Journal of Threatened Taxa | www.threatenedtaxa.org | 26 December 2021 | 13(14): 20190–20200

 

ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print) 

https://doi.org/10.11609/jott.7554.13.14.20190-20200

#7554 | Received 02 July 2021 | Final received 10 October 2021 | Finally accepted 01 December 2021

 

 

Ichthyofaunal diversity with relation to environmental variables in the snow-fed Tamor River of eastern Nepal

 

Jawan Tumbahangfe 1, Jash Hang Limbu 2, Archana Prasad 3, Bhrarat Raj Subba 4 & Dil Kumar Limbu 5

 

1,3 Central Department of Zoology, Tribhuvan University, Kirtipur Kathmandu Nepal.

2,5 Central Campus of Technology, Department of Biology, Tribhuvan University, Dharan, Nepal.

2,4 Nature Conservation and Health Care Council (NCHCC), Biratnagar, Nepal.

1 jawansubba37@gmail.com, 2 limbujash@gmail.com (corresponding author), 3 archanaprasad001@gmail.com,

4 subbabharatraj@gmail.com, 5 dilklimbu@gmail.com

 

 

 

Editor: Mandar Paingankar, Government Science College Gadchiroli, Maharashtra, India. Date of publication: 26 December 2021 (online & print)

 

Citation: Tumbahangfe, J., J.H. Limbu, A. Prasad, B.R. Subba & D.K. Liimbu (2021). Ichthyofaunal diversity with relation to environmental variables in the snow-fed Tamor River of eastern Nepal. Journal of Threatened Taxa 13(14): 20190–20200. https://doi.org/10.11609/jott.7554.13.14.20190-20200

 

Copyright: © Tumbahangfe et al. 2021. Creative Commons Attribution 4.0 International License.  JoTT allows unrestricted use, reproduction, and distribution of this article in any medium by providing adequate credit to the author(s) and the source of publication.

 

Funding: This study has not received any specific funding.

 

Competing interests: The authors declare no competing interests.

 

Author details: Jawan Tumbahangfe is a PhD student at Tribhuvan University’s Central Department of Zoology in Kirtipur, Kathmandu, Nepal, with research interests in reproductive biology, molecular biology, stream ecology, and water quality indicators. Jash Hang Limbu is a program coordinator for the Nature Conservation and Health Care Council (NCHCC) and works at the Central Campus of Technology, Department of Biology, Tribhuvan University, Hattisar, Sunsari district, Dharan, Nepal. Molecular taxonomy, phylogeny, molecular ecology, and conservation ecology are among his study interests. Archana Prasad’s research interests include herbal pesticide, malathion and drug effect on the tissue at cellular level and subcellular level. Bharat Raj Subba’s research interest’s include ichthyology and ornithology. Dil Kumar Limbu’s research interests include Himalayan Rangeland ecology.

 

Author contributions: JT, JHL and DKL performed field surveys, collected data and prepared the manuscript. AP and BRS supervised the research and provided inputs on manuscript preparation. JHL analyzed the data.

 

Acknowledgements: The authors express sincere gratitude to Prof. Dr. Tej Bahadur Thapa, HOD, Central Department of Zoology (CDZ), Tribhuvan University for his continuous suggestions and inspiration. We are thankful to Post Graduate Campus, Biratnagar for providing laboratory facilities. We are also thankful to Ms. Jyoti Karna, Ms. Kesika Shrestha, Mr. Ram Bahadur Shrestha, and Mr. Man Kumar Shrestha for their valuable help during field visits.  We are thankful to Mr. Asmit Limbu for mapping.

 

 

 

Abstract: Tamor River in eastern Nepal supports diverse hill stream fishes. From winter, spring, summer, and autumn of 2020, we investigated the ichthyofaunal diversity with environmental variables in the snow-fed Tamor River covering four seasons (winter, spring, summer, and autumn) and field surveys were carried out in January, April, July, and October 2020. We used two cast nets of different sizes, one with a mesh size of 2 cm, 6 m diameter and 6 kg weight and another having 0.5 cm, 3 m diameter and 2 kg weight. In addition, monofilament gill nets with mesh sizes of 6, 8, and 10 were used for fish sampling. A total of 6,373 fish individuals representing 28 species belonging to three orders, seven families, and 16 genera were recorded. One-way permutational multivariate analysis of variance (perMANOVA) on the Non-metric Multidimensional Scaling (NMDS) showed no significant (P >0.05) difference between winter, spring, and autumn season but summer season showed significant (P <0.05) difference from winter, spring, and autumn seasons. Furthermore, one-way analysis of variance on redundancy analysis (RDA) vindicated that among the selected parameters, pH, air temperature and total hardness were the influencing factors (P <0.05) to determine the fish community structure in Tamor River.

