Int. J. Aquat. Biol. (2020) 8(4): 272-280

ISSN: 2322-5270; P-ISSN: 2383-0956

Journal homepage: www.ij-aquaticbiology.com

Original Article
Prey identification of invasive peacock bass from Telabak Lake Malaysia using DNA

barcoding technique

Aliyu Garba Khaleel1,2, Najlaa Nawwarah Rusli1, Nurul Izzati Mohd Radzif1, Aiman Syafiq Muhd Nasir1, Mohamad

Zulkarnain Mohd Dali1, Norshida Ismail1, Hou Chew Ha1, Ahmad-Syazni Kamarudin*1

1School of Animal Science, Faculty of Bioresources and Food Industry, Universiti Sultan Zainal Abidin, Besut Campus, 22200 Besut, Terengganu, Malaysia.

2Department of Animal Science, Faculty of Agriculture and Agricultural Technology, Kano University of Science and Technology, Wudil, P.M.B. 3244 Kano State,
Nigeria.

Article history:
Received 7 June 2020

Accepted 21 August 2020

Available online 2 5 August 2020

Keywords:
Conservation

Feeding habit

Invasive species

Abstract: Invasive peacock bass Cichla spp. have recently invaded freshwater habitats across
Malaysia. Stomach contents of 135 peacock bass captured from the Telabak Lake of East Coast of

Peninsular Malaysia were analysed. The preys were examined using visual identification method and

mitochondrial DNA barcoding technique to identify the partial digested and decaying preys in the

stomach. The current study identified 7 prey species (6 fishes 43.0% and 1 shrimp 5.1%) belongs to

5 families in fishes’ stomach. The results revealed that peacock bass is highly predator and generalist

feeder with an opportunistic feeding behaviour. It is highly important to reduce and monitor the

abundance of this species for future survival of native species in the lake.

Introduction

The existence of an invasive fish species especially in

inland waters is regarded as a crucial challenge in the

conservation of tropical fish biodiversity (Clavero and

Garcia-Berthou, 2005; Agostinho et al., 2005;

Cucherousset and Olden, 2011; Matsuzaki et al.,
2016). Non-native fish species are intentionally or

accidentally introduced to a new habitat by human

activities (Radkhah et al., 2016; Mousavi-Sabet and

Eagderi, 2016; Eagderi et al., 2018). Peacock bass

Cichla spp. are highly predatory fishes originated from
the Amazon and introduced to many countries (Fugi

et al., 2008; Kovalenko et al., 2009; Marques et al.,
2016). These fishes were intentionally introduced into

Malaysian freshwater by anglers in early 1990s

(Rahim et al., 2013). Since then, it spreads to many

freshwater bodies such as Temengor Reservoir and

Lake, Raban Lake, Kapal Tujuh Lake, Kampar River

(Hamid and Mansor, 2013; Desa and Aidi, 2013; Saat

et al., 2014; Tan and Sze, 2017; Yap et al., 2016; Ng
et al., 2018). Peacock bass exert high predation on
prey fish population which may lead to the decreasing

of the prey fish abundances and diversity in a

*Correspondence: Ahmad-Syazni Kamarudin

E-mail: ahmadsyazni@unisza.edu.my

particular area (Zaret and Paine, 1973; Santos et al.,

2001; Pelicice and Agostinho, 2008; Franco et al.,
2017). These fishes are daytime active piscivorous

that consume a wide range of prey and tend to ingest

the whole prey (Zhao et al., 2014). To date, there is no

documentation regarding their prey species across

Malaysian freshwater bodies. Thus, diet composition

study of this invasive fishes is necessary for better

understanding of their ecological impacts on native

biodiversity (Garvey and Chipps, 2012).

Study on piscivorous fish diet composition is

traditionally based on stomach contents analysis.

