters like specific conductivity and total dissolved solids (TDS) reflect pollution levels, affecting fish osmoregulation and reducing biodiversity in sensitive species (Dudgeon et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Additionally, reduced transparency from sedimentation or algal blooms decreases primary productivity and disrupts visual predators, while limited depth affects habitat availability for certain species (Reid et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The introduction of non-native species, either through human activity or as a result of changing environmental conditions, poses another significant threat to the integrity of tropical river ecosystems (Palmer et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). These invasive species often outcompete native species for resources, leading to declines in biodiversity and alterations in ecosystem function (Dudgeon et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Therefore, monitoring and assessing fish community structures provide valuable information for fisheries management, conservation efforts, and ecosystem health assessments. The structure of fish communities is a reliable indicator of environmental stress (Barrella and Petrere \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), and specific community compositions can reflect the degree of habitat degradation (Wichert and Rapport \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Environmental and anthropogenic factors (Mondal and Bhat \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), biotic factors (Robinson and Tonn \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), abiotic factors (Debnath et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), trophic interactions and life-history traits have significantly influenced fish and other biotic community structures in aquatic systems worldwide. Anthropogenic influences have altered water flow and habitat quality for many freshwater fish species, considerably contributing to decline in freshwater biodiversity (Wilkinson et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zeng et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNortheast India covers an ecologically diverse region, encompassing the seven states of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, and Tripura. This region is located within Eastern Himalayan biodiversity hotspot and shares borders with Bhutan, Myanmar, and Bangladesh. Its unique geographical location, combined with varied topography, has resulted in creation of numerous distinct ecosystems. Rivers and water bodies in Northeast India are crucial components of its biodiversity. The mighty Brahmaputra River and its tributaries, including the Dhansiri River, play a vital role in supporting aquatic life, such as endangered Ganges river dolphin, freshwater turtles and numerous fish species. The Dhansiri River, a significant waterway of the Brahmaputra basin, flows through Nagaland and Assam. It originates from Laisong Peak in Wokha district of Nagaland and traverses various regions before joining Brahmaputra at Golaghat district, Assam. Its diverse habitats provide favourable conditions for numerous fish species to thrive. The Nagaland Pollution Control Board (NPCB) has designated lower stretch of the Dhansiri (near Dimapur town) as highly polluted and categorized it under Priority I due to high BOD levels (30 mg/l) (Anon \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This part of the river has been severely stressed by immense anthropogenic pressures in recent years due to domestic and municipal sewage dumping. Dhansiri is one of many rivers in the biodiversity hotspot of North East India that has yet to receive much scientific attention regarding its fish diversity and ecology.\u003c/p\u003e \u003cp\u003ePreviously, several studies have been conducted on the Dhansiri River, mostly focusing on land use, land cover changes and geomorphological aspects, such as channel sinuosity, erosion and sediment dynamics using remote sensing and geographical information system (GIS) techniques (Kotoky et al. 2012; Mili and Acharjee \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Barman and Goswami 2015). However, research on the fish community has been limited. Acharjee et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) reported 34 species under 5 orders, 25 families and 24 genera from the Dimapur stretch of Dhansiri River. A study by Daimari (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) identified 15 fish species from the river, representing 4 orders and 8 families. These studies primarily focused on species composition and abundance, lacking a comprehensive understanding of how environmental factors influence fish communities. Understanding fish assemblage structure in relation to environmental variables in rivers remains a challenge due to limited knowledge on the subject (Mondal and Bhat \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study aims to investigate how specific environmental factors influence fish community structures in the Eastern Himalayan tropical river ecosystem, seeking to identify patterns in species distribution and biodiversity linked to distinct environmental signatures. The present study holds significance as it addresses these knowledge gaps, providing valuable insights into ecosystem functioning and conservation needs, which will aid in the sustainable riverine fisheries management. Additionally, the research helps address the impacts of climate change on fish communities, providing valuable insights for adaptation strategies. The study also contributes to protecting endangered species, ensuring their survival amid growing environmental challenges. Preserving fish community structure can ensure long-term health and sustainability of our riverine ecosystems in context of changing scenarios and ever-increasing stressors.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area and sampling station description\u003c/h2\u003e \u003cp\u003eThe study was conducted on the Dhansiri River, one of the largest tributaries of the Brahmaputra. Dhansiri is a perennial river with a total length of 352 km (Long: 25\u0026deg;54\u0026rsquo;45\u0026rdquo; N, 93\u0026deg;44\u0026rsquo;30\u0026rdquo; E and Lat: 25\u0026deg;91\u0026rsquo;25\u0026rdquo; N, 93\u0026deg;74\u0026rsquo;16\u0026rdquo; E). It originates from Laishong Peak in the Barail range of Nagaland and flows from south to north before joining Brahmaputra at Dhansirimukh, Assam. Samples were collected during 2020-21 from four designated sampling stations, each representing different stretches of the river. The stations were selected based on their ecological significance and geographic distribution along the river\u0026rsquo;s course. Intangki National Park (INP) (S1; upper stretch, 25\u0026deg;43'19.5\" N and 93\u0026deg;32'35.4\" E), is situated within a protected forest area and characterized by minimal anthropogenic disturbance. Mangalmukh (S2; middle stretch, 25\u0026deg;43'19.3\" N and 93\u0026deg;32'35.7\" E), is characterized by a mixed forested landscape with moderate human activities. Doyapur (S3; middle stretch, 25\u0026deg;46'9.4\" N and 93\u0026deg;35'54.3\" E), lies further downstream with increasing agricultural and human activities. Domukhia (S4; lower stretch, 25\u0026deg;57'26\" N and 93\u0026deg;46'10\" E), is influenced by urbanization and agricultural runoff (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Samples were collected across three distinct seasons \u003cem\u003eviz.