Heliyon 7 (2021) e08478
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Heliyon
journal homepage: www.cell.com/heliyon
Research article
Diversity of fishery resources and catch efficiency of fishing gears in Gorai
River, Bangladesh
Kishor Kumar Tikadar a, Mrityunjoy Kunda b, *, Sabuj Kanti Mazumder c
a
b
c
Department of Fishery Resources Conservation and Management, Khulna Agricultural University, Khulna, 9100, Bangladesh
Department of Aquatic Resource Management, Sylhet Agricultural University, Sylhet, 3100, Bangladesh
Department of Genetics and Fish Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, 1706, Bangladesh
A R T I C L E I N F O
A B S T R A C T
Keywords:
Abundance
CPUE
Catch composition
Margalef's richness index
Pielou's evenness index
Shannon-weaver diversity index
Simpson's index
Gorai River is one of the important rivers in Bangladesh for rich aquatic biodiversity. The river is originated from
the Ganges-Padma River system, a trans-boundary river between India and Bangladesh. Once the river was rich in
fish biodiversity, but due to man-made and natural causes the availability of fish reduced drastically. A
comprehensive analysis of fish diversity indices, gear efficiency, catch composition and decline causes of fish
diversity in Gorai River, Bangladesh was accomplished. The data were collected on monthly basis from January to
December 2018 from three major fishing sites of the river. A total of 62 fish and 2 prawn species under 12 orders
and 24 families were recorded. Cypriniformes was the leading order consisting 27% of the total catch. The mean
values of Shannon-Weaver diversity (H0 ), Simpson's index (1-D), Margalef's richness (d) and Pielou's evenness (J0 )
indices were recorded as, 1.478 0.495, 0.57 0.197, 15.115 4.435 and 0.481 0.152, respectively. At the
similarity of 58.7%, two groups were attained in the cluster analysis and the Non-metric Multidimensional Scaling
(nMDS) showed 40% similarity among the three sites in twelve months based on the Bray-Curtis similarity matrix.
The highest and lowest CPUE were recorded from seine net (5.2 1.72 kg gear 1 haul 1) and hook & long lines
(0.0135 0.0015 kg gear 1haul 1), respectively whereas, highest and lowest gear efficiency were recorded from
lift net (0.321 0.036 kg gear 1person 1hour 1) and fish trap (0.0005 0.0002 kg gear 1person 1hour 1),
respectively. Alternatively, the highest fish catch was recorded on April (21228 464.38 kg) and lowest on
August (3855 138.21 kg). According to the fishermen fish biodiversity of the Gorai River declined day by day
due to overexploitation, destructive fishing practice, pollution, construction of obstacles for fish movement, and
natural causes like siltation. Proper implementation of fish acts and regulations, use of authorized fishing gear,
community-based fisheries management, sanctuary establishment and management, stocking of fish fingerling,
and raising public awareness can play a great role in enhancing and conserving fish biodiversity in the Gorai River
of Bangladesh.
1. Introduction
Bangladesh, with its large river systems, has significant capture
fishery potential and the suitable geographic location of Bangladesh
comes with a large number of fish and other aquatic species (Shamsuzzaman et al., 2017). Total fish production of Bangladesh in 2018 was
4.1 million MT, placing it fourth in open water and fifth in aquaculture
fish production in the world (Mredul et al., 2020). In the face of the
possession of exceptionally productive inland waters of around 45,000
km2, the proceeding with a decline in fish catch progressively undermines the livelihoods of over 12 million fishermen in Bangladesh
(Hossain et al., 2006). Gorai River is one of the most important rivers in
Bangladesh that is originated from the Ganges-Padma River system, a
transboundary river between India and Bangladesh. Once the river was
rich in fish biodiversity and the livelihood of thousands of fishers'
families were fully dependent on Gorai River, but in the recent years
due to many man-made and natural causes the availability of fish was
drastically reduced (Hanif et al., 2016). But very few researches were
conducted on fish biodiversity status of the Gorai River. Therefore, this
study has been conducted to find out the history and present status of
fish biodiversity along with the causes of loss of biodiversity over the
years. The Gorai River ecosystems originated from the Ganges-Padma
River system play a vital role in supporting the biodiversity of fish
fauna and contribute to the supply of animal protein and overall
* Corresponding author.
E-mail address: kunda.arm@sau.ac.bd (M. Kunda).
https://doi.org/10.1016/j.heliyon.2021.e08478
Received 22 June 2021; Received in revised form 15 October 2021; Accepted 22 November 2021
2405-8440/© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
K.K. Tikadar et al.
Heliyon 7 (2021) e08478
fishing gear, effects of fishing gear on fish biodiversity, and total fish
catch of the three study sites?
4. What are the main reasons for fish biodiversity depletion in the Gorai
River of Bangladesh with their solutions and recommendations?
economy of the south-western part of this country through fish production (Hanif et al., 2016; Rahman et al., 2012). All along with the
world, freshwater conditions are encountering genuine dangers of
biodiversity and environmental security and numerous techniques have
been proposed to tackle this emergency (Suski and Cooke, 2007; Sarkar
et al., 2008). In the last few decades, stress caused by anthropogenic
degradation due to urbanization, construction of dams, abstraction of
water for irrigation and power generation, and pollution had many
negative impacts on the biodiversity of freshwater fish species in the
river (Sarkar et al., 2008). Recently, the importance of monitoring
biodiversity in the protected areas has been realized by the developing
countries (Danielsen et al., 2000).
Diversity index provides more information than simply the number of
species present in a particular water body which acts as an important tool
that gives vital information on the scarcity and commonness of species in
a community (Sultana et al., 2018). It is well known that the catch per
unit effort (CPUE) is a measure of stock density, physical and financial
productivity, and an indicator of the efficiency of a fishing operation
(Ghosh and Biswas, 2017). CPUE is a useful index of the abundance and
exploitation of fishery resources to determine the number of fishing units
of a sustainable fishery. CPUE is expected to be proportionate to the fish
population that is utilized as the relative abundance index (Karim et al.,
2019). Assessment of species abundance and biomass usually give an
outline of the population structure that exists in the water bodies (Saha
et al., 2018). There was no study found on CPUE and efficiency of fishing
gear used to catch fish in the Gorai River of Bangladesh. But some researches were conducted on the CPUE and gear efficiency in different
waterbodies of Bangladesh (Ahmed and Hambrey, 2005; Ahmed, 2008;
Galib et al., 2009; Sayeed et al., 2014).
While the loss of biodiversity continues globally (Tittensor et al.,
2014), the need for evidence-based decision-making in the environmental sector is increasingly recognized (Lundquist et al., 2015; Perrings
et al., 2011). Management of open water fisheries has been a problem
confronting all fisheries countries around the world. Fisheries management refers to a bunch of lawful, social, financial, and political game
plans for the management of fisheries at local, domestic and international
levels (Huang and He, 2019). There is a need for greater emphasis on
dialogue and mutual learning between researchers and decision-makers
to increase the policy impact and ultimately the societal impact of
ecological research. This dialogue must include the entire information
generation process through scientific research, policy design, and
implementation. There is also a need for better framing of the
science-policy interfaces (SPIs) to increase transparency, address potential limitations and procedural biases and assess the progress made in
o ver et al.,
such collaborative undertakings (Carmen et al., 2015; Nessh€
2016; Schindler et al., 2016). However, very few efforts have yet been
made to recognize the status of fish diversity of Gorai River with potential effects and declining reasons for fish species.
