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 |
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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 |