\u003c/em\u003e, post-monsoon (POM), pre-monsoon (PRM) and monsoon (MON) to account for seasonal variations in fish community structure and environmental conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFish diversity\u003c/h3\u003e\n\u003cp\u003eExperimental fishing was carried out at each station using various gear types, including gill nets (2 no.; 10 m in length; 1m width; 25 mm and 30 mm mesh size), cast nets (3 no.; 2.4 m length and 3 m width; 10 mm and 20 mm mesh size), scoop nets, hooks and lines, and traditional bamboo traps, to assess fish diversity. Gill nets were set along the current in deeper pools and kept overnight. Other fishing gear was operated during early morning hours for approximately 2\u0026ndash;3 hours. Fish samples collected were cleaned, labeled and preserved in 8\u0026ndash;10% formalin and transported to laboratory for identification. Identification of fish was done following Talwar and Jhingran (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) and Jayaram (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Taxonomic status and systematic position of fishes were cross-verified using the Catalog of Fishes (Fricke et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Conservation status of fish species was assessed based on the IUCN Red List of Threatened Species (IUCN \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEnvironmental parameters\u003c/h3\u003e\n\u003cp\u003eA total of 12 environmental variables \u003cem\u003eviz.\u003c/em\u003e water temperature (WT), depth, transparency, pH, dissolved oxygen (DO), total dissolved solids (TDS), CO\u003csub\u003e2\u003c/sub\u003e, specific conductivity, total alkalinity (TA), nitrate (NO\u003csub\u003e3\u003c/sub\u003e), nitrite (NO\u003csub\u003e2\u003c/sub\u003e) and ammonia (NH\u003csub\u003e3\u003c/sub\u003e) was systematically measured to assess water quality. Water samples were collected from surface and sub-surface (up to 0.5 m depth), homogenized and immediately transferred to pre-rinsed polyethylene bottles (1 L capacity). WT, pH, DO and specific conductivity were measured in field using a multi-parameter water quality meter ((Model 9829, HANNA, Romania) to ensure immediate and accurate in-situ readings. All the other remaining water quality parameters were analyzed in the laboratory following standard procedures (APHA 2017). Transparency was measured with a Seechi disc, following the method of Strickland and Parsons (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1972\u003c/span\u003e). Depth measurements were taken manually to ensure precision.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe assessment of fish community structure and diversity employed a range of indices calculated from species abundance data. These indices included the Shannon-Wiener index (H\u0026prime;), the Margalef richness index (d), Pielou\u0026rsquo;s evenness index (J\u0026rsquo;), Simpson\u0026rsquo;s dominance (λ) and Simpson\u0026rsquo;s diversity (D) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All indices were calculated using Primer (Ver. 7.0). Cumulative dominance was also assessed using Primer (Ver. 7.0) (Clarke and Gorley \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Relative abundance was calculated for each family across seasons and stations in MS Excel, using the following formula:\u003c/p\u003e \u003cp\u003e \u003cb\u003eRelative abundance = (Abundance (no.) in each family/Total abundance (no.)) \u0026times; 100.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo analyse species composition patterns, non-metric dimensional scaling (NMDS) was employed. NMDS particularly effective in visualizing community structure by reducing high-dimensional datasets, was applied to explore dissimilarity patterns within the dataset. Conducted in Primer (Ver. 7.0), this ordination technique facilitated the visualization of seasonal and spatial patterns in species distribution along the river gradient (Clarke and Gorley \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Principal component analysis (PCA), another statistical technique for dimensional reduction and inter-variable data exploration, was conducted in R (Ver. 4.3.0) (R Development Core Team \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This approach transformed interrelated water quality variables into uncorrelated principal components, aiding in elucidating the key environmental gradients that influences species distribution across the sampling stations. To examine spatial variability in water quality parameters, one-way analysis of variance (ANOVA) was performed, with post-hoc comparisons using Duncan\u0026rsquo;s multiple range tests to distinguish significant difference among stations, using SPSS (Ver. 23.0) (Das et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The BIO\u0026thinsp;\u0026minus;\u0026thinsp;ENV (Biota and/or Environment matching) method was executed using the vegan-package in R (R Development Core Team, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) to identify and quantify the environmental variables most strongly correlated with observed variations in fish community structure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription and formulas used for the calculation of diversity indices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSl no.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiversity indices\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFormula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDescription of the formula\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShannon diversity index (H\u0026prime;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eprovides information about community composition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eH\u0026prime;=\u003csub\u003ei\u003c/sub\u003e log\u003csub\u003ee\u003c/sub\u003e P\u003csub\u003ei\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH\u0026prime;= species diversity in bits of information per individual. n\u003csub\u003ei\u003c/sub\u003e = proportion of the samples belonging to the i\u003csup\u003eth\u003c/sup\u003e species\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMargalef richness index (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eweighs number of species in the community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ed = (S-1) / log N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS\u0026thinsp;=\u0026thinsp;total number of species and N\u0026thinsp;=\u0026thinsp;total number of individuals in the collection.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePielou\u0026rsquo;s evenness index (J\u0026rsquo;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erefers to the degree of species abundance in an ecosystem.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJ\u0026prime; = H'/ln(S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH' is Shannon Weiner diversity and S is the total number of species in a sample\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSimpson dominance index (λ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emeasure of community diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eD\u0026thinsp;=\u0026thinsp;Σp\u003csub\u003ei\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003csub\u003ei\u003c/sub\u003e\u0026nbsp;is the proportion of individuals in the i\u003csup\u003eth\u003c/sup\u003e species.