 

Keywords: Field survey, fish diversity, hill-stream, multivariate, spatio-temporal.

 

 

INTRODUCTION

 

Fish community structure, which is regionally diverse and seasonally varied, is often influenced by many environmental variables, as well as biotic interactions like competition and predation (Gorman 1988; Harvey & Stewart 1991; Grossmann et al. 1998; Frelat et al. 2018; He et al. 2020). Habitat variables such as water temperature, depth (Kadye et al. 2008; Hossain et al. 2012; Li et al. 2012), water velocity (Yu & Lee 2002; Arvendo & Ramirez 2017; Limbu et al. 2019), stream width (Gerhard et al. 2004), substrate, altitude, conductivity (Yu & Lee 2002; Kadye et al. 2008; Yan et al. 2010), dissolved oxygen, pH, free-carbon dioxide (Limbu et al. 2019; Prasad et al. 2020) and climate (Magalhaes et al. 2002) have all been shown to affect fish assemblages. However, changing environmental parameters can affect biotic communities in multiple ways and influence the function of ecosystems (McGill et al. 2006; Conversi et al. 2015). Environmental variables are reported to shape the spatial distribution of species (Perry et al. 2005; Vieira & Garro 2020) and influence the temporal variation of communities (Rouyer et al. 2008; Vieira & Garro 2020).

The spatial and temporal variations of the fish community structure in rivers and streams of eastern Nepal are poorly understood (Limbu et al. 2019; Adhikari et al. 2021). However, some of the important studies done in  eastern Nepal’s rivers and streams include (Shrestha 2009; Shrestha 2016; Shah 2016; Subba et al. 2017; Limbu & Prasad 2017, 2020; Limbu et al. 2018, 2019, 2020). Some outlook of the fisheries and fish ecological studies such as their diversity, spatial & seasonal distribution, and plenty in rivers of Nepal are needed (Mishra & Baniya 2017). To better understand, manage, and conserve (Ngor et al. 2018), and also to know the status (Limbu et al. 2019) of the fisheries, there is an urgent need to update the information on the spatial and temporal fish diversity, community structure and distribution patterns (Ngor et al. 2018).

Thus, the present study aimed to understand relationships among spatio-temporal variation in fish and environmental variables of Tamor River, to reduce the gap in the information and hence dilate the fish diversity profile of Nepal. The present study hypothesized that fish numbers in the Tamor River would be greater during the annual dry season when water current and volume are reduced. We also hypothesized that fish assemblage structure would vary between seasonal variation defined by environmental variables.

 

MATERIALS AND METHODS

 

Study area

Tamor River lies in eastern Nepal, which begins around Kanchenjunga. The Tamor and the Arun join the Sunkoshi at Tribeni Ghat to form the giant SaptaKoshi which flows through Mahabharat range (Shrestha 2009). It lies in the latitude and longitude co-ordinates of 26.913o N and 87.1570 E respectively. The total length of this river is about 190 km with 5,817 km catchment area (Shrestha et al. 2009). The study area has connections with four districts, i.e., Taplejung, Panchthar, Terathum, and Dhankuta. Boulders, pebbles, sand, and gravels were the major characteristic features of this river.

 

Data collection, Identification and Preservation

Fish sampling was done in winter, spring, summer, and autumn (January, April, July, and October) of 2020. It started on the 15th and continued to the 30th of the selected months. We made 28 samples at seven stations, namely, (SA) Kabeli Dovan, (SB) Hewa Dovan, (SC) Nawa Khola Dovan, (SD) Chharuwa Dovan, (SE) Yakchana Ghat, (SF) Mulghat, and (SG) Triveni with fish sampling carried out between 0700 and 1100 h.  We used two cast nets of different sizes, one with mesh size of 2 cm, 6 m diameter, and 6 kg weight and another with 0.5 cm mesh size, 3 m diameter, and 2 kg weight. Cast netting was carried out covering 150–200 m (Limbu et al. 2021) across each station and all possible habitats were covered. In addition, monofilament gill nets with mesh sizes of 6, 8, and 10 were used to capture the fish. In each station, nine gill nets were left late in the evening (1700–1800 h) and taken out early in the morning (0600–0700 h) in a sampling distance of 150–200 m.