Visual identification methods have been widely used

in taxonomic identification of fish diet content (Morris

and Akins, 2009; Layman and Allgeier, 2012; Côté et

al., 2013). However, this method has failed to identify

70% prey content to the lowest taxonomic species

level in the stomach content due to high digestion

effect and prey degradation (Morris and Akins, 2009;

Côté et al., 2013). This weakness, especially at low

sample sizes may bias the ecological impact

predictions since the detected prey might not represent

the unknown percentage (Côté et al., 2013).

273

Int. J. Aquat. Biol. (2020) 8(4): 272-280

Therefore, DNA barcoding technique is used for high

taxonomic resolution of fish diet as a supplement to

traditional method (Leray et al., 2011).

Analysis of mitochondrial DNA is proven to be a

useful tool for the study of genetic diversity (Ahmad-

Syazni et al., 2017; Ha et al., 2017; Khaleel et al.,
2019) and species identification (Li et al., 2019;

Golani et al., 2019). Matching of a short DNA

sequences from unknown samples to known

sequences in global databases such as National Centre

for Biotechnology Information (NCBI) and Barcode

of Life Database (BOLD) is known as barcoding

(Ratnasingham and Hebert, 2007; Moran et al., 2015).

This approach has been used effectively to classify

dietary components in fishes (Côté et al., 2013; Moran

et al., 2015), small body sized larval fish (Riemann et

al., 2010), rare deep-water sharks (Dunn et al., 2010),

and coral reef fish with rich generalist diet (Leray et

al., 2011). Telabak Lake is a man-made freshwater

lake which play a pivotal socio-economic and

ecosystem role for the people living in the surrounding

area (Khaleel et al., 2020). Freshwater lakes in

Malaysia are known for the vast diversity of the

aquatic live and fishes (Shahabudin and Musa, 2018).

However, the introduction of invasive species such as

peacock bass which preying on native fishes might

give a threatening effect on the fish diversity. In this

regard, current study aimed to provide first

information concerning the prey identification and

feeding habit of peacock bass in Telabak Lake,

Malaysia using DNA barcoding technique.

Materials and Methods

Sampling: A total of 135 peacock bass samples with
average total body length of 24±2.1 cm and body

weight of 244±2.3 g were collected from the Telabak

Lake (5°37'56.9"N, 102°28'24.5"E), East Coast of

Peninsular Malaysia from October 2018 to January

2019. The samples were immediately transferred to

the Aquatic Laboratory, Faculty of Bioresources and

Food Industry, University Sultan Zainal Abidin

Malaysia for further analyses.

Taxonomic classification and feeding habit: Fish were

dissected to remove the stomach content based on

Barbato et al. (2019). Following the protocol of Côté

et al. (2013) with some modification, all prey items in

the stomach were identified to the minimum

taxonomic level. The highly digested preys with

difficulty to identify were classified as fish and

invertebrates, labelled separately and frozen. The

feeding regime of Cichla spp. was measured in
qualitative and quantitative methods based on Hynes

(1950) and Sahtout et al. (2018). The following

indices were used to evaluate the importance of

different prey items in the diets of Cichla spp.
𝑉𝐶 (%) = 𝑁𝑜. 𝑜𝑓 𝑒𝑚𝑝𝑡𝑦 𝑠𝑡𝑜𝑚𝑎𝑐ℎ ×

100

𝑁𝑜. 𝑜𝑓 𝑓𝑢𝑙𝑙 𝑠𝑡𝑜𝑚𝑎𝑐ℎ𝑠
(Peyami et al., 2018)

𝐹𝑂 (%) = 𝑁𝑜. 𝑜𝑓 𝑠𝑡𝑜𝑚𝑎𝑐ℎ 𝑐𝑜𝑛𝑡𝑎𝑖𝑛𝑖𝑛𝑔 𝑝𝑟𝑒𝑦 ×

100

𝑁𝑜. 𝑜𝑓 𝑓𝑢𝑙𝑙 𝑠𝑡𝑜𝑚𝑎𝑐ℎ𝑠
(Ashelby et al., 2016)