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSpecies composition and diversity\u003c/h2\u003e \u003cp\u003eThis study documented 3399 individual fish, representing 69 species across 20 families and 46 genera from the Dhansiri River. A systematic checklist of fish and their IUCN conservation status are illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The Cyprinidae family was the most diverse group, represented by 22 species, followed by Danionidae (14 species), Sisoridae (6 species), Bagridae (5 species) and Channidae (5 species). Families such as Botiidae and Nemacheilidae were represented by 2 species each, while single species were identified in the families Siluridae, Erethistidae, Schilbeidae, Cobitidae, Gobiidae, Ambassidae, Osphronemidae, Mastacembelidae, Psilorhynchidae, Belonidae, Badidae, Balitoridae and Notopteridae. In terms of abundance, \u003cem\u003eCabdio morar\u003c/em\u003e, \u003cem\u003eSalmostoma acinaces\u003c/em\u003e, \u003cem\u003ePethia ticto\u003c/em\u003e, \u003cem\u003eP. conchonius\u003c/em\u003e, \u003cem\u003ePuntius chola\u003c/em\u003e, \u003cem\u003eOpsarius tileo\u003c/em\u003e and \u003cem\u003eAcanthocobitis botia\u003c/em\u003e were dominant. Number of species was highest at S1 during monsoon season with 52 species, followed by 47 species in the post-monsoon and 37 species in the pre-monsoon season. At station S2, number of species was highest in the pre-monsoon (40), while both monsoon and post-monsoon recorded 38 species. For station S3, species numbers peaked during monsoon (39), followed by pre-monsoon (37) and post-monsoon (36). Station S4 showed similar trend, with 38 species recorded in the monsoon, 36 species in the pre-monsoon and 33 species in the post-monsoon. Overall, the highest number of species was recorded along the upper stretch of the river at S1 (54), followed by S2 (45), S3 (41 species) and lowest at S4 (37). Seasonal analysis showed that highest number of species was recorded in monsoon (64), followed by post-monsoon (59) and pre-monsoon (54). An assessment of the conservation status of fish species revealed that 57 species (82.61% of total) were classified as Least Concern (LC), 5 species (7.25%) as Near Threatened (NT), 3 species (4.35%) as Vulnerable (VU), 2 species (2.90%) as Data Deficient (DD). \u003cem\u003eSchistura fasciata\u003c/em\u003e has not been evaluated and is grouped under Not Evaluated (NE). A single exotic species, \u003cem\u003eCyprinus carpio\u003c/em\u003e was also recorded from the river.\u003c/p\u003e \u003cp\u003eBiodiversity indices are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Shannon index (H') values ranged from 3.327 at station S4 (post-monsson) to 3.750 at station S1 (monsoon). Along the upper stretch (S1), value of H' peaked in the monsoon period, with slightly lower value observed during post-monsoon (3.664) and pre-monsoon (3.465) periods. In case of station S2 (middle stretch), the highest H' value was noted in pre-monsoon at 3.496, while post-monsoon at 3.431 and monsoon recorded the lowest at 3.385. Similarly, at station S3 (middle stretch), H' values were highest in pre-monsoon (3.414), followed closely by the monsoon (3.409) and post-monsoon (3.391). Along lower stretch (S4), H' reached its maximum during the pre-monsoon (3.427), with a slight decrease in the monsoon (3.361) and lowest in post-monsoon (3.327).\u003c/p\u003e \u003cp\u003eThe Margalef richness index (d) varied across stations and seasons, with values ranging from 6.544 (S4, post-monsoon) to 9.875 (S1, monsoon). In case of station S1, the richness index (d) was highest in the monsoon, with slightly lower values observed during post-monsoon (8.626) and pre-monsoon (8.624). For the middle stretch at station S2, the richness index reached its maximum in pre-monsoon (8.544), while monsoon values were moderately lower (7.715) and the post-monsoon had the lowest index (7.601). At station S3, monsoon again recorded the highest richness index (7.924), followed closely by pre-monsoon (7.767) and then post-monsoon (7.135). At station S4, lowest value of \u0026lsquo;d\u0026rsquo; was observed in post-monsoon, highest during monsoon (7.742) and intermediate in pre-monsoon (7.722). Generally, the value of \u0026lsquo;d\u0026rsquo; was found to be higher during monsoon at all stations, except for S2, where highest species richness appeared in the pre-monsoon and the lowest in the post-monsoon. Pielou\u0026rsquo;s eveness index (J') ranged from 0.924 (S4, monsoon) to 0.9596 (S1, pre-monsoon). The J' values were lower during the monsoon across all stations and higher during pre-monsoon, except for station S3, where it was higher during post-monsoon (0.9463). The mean values of J' were highest at station S1 (0.9535), followed by S4 (0.9440) and lowest at S2 (0.9410). Simpson dominance index (D) ranged from 0.027 (S1, monsoon) to 0.045 (S4, monsoon). Values of D were found to be on the lower side at S1 (0.027\u0026ndash;0.037) and increased downstream, with highest values at S4 (0.37\u0026ndash;0.45). Values of D were intermediate in middle stretch, ranging from 0.037\u0026ndash;0.042 at S2 and from 0.038\u0026ndash;0.040 at S3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe cumulative dominance curve (\u003cem\u003ek\u003c/em\u003e-dominance) extracted for different stations showed that fish species dominance in S1, S2 and S3 did not differ significantly. However, station S4 exhibited a significantly different dominance pattern compared to other three stations. A higher curve in the cumulative dominance plot and more quickly the curve reaches 100% value, indicates lower fish species richness. S4 had the lowest species richness, while S1 showed the highest species richness, as evident in the \u003cem\u003ek\u003c/em\u003e-dominance plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSpatio-temporal variation in the relative abundance of different fish families is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Relative abundance of most families was higher at S1 and progressively decreased downstream. The proportion of fish families observed across the stations varied between 0% and 5.63%. Cyprinidae family was the most abundant, with its relative abundance varying between 1.81% (S1, pre-monsoon) and 5.63% (S1, post-monsoon), followed by Danionidae family, with values ranging from 0.87% (S1, pre-monsoon) to 3.02% (S1, post-monsoon). Relative abundance of all other fish families was found to be \u0026lt;\u0026thinsp;1%, except for Channidae family, which reached 1.27% at S1 during post-monsoon. Cobitidae followed by Botiidae were the least abundant families in terms of number of specimens reported during the study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNon-metric multidimensional scaling reflected that samples from S4 were distinctively separated from those collected at S1, S2 and S3. Further, S1 post-monsoon sample also demonstrated distinct separation from the remaining samples. A stress value of 0.07 portrayed a good ordination pattern for the observed data (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSystematic checklist of fishes recorded from Dhansiri River along with their IUCN conservation status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConservation status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eSite 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNotopteridae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eNotopterus notopterus\u003c/em\u003e (Pallas, 1769)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"21\" rowspan=\"22\"\u003e \u003cp\u003e\u003cb\u003eCyprinidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBangana dero\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eChagunius chagunio\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC. nicholsi\u003c/em\u003e (Myers, 1924)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCirrhinus reba\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC. cirrhosus\u003c/em\u003e (Bloch, 1795 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCyprinus carpio\u003c/em\u003e (Linnaeus, 1758)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHypsibarbus wetmorei\u003c/em\u003e (Smith, 1931)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eLabeo dyocheilus\u003c/em\u003e (McClelland, 1839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eL. rohita\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eL. pangusia\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eL. gonius\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eNeolissochilus hexagonolepis\u003c/em\u003e (McClelland, 1839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePuntius chola\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. sophore\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePethia conchonius\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. ticto\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSystomus sarana\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTor tor\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTariqilabeo latius\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eGarra gotyla\u003c/em\u003e (Gray, 1832)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eG. nasuta\u003c/em\u003e (McClelland, 1839 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eG. rupecula\u003c/em\u003e (McClelland, 1839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003e\u003cb\u003eDanionidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSalmostoma acinaces\u003c/em\u003e (Valenciennes, 1842)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eS. bacaila\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAmblypharyngodon mola\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBarilius barila\u003c/em\u003e (Hamilton,1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOpsarius bendelisis\u003c/em\u003e (Hamilton,1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eO. dogarsinghi\u003c/em\u003e (Hora, 1921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eO. tileo\u003c/em\u003e (Hamilton,1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eO. barna\u003c/em\u003e (Hamilton,1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDanio rerio\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCabdio morar\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDevario devario\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eD. aequipinnatus\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEsomus danrica\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRasbora rasbora\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsilorhynchidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePsilorhynchus sucatio\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBalitoridae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBalitora brucei\u003c/em\u003e (Gray, 1830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNemacheilidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAcanthocobitis botia\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSchistura fasciata\u003c/em\u003e (McClelland,1838)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCobitidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCanthophrys gongota\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eBotiidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBotia dario\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB. rostrata\u003c/em\u003e (Grunther, 1868)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eBagridae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSperata seenghala\u003c/em\u003e (Hamilton,1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOlyra longicaudata\u003c/em\u003e (McClelland, 1842)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMystus tengara\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM. bleekeri\u003c/em\u003e (Day, 1877)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM. dibrugarensis\u003c/em\u003e (Chaudhuri, 1913)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eErethistidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHara jerdoni\u003c/em\u003e (Day, 1870)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSiluridae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOmpok bimaculatus\u003c/em\u003e (Bloch, 1797)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchilbeidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eClupisoma garua\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eSisoridae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBagarius lica\u003c/em\u003e (Volz, 1903)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eGagata cenia\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eGlyptothorax telchitta\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eG. trilineatus\u003c/em\u003e (Blyth, 1861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eG. platypogonoides\u003c/em\u003e (Bleeker, 1855)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSisor rabdophorus\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBelonidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eXenentodon cancila\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmbassidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eParambassis baculis\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBadidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBadis badis\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGobiidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eGlossogobius giuris\u003c/em\u003e (Hamilton,1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eChannidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eChanna barca\u003c/em\u003e (Hamilton, 1822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC. marulius\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC. gachua\u003c/em\u003e (Hamilton, 1822)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC. punctata\u003c/em\u003e (Bloch, 1793)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eC. striata\u003c/em\u003e (Bloch, 1793)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOsphronemidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTrichogaster fasciata\u003c/em\u003e (Bloch and Schneider, 1801)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMastacembelidae\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMastacembelus armatus\u003c/em\u003e (Lacepede, 1800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e+\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003e+, Present; -,Absent\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEnvironmental parameters\u003c/h3\u003e\n\u003cp\u003eMean values of environmental parameters for the Dhansiri River, Nagaland, across seasons and stations are given in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. It was observed that water temperature was lower at S1 and increased downstream of river. Maximum value of DO was observed at S1 during post-monsoon (12 mg/l), while minimum value was observed at S4 during monsoon (8 mg/l). Water pH was observed to range from 7-8.5. NH\u003csub\u003e3\u003c/sub\u003e was not detected at S1, S2 and S3, while at S4 it was found to range from 1\u0026ndash;3 mg/l. NO\u003csub\u003e2\u003c/sub\u003e and NO\u003csub\u003e3\u003c/sub\u003e were not detected in water samples at S1, while at S2 and S3, nitrate and nitrite respectively were found to range from 0.1\u0026ndash;0.2 mg/l and 0.1\u0026ndash;0.16 mg/l, and were observed during pre-monsoon and monsoon. Values of CO\u003csub\u003e2\u003c/sub\u003e were found to range from 1.7\u0026ndash;3.2 mg/l, with higher values recorded at S4. TA was found to range from 95\u0026ndash;160 mg/l, with a higher mean values observed during monsoon season at all stations except for S1, where higher mean value was observed in pre-monsoon. Spatial analysis showed that mean values of TA were reportedly higher at S1 and lowest at S2. TDS was observed to range from 76\u0026ndash;125 mg/l, with S1 showing the highest mean values and S4 the lowest. Across seasons, higher mean values of TDS were observed in monsoon at all stations. Specific conductivity was observed to range from 116\u0026ndash;174 \u0026micro;S/cm in the Dhansiri River. Higher mean values of specific conductivity were observed at S1 and lowest at S2. Specific conductivity did not show any particular trend across seasons in the river.