Hence, it is important to do logical work concerning accessible fishing
gears including their work measure, catch per unit effort (CPUE), gear
efficiencies, catch composition of various angling gear, all-out fish catch,
fish diversity index, and some potential effects in charge of decreasing
fish fauna to speak to pattern information to shield the fisheries decent
variety to close eradication of the river. Considering all the thrust issues,
the objectives of the study were to assess fish assemblages, diversity,
CPUE, gear efficiencies, catch composition of various gears, the significant reasons for the eradication of fish fauna, and find out some recommendations to enhance the fish biodiversity of the Gorai River in
Bangladesh. This study was mainly designed to provide answers to the
following questions:
2. Materials and methods
2.1. Ethical approval
The Ethics Committee of the Department of Aquatic Resource Management, Sylhet Agricultural University, Sylhet, Bangladesh, approved
the specific experimental design.
2.2. Study area and data collection
The study area was including about 50 km of the river area from
Gongaramkhali Ghat of Magura district to Kamarkhali Bazar of Rajbari
District. Three sampling stations named Site 1- Kamarkhali Bazar (23 320
N, 89 330 E), Site 2- Matikata Ghat (23 350 N, 89 300 E) and Site 3Gongaramkhali Ghat (23 350 N, 89 29’ E) were selected for the study
(Figure 1). The study was conducted for a period of twelve months from
January 2018 to December 2018. The study was guided by the data
collected from the direct catch assessment survey (CAS) and fishing effort
survey (FES) conducted at the study sites. The fishing gears were overviewed by direct physical perceptions and dependent on participatory
rural appraisal (PRA), for example, questionnaire interview (QI), focus
group discussion (FGD), and cross-checking of data by key informant
interviews (KII). During the study period, a total of 80 fishermen, 25
Aratders and 40 fish traders were randomly selected for questionnaire
interviews from 7 villages and 5 fish market surrounding the study area.
The questionnaire interviews were done at household, during fishing in
the river, and market places depending on the presence of the fishermen
and fish traders. Focus group discussion (FGD) refers to objective
focusing informal discussions with small groups (6–12) of people,
generally with same vocation or belonging to same level of community. A
total of seven (7) FGD were made from 7 villages of the study area. Each
of the FGD performed with 6–12 members. The participants of the FGD
were fisherman of young, middle and old ages. The QIs and FGDs were
led with a semi-organized and pre-trialed questionnaire.
2.3. Catch assessment and fishing gear survey
Catch assessment information was collected by direct observation of
fish species caught by the fishermen using different types of fishing gear
like seine net, drifting gill net, gill net, lift net, fish trap, hook, and line, and
wounding gear also. Data were collected only from small-scale and artisanal fishermen but not from any fishing industries. Fishing Effort Survey
(FES) and Catch Assessment Survey (CAS) were carried out by using a
vessel from 7 am to 5 pm twice a month throughout the year. Every inspection was done in a similar locality with three replicates. The number of
fishermen catches recorded was not the same in each month because their
number was varying with the types of fishing gear were used to catch fish.
Different types of fishing gear used in different months or seasons to catch
fish. Samples were gathered entirely for little catch and various sub-sample
for huge catch legitimately from fishers during fishing. Weight of fish was
measured by using a digital balance. All out weight of catch, time of
fishing, the span of fishing, individuals connected with each gear, number
of species caught, number of individuals of each species per unit weight,
number of fishing efforts of each gear were recorded. In case of little catch,
the total catch was arranged by the number and weight of every species. A
huge catch was surveyed by taking at least one sub-sample.
1. Which species of fish and prawns are present in the Gorai River of
Bangladesh?
2. Which species are most abundant in the study area?
3. What types of fishing gears and crafts are used to catch fish with their
basic features, mode of operations, CPUE, and gear efficiency of
2.4. Fish abundance and biodiversity status
In this study, the Shannon-Weaver diversity index (H0 ), Simpson's
index (1-D), Pielou's evenness index (J0 ) and Margalef's richness index (d)
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K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Figure 1. Map showing study area in the Gorai River of Bangladesh.
density. The percentage variation was calculated by dividing the Margalef index obtained from the density matrix by the Margalef index obtained from the absolute number matrix (Gamito, 2010).
were calculated on monthly sampling in each site for understanding the
status of fish diversity using the following formulas:
P
Shannon-Weaver diversity index, H' ¼ - Pi ln Pi (Shannon and Weaver, 1949)
Pielou's evenness index, J' ¼ H/ln S (Pielou, 1996)
Where, H’ is the diversity index and Pi is the relative abundance (s/
N), where, s is the number of individuals of one species and N is the total
number of individuals in the sample. The Shannon-Weaver diversity
index is one widely used index for comparing diversity between various
habitats (Clarke et al., 2014). It assumes that individuals were randomly
sampled from an independent large population, and all the species were
represented in the sample (Shannon and Weaver, 1949).
Simpson's dominance index is often used to quantify the biodiversity
of habitat which takes into account the number of species, as well as the
abundance of each species (Vijaylaxmi et al., 2010). The formula used for
calculating is:
P
Simpson's index, 1-D ¼ 1–( n (n–1) / N (N–1)) (Simpson, 1949)
Here, J0 is the similarity or evenness index, S is the total number of
species, ln is the natural logarithm and H0 is the Shannon-Weaver index.
Pielou's evenness index represents the probability that two individuals,
picked independently and at random from a population, will belong to
different species (DeJong, 1975).
2.5. Catch per unit effort (CPUE) and gear efficiency
The catch per unit effort (CPUE) of the angling gears were taken
dependent on the weight of fish discovered amid an angling day (kg
gear 1haul 1) for the various species consolidated and the gear efficiency (kg gear 1person 1hour 1) additionally assessed based on the
weight of fish got and a number of individuals drew in with each fishing
gear per hour.
Where, n ¼ the total number of organisms of a particular species, N ¼ the
total number of organisms of all species.
Margalef's richness index, d ¼ S-1/ln N (Margalef, 1968)
Here, d is the richness index, S is the total number of species and N is
the total number of individuals in the sample. Although it attempts to
mitigate for sampling effects, the Margalef index evaluates species richness and is very sensitive to sample size (Magurran, 2004). The species
richness (total number of species in each sample) and the Margalef index
were computed using either the absolute number of individuals or the
2.6. Statistical analyses
Tabular technique was applied for processing the data by using simple
statistical tools like averages and percentages. Hierarchical agglomerative clustering with group average linking and nonmetric multidimensional scaling (nMDS) were performed to investigate similarities among
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K.K. Tikadar et al.
Heliyon 7 (2021) e08478
formed a single cluster with three stations. However, at 80% similarity,
overlay clusters were observed for August, September, October, and
November with all stations and, another overlay cluster was found in
January, February, and March (except station 1 in March). The individual
and separate clusters were observed for April, May, June, July, and
December with three stations respectively (Figure 4).
stations and months. The community succession at three stations during
12 months was summarized using the submodule of CLUSTER of BrayCurtis similarities from species abundance. The multivariate Cluster
and nMDS analyses were performed using the software PRIMER (Plymouth Routines Multivariate Ecological Research) v7.0.13 (Clarke and
Gorley, 2015). The differences in CPUE, species composition and gear
efficiency of the catch between months and fishing sites were analyzed,
employing analysis of variance (ANOVA) techniques. Tukey's post hoc
tests were used to compare the significant differences (p < 0.05) in the
gear efficiencies of different sites and mean monthly variations of fish
catch. All the data were analyzed by using Origin V9 and Minitab V17
software and the differences were significant at p-values of less than 5%.