The collected fish were photographed in a fresh condition and identified in the field and if not, then the voucher specimens were preserved in 10% formalin. After the photography, the remaining samples were returned to their own natural habitat from where they were captured. Fishes were identified with the help of standard literature (Talwar & Jhingran 1991; Jayaram 2010; Shrestha 2019) and other available standard literature. The environmental variables were examined during field visit following the standard methods of American Public Health Association (APHA 2012). Water temperature, dissolved Oxygen (DO), pH, total hardness, water velocity, conductivity, alkalinity, and free carbon-dioxide (CO). Water temperature (0C) was measured with a digital thermometer by placing it in the water at a depth of 0.3 m. DO (mg/l) was measured by the Winkler titrimetric method. pH was measured using a pH meter (HI 98107, HANNA Instrument). Total hardness (mg/l) was determined using EDTA titrimetric method. Water velocity (m/s) was measured by the float method with the help of a stop watch, small ball and measuring tape. Titration method was used to measure the alkalinity (mg/l). Free carbon dioxide (mg/l) was measured by the titrimetric method using phenolphthalein as an indicator.

 

Data analysis

One-way analysis of variance (ANOVA) was used for temperature, pH, dissolved oxygen, hardness and water velocity to calculate the existence of any differences between space and time spectrum. A post-hoc Tukey HSD test was used to test which means were significantly different at a 0.05 level of probability (Spjøtvoll & Stoline 1973). The diversity of the fish assemblage was quantified in the first step of data processing, and then statistical comparison was performed (Appendix I). Fish abundance data were subjected to various diversity indices (Shannon, Simpson, an evenness). All three diversity indices were generated using data from the four seasons (in each season seven samples were made, SA–SG) and seven stations (in each station four samples were made, winter, spring, summer, and autumn), and were used directly in the analysis (Yan et al. 2010) for each fish community sample according to Magurran (1988). Shannon diversity index (Shannon & Weaver 1963) considers both the number of species and the distribution of individuals among species. The Shannon diversity was calculated by following formula:

       s

H = ∑                Pi * logPi

       i = 1

where S is the total number of species and Pi is the relative cover of ith of species.

The dominance index (Harper 1999) was calculated by using following formula:   

D = ∑i -(  ni ) 2

                n

where ni is number of individuals of species i.

Evenness index (Pieleu 1966) was determined by the following equation:

E= H’/ log S

where, H’= Shannon-Weiner diversity index

S= Total number of species in the sample.

 

All of the sample (28) was used in the multivariate analysis, and no species or environmental variables were excluded (Appendix I & II). Collected fish abundance and determined environmental variables were used directly in the multivariate analysis (Yan et al. 2010; Hossain et al. 2012; Vieira et al. 2020)

One-way permutational multivariate analysis of variance (perMANOVA) (Clarke 1993) was used to test the significant difference among the spatial and temporal scales of the collected fish data. To visualize the major contributing species both to space and time, similarity percentage (SIMPER) (Clarke 1993) analysis was performed.

Detrended correspondence analysis (DCA) (Hill & Gouch 1983) was used to investigate the relationship between fish community structure and environmental variables. The eigen value (0.13) and axis length (1.17) obtained from DCA suggested that the linear model associated with RDA was more applicable. Therefore, a direct multivariate ordination method (Legendre & Legendrem 1998) based on a linear response of species to environmental gradients was applied. In addition, using non-metric multi-dimensional scaling analysis (NMDS), the relationships between assemblages from each station and seasons are graphically depicted (Clarke & Warwick 2001).