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean values of physico-chemical parameters of Dhansiri River\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTATION\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eS 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eS3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c17\" namest=\"c14\"\u003e \u003cp\u003eS4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEASON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAVG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAVG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eAVG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003ePOM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003ePRM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eMON\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eAVG\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTemperature (\u0026deg;C)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e23.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e16.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e24.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e24.11\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDO (mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.69\u0026thinsp;\u0026plusmn;\u0026thinsp;.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e9.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e11.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e9.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e8.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e9.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e7.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e7.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTA (mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151.25\u0026thinsp;\u0026plusmn;\u0026thinsp;4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e147.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e147.83\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e133.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e152.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e135.13\u0026thinsp;\u0026plusmn;\u0026thinsp;6.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e141.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e142.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e137.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e102.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e126.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e131\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e121.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.77\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNitrite (mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e0.045\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNitrate (mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e4.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmmonia (mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpecific conductivity (uS/cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e153.13\u0026thinsp;\u0026plusmn;\u0026thinsp;5.62\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e129\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e119\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e127\u0026thinsp;\u0026plusmn;\u0026thinsp;2.93\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e138.5\u0026thinsp;\u0026plusmn;\u0026thinsp;30.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e128.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e117\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e128.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5.51\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e148\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e140\u0026thinsp;\u0026plusmn;\u0026thinsp;11.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e131\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e139.75\u0026thinsp;\u0026plusmn;\u0026thinsp;6.23\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTDS (mg/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103\u0026thinsp;\u0026plusmn;\u0026thinsp;3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.82\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e106\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e91.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e88.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e84.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e120\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e94.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e94.25\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e118\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e98.12\u0026thinsp;\u0026plusmn;\u0026thinsp;5.63\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTransparency (cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.84\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e29.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepth (ft)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c14\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c15\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c16\"\u003e \u003cp\u003e5.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"17\"\u003eValues with different superscript are significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05); ND\u0026thinsp;=\u0026thinsp;Not detected\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePCA plot of water quality parameters is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The first principal component (Dim1), with an eigenvalue of 5.29 explains 44.13% of total variation. The second principal component (Dim2), with an eigenvalue of 3.86 explains an additional 32.23% of the variation. First principal component (Dim1) is mainly influenced by variables, such as pH (20.96%), total alkalinity (13.80%), specific conductivity (9.92%), NO\u003csub\u003e2\u003c/sub\u003e (12.19%), and TDS (6.22%). These variables contribute significantly to the observed variation in Dim1. On the other hand, second principal component (Dim2) is primarily influenced by NO\u003csub\u003e3\u003c/sub\u003e (53.43%) and water temperature (6.05%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eInfluence of environmental parameters on fish community structure\u003c/h3\u003e\n\u003cp\u003eThe BIO-ENV analysis indicated significant correlations between fish abundance and composition and environmental variables, including NH\u003csub\u003e3\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, TDS, TA, pH, specific conductivity (Sp. Con.), DO and WT. The strongest correlation (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6203) was observed with the combination of NO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, TDS. This was followed by the combination of pH, NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con. and TDS (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6134) and by the combination of pH, NO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS (\u003cem\u003eρ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6073). Details of correlation of environmental parameters with fish abundance are given in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBIO-ENV analysis of fish assemblage compared with environmental variables (pooled data)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of\u003c/p\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrelation selection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpearman correlation\u003c/p\u003e \u003cp\u003e( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNH\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNO\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003eCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e,\u003cb\u003eTDS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.6203\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTA,NO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e,TDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH,NO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH,NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.6134\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH,TA,NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDO, pH,TA,NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5964\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT, DO, pH, TA,NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT,DO, pH, TA,NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS, Depth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT,DO, pH, TA,NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS, Trans, Depth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWT,DO, pH, TA,NO\u003csub\u003e2\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e3\u003c/sub\u003e,CO\u003csub\u003e2\u003c/sub\u003e, Sp. Con., TDS, Trans, Depth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study