3.6. Fishing crafts and gears
About 176 fishing boats were recorded from the study area used by
the fisherman for fishing purpose. Among them 36 were mechanized,
111 were non-mechanized and 29 were small fishing craft (locally known
as talo dingi). The range of diesel engines used for operating the mechanized fishing boat varied from 2 to 40 HP. On the other hand, nonmechanized and small fishing craft operated manually by one or more
fishermen. The range of the length of mechanized fishing craft varied
from 30 to 40 ft. and non-mechanized fishing boats was 20–25 ft. long.
Most of the fishermen used wooden boat for fishing in the Gorai River.
Amidst the time of study, 10 unique gears under 4 categories were found
to operate in the Gorai River. A large portion of the fishing gears was
utilized in the pre-monsoon and after the monsoon and a portion of all
year equips likewise recorded from the sampling area (Table 3).
3. Results
3.1. Fish biodiversity status
During the study period, a total of 62 fish and 2 prawn species under
12 orders and 24 families were recorded. Among these 64 species, 50
species were found in the catch assessment period, but according to the
statement of fishermen and record from Upazila Fisheries Office another
14 species also found in the study area (Table 1). Cypriniformes order
contributed highest (27%, 18 species) in which Cyprinidae family along
contributed 25% (16 species) out of 24 families. According to the IUCN
red list 2015 of Bangladesh, 2 species were critically endangered, 7
species were endangered and 6 species were found as vulnerable.
3.7. Catch composition of different fishing gears
Maximum 50 fish species caught by using seine net where maximum
30.60% fish species were belonging to the Siluriformes order and minimum 2.04% belonging to the Tetraodontiformes order. But in the case of
Drift gill net, there were only one species (Tenualosa ilisha) caught by the
gear belonging to the Clupeiformes order which contributes 100% of the
total fish caught by the drift gill net in the study area (Figure 5). Each
different fishing gear can catch a large variety of species exist in most
fishing grounds in the Gorai River.
3.2. Abundance of ten most available fish species
During the study period, a total of 10 most abundant fish species were
identified among the 64 available fish species (Figure 2). Kachki (Corica
soborna) ranked as the highest with the number of 84061 14378 and
followed by Macrobrachium malcolmsonii (65073 27469), Glossogobius
giuris (7317 2108), Parambassis ranga (7038 1783), Cabdio morar
(5778 1056), Parambassis lala (4930 927), Eutropiicthys vacha (4855
1668), Salmostoma phulo (3327 797), Clupisoma garua (2489 460)
and Gudusia chapra (1976 667). Though these species were found
available in every month of the study period but the intensity of abundance varied with the different months and different sampling sites.
3.8. CPUE and gear efficiency
During the survey period the highest CPUE (kg gear 1 haul 1) was
recorded from seine net 5.2 1.72 kg and lowest CPUE showed by hook
and long lines 0.0135 0.0015 kg in the study area. The maximum
average CPUE 4.59 3.46 kg of all gears and minimum average CPUE
1.09 1.18 kg of all gears was recorded during April and August,
respectively (Figure 6).
The CPUE of the 7 most used frequently available fishing gears in
three different sites of the Gorai River are clarifying in Figure 7. Highest
CPUE was recorded from seine net 5.2 1.72 kg in site-3 and lowest
0.0135 0.0015 kg from hook and long line in site-2.
The monthly variations in gear efficiency (kg gear 1person 1hour¡1)
of frequently used gears and trap in three different sites of the Gorai River
showed in Figure 8. The maximum level of gear efficiency (0.65 kg
gear 1person 1hour¡1) was recorded from the gill net during April and
lowest 0.000897 kg was recorded during May. The maximum average
gear efficiency (0.35 kg) of all gear was recorded during February and
minimum average gear efficiency (0.08 kg) of all gear was recorded on
March and October, respectively.
The gear efficiency (kg gear 1 person 1 hour¡1) of the 7 most used
frequently available fishing gears in three different sites of the Gorai
River are displayed in Figure 9. The average gear efficiency of dhoar, and
hook and line were significantly lower than others (p < 0.05). However,
gear efficiency of a specific gear in three different sites were not significantly different (p > 0.05). A fisherman used 150 to 200 or more dhoar
and 400–500 or more hook to catch fish at a time. Though a single dhoar
or hook can catch a small amount of fish but the total catch of these large
number of dhoar or hook become more or less equal to a gill net or a lift
net. Mainly carnivorous fish species were targeted to catch through dhoar
and hook, and their economic values were not so different from other
species.
3.3. Diversity indices
Diversity was highest (H' ¼ 2.245, 1-D ¼ 0.84) in June and lowest in
September (H' ¼ 0.635, 1-D ¼ 0.21); richness was highest (d ¼ 22.035) in
September and lowest in August (d ¼ 7.033) and the values of evenness
index (J0 ) was recorded highest (J' ¼ 0.769) in August and lowest in
September (J' ¼ 0.239). The mean value of Shannon-Weaver diversity
(H0 ), Simpson's index (1-D), Margalef's richness (d) and Pielou's evenness
(J0 ) indices were recorded as, 1.478 0.495, 0.57 0.197, 15.115
4.435 and 0.481 0.152, respectively (Table 2).
3.4. Cluster analysis
Cluster analysis revealed a clear structural variation in fish communities among the three stations in twelve months (Figure 3). At the
similarity level of 58.7% separation, two major clusters were observed.
The first cluster consists of January, February, March, April, May, June,
and the second cluster consist of July, August, September, October,
November, and December for station 1, station 2, and station 3.
3.5. Non-metric multidimensional scaling (nMDS)
Non-metric Multidimensional Scaling (nMDS) analysis was performed to investigate similarities among fish abundance. nMDS showed
40% similarity for all months, while 60% similarity showed four marked
separations in the fish abundance in different months where only July
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K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Table 1. Present status of fish diversity in the Gorai River.