 

 

RESULTS AND DISCUSSION

 

Fish Community structure

A total of 6,373 fish individuals representing 28 species belonged to three orders, seven families, and 16 genera were recorded during the investigation period (Table 1). Among these, Cypriniformes comprise most of the species with 78.57%, followed by Siluriformes 17.86%, and Anguilliformes with 3.57%. Cyprnidae was the most abundant family which contributed 46.14%, followed by Sisoridae 18%, Cobitidae 10.7%, Danionidae 10.7%, Botiidae 7.14%, Anguillidae 3.5%, and Psilorhynchidae 3.5% (Figure 2). The Cyprinidae was the most species rich family (13 species), followed by Sisoridae (5 species), Danionidae (3 species), Cobitidae (3 species), Botiidae (2 species), Psilorhynchidae and Anguillidae with single species. An environmental impact assessment (EIA) study for the Tamor Hydropower Project has reported the presence of 19 fish species in Tamor River (Swar & Shrestha 1998) while EIA study of Kabeli Hydropower Project has reported the presence of 21 fish species (Swar & Upadhaya 1998) and fish diversity study reported 30 species in Tamor River (Shrestha 2009). The diversity in terms of number (28 species) observed in the present study was nine species greater than Swar & Shrestha (1998), seven species greater than Swar & Upadhaya (1998). It’s possible that this is due to the preceding report’s limited scope of research. Furthermore, the species diversity may be influenced by fishing gear selectivity and survey efforts. As a result, the current investigation identified a greater number of fish species. But the present study reported two species lower than Shrestha et al. (2009). It might be due to riparian loss, deforestation, river corridor engineering, dams and water diversion, aquatic habitat loss and fragmentation (Dudgeon et al. 2006; Limbu et al. 2021). Ongoing road development, micro-hydropower generation, poisonous herbicide use, illegal electro-fishing, deforestation, and water diversion are all found to be major threats to the current fish species of Nepal’s hillside rivers and streams, according to Limbu et al. (2021) and Adhikari et al. (2021).

Garra nasuta, Botia Dario, Schistura rupecula, Schistura multifaciata, and Pseudecheneis crossicauda, according to local fishermen, have suffered a serious drop in population and are not detected in our collection. The most abundant and species-rich order and family, respectively, were Cypriniformes and Cyprinidae. This is in line with the results of previous studies conducted in Nepal’s various rivers and streams. For instance, Subba et al. (2017), Limbu et al. (2018, 2019, 2020), GC & Limbu (2020), Limbu & Prasad (2020), Prasad et al. (2020, 2021a,b), Chaudhary et al. (2020) from Tamor, Triyuga, Dewmai, Melamchi, Morang district, Damak, Ratuwa, eastern Nepal, Nuwa Babai River, River Andhi Khola, Seti Gandaki, West Rapti and Betani River. Nelson (2007) also stated that the majority of the fish in the river belong to the Cypriniformes order, which includes 2,422 species of freshwater fish.

Results from the similarity percentage analysis (SIMPER), 64.53% similarity were found among the seasons and major contributing species were Labeo gonius (9.72%), Labeo angra (8.46%), Schizothorax richardsonii (5.92%), Opsarius shacra (5.87%), Garra gotyla (5.55%), Pseudecheneis sulcata (5.48%), Labeo dero (5.36%), and Botia lohachata (5.30%). On the contrary, 50.33% similarity were found among the sites and major contributing species were Labeo gonius (7.54%), Labeo angra (6.69%), Schizothorax richardsonii (5.35%), Psilorhynchus pseudecheneis (5.30%), and Pseudecheneis sulcata (5.09%) (Table 2).

The present study reported two mahseer fishes (Tor spp.) representing an iconic genus of large-bodied species of the Cyprinidae family. Throughout southern and southeastern Asia, these species are revered for their religious and cultural significance (Pinder et al. 2019). Despite their economic and cultural importance, Tor fishes have seen their riverine habitats damaged by anthropogenic activities such as hydroelectric dam construction and exploitation, putting their survival in jeopardy. Furthermore, conservation attempts have been hampered by the fact that the genus’ expertise is primarily bent toward aquaculture with significant knowledge gaps on their taphonomy (Bhatt & Pandit 2016; Pinder et al. 2019). The IUCN Red List has classified Tor putitora as an ‘Endangered’ species, whereas Tor tor has been classified as ‘Data Deficient’ (Image 1, 2). Urbanization, poaching, overfishing, and ecological changes in the natural environment’s physical, chemical, and biological qualities, according to local fishermen and consent authority, have severely reduced the population of these species in their native habitat. As a result, the conservation of these species is critical.