𝑁𝐼 (%) = 𝑁𝑜. 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 𝑝𝑟𝑒𝑦 𝑖𝑡𝑒𝑚𝑠 ×

100

𝑇𝑜𝑡𝑎𝑙 𝑁𝑜. 𝑜𝑓 𝑝𝑟𝑒𝑦𝑠
(Karimi et al., 2019)

𝑉𝐼 (%) = 𝑊𝑒𝑖𝑔ℎ𝑡 𝑜𝑓 𝑝𝑟𝑒𝑦 𝑖𝑡𝑒𝑚𝑠 ×

100

𝑇𝑜𝑡𝑎𝑙 𝑤𝑒𝑖𝑔ℎ𝑡 𝑜𝑓 𝑠𝑡𝑜𝑚𝑎𝑐ℎ 𝑐𝑜𝑛𝑡𝑒𝑛𝑡
(Karimi et al., 2019)

𝐼𝑅𝐼 = (%𝑁 + %𝑉) × %𝐹 (Barbato et al., 2019)

Where VC is vacuity coefficient, FO = frequency

of occurrence, NI = number of individuals, VI =

volume of individuals and IRI = index of relative

importance.

Barcoding sample preparations: A small piece of the

muscle tissue (2-3 mm3) was used from every frozen

prey item identified as fish and invertebrates,

respectively. Then, all samples were carefully taken

from each prey (preferably from dorsal muscle). To

minimize the sample contamination by peacock bass

cells, approximately 1 mm top layer of the tissue

muscle of the prey that has direct contact to stomach

fluids were removed prior to sampling for barcoding.

All tools were sterilized using 95% ethanol and

Bunsen burner flame between each sample removing

to avoid any possible contamination.

Prey DNA extraction, amplification and sequencing:

The total genomic DNA of each prey item was isolated

using Favorgen DNA extraction Kit (Favorgen

Biotech Corp., Ping-Tung 908, Taiwan) by following

manufacturer’s protocol. The partial COI gene of

mitochondrial DNA was amplified by PCR using the

universal primers COI-Fish2 F (5’TCGACTAATCA

274

Khaleel et al./ Invasive peacock bass prey identification in Malaysia

TAAAGATATCGGCAC3’) and COI-Fish2

R (5’ACTTCAGGGTGACCGAAGAATCAGAA3’)

(Ward et al., 2005) for unidentified fish samples and

LCO1490: 5'-GGTCAACAAATCATAAAGATATT

GG-3' and HCO2198: 5'-TAAACTTCAGGGTGAC

CAAAAAATCA-3' (Folmer et al., 1994) for

unidentified invertebrates. For both fish and

invertebrates preys, the PCR was carried out in a 25 μl

reaction volume containing 18.2 μl sterile distilled

water, 2.5 μl Taq buffer, 2.0 μl dNTP Mix (2.5mM),

0.5 μl of each primer (10 μM), 0.3 μl of 5 unit/μl Taq

polymerase (TaKaRa) and 1 μl template DNA (1-50

ng/μl) on a thermal cycler PCR machine Veriti 96

Well Thermal Cycler (Applied Biosystem, California,

USA), under the following thermal cycling conditions.

Initial denaturation at 95°C for 5 min, 35 cycles

including denaturation at 95°C for 30s, annealing at

50°C for 30s and elongation at 72°C for 10 min,

followed by final extension for 10 min at 72°C and the

PCR product was maintained at 4°C. Sequencing was

succeeded using BigDye Terminator v3.1 cycle

sequencing kit (Applied Biosystems) following

manufacturer's instructions, performed on an ABI

Prism 3730xl Genetic Analyser (Applied Biosystems).

Data analysis: Unknown sequences from fish and

invertebrates were aligned and edited using ClustalW

multiple sequence alignment program in MEGA 7

(Kumar et al., 2016). DnaSP software was used to

determine the variable sites among the sequence

(Librado and Rozas, 2009). To discover the taxonomy

of each prey species, the obtained haplotypes were

queried using basic local alignment search tool

(BLAST) against National Center for Biotechnology

(NCBI) nucleotide database. A top species match was

identified with a sequence similarity of at least >94%

to avoid false positives. Number of observed and

detected prey species in the stomach of peacock bass

was computed in percentages using Minitab 16

software.