Order
Family
English name
Scientific name
Present status
IUCN status (BD)
IUCN status (Global)
Beloniformes
Beloniidae
Freshwater gar fish
Xenentodon cancila
A
LC
NE
Clupeiformes
Clupeidae
Engraulidae
Channiformes
Cypriniformes
Channidae
Cobitidae
Cyprinidae
Decapoda
Palaemonidae
Mugiliformes
Mugillidae
Hilsa shad
Tenualosa ilisha
A
LC
LC
Indian river shad
Gudusia chapra
A
VU
LC
Ganges river sprat
Corica soborna
A
LC
LC
Gangetic hairfin anchovy
Setipinna phasa
VR
LC
LC
Spotted snakehead*
Channa punctata
A
LC
LC
Asiatic snakehead*
C. orientalis
R
LC
LC
LC
Snakehead murrel
C. striatus
LA
LC
Giant snakehead*
C. marulius
R
EN
LC
Guntea loach
Lepidocephalichthys guntea
A
LC
LC
Necktie loach
Botia dario
R
EN
LC
Indian major carp
Labeo catla
LA
LC
NE
Indian major carp
Labeo rohita
LA
LC
LC
Indian major carp
Cirrhinus cirrhosus
R
NT
VU
Reba carp
C. reba
A
NT
LC
Carplet/Morari
Cabdio morar
A
LC
LC
Bata
Labeo bata
LA
LC
LC
Black Rohu
L. calbasu
LA
LC
LC
Fine scale razorbelly minnow*
Chela cachius
R
VU
LC
Large razorbelly minnow
Salmostoma bacaila
A
LC
LC
Fine scale razorbelly minnow
S. phulo
A
NT
LC
Mola Carplet
Amblypharyngodon mola
LA
LC
LC
Flaying barb*
Esomus danrica
LA
LC
LC
Cotio
Osteobrama cotio
R
NT
LC
Ticto barb
Pethia ticto
LA
VU
LC
Spot fin swamp barb
P. sophore
A
LC
LC
Olive barb*
Systomus sarana
R
NT
LC
Monsoon river prawn
Macrobrachium malcolmsonii
A
LC
NE
Monsoon river prawn
M. lamarrei
A
LC
NE
Mullet
Rhinomugil corsula
A
LC
LC
Osteoglossiformes
Notopteriidae
Clown knife fish
Chitala chitala
VR
EN
NT
Perciformes
Ambassidae
Elongated glass perchlet
Chanda nama
LA
LC
LC
Parambasis lala
A
LC
NE
P. ranga
A
LC
LC
Climbing perch
Anabas testudineus
LA
LC
DD
Badidae
Badis and Dwarf chameleon fish
Badis badis
R
NT
LC
Gobiidae
Tank goby
Glossogobius giuris
A
LC
LC
Osphronemidae
Honey gourami
Trichogaster chuna
LA
LC
LC
Nandidae
Siluriformes
Highfin glassy perchlet
Indian glassy fish
Dwarf gourami
Trichogaster lalia
R
LC
LC
Mud perch
Nandus nandus
R
NT
LC
Sciaenidae
Pama croaker
Otolithoides pama
A
NE
NE
Bagridae
Day's mystus
Mystus bleekeri
LA
LC
LC
Tengara mystus
M. tengara
A
LC
LC
Striped dwarf catfish
M. vittatus
A
LC
LC
Long whiskered catfish
Sperata aor
LA
VU
LC
Rita
Rita rita
VR
EN
LC
Heteropneustidae
Stinging catfish
Heteropneustes fossilis
LA
LC
LC
Pangasiidae
Yellow tail catfish*
Pangasius pangasius
VR
EN
LC
Schilbeidae
Siluridae
Sisoridae
Batchwa vacha
Eutropiichthys vacha
A
LC
LC
Murius vacha
E. murius
A
LC
LC
Garua Bachcha
Clupisoma garua
A
EN
NE
Gangetic ailia
Ailia coila
LA
LC
NT
Indian potasi
Pachyterus atherinoides
R
LC
LC
Silond catfish*
Silonia silondia
VR
LC
LC
Freshwater shark
Wallago attu
LA
VU
NT
Pabo catfish
Ompok pabo
VR
CR
NT
Dwarf goonch
Bagarius bagarius
VR
CR
NT
Indian gagata
Gagata cenia
A
LC
LC
(continued on next page)
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Heliyon 7 (2021) e08478
Table 1 (continued )
Order
Family
English name
Scientific name
Present status
IUCN status (BD)
IUCN status (Global)
Synbranchiformes
Mastacembelidae
Zig-zag eel
Mastacembelus armatus
A
EN
NE
Barred spiny eel
Macrognathus pancalus
LA
LC
LC
Lesser spiny eel*
M. aculeatus
R
NT
NE
Mud eel*
Monopterus cuchia
R
VU
VU
Tetraodontiformes
Tetraodontidae
Ocellated pufferfish
Leiodon cutcutia
LA
LC
LC
Cyprinodontiformes
Aplochaeilidae
Blue panchax*
Aplocheilus panchax
R
LC
LC
*
Species not found during catch assessment but also reported from local fishermen and UFO. R: rare, VR: very rare A: available, LA: less available, EN: endangered,
CR: critically endangered, VU: vulnerable, NE: not evaluated, NT: near threatened, LC: least concern, DD: data deficient, and EX: exotic species, BD: Bangladesh, IUCN
status (IUCN 2015).
Figure 2. Abundance of 10 most available fish species found in the study area. Values are mean SD.
3.9. Total fish catch in the study area
Table 2. Number of calculated species, individuals, and values of ShannonWeaver diversity, Simpson's index, Margalef's richness and Pielou's evenness
indices in each sampling month.
Month
Number of
species (S)
Diversity,
H0
Simpson's,
1-D
Richness,
d
The month-wise fish catch of three sampling sites of the Gorai River
was recorded by catch assessment method (Figure 10). The highest fish
catch 21228 464.38 kg was recorded from April and lowest 3855
138.21 kg during August. However, the mean monthly fish catch in April
was significantly higher (P < 0.05) from other months.
Evenness,
J0
January’18
21
1.283
0.54
16.371
0.415
February’18
23
1.116
0.41
19.716
0.356
March’18
30
1.619
0.66
17.914
0.476
April’18
31
1.575
0.62
19.052
0.459
May’18
28
1.639
0.69
16.477
0.492
June’18
32
2.245
0.84
13.811
0.648
July’18
22
1.928
0.72
10.894
0.624
August’18
16
2.133
0.82
7.033
0.769
September’18
15
0.635
0.21
22.035
0.235
October’18
16
1.011
0.37
14.842
0.365
November’18
16
1.621
0.61
9.252
0.585
December’18
14
0.930
0.35
13.983
0.352
Average
22
1.478
0.495
0.57
0.197
15.115
4.435
0.481
0.152
3.10. Decline causes of fish diversity in the Gorai River
The threats to fisheries biodiversity can be described under some
interacting categories such as Change of river course, overexploitation of
fisheries resources, destruction of habitat, and water quality deterioration by pollution. Due to the increasing population, overexploitation, use
of illegal fishing gear and fishing pressure is increasing day by day. The
river course was changed because of establishing dam, bridges across the
river. As indicated by the respondents the interacting and combined influences of some natural and man-made causes under these major threat
categories have resulted in a reduction of fisheries biodiversity of the
Gorai River (Table 4).
6
K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Figure 3. Dendrogram of clusters based on Bray-Curtis similarity matrix of different months and stations showing structural variability of the fish communities.
Figure 4. Dendrogram of the species distribution at three stations in twelve months using group average clustering based on Bray-Curtis similarities coordinating nonmatric multidimensional scaling (nMDS) from square root transformed species abundance data of each species.
4. Discussions
findings of Cyprinidae family were also reported from many other rivers
of Bangladesh. In this study area, Cypriniformes order was the most
members compared to the other orders because of the ideal environmental conditions and river bottom that this family prefers (Hanif et al.,
2016).
In this study, 15 fish species were recorded as threatened. Hanif et al.
(2016) recorded 16 species as threatened at the river Gorai and categorized as 7 vulnerable, 7 endangered and 2 species were critically endangered. These findings are more or less similar to the present study.
But Rubel et al. (2016) found 30 species in the Lohalia River of
Bangladesh among which 60% recorded as threatened and categorized as
vulnerable (37%), endangered (17%) and critically endangered (6%).
4.1. Present status of fish biodiversity
In this study a total of 62 fish and 2 prawn species under 12 orders and
24 families were recorded. Among these Cypriniformes order contributed
a maximum of 27% (18 fish species) and the Cyprinidae family
contributed a maximum of 25% (16 fish species). Hanif et al. (2016)
identified Cypriniformes as dominant order with 12 species in the Gorai
River and Sultana et al. (2017) also found Cypriniformes (32.38%) was
the most dominant order and Cyprinidae was the most dominant family
contributing 20 species in wetlands of Chhatak, Bangladesh. Similar
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K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Table 3. Types of fishing gears and period of operation in the study area.