 

Diversity status

The Shannon diversity index considers the richness and proportion of each species, while the Evenness and Dominance indices represent the sample’s relative number of individuals and the proportion of common species, respectively (Hossain et al. 2012). Highest Shannon diversity index (2.88) was found at station SB and in summer (3.01) whereas lowest (2.63) was found at SE and in winter (2.56). In contrast, highest Simpson dominance index value was observed at station SA, SB, and SC (0.932, 0.93, 0.93) and in summer (0.94) whereas lowest value was observed at, SG (0.908) and in winter (0.90). Similarly, highest value of evenness index was observed at SB (0.69) and in summer (0.65) whereas lowest value of evenness index was observed at SG and in winter (0.62) (Table 4 & 5). According to Hossain et al. (2012), a high Shannon diversity index is associated with a small number of individuals, whereas a low Shannon diversity index is associated with a large number of individuals. A biodiversity index attempts to classify the diversity of a sample (Magurran 1988) and is easily affected by the number of specimens, sampling size, and ecological factors (Leonard et al. 2006).

 

Fish community structure vs. environmental variables

The result obtained after the redundancy analysis (RDA) was plotted in Figure 3. The first and second axis of the RDA accounted for 76% and 5.6%, respectively. The fish species of Glyptothorax cavia (C12), Garra annandalei (C10), Tor tor (C28), Tarquilabeo latius (C8), Barilius barila (C3), Glyptothorax pectinopterus (C13), Botia lohachata (C7), Bangana dero (C16), Schizothorax richardsonii (C26), Labeo angra (C15), and Labeo gonius (C17) are positively related to water velocity, dissolved oxygen and water temperature but negatively related to pH and alkalinity. Fish species of Bagarius bagarius (C2) and Schizothorax labiatus (C24) are positively related to pH and alkalinity but negatively related to water velocity, DO, and water temperature. In contrast, species of Anguilla bengalensis (C1), Neolissochilus hexagonolepis (C18), Botia almorhae (C6), Barilius bendelisis (C4), Schizothorax progastus (C25), Schistura horai (C22), Glyptothorax telchitta (C14), Schistura savana (C23), Psilorhynchus pseudecheneis (C20), Pseudecheneis sulcata (C19), Garra gotyla (C11), and Opsarius shacra (C5) are positively related to conductivity, free carbon-dioxide and total hardness. One way analysis of variance on redundancy analysis (RDA) vindicated that among the selected parameters, pH, air temperature and total hardness were the influencing factors (P <0.05) to shape the fish community structure.

One-way permutational multivariate analysis of variance (perMANOVA) on the Non-metric Multidimensional Scaling (NMDS) showed no significant (P >0.05) difference between winter, spring, and autumn season but summer season showed significant (P <0.05) differences with winter, spring and autumn seasons. Furthermore, there was no substantial (P >0.05) difference in fish population structure of spatial variation between the various sampling stations.

Edds (1993) and Dubey et al. (2012) observed that the environmental variables such as conductivity, DO, pH, alkalinity, and salinity were most intensely correlated with the fish community composition of the Kali Gandaki River Basin, Nepal, and the Ganga River Basin, India. The most important environmental variables forming the fish assemblage in the Seti Gandaki River Basin were depth, width, conductivity, DO, F-CO2, SiO2 and chlorides. Some other variables such as, pH, PO4 3¡, chlorides and NO3–N were also important in structuring the fish communities (Pokhrel et al. 2018). The role of stream order in deciding the number and abundance of organisms has been clarified (Horwitz 1978; Payne 1986; Leveque 1997). Low temperature as well as other stressing physicochemical conditions are also usual in low order streams at high altitude (Bistoni & Hued 2002).

 

 

Table 1. List of fish collected from Tamor River.

Order

Family

Code

Species

Cypriniformes

Danionidae

 

C3

Barilius barila Hamilton, 1822

 