Results

Feeding intensity of peacock bass: Among 135

examined stomach contents monthly from October

2018 till January 2019, 70 were empty (average

51.8%) with high value in December (87%) and

sudden decline in January (26%) (Fig. 1). Using visual

identification method, the remaining prey samples

were successfully identified as fish and invertebrates

with their percentages (Fig. 2B, C, respectively).

Table 1. Monthly variations of peacock bass dietary items with respect to their percentage frequency of occurrence (%FO), percentage number of

individual (%NI), percentage volume of individuals (%VI) and percentage index of relative importance (%IRI).

Variables Prey Oct. Nov. Dec. Jan. Male Female

FO (%) Fish 68.4 85.7 66.7 78.6 42.2 04.7

Invertebrates 42.1 25.0 33.3 42.9 26.6 32.8

NI (%) Fish 64.5 80.5 20.0 65.2 38.0 31.0

Invertebrates 35.5 19.5 80.0 34.8 05.0 26.0

VI (%) Fish 67.1 42.1 62.7 57.5 23.5 31.1

Invertebrates 04.1 01.1 04.4 02.5 01.9 00.7

IRI (%) Fish 84.4 87.2 32.8 85.8 92.6 96.3

Invertebrates 15.6 12.8 67.2 14.2 07.4 04.7

Figure 1. Monthly variations of vacuity index of peacock bass

stomachs examined between October 2018 and January 2019.

275

Int. J. Aquat. Biol. (2020) 8(4): 272-280

However, it failed to classify prey to their lowest

taxonomy due to high ingestion effect and

degradation. Table 1 provides the overall results of the

classification and diet composition on prey of the

examined peacock bass between October 2018 and

January 2019. The fish preys dominated the entire diet

with the exception of December at which high number

values of invertebrates were recorded.

Mitochondrial DNA barcode: A total of 656 base pair

(bp) of COI for fish species and 679 bp of COI for

invertebrates were obtained after deletion of low-

quality nucleotides at the 5’ and 3’ ends. Six different

sequences were obtained from COI of fishes (PSC01,

PSC02, PSC03, PSC04, PSC05, and PSC06) and one

sequence for invertebrate (PSC07). After blasting, in

NCBI, following our criterion of >94% sequence

similarities, 7 prey species belong to five families

were Cichla ocellaris, Pristolepis fasciata,
Parambassis ranga, Rasbora trilineata, Cyprinus
carpio and Cyclocheilichthys enoplos (Table 2). The
percentage of each prey species identified (% N0)

using DNA barcode were also recorded with high

value of 15.2% in P. fasciata.

Discussions

The introduction of peacock bass into Telabak Lake

was accompanied by a sharp and gradual decline of

small-sized fishes (personal communication). This

study showed that the decrease in fish diversity might

be associated with feeding habit of peacock bass in the

Lake, since the observed prey items in the peacock

bass stomach confirm its piscivorous feeding habit on

targeted native prey species. We used traditional

visual identification method and further DNA

barcoding technique to identify its preys. The highest

vacuity coefficient was observed in December

indicating their breeding and spawning season

(Gomiero et al., 2009) which limits their hunting time.

High vacuity coefficient during breeding season was

also reported from other fish species such as Diplodus
vulgaris (Pallaoro et al., 2006), Caranx rhonchus (Sley
et al., 2008), Pagellus erythrinus (Šantić et al., 2011).

Table 2. BLAST sequence match showing percentage identity of prey in peacock bass using barcode.