Category
Type of gear
Name of gear
Person engaged
Mesh size (cm)
Target species
Period of operation
Fish net
Seine net
Ber jal
12–14
0.25–1
All
December–June
Jangle jal
10–12
Fine
All
November–May
Gill net
Current jal
1–2
2.5–10
All
Year round
Lift net
Dharma jal
1–2
0–0.5
All
August–November
Drift gill net
Chandi jal
3–4
3–6
Ilish
August–October
Drag net/push net
Thala jal
1
0–0.25
All
Year round
Cast net
Jhaki jal
1–2
0.5–1
All
Year round
Hook & line
Hook & line
Chip borshi
1–2
-
Carnivorous
August–October
Fish trap
Fish Trap
Dhoar
1–2
-
Punti, Baim
April–August
Wounding gear
Wounding gear
Koch/juti
1
-
Large fish
Year round
Figure 5. Percentage compositions of different categories of fish harvested with different fishing gear. FAD: Fish aggregating devices, Td: Tetraodontiformes, Sy:
Synbranchiformes, Sl: Siluriformes, Pr: Perciformes, Os: Osteoglossiformes, Mg: Mugiliformes, Dc: Decapoda, Cp: Cypriniformes, Ch: Channiformes, Cl: Clupeiformes,
Bl: Beloniformes.
These findings are different from the present study due to differences in
geographical location.
Hossain et al. (2009) found jat punti (Puntius sophore), tit punti (Pethia
ticto) followed by chanda (Chanda nama and Parambasis ranga), chapila
(Gudusia chapra) and tengra (Mystus vittatus) as the most dominant species in the Chalan beel of Bangladesh. Galib et al. (2013) recorded jat
punti (Puntius sophore) as the most dominated species in the Halti beel of
Bangladesh. Kamrujjaman and Nabi (2015) documented kalo bujuri
(Mystus tengara), and jat punti (Puntius sophore) as the most abundant fish
species from the Bangshi river of Bangladesh. These results are different
from the present study due to the difference in geographical location of
these water bodies, survey periods, choice of fishing gear, etc.
4.2. Diversity indices
Shannon-Weaver variety (H0 ) index considers each the number of
species and the distribution of folks amongst species of Gorai River.
During the study period, the highest value of H0 was found as 2.245 in
June and the lowest value was found as 0.635 in September. The average
value of the index was recorded as 1.478 (Table 2). In each case of the
Figure 6. Monthly variations in CPUE of different fishing gears employed in the
Gorai River.
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K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Figure 7. Variation of CPUE in three different sampling sites. Values are mean SD.
lowest 0.21 in September with a mean value of 0.57 0.197 (Table 2).
Islam and Yasmin (2018) recorded Simpson's index 0.325 to 0.893 in
Dhaleshwari River, Bangladesh; which was higher than the present
findings.
Margalef's richness is the simplest measure of biodiversity and is
simply a count of the number of different species in a given area. This
measure is strongly dependent on sampling size and effort (Siddique
et al., 2016). In this study, the lowest and highest Margalef's richness
index value was observed as 7.033 in August and 19.716 in February
(Table 2), respectively. Most fish species started breeding from June
when the monsoon start in Bangladesh which might be the purpose in the
back of the lowest and very best richness value during August and
February. As a result, numbers of new individuals joined the fish shares
increased the species richness in winter (Siddique et al., 2016). Islam and
Yasmin (2018) recorded richness index (d) 4.793 to 7.438 on Dhaleshwari River, Galib et al. (2013) calculated fish species richness value
in the Choto Jamuna River of Bangladesh and found values varied from
6.973 in June to 8.932 in November, Jewel et al. (2018) recorded overall
values of richness index (d) in the Atrai River was 5.87. Rahman et al.
(2015) carried out a study on the Talma River and the average values of
richness (d) index was recorded 6.64. The Margalef's index may deviate
from actual diversity value to some extent because it does not confound
the evenness and species richness value properly and it is depending on
sample size (Nair et al., 1988). This might be occurred as a result of
reduced water depth due to lack of rainfall, which disturbed fishermen to
operate their fishing gears more effectively (Iqbal et al., 2015). Besides,
ecological conditions also affected the distribution of the fish species
(Siddique et al., 2016). Construction of several bridges on the river,
heavy river erosion in the monsoon and construction of unruly earthen
dam during lean period for fishing are the main causes for ecological
degradation.
Pielou's evenness index (J0 ) measures the evenness in which individuals is divided among the taxa present (Siddique et al., 2016).
During the study period, the recorded highest evenness (J0 ) value was
found as 0.763 (September) and the lowest as 0.235 (September)
whereas the average value was recorded as 0.481 in the sampling area of
Gorai river (Table 2). Therefore, the species equitability index among the
sampling area and in the different months reveals that the distribution of
fish population of Gorai River is more or less equally distributed. The
values are also close to the findings of Islam & Yasmin (2018); they
recorded evenness index (J0 ) 0.117 to 0.588 in Dhaleshwari River, Jewel
et al. (2018) recorded overall values of the evenness index (J0 ) in the
Figure 8. Monthly variations of gear efficiency of different gears frequently
used in the Gorai River.
highest Shannon-Weaver, diversity index is involved with high individuals and the lowest diversity involved with a low number of individuals. Islam and Yasmin (2018) recorded diversity indices (H0 ) 0.122
to 0.634 on Dhaleshwari River of Bangladesh, Jewel et al. (2018)
recorded overall values of the diversity index (H0 ) in the Atrai River of
Bangladesh were 3.12, Rahman et al. (2015) carried out a study on the
Talma River of Bangladesh and the average values of diversity (H0 ) were
recorded 1.42. So, present study is supported by these findings which are
slightly different from the present findings because of different
geographical locations, survey periods, different fishing methods and
choice of fishing gear. But, Biligrami (1988) recommended better condition of water body for fish diversity when H0 index ranged from 3.0-4.5.
According to this recommendation, Gorai River is strongly degraded
which led to decline the fish diversity. Simpson's dominance index gave
the probability of any two individuals drawn at random sampling from an
infinitely large community belonging to different species. The Simpson
index is therefore expressed as 1-D. It's a species diversity index derived
by Simpson in 1949. Simpson's index is heavily weighted towards the
most abundant species in the sample while being less sensitive to species
richness (Islam and Yasmin, 2018). In the present study, the highest
Simpson Dominance index (1-D) value 0.84 was observed in June and the
9
K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Figure 9. Variation of gear efficiency in three different sampling sites. Values are mean SD.
Figure 10. Month wise variation in fish catch of the Gorai River. Values are mean SD.
72.9% similarity in the Ratargul swamp forest where group A comprises
the fish species of January, February, and March month and group B
contains fish species of April to December month. Hossain et al. (2012)
found two different clusters of fish species at the similarity of 32% in the
Meghna River of Bangladesh. On the other hand, the Multidimensional
Non-metric scaling (nMDS) showed an overall 40% similarity among the
three stations in twelve months. Shamsuzzaman et al. (2016) found 20%
similarities in all seasons in Karnafully river and Rashed-Un-Nabi et al.
(2011) found 65% similarity for finfish and shellfish in all seasons in
Bakkhali river estuary. Their findings are dissimilar from the present
findings because of the different geographical locations, different survey
periods, and sampling error variation.