C4

Opsarius  bendelisis Hamilton, 1822

C5

Opsarius shacra Hamilton, 1822

Cyprinidae

C8

Tarquilabeo latius Hamilton, 1822

C9

Culpisoma garua Hamilton, 1822

C10

Gara annandeli Hora, 1921

C11

Garra gotyla Gray, 1830

C15

Labeo angra Hamilton, 1822

C16

Bangano dero Hamilton-Buchanan, 1822

C17

Labeo gonius Hamilton-Buchanan, 1822

C18

Neolissochilus hexagonolepis McClelland, 1839

C24

Schizothorax labitus McClelland, 1839

C25

Schizothorax progastus McClelland, 1839

C26

Schizothorax richardsonii Gray, 1832

C27

Tor putitora Hamilton, 1822

C28

Tor tor Hamilton, 1839

Psilorhynchidae

C20

Psilorhynchus pseudecheneis Menon & Datta, 1964

Botiidae

C6

Botia almorhae Gray, 1831

C7

Botia lohachata Chaudhauri, 1912

Cobitidae

C21

Schistura beavani Gunther, 1868

C22

Schistura horai Menon, 1952

C23

Schistura savona Hamilton-Buchanan, 1822

Siluriformes

Sisoridae

C2

Bagarius bagarius Hamilton-Buchanan, 1822

C12

Glyptothorax cavia Hamilton-Buchanan, 1822

C13

Glyptothorax telchitta Hamilton-Buchanan, 1822

C14

Glyptothorax pectinopterus McClelland, 1842

C14

Pseudecheneis sulcatus

McClelland, 1842

Anguilliformes

Anguillidae

C1

Anguilla bengalensis Gray, 1832

 

 

Table 2. Average similarity and discriminating fish in each season and station using SIMPER analysis.

Season (64.53%)

Contribution

Stations (50.33%)

Contribution

Contributory species

%

Contributory species

%

Labeo gonius

9.72

Labeo gonius

7.54

Labeo angra

8.46

Labeo angra

6.69

Schizothorax richardsonii

5.92

Schizothorax richardsonii

5.35

Opsarius shacra

5.87

Psilirhynchus pseudecheneis

5.30

Gara gotyla

5.55

Pseudecheneis sulcata

5.09

Pseudecheneis sulcate

5.48

Neolissochilus hexagonolepis

4.98

Bangano dero

5.36

Opsarius shacra

4.98

Botia lohachatta

5.30

Gara gotyla

4.95

Glyptothorax pectinopterus

4.70

Glyptothorax telchitta

4.78

Glyptothorax telchitta

4.51

Labeo dero

4.48

Barilius barila

4.13

Botia lohachata

4.47

Tarquilabeo latius

4.01

Schizothorax progastus

4.26

Psilorhynchus pseudecheneis

3.64

Gara annandalei

4.24

Schistura savana

3.51

Glyptothorax pectinopterus

4.00

Tor tor

3.18

Schistura savana

3.57

Schizothorax progastus

3.05

Barilius barila

3.55

Neolissochilus hexagonolepis

3.00

Opsarius bendelisis

3.5

Gara annandalei

3.00

Botia almorhae

3.49

Opsarius bendelisis

2.88

Tarquilabeo latius

3.33

Botia almorhae

2.53

Glyptothorax cavia

3.3

Schistura horai

2.12

Tor tor

2.5

Glyptothorax cavia

1.97

Schistura horai

2.01

 

 

Table 4. Station-wise fish faunal diversity indices in the snow-fed Tamor River, Nepal.

Station

Shannon Weiner index (H)

Simpson index (D)

Evenness index (E)

SA- Kabeli Dovan

2.82±0.15

0.932±0.012

0.64±0.008

SB Hewa Dovan

2.88±0.13

0.93±0.012

0.646±0.008

SC– Nuwa Khola Dovan

2.87±0.126

0.93±0.01

0.64±0.0075

SD– Chhaurawa Dovan

2.66±0.25

0.91±0.026

0.63±0.018

SE– Yakchana Ghat

2.63±0.307

0.91±0.031

0.63±0.022

SF– Mulghat

2.74±0.209

0.924±0.018

0.63±0.012

SG– Triveni Ghat

2.66±0.29

0.908±0.038

0.62±0.026

 

Table 5. Season-wise fish faunal diversity indices in the snow-fed Tamor River, Nepal.

Season

Shannon Weiner index (H)

Simpson index (D)

Evenness index (E)

winter

2.56±0.21

0.90±0.02

0.62±0.01

spring

2.703±0.12

0.92±0.01

0.63±0.01

summer

3.01±0.02

0.94±0.003

0.65±0.002

autumn

2.74±0.16

0.92±0.01

0.63±0.01

 

For figures & images - - click here

 

 

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Appendix I. Determined values of environmental variables in different seasons and stations.