investigated alterations in the structure, diversity and richness of fish species communities during three different seasons, while also comparing physico-chemical characteristics of the Dhansiri River, one of the largest tributaries of Brahmaputra. Spatio-temporal changes in environmental factors\u0026nbsp;are key determinants of freshwater fish assemblages, influencing habitat structure and species composition (Fischer and Paukert 2008; El\u0026iacute;as et al. 2020). This study offers valuable insights into ecological shifts within the river, enhancing the understanding of the intricate interrelationships between fish populations and their habitat. The Dhansiri River is characterized by high DO levels, high total alkalinity and an alkaline pH, which are comparable to other hilly rivers in the region (Gurumayum et al. 2014; Sarmah et al. 2020; Lkr et al. 2020). Spatial analysis of water quality parameters revealed that the upper stretch (S1) reflects a relatively pristine habitat with minimal human impact. On the contrary, a slight deterioration in water quality was noticed downstream, with comparatively poorest condition at S4 near Dimapur town. This stretch of the river is characterized by low DO levels, high CO\u003csub\u003e2\u003c/sub\u003e and presence of NH\u003csub\u003e3\u003c/sub\u003e, NO\u003csub\u003e2\u003c/sub\u003e and NO\u003csub\u003e3\u003c/sub\u003e. Stretch of the Dhansiri near Dimapur town has been listed as polluted and placed under Priority I category due to high BOD load (Anon 2019). Poor downstream environment quality may be attributed to increased human habitation, high anthropogenic discharge, agricultural runoff and changes in land use patterns (Premke et al. 2020; Ji et al. 2021). Pristine nature of water at S1 may be explained by its location within INP, where human interference is restricted. Distinct seasonal changes in current patterns, discharge rates, and temperature bring about unique alterations in the physico-chemical properties of riverine ecosystems (Pradhan et al. 2009). These seasonal changes affect the distribution of nutrients and dissolved gases, which in turn influence biological productivity and the species composition of the river.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCA analysis indicated the importance of water chemistry, such as pH and total alkalinity in determining primary axis of water quality variation (Saalidong et al. 2022). \u0026nbsp; The dominance of these parameters suggests that river\u0026rsquo;s buffering capacity and its ability to neutralize acidic inputs are critical to maintaining its ecological balance. Additionally, the significant presence of NO\u003csub\u003e2\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e and TDS as influential contributors highlights the role of nitrogen compounds (Vorobyeva et al. 2021) and dissolved solids in shaping water quality profile and its biological productivity. Excess nitrogen in aquatic ecosystems can lead to eutrophication, which disrupts aquatic food webs and reduce biodiversity (Dodds and Smith 2016).\u0026nbsp;Furthermore, water temperature also emerged as a critical abiotic factor influencing Dim2. Relatively smaller contributions of other variables to Dim2 indicate their secondary importance in explaining water quality variation.\u003c/p\u003e\n\u003cp\u003eThe study revealed a total of 69 fish species, distributed across 20 families and 46 genera, indicating significant diversity of freshwater fishes comparable to other major river systems in India (Sarkar et al. 2010; Shukla and Bhat 2017). Highest number of species was recorded along the upper stretch of river at S1 (54), while the least was observed along the lower stretch at S4 (37). The upper stretch (S1) is located within the Intangki National Park, an authorized biodiversity conservation area. This site is restricted from anthropogenic interference and features a pristine ecosystem with high diversity, contributing to the observed richness and diversity of fish species. Conversely, the lower stretch (S4) near Dimapur town showed significant declines in fish diversity. This decline can be attributed to the deterioration of environmental variables, as recorded in the study (Table 3), along with the decline in structural habitat complexity, and the increased human habitation and activities observed during downstream sampling. Poor environmental parameters (lower DO, higher NH₃ and higher CO₂) (Anon 2019) along with increased anthropogenic pressure (e.g. pollution, over exploitation etc.) may have negatively impacted fish species richness, diversity, distribution and relative abundance. These findings are consistent with previous studies showing that degraded water quality and habitat deterioration adversely affect freshwater fish populations (Anon 2019; Dudgeon et al. 2006). Typically, in riverine systems species richness, diversity, and abundance increase from upper to lower stretches due to broad range of habitats and resources available (Weber and Peter 2007). However, the Dhansiri River exhibited an opposite trend, with species numbers declining from upstream to downstream. The observed spatial variation in diversity, number, and distribution of fish species is attributed to several factors, including natural topography, environmental influencers (Hashemi et al. 2015), pollution (Anon 2019), habitat complexity (Smokorowski and Pratt 2007), reduced water quality and increased anthropogenic pressures, which limit the suitability of downstream habitats for diverse fish communities (Table. 3) (Lakra et al. 2010; Pandey and Radhakrishnan 2022).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeasonally, a higher number of fish species was observed in the Dhansiri River during monsoon at all stations, with the exception of S2 (pre-monsoon). Water discharge has been identified as the single most important factor driving fish species richness in Himalayan rivers (Bhat et al. 2012). Increased water discharge during monsoon creates new habitats and improves connectivity between different habitats and sections of the river, facilitating fish migration and colonization of new areas, thereby increasing likelihood of encountering higher number of species. Higher number of fish species observed at S2 during pre-monsoon may be attributed to increased natural food availability (Acharjee and Barat 2014). Previous studies across rivers in south and Southeast Asia have consistently reported cyprinids as most dominant group of fishes (Bhat 2003). The results of this study, which observed that cyprinids exhibit the highest relative abundance compared to other groups is a testimony to this statement. Cyprinids dominate fish community structure in tropical Indian rivers owing to their high adaptive variability and ability to occupy heterogeneous habitats (Johnson and Arunachalam 2009).