Atrai River was 0.66, Rahman et al. (2015) carried out a study on the
Talma River and the average values of Evenness (J0 ) index was recorded
as 0.86. These findings are different from the present findings because of
different geographical locations of the study. Murugan and Prabaharan
(2012) found highest evenness value 0.99 at late monsoon indicating
evenly distributed and rich fauna in the monsoon and post-monsoon.
4.3. Cluster analysis and non-metric multidimensional scaling (nMDS)
The cluster analysis showed distinct separation among the three
sampling stations in twelve months. At the similarity of 58.7%, two major
groups were attained. Nasren et al. (2021) found two cluster groups at
10
K.K. Tikadar et al.
Heliyon 7 (2021) e08478
winter period. Hossain et al. (2009) recorded a total of 12,217 tons of
annual fish production in the Chalan beel during 2005–2006 which was
half of the production observed in 1982. Ahmed and Hambery (2005)
found that the production and richness of fish fauna are bound to the
inundating pattern in the monsoon period. These production patterns are
similar to the present study. The availability of the fish species was
comparatively higher in the pre-monsoon season due to the optimum
level of water and temperature but during the post-monsoon water current and water level increases which made the fishing activities very
difficult. That's why the total fish catch becomes low during August.
Table 4. Causes of loss of fish diversity.
SL
No.
Threats to fish diversity
No. of
Respondent
Percentage of
Respondents
1.
Siltation and sedimentation, decreasing
the water depth of the river
78
98%
2.
High fishing pressure
70
88%
3.
Catching of brood fish, fry and fingerling
through seine net
67
84%
4.
Use of illegal fishing gear like current jal
61
76%
5.
Practicing illegal and destructive fishing
methods like poison fishing by gas tablet
(Rotenone)
58
73%
6.
Increasing fishing pressure and fishing
during breeding season
46
58%
7.
Construction of different types of flood
control, development and communication
infrastructures like bridge, dams,
embankments, etc.
45
56%
8.
Creation of barrier and making obstacle in
natural migratory route of fishes
41
51%
9.
Low water velocity (water current)
40
50%
10
Poor implementations of fishing rules and
regulations
38
48%
11.
Use of insecticides and pesticides in
agricultural crop land
36
45%
12.
Use of chemical fertilizers like urea, TSP,
MoP etc.
35
44%
13.
To make agricultural crop land by filling
the river side
33
41%
14.
Drought in summer season
30
38%
15.
Use of river water for irrigation purposes
16
20%
4.5. Threats on fish biodiversity
Anthropogenic and natural hazards increasing day by day and
squeeze the fish species distribution across the country (Sarkar et al.,
2008) and subsequently, many fish species are documented as endangered in Bangladesh (IUCN Bangladesh, 2015). A large number of
indigenous fish species and some anadromous fish species use the Gorai
River as a major feeding, breeding ground, and migratory route (Hanif
et al., 2016). But in recent years the riverine ecosystem in Bangladesh has
changed considerably due to pollution, human intervention, and global
warming which have destroyed the riverine ecosystem (Alam et al.,
2017; Islam et al., 2015, 2017). Habitat destruction, reduced water flow,
indiscriminate fishing of fry, and fingerling are also considered as significant factors for declining fish species diversity in Bangladesh (Sultana
et al., 2019; Pandit et al., 2015; Rahman et al., 2012). These researches
found similar declining causes that represent the declining trends of fish
diversity in the study area which warning the gradual declination of fish
diversity of Bangladesh.
5. Conclusion and recommendations
4.4. Fishing gear, gear efficiency and fish catch
Gorai River is a moderate productive water body with diminishing
fish species of decent variety. Species selectivity of various gear contrasted significantly. Gill nets and fine coincided seine nets were
discovered more destructive than those of different gears. These sorts of
unlawful fishing rehearse were across the board and asset poor fishers
proceeded these for their employee as they couldn't discover other
elective works amid the periods. This research is a primer endeavor to
think about fish diversity index, gear efficiency, CPUE and catch
composition of various fishing gears and reasons for decrease of fish
fauna in Gorai River. Subsequently, fishing ought to be prohibited amid
breeding seasons by NGOs and government just as fisheries look into
foundation. Fishing gears ought to be developed relying upon target fish
species. Fishing nets (seine net and gill net) with large mesh size would
be a potential helpful gear for conservation of fish species. The followings
are recommended for policy making, implementation, and conservation
of fish biodiversity in the Gorai River:
Rubel et al. (2016) recorded 11 types of fishing net under 5 main
categories in the Lohalia River of Bangladesh of which ber jal under the
group seine net, current jal, chandi jal under the group gill net was
responsible for large scale catch. Ali et al. (2015) has identified eight
major types of fishing gears using in the Ramnabad River. Sultana et al.
(2016) recorded 18 types of fishing gear and 3 types of traps in the Payra
River, Bangladesh. The previously documented studies on fishing gears
are different from the present study. Because the choice of fishing gears
by the fishermen depends on many factors like types of fish species
available in the river, the physical condition of the river such as the
presence of currents, bottom conditions, and types of aquatic vegetation
present in the river. Some fishermen use illegal fishing gear like
fine-meshed seine net (locally called Jangle jal), gill net (current jal), and
illegal fishing method like poison fishing in the Gorai River. Which are
adversely affects the fish biodiversity and causes the extinction of many
fish species from the river. In addition to fishing gears, fishers of
Bangladesh also use other methods such as fishing in ditches and the
draining of canals, sections of small river channels, and ponds (Craig
et al., 2004).
Saberin et al. (2018) recorded a total of 19 types of fishing gear in the
Old Brahmaputra River from April 2011 to March 2012. Among which
Seine net showed the highest CPUE of 5.56 kg gear 1day 1 with fishing
effort 0.0224 gear 1haul 1day 1 followed by push net and lift net.
Ahmed and Hambery (2005) recorded the CPUE ranged between 2.91
and 30.86 kg gear 1day 1. Sayeed et al. (2014) recorded a total of 34
different types of fishing gears operated in Chalan beel in which seine
nets were the dominant gear followed by gill nets and set bag nets. These
previously documented study on CPUE is different from the present study
due to the difference of fishing places, the net sizes, the number of hooks,
lures, and baits, etc.
In the present study it was found that fish catch in the Gorai River was
higher in the pre-monsoon period and lower during the monsoon and
➢ Banning of indiscriminate killing of brood fish and fry/fingerlings.
➢ Banning or controlling destructive fishing gears like current jal and
destructive fishing methods like fishing by poisoning.
➢ Identification of the fish breeding and nursery grounds and its
protection.
➢ Identification of fish migration and fish breeding period of different
indigenous fish species.
➢ Establish a sufficient number of fish sanctuaries and ensure proper
maintenance of them.
➢ Dredging river bed for continuous river water flow to facilitate fish
migration.
➢ Minimizing the uses of harmful insecticides and pesticides in agricultural crops.
➢ Providing alternative income opportunities to the poor fisherman
during the banned fishing period.
➢ National strategies are formulated for policymaking, monitoring, and
implementation of the Gorai River.
11
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Heliyon 7 (2021) e08478
➢ Overall public awareness should be expanded through training program to restore the habitat of these valuable fish species from close
extinction.
Galib, S.M., Samad, M.A., Kamal, M.M., Haque, M.A., Hasan, M.M., 2009. A study on
fishing gears and methods in the Chalan Beel of north-west Bangladesh. J. Environ.