Stations

Seasons

pH

 

WT

FCO2

DO

ALK

CD

WV

TH

A

Winter

7.1

 

17.6

7

8.6

17

55

1.9

34

B

Winter

7

 

17.8

6.5

9

18

55

2

32

C

Winter

6.5

 

17.5

7

8.7

18

56

1.8

31

D

Winter

7

 

17

5

8

16.5

52

2

29

E

Winter

7.4

 

17.5

6.5

7.9

16.6

53

2.2

23

F

Winter

7.1

 

17.8

6

8.2

16.6

52

2.1

27

G

Winter

6.5

 

17

7

8

15.5

51

1.9

28

A

spring

6.5

 

17.1

5.9

8.6

15.4

52

1.9

30

B

spring

7

 

17.6

6

9

15.4

51

2

36

C

spring

7.2

 

18

6

8.9

17

51.5

1.5

34

D

spring

6.5

 

19

6.4

8.4

17.5

54

1.8

35

E

spring

7.2

 

18.6

7

8

17.5

52.4

2

34

F

spring

7.4

 

18

6

8.4

16

50.1

1.9

36

G

spring

7

 

18.5

7.5

8.6

17

52.3

2

37

A

Summer

6.5

 

18.9

7

8.9

17.5

52

1.8

40

B

Summer

7.8

 

18.4

6

7.9

17.5

53.1

1.7

39

C

Summer

7.7

 

15.9

6.8

8

16.5

53

1.9

38

D

Summer

7.9

 

17

6.9

8.3

16.5

52

1.7

39

E

Summer

7.5

 

19

7

8.6

17

54

1.7

40

F

Summer

7.8

 

18.9

6.8

8.8

18

52

1.6

41

G

Summer

7.6

 

19

7

9

18

53

1.9

39

A

autumn

7.5

 

15

5

8

16

55

2

40

B

autumn

7

 

17

6

9

19

45

2.3

24

C

autumn

8

 

17.5

8

7

18

56

2.5

28

D

autumn

6

 

18

6

8

17

49

2.9

37

E

autumn

7

 

18.3

9

8

16

53

3

35

F

autumn

7.3

 

18

6

9

17

60

2.7

39

G

autumn

8

 

18.5

7

8

15

77

1.6

40

 

 

Appendix II. Fish species recorded from the Tamor River.

Stations

Seasons

C1

C2

C3

C4

C5

C6

C7

C8

C9

C10

C11

C12

C13

C14

C15

C16

C17

C18

C19

C20

C21

C22

C23

C24

C25

C26

C27

C28

A

Winter

0

0

5

11

2

8

6

6

0

15

4

10

5

10

3

0

4

20

2

24

0

0

1

0

12

10

0

0

B

Winter

1

0

4

5

5

6

6

5

0

11

6

15

1

9

1

1

0

8

0

11

0

5

0

2

23

9

1

0

C

Winter

0

0

0

10

9

9

6

1

1

18

9

12

0

3

0

3

0

3

8

23

0

4

0

7

11

8

4

0

D

Winter

0

0

3

11

1

4

4

1

0

5

1

0

1

1

0

8

0

25

9

10

0

1

5

5

9

11

2

0

E

Winter

0

0

5

19

0

12

1

2

2

15

0

0

0

21

3

0

0

24

7

35

0

1

6

0

0

0

0

0

F

Winter

0

0

8

3

0

21

4

3

1

2

10

9

3

6

4

0

1

6

13

9

5

0

11

2

0

1

0

0

G

Winter

0

1

1

0

0

0

0

4

0

26

0

22

8

0

2

5

6

8

1

4

4

0

2

0

2

0

2

1

A

spring

0

0

9

24

0

9

9

8

0

28

8

11

2

19

0

 

0

22

16

19

0

1

0

1

16

15

0

8

B

spring

0

0

3

3

1

12

2

1

0

12

5

16

8

12

1

1

0

13

9

12

0

2

0

6

9

10

3

3

C

spring

0

0

1

7

4

9

14

6

2

9

0

8

6

9

2

6

0

7

13

9

0

0

0

3

12

6

7

12

D

spring

0

0

0

1

1

8

23

3

1

7

0

4

9

5

0

3

0

0

6

16

0

4

1

0

2

3

2

19

E

spring

0

0

3

6

3

1

12

8

0

12

3

8

3

12

0

0

0

12

12

5

0

1

0

0

4

9

0

10

F

spring

0

0

14

10

1

7

9

2

0

1

4

0

1

8