Sequence Family Species Accession No. % Identity % N0

PSC01 Cichlidae Cichla ocellaris KU878410 99.20 5.1

PSC02 Pristolepididae Pristolepis fasciata MK049486 99.07 15.2

PSC03 Ambassidae Parambassis ranga MK448145 94.87 10.1

PSC04 Cyprinidae Rasbora trilineata KU569018 99.99 2.5

PSC05 Cyprinus carpio LN591958 94.03 2.5

PSC06 Cyclocheilichthys enoplos KU692459 99.68 7.6

PSC07 Palaemonidae Macrobrachium lanchesteri KP759429 98.18 5.1

% N0 = species percentage number identified after barcoding

Figure 2. Visual identification of 135 peacock bass stomach content from October 2018 to January 2019 captured in Telabak Lake, (A) 51.8%

Empty stomach, (B) 43.1% unidentified fish species and (C) 5.1% unidentified invertebrate species.

276

Khaleel et al./ Invasive peacock bass prey identification in Malaysia

The lowest vacuity coefficient observed in January

(26.3%) revealed its feeding initiation after breeding

period. Full recovery to feeding activity helps fishes

to compensate the energy used during breeding

(Derbal et al., 2007). Fish dominates the entire diet of

the peacock bass in all months, except in December

where invertebrates (prawn) were dominated.

Macrobrachium lanchesteri (Prawn) spawns
throughout the year with a peak at November (Phone

et al., 2005). Therefore, it could be more available in

December for peacock bass. Another explanation for

high predation of peacock bass on fish prey species

might be related to naturally clear transparency of

Telabak Lake. It is reported that peacock bass thrive

well in clear freshwater for excellent predation

(Kovalenko et al., 2010).

Visual identification has failed to identify the prey

items to the lowest species level due to the degradation

of essential features such as fin ray shape and body

coloration. However, only 48.2% of the ingested prey

into fish and invertebrates were visually distinguished.

This percentage is closer to the results of other similar

studies (Côté et al., 2013; Dahl et al., 2017). Only few

species were successfully identified to the lowest

species taxonomic level using visual method similar

to other works (Morris and Akins, 2009; Côté et al.,

2013; Moran et al., 2015; Mzaki et al., 2017; Sahtout

et al., 2018). All identified prey species were native to

Malaysia freshwater except for C. carpio and Cichla
spp. Opportunistic feeding habit of Cichla spp. is one
of the serious aspects that helped them adapt to a new

environmental condition. The presence of Cichla spp.
in the stomach as a prey item might be due to

cannibalism, and as proof of its opportunistic feeding

habit in nature. It was previously examined that

cannibalism is more pronounced during the spawning

periods with scarcity of alternative foods, like small

indigenous species of fish (Junior and Gomiero,

2010). In addition, low rates of cannibalism observed

in this study might be due to native prey abundance

(Carvalho et al., 2014). Once Cichla spp. is introduced
into a lake, they prey on variety of available fish

species, shrimps and cichlids (Pereira et al., 2015;

Mendonça et al., 2018). All native species found in the

stomachs are of least concern (IUCN Red List, 2012)

but they contribute largely in aquaculture, and as a

source of income for the local community e.g.

M. lanchesteri is used as food by locals (Phone et al.,
2005; Aznan et al., 2017).

The studies on introduction peacock bass have

indicated a negative effect on local fish species (Zaret

and Paine, 1973; Molina et al., 1996; Pinto-Coelho et

al., 2008; Pelicice and Agostinho, 2008; Rahim et al.,
2013). Previous works of the fish population in Lake

Redonda of Cuba from 1989 to 1990, documented that

many local fish species have been extinct after the

introduction of peacock bass (Molina et al., 1996).

Recently, Menezes et al. (2012) reported that the

introduction of peacock bass in the coastal Lakes of

Rio Grande do Norte Brazil had reduced native fish

abundantly with a negative impact on their diversity.

The invasion and adaptation of peacock bass in

Telabak Lake might likely lead to the reduction of

native fish species. The existence of these highly

adaptive and fast-growing piscivorous fish may cause

severe damages to the local aquatic populations

through competition, predation and cascade effects

across the trophic chain. Although peacock bass

attracts recreational anglers (Mendonça et al., 2018),

but local people depends on native aquatic species in

the Telabak Lake. The lake plays a significant role for

their daily needs and incomes. As our finding, 48.2%

of the prey items submitted for barcoding were 100%

identified to species level. Other studies identified less

than 70% when submitted for barcoding (Morris and

Akins, 2009; Côté et al., 2013), which is due to species

differences. Without using DNA barcoding technique,

most of the prey items could have been labelled as

partially digested unidentified prey, leading to missing

information, misidentification and less understanding

of invasive peacock bass impact in the lake.