Sci. Nat. Resour. 2 (2), 213–218.
Gamito, S., 2010. Caution is needed when applying Margalef diversity index. Ecol.
Indicat. 10 (2), 550–551.
Ghosh, D., Biswas, J.K., 2017. Fish Fauna faces anthropogenic double trouble: erosion of
fish diversity in tropical Oxbow Lake of the Ganga River Basin in Eastern India.
J. Biodivers. Endanger. Species. 5 (2), 188.
Hanif, M.A., Siddik, M.A.B., Nahar, A., Chaklader, M.R., Rumpa, R.J., Alam, M.J.,
Mahmud, S., 2016. The current status of small indigenous fish species (SIS) of River
Gorai, a distributary of the river Ganges. Bangladesh. J. Biodivers. Endanger. Species.
4 (162), 2.
Hossain, M.S., Das, N.G., Sarker, S., Rahaman, M.Z., 2012. Fish diversity and habitat
relationship with environmental variables at Meghna river estuary, Bangladesh.
Egypt J. Aquat. Res. 38 (3), 213–226.
Hossain, M.A., Nahiduzzaman, M., Sayeed, M.A., Azim, M.E., Wahab, M.A., Olin, P.G.,
2009. The Chalan beel in Bangladesh: habitat and biodiversity degradation, and
implications for future management. Lakes Reservoirs Res. Manag. 14 (1), 3–19.
Hossain, M.M., Islam, M.A., Ridgway, S., Matsuishi, T., 2006. Management of inland open
water fisheries resources of Bangladesh: issues and options. Fish. Res. 77 (3),
275–284.
Huang, S., He, Y., 2019. Management of China's capture fisheries: review and prospect.
Aquac. Fish. 4 (5), 173–182.
Iqbal, M.M., Kanon, M.H., Hossain, M.A., Hossain, A., Nasren, S., Islam, M.J.,
Rahman, M.A., 2015. Diversity of indigenous fish species in Konoskhaihaor,
Northeast Bangladesh. Punjab Univ. J. Zool. 30 (2), 73–79.
Islam, M., Yasmin, R., 2018. Assemblage, abundance and diversity of fish species in River
Dhaleshwari, Bangladesh. Asian J. Fish. Aquat. Res. 1–28.
Islam, M.A., Al Asif, A., Samad, M.A., Sarker, B., Ahmed, M., Satter, A., Hossain, A., 2017.
A comparative study on fish biodiversity with conservation measures of the
Bhairabriver, Jessore, Bangladesh. Asian J. Med. Biol. Res. 3 (3), 357–367.
Islam, M.A., Hossain, M.M., Ahsan, M.E., Nahar, A., 2015. Status and current worries of
fish diversity in the Payra River, Patuakhali, Bangladesh. Int. J. Fish. Aquat. Stud. 2
(3), 160–165.
IUCN Bangladesh, 2015. Red Book of Threatened Fishes of Bangladesh. IUCN. The world
conservation union, Dhaka, Bangladesh.
Jewel, M., Sayed, A., Haque, M., Khatun, R., Rahman, M., 2018. A comparative study of
fish assemblage and diversity indices in two different aquatic habitats in Bangladesh:
Lakhandaha wetland and Atari river. Jordan. J. Biol. Sci. 11 (4), 427–434.
Karim, E., Liu, Q., Sun, M., Barman, P.P., Hasan, S.J., Hoq, M.E., 2019. Assessing recent
gradual upsurge of marine captured Hilsa stock (Tenualosa ilisha) in Bangladesh.
Aquac. Fish. 4 (4), 156–165.
Kamrujjaman, M., Nabi, M.R., 2015. Ichthyodiversity of the Bangshi river, Savar, Dhaka.
Jahangirnagar Univ. J. Biol. Sci. 4 (1), 19–25.
Lundquist, C.J., Baldi, A., Dieterich, M., Gracey, K., Kovacs, E.K., Schleicher, J., et al.,
2015. Engaging the conservation community in the IPBES process. Conserv. Boil. 29
(6), 1493–1495.
Margalef, R., 1968. Perspective in Ecological Theory. University of Chicago press,
Chicago Ill, p. 111.
Mredul, M.M.H., Alam, M.R., Akkas, A.B., Sharmin, S., Pattadar, S.N., Ali, M.L., 2020.
Some reproductive and biometric features of the endangered Gangetic Leaf Fish,
Nandus nandus (Hamilton, 1822): implication to the baor fisheries management in
Bangladesh. Aquac. Fish. (In press).
Murugan, A.S., Prabaharan, C., 2012. Fish diversity in relation to physico-chemical
characteristics of Kamala basin of Darbhanga district, Bihar, India. Int. J. Pharm. Biol.
Arch. 3 (1), 211–217.
Magurran, A.E., 2004. Measuring Biological Diversity. Blackwell Publishing, London.
Nair, N.B., Arunachalam, M., Madhusoodhanan Nair, K.C., Suryanarayanan, D., 1988.
Seasonal variation and species diversity of fishes in the Neyyar river of the western
ghats. J. Indian Fish. Assoc. 18, 253–260. http://aquaticcommons.org/id/eprint
/15976.
Nasren, S., Talukder, S., Barman, P.P., Al Mamun, M.A., 2021. Ichthyofaunal diversity of
the freshwater swamp forest Ratargul, Sylhet, Bangladesh. J. Adv. Zool. 42 (1),
135–147.
Nessh€
over, C., Vandewalle, M., Wittmer, H., Balian, E.V., Carmen, E., et al., 2016. The
Network of Knowledge approach: improving the science and society dialogue on
biodiversity and ecosystem services in Europe. Biodivers. Conserv. 25 (7),
1215–1233.
Pandit, D., Kunda, M., Harun-Al-Rashid, A., Sufian, M.A., Mazumder, S.K., 2015. Present
status of fish biodiversity in dekhar haor, Bangladesh: a case study. World J. Fish
Mar. Sci. 7 (4), 278–287.
Perrings, C., Duraiappah, A., Larigauderie, A., Mooney, H., 2011. The biodiversity and
ecosystem services science-policy interface. Science 331 (6021), 1139–1140.
Pielou, E.C., 1966. Species-diversity and pattern-diversity in the study of ecological
succession. J. Theor. Biol. 10 (2), 370–383.
Rahman, M.A., Mondal, M.N., Hannan, M.A., Habib, K.A., 2015. Present status of fish
biodiversity in Talma River at Northern part of Bangladesh. Int. J. Fish. Aquat. Stud. 3
(1), 341–348.
Rahman, M.M., Hossain, M.Y., Ahamed, F., Fatematuzzhura, S.B., Abdallah, E.M.,
Ohtomi, J., 2012. Biodiversity in the Padma distributary of the Ganges river,
Northwestern Bangladesh: recommendations for conservation. World J. Zool. 7 (4),
328–337.
Rashed-Un-Nabi, M., Al-Mamun, M.A., Ullah, M.H., Mustafa, M.G., 2011. Temporal and
spatial distribution of fish and shrimp assemblage in the Bakkhali river estuary of
Bangladesh in relation to some water quality parameters. Mar. Biol. Res. 7 (5),
436–452.
Declarations
Author contribution statement
Kishor Kumar Tikadar: Conceived and designed the experiments;
Performed the experiments; Contributed reagents, materials, analysis
tools or data; Wrote the paper.
Mrityunjoy Kunda: Conceived and designed the experiments;
Analyzed and interpreted the data; Contributed reagents, materials,
analysis tools or data.