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDiversity indices in general are functions of different species available in an ecosystem and relative abundance of each species. Shannon diversity index is widely used to quantify diversity or richness of species in a specific ecological community and is one of the most commonly employed indices for comparing species diversity across habitats (Clarke and Warwick 2001). Margalef richness index is a biodiversity metric used to assess species richness in an ecological community (Margalef 1958). Simpson dominance index assesses the dominance or evenness of species abundances within an ecological community (Simpson 1949). On a spatial scale, values of \u0026lsquo;H\u0026prime;\u0026rsquo;\u0026nbsp;and \u0026lsquo;d\u0026rsquo; were highest in pristine upper stretch (S1) with a gradual decline downstream. Conversely, values of \u0026lsquo;D\u0026rsquo; increased from upstream to downstream, indicating a higher dominance of fewer species. Highest values of \u0026lsquo;H\u0026prime;\u0026rsquo; (3.750) and \u0026lsquo;d\u0026rsquo; (9.875) and lowest value of \u0026lsquo;D\u0026rsquo; were observed during monsoon at S1, highlighting a high level of species richness and uneven distribution. This aligns with established ecological principles, as fish typically\u0026nbsp;migrate, spawn and recruit during monsoon, leading to increased diversity and abundance in the ecosystem (Sreekanth et al. 2016). Restricted human interference by virtue of location and congenial habitat might be major factors for migration and breeding of fish during monsoon, leading to higher fish diversity and low dominance at S1. Pielou\u0026apos;s evenness index quantifies the distribution of species within a community, providing a measure of how evenly individuals are spread across species. The index ranges from 0 to 1, where 0 represents maximum species dominance (only one species present), and 1 represents maximum evenness (all species are equally abundant) (Pielou 1966). In this study, it was observed that upper stretch (S1) has an even distribution of fish species, followed by S4. It should be noted that instances of high abundance in certain species may result in a deviation from evenness in overall species diversity (Saha et al. 2022), which might be one of the possible reasons for lower evenness in S2 and S3.\u003c/p\u003e\n\u003cp\u003eCumulative dominance curve (\u003cem\u003ek\u003c/em\u003e-dominance), which ranks fish species based on their abundance and the proportion of individuals per species, plotted against the logarithmic rank of species (Clarke 1990). The curved showed S4 as least diverse site, with a steep dominance curve indicating a few species dominating the community. Concept of species richness is commonly utilized as an indicator of environmental quality, as it tends to rise in presence of healthy ecosystems and minimal anthropogenic impairment (Roth et al. 2000; Kirk and Rahel 2022). Conversely, a decrease in species richness accompanied by proliferation of a few dominant species indicates a progressively deteriorating environment (Jacinto et al. 2023). It is important to note that freshwater assemblages are not solely affected by species zonation or spatial arrangement, but also shaped by physical disturbances, and habitat modifications (Daufresne and Boet \u0026nbsp;2007; Perkin et al. 2015). NMDS is an ordination technique used to visualize the similarity between samples based on ecological data. In the present study NMDS analysis revealed a clear separation of S4 from the other three stations. As per guidelines forwarded by Clarke (1993) stress values \u0026lt; 0.05 are considered excellent; \u0026lt; 0.10, good; \u0026lt; 0.20, useable; and\u0026nbsp;\u0026gt; 0.20, not reliable. Lower the stress value, better the fitting in ordination plot. In the present study, a stress value of 0.07 indicates a good fit for the distances/dissimilarities in the spatial ordination plot.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEnvironmental factors play a crucial role in maintaining fundamental habitat characteristics and ecosystem functions, and they are known to significantly influence fish community structure in aquatic systems (Mondal and Bhat 2020; Debnath et al. 2022). Understanding the impact of environmental influencers on fish communities is essential for elucidating fish-habitat relationships, which can contribute to more effective ecosystem management and preservation (Gillooly et al. 2001; Wang and Lyons 2003; Li et al. 2018).\u0026nbsp;BIO-ENV analysis found strong correlations between environmental parameters, fish abundance and composition, with NH\u003csub\u003e3\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e,\u0026nbsp;CO\u003csub\u003e2\u003c/sub\u003e, TDS, TA, pH, specific conductivity, DO and WT\u0026nbsp;being the most influential factors. Highest degree of correlation with fish abundance was observed in the combinations of NO\u003csub\u003e3\u003c/sub\u003e,\u0026nbsp;CO\u003csub\u003e2\u003c/sub\u003e and TDS.\u0026nbsp;Environmental variables affects fish abundance and composition both directly or indirectly by influencing dynamics of fish food organisms such as plankton (Gogoi et al. 2019) and aquatic invertebrates (Das et al. 2022). WT is one of the critical influencers that affect distribution of fishes, both directly by influencing their metabolic and physiological processes (Gillooly et al. 2001) and indirectly by affecting biological productivity and food matter availability (Sarkar et al. 2021). Additionally, TDS, TA and pH have been shown to reportedly influence chlorophyll contents in rivers (Sarkar et al. 2021), which are closely associated with productivity and the availability of food sources, thereby affects fish distribution.\u0026nbsp;Similarly, NH\u003csub\u003e3\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e,\u0026nbsp;CO\u003csub\u003e2\u003c/sub\u003e are also associated with biological productivity of aquatic ecosystems (Galloway et al. 1994; Sigman and Hain 2012) and can directly influence fish community structure. Parameters like pH, WT, TDS, NO\u003csub\u003e3\u003c/sub\u003e, DO are known to influence dynamics of fish food organisms (Gogoi et al. 2019; Das e al. 2022), which in turn affects distribution of fishes. Furthermore, DO, pH,\u0026nbsp;NH\u003csub\u003e3\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e,\u0026nbsp;CO\u003csub\u003e2\u003c/sub\u003e, TA have direct effects on fish metabolism, which may influence their distribution and abundance (Boyd and Tucker 1998). It is to be noted that, DO is the single most critical parameter for the survival of all forms of aquatic life (Keke et al. 2016) and it therefore exerts influence on fish communities. Managing adequate DO levels is essential for sustaining healthy fish populations and preserving the overall balance of aquatic ecosystems.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe present study highlighted the impact of human activities, particularly at S4 near Dimapur town, as evidenced by reduced species richness, higher dominance of fewer species, and poorer water quality parameters. The presence of higher concentration of NH₃, NO₃ and CO₂ at S4 reflects inputs from agricultural runoff, urban wastewater and industrial discharges, all of which contribute to the degradation of Dhansiri River ecosystem. The finding of this study underscore the need for implementation of effective regulation and management measures to protect this Dhansiri River\u0026rsquo;s biodiversity, particularly in downstream areas. Establishing buffer zones, improving wastewater treatment and controlling agricultural runoff are critical steps towards mitigating the negative impact of anthropogenic activities (Hughes et al. 2018). Additionally, the presence of several species listed as Near Threatened and Vulnerable highlights the importance of targeted conservation efforts. Protecting critical habitats, especially in the upper stretches of the river, is essential for maintaining the ecological integrity of the entire system. Further research on the population dynamics of these threatened species is necessary to inform conservation strategies and ensure their long-term survival. As previously mentioned, environmental aspects participate crucially in shaping fish communities. Given the current state of rapid urbanization and climate change, it is imperative that we gain critical insights into ecological mechanisms affecting fish communities in order to develop effective protection and conservation strategies. The present study, conducted in a least-explored tropical river from a globally significant biodiversity hotspot, contributes to our knowledge and understanding, providing cues for sustainable riverine fisheries management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProcedures and activities performed during the study period involving animals were in agreement with ethical standards of the institution. Sampling was performed after due approval from Institute Research Committee (IRC) of ICAR-Central Institute of Fisheries Education.