Conclusion

This study provided useful information about feeding

habits of Cichla spp. for better understanding of the
relationship between fish species and other living

organisms in Telabak Lake. The presence of this

invasive species may affect the government effort on

277

Int. J. Aquat. Biol. (2020) 8(4): 272-280

boosting and promoting the lake as recreational and

aquaculture centre. The technique of DNA barcoding

has proved to be a useful tool in discovering diet of the

Cichla spp. in the lake. The information gathered in
this recent study is important for stakeholders and

policy makers in considering the management of

biodiversity of the lake in the future.

Acknowledgment

The authors would like to thank the Mr Mohamad

Amirul Aimi Md Kamail and Mohd Hanafiah Mohd

Jayapal for helping in fish sampling. This study is

funded by Fundamental Research Grant Scheme

(FRGS/1/2018 /WAB13/UNISZA/02/2) awarded to

Dr. Ahmad Syazni Kamarudin by the Ministry of

Higher Education, Malaysia.

References

Agostinho A.A., Thomaz S.M., Gomes L.C. (2005).

Conservation of the biodiversity of Brazil’s inland

waters. Conservation Biology, 19: 646-652.
Ahmad-Syazni K., Khaleel A.G., Norshida I., Connie F.K.,

Nguang S.I., Ha H.C. (2017). Population structure of

swamp eel Monopterus albus in East Coast of
Peninsular Malaysia inferred from 16S mitochondrial

DNA. World Applied Sciences Journal, 35: 1392-1399.

Ashelby C.W., De Grave S., Johnson M.L. (2016). Diet

analysis indicates seasonal fluctuation in trophic

overlap and separation between a native and an

introduced shrimp species (Decapoda, Palaemonidae) in

the tidal river Thames (UK). Crustaceana, 89: 701-719.

Aznan A.S., Iberahim N.A., Rahman N.I., Zakaria K.,

Leong L.K., Ibrahim W.N.W. (2017). Health

surveillance of freshwater prawn, Macrobrachium
lanchesteri in Setiu wetland, Terengganu, Malaysia.
Journal of Sustainability Science and Management, 12:

167-175.

Barbato M., Kovacs T., Coleman M.A., Broadhurst M.K.,

de Bruyn M. (2019). Metabarcoding for stomach-

content analyses of Pygmy devil ray (Mobula kuhlii cf.
eregoodootenkee): Comparing tissue and ethanol
preservative-derived DNA. Ecology and Evolution, 9:

2678-2687.

Carvalho D.C., Oliveira D.A.A., Sampaio I., Beheregaray

L.B. (2014). Analysis of propagule pressure and genetic

diversity in the invisibility of a freshwater apex

predator: the peacock bass (genus Cichla). Neotropical
Ichthyology, 12: 105-116.

Clavero M., Garcia-Berthou E. (2005). Invasive species are

a leading cause of animal extinctions. Trends in

Ecology and Evolution, 20: 110-110.

Côté I., Green S., Morris J., Akins J., Steinke D. (2013).

Diet richness of invasive Indo-Pacific lionfish revealed

by DNA barcoding. Marine Ecology Progress Series,

472: 249-256.

Cucherousset J., Olden J.D. (2011). Ecological impacts of

non-native freshwater fishes. Fisheries, 36: 215-231.

Dahl K.A., Patterson III W.F., Robertson A., Ortmann A.C.

(2017). DNA barcoding significantly improves

resolution of invasive lionfish diet in the Northern Gulf

of Mexico. Biological Invasions, 19: 1917-1933.