Sabuj Kanti Mazumder: Analyzed and interpreted the data.
Funding statement
This work was supported by the Ministry of National Science and
Technology, Peoples Republic of Bangladesh (2017–2018 FY).
Data availability statement
Data included in article/supplementary material/referenced in
article.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
Acknowledgements
The authors are thankful to fishers' community of the Gorai River. The
authors also thank the editor and anonymous reviewers of this journal for
their valuable comments and suggestions.
References
Ahmed, K., Hambrey, J., 2005. Studies on the fish catch efficiency of different types of
fishing gear in Kaptai Reservoir, Bangladesh. Lakes Reservoirs Res. Manag. 10,
221–234.
Ahmed, M.S., 2008. Assessment of fishing practices on the exploitation of the Titas
floodplain in Brahmanbaria, Bangladesh. Turk. J. Fish. Aquat. Sci. 8 (2), 329–334.
Alam, M.T., Hussain, M.A., Sultana, S., Mazumder, S.K., 2017. Impact of sanctuary on fish
biodiversity and production in two important beels of Bangladesh. Adv. Biol. Res. 11
(6), 348–356.
Ali, M.M., Hossain, M.B., Al-Masud, M., Alam, M.A., 2015. Fish species availability and
fishing gears used in the Ramnabad River, Southern Bangladesh. Asian J. Agric. Res.
9 (1), 12–22.
Biligrami, K.S., 1988. Biological monitoring of rivers, problems and prospect in India.
Aquat. Ecotoxicol 245–250.
Carmen, E., Nessh€
over, C., Saarikoski, H., Vandewalle, M., Watt, A., Wittmer, H.,
Young, J., 2015. Creating a biodiversity science community: experiences from a
European Network of Knowledge. Environ. Sci. Pol. 54, 497–504.
Craig, J.F., Halls, A.S., Barr, J.J.F., Bean, C.W., 2004. The Bangladesh floodplain fisheries.
Fish. Res. 66 (2-3), 271–286.
Clarke, K.R., Gorley, R.N., 2015. PRIMER V7: User Manual/tutorial. Primer-E Ltd,
Plymouth, United Kingdom.
Clarke, K.R., Gorley, R.N., Somerfield, P.J., Warwick, R.M., 2014. Change in marine
Communities: an Approach to Statistical Analysis and Interpretation, third ed.
Primer-E Ltd, Plymouth, p. 256pp.
Danielsen, F., Balete, D.S., Poulsen, M.K., Enghoff, M., Nozawa, C.M., Jensen, A.E., 2000.
A simple system for monitoring biodiversity in protected areas of a developing
country. Biodivers. Conserv. 9 (12), 1671–1705.
DeJong, T.M., 1975. A Comparison of Three Diversity Indices Based on Their Components
of Richness and Evenness, pp. 222–227. Oikos.
Galib, S.M., Naser, S.A., Mohsin, A.B.M., Chaki, N., Fahad, F.H., 2013. Fish diversity of
the river Choto Jamuna, Bangladesh: present status and conservation needs. Int. J.
Biodivers. Conserv. 5 (6), 389–395.
12
K.K. Tikadar et al.
Heliyon 7 (2021) e08478
Shannon, C.E., Weaver, W., 1949. The Mathmatical Theory of Communication. University
of Illinois Press, Urbana, IL.
Siddique, M.A.B., Hussain, M.A., Flowra, F.A., Alam, M.M., 2016. Assessment of fish
fauna in relation to biodiversity indices of Chalan Beel, Bangladesh. Int. J. Aquat.
Biol. 4 (5), 345–352.
Simpson, E.H., 1949. Measurement of diversity. Nature 163, 688.
Sultana, M.A., Kunda, M., Mazumder, S.K., 2019. Status and decline causes of fish
diversity of Bhawal beel, Bangladesh. Malays. J. Med. Biol. Res. 6 (2), 93–100.
Sultana, M.A., Mazumder, S.K., Kunda, M., 2018. Diversity of fish fauna and fishing gears
used in the River Banar, Mymensingh, Bangladesh. Bangladesh J. Fish. 30 (2),
229–240.
Sultana, A., Sarker, A.C., Kunda, M., Mazumder, S.K., 2017. Present status and threats to
fish diversity of wetlands of Chhatak, Bangladesh. Int. J. Fish. Aquat. Stud. 5 (5),
43–48.
Sultana, M.A., Mazumder, S.K., Kunda, M., 2016. Fishing gears and crafts used in Payra
River, Bangladesh. Eur. J. Appl. Sci. 8 (6), 337–346.
Suski, C.D., Cooke, S.J., 2007. Conservation of aquatic resources through the use of
freshwater protected areas: opportunities and challenges. Biodivers. Conserv. 16 (7),
2015–2029.
Tittensor, D.P., Walpole, M., Hill, S.L., Boyce, D.G., Britten, G.L., et al., 2014. A mid-term
analysis of progress toward international biodiversity targets. Science 346 (6206),
241–244.
Vijaylaxmi, C., Rajshekhar, M., Vijaykumar, K., 2010. Freshwater fishes distribution and
diversity status of Mullameri river, a minor tributary of Bheema river of Gulbarga
district, Kamataka. Int. J. Syst. Biol. 2 (2), 1.
Rubel, M., Hashem, S., Jaman, N., Rana, K., Ferdousi, K., Hossain, M.S., 2016. A study on
the fish biodiversity of Lohalia River of Bangladesh. Int. J. Environ. Biol. 6 (1),
11–15.
Saha, D., Pal, S., Mukherjee, S., Nandy, G., Chakraborty, A., Rahaman, S.H., Aditya, G.,
2018. Abundance and biomass of assorted small indigenous fish species:
observations from rural fish markets of West Bengal, India. Aquac. Fish. 3 (3),
129–134.
Saberin, I.S., Reza, M.S., Hasan, M.M., Kamal, M., 2018. Fishing gear efficiency and their
effects on fish biodiversity in the Old Brahmaputra River, Mymensingh, Bangladesh.
Bangladesh J. Fish. 30 (1), 73–81.
Sarkar, U.K., Pathak, A.K., Lakra, W.S., 2008. Conservation of freshwater fish resources of
India: new approaches, assessment and challenges. Biodivers. Conserv. 17 (10),
2495–2511.
Sayeed, M.A., Hashem, S., Salam, M.A., Hossain, M.A.R., Wahab, M.A., 2014. Efficiency of
fishing gears and their effects on fish biodiversity and production in the Chalan Beel
of Bangladesh. Eur. Sci. J. 10 (30), 294–309.
Schindler, S., Livoreil, B., Pinto, I.S., Araújo, R.M., Zulka, K.P., Pullin, A.S., et al., 2016.
The network BiodiversityKnowledge in practice: insights from three trial assessments.
Biodivers. Conserv. 25 (7), 1301–1318.
Shamsuzzaman, M.M., Islam, M.M., Tania, N.J., Al-Mamun, M.A., Barman, P.P., Xu, X.,
2017. Fisheries resources of Bangladesh: present status and future direction. Aquac.
Fish. 2 (4), 145–156.
Shamsuzzaman, M.M., Barman, P.P., Hasan, A., Rashed-Un-Nabi, M., 2016. Fish
assemblage patterns: Temporal distribution structure and influence of environmental
variables in the Karnafully River Estuary, Bangladesh. Int. J. Mar. Sci. 6.
13