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement on ‘Authors contributions’\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed in preparing the manuscript through designing of study, sampling methodology, data collection, data analysis, drafting and revision of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSO, major contribution in writing, data collection; ATL, overall guidance, supervision, manuscript writing and revision and facilitation; KR, data analysis, manuscript writing and methodology; SB, conceptualization, major contribution in writing, data analysis and methodology; JB, data collection, taxonomy; SKM, manuscript correction and facilitation; NC, Data analysis and graphs, contribution in manuscript writing and revising; BKD, overall guidance, manuscript correction and facilitation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors\u0026nbsp;\u003c/em\u003eare thankful to the Indian Council of Agricultural Research, New Delhi for financial support to carry out the research work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no conflicts of interest in the research activity and in data presented in the manuscript. Further\u0026nbsp;\u003cem\u003ethe authors declare that they have no relevant financial or non-financial interests to disclose.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe data generated in the present study have been submitted to ICAR-CIFE data repository and can be obtained from the Institute through proper channel and with due permission from competent authority. \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial and financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors are grateful to the Director, ICAR-CIFE, Mumbai for providing necessary facilities to carry out the research work. The first author thankful to the Director, ICAR-CIFRI, Barrackpore, Kolkata for providing necessary laboratory facilities and valuable guidance for completing the research work. The authors also thankful to the fisher community of river Dhansiri River, Nagaland, India.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue consent has been taken from all authors prior to preparation of the manuscript and all have agreed to participate in the manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have given their consent to submit the manuscript for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAcharjee B, Borah P, Das M, Purkayastha J (2012) Ichthyofaunal diversity of Dhansiri River, Dimapur, Nagaland, India. 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Aquac Fish 7(6): 693-702\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aquatic-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aqsc","sideBox":"Learn more about [Aquatic Sciences](http://link.springer.com/journal/27)","snPcode":"27","submissionUrl":"https://submission.nature.com/new-submission/27/3","title":"Aquatic Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Fish assemblage, Ecology, Spatio-temporal diversity, Himalayan River, Sustainable fisheries","lastPublishedDoi":"10.21203/rs.3.rs-5340746/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5340746/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnvironmental characteristics significantly influence the distribution of fish communities in aquatic ecosystems. This study examined the relationship between fish community structure and ecological characteristics in the Dhansiri River, a tropical river within the Eastern Himalaya eco-region. Sampling was conducted across three seasons (monsoon, pre-monsoon and post-monsoon) at four stations representative of the whole river stretch. Highest number of species was recorded along upper stretch S1 (54), followed by S2 (45), S3 (41) and least in S4 (37). Seasonally, the number of species peaked during monsoon (64), decreased in post-monsoon (59) and was lowest in pre-monsoon (54). Shannon diversity index (H') ranged from 3.327 to 3.750, with higher values upstream and gradually declining downstream. Species diversity was lowest at S4, likely due to poor environmental conditions and high anthropogenic pressure. Cyprinids emerged as the most dominant fish group, with relative family abundance varying from 0-5.63%. Non-metric dimensional scaling indicated a distinct separation of S4 from S1, S2 and S3. Analysis of water quality revealed a pristine nature at S1, with gradual deterioration downstream. Significant relationships were identified between most water quality variables and fish community structure. Principal component analysis showed that pH (20.96%), total alkalinity (13.80%), specific conductivity (9.92%), NO\u003csub\u003e2 \u003c/sub\u003e(12.19%), and TDS (6.22%) contributed significantly to Dim1, while NO\u003csub\u003e3\u003c/sub\u003e (53.43%) and water temperature (6.05%) influenced Dim2. BIO-ENV analysis reflected that NH\u003csub\u003e3\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, TDS, total alkalinity, pH, specific conductivity, DO and water temperature significantly correlated with fish abundance and community composition. This study provides critical insights into the role of environmental parameters in shaping the fish community structure in a less-explored tropical river of the Eastern Himalayan and offers valuable information for the sustainable management of riverine fish diversity.\u003c/p\u003e","manuscriptTitle":"Fish community structure in accordance with environmental signatures in tropical river ecosystem, Eastern Himalayan eco-region","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-06 09:31:20","doi":"10.21203/rs.3.rs-5340746/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-03T15:36:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-18T11:43:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33620123354877085913004332584356261852","date":"2024-11-04T13:32:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35483223100386158645012770776361154700","date":"2024-10-31T06:57:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-30T08:00:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-28T08:53:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-27T14:04:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aquatic Sciences","date":"2024-10-27T09:57:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aquatic-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aqsc","sideBox":"Learn more about [Aquatic Sciences](http://link.springer.com/journal/27)","snPcode":"27","submissionUrl":"https://submission.nature.com/new-submission/27/3","title":"Aquatic Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4c9f27ca-154e-417d-91b8-a6c9e6951473","owner":[],"postedDate":"November 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-10T16:11:17+00:00","versionOfRecord":{"articleIdentity":"rs-5340746","link":"https://doi.org/10.1007/s00027-025-01169-z","journal":{"identity":"aquatic-sciences","isVorOnly":false,"title":"Aquatic Sciences"},"publishedOn":"2025-02-05 15:57:33","publishedOnDateReadable":"February 5th, 2025"},"versionCreatedAt":"2024-11-06 09:31:20","video":"","vorDoi":"10.1007/s00027-025-01169-z","vorDoiUrl":"https://doi.org/10.1007/s00027-025-01169-z","workflowStages":[]},"version":"v1","identity":"rs-5340746","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5340746","identity":"rs-5340746","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}