Derbal F., Nouacer S., Kara M.H. (2007). [Composition

and variations of dietary regime of sparaillon Diplodus
annularis (Sparidae) in Annaba Golf (East of Algeria)].
Cybium, 31: 443-450. (In French)

Desa S., Aidi D. (2013). A proposed model of fish

distribution in shallow lake based on feeding behaviour

of fishes in Raban Lake. Conference: UMTAS 2013:

The 12th International UMT Annual Symposium, At

Terengganu, Malaysia.

Dunn M.R., Szabo A. McVeagh M.S., Smith P.J. (2010).

The diet of deep-water sharks and the benefits of using

DNA identification of prey. Deep Sea Research Part I:

Oceanographic Research Papers, 57: 923-930.

Eagderi S., Nasri M., Çiçek E. (2018). First record of the

Amur goby Rhinogobius lindbergi Berg 1933
(Gobiidae) from the Tigris River drainage, Iran.

International Journal of Aquatic Biology, 6(4): 202-207.

Folmer O., Black M., Hoeh W., Lutz R., Vrijenhoek R.

(1994). DNA primers for amplification of

mitochondrial cytochrome c oxidase sub-unit I from

diverse metazoan invertebrates. Molecular Marine

Biology and Biotechnology, 3: 294-299.

Franco A.C.S., dos Santos L.N., Petry A.C., García-

Berthou E. (2017). Abundance of invasive peacock bass

increases with water residence time of reservoirs in

South-eastern Brazil. Hydrobiologia, 817: 155-166.
Fugi R., Luz-Agostinho K.D.G., Agostinho A.A. (2008).

Trophic interaction between an introduced peacock bass

and a native dogfish piscivorous fish in a Neotropical

impounded river. Hydrobiologia, 607: 143-150.
Garvey J.E., Chipps S.R. (2012). Diets and energy flow. In:

A.V. Zale, D.L. Parrish, T.M. Sutton (Eds.). Fisheries

techniques, 3rd edition. American Fisheries Society,

278

Khaleel et al./ Invasive peacock bass prey identification in Malaysia

Bethesda, Maryland. 7 pp: 33-779.

Golani D., Sonin O., Snovsky G., David L., Tadmor-Levi

R. (2019). The occurrence of the peacock bass (Cichla
kelberi Kullander and Ferreira 2006) in Lake Kinneret
(Sea of Galilee), Israel. BioInvasions Records, 8: 706-

711.

Gomiero L., Villares J.G., Naous F. (2009). Reproduction

of Cichla kelberi Kullander and Ferreira, 2006
introduced into an artificial lake in South-eastern Brazil.
Brazilian Journal of Biology, 69: 175-183.

Ha H.C., Nguang S.I., Zarizal S., Komilus C.F., Norshida

I., Ahmad-Syazni K. (2017): Genetic diversity of

kampung chicken (Gallus gallus domesticus) from
selected areas in East Coast Peninsular Malaysia

inferred from partial control region of mitochondrial

DNA. Malaysian Journal of Applied Biology, 46: 63-

70.

Hamid M.A., Mansor M. (2013). The inland fisheries with

special reference to Temengor and Bersia Reservoirs,

Perak. Malaysian Journal of Applied Biology, 42: 73-
76.

Hynes H.B.N. (1950). The food of fresh-water sticklebacks

(Gasterosteus aculeatus and Pygosteus pungitius), with
a review of methods used in studies of the food of fishes.
The Journal of Animal Ecology, 19: 36.

Junior G.A., Gomiero L.M. (2010). Feeding dynamics of

Cichla kelberi Kullander & Ferreira, 2006 introduced
into an artificial lake in South-eastern Brazil.

Neotropical Ichthyology, 8: 819-824.

Karimi S., Katiraei E., Soofiani N.M., Taghavimotlagh

S.A., Vazirizadeh, A. (2019). Feeding habits of striped

piggy, Pomadasys stridens (Forsskal, 1775)
(Haemulidae) in northern part of the Persian Gulf.

International Journal of Aquatic Biology, 7: 85-92.

Khaleel A.G., Ha H.C., Ahmad-Syazni K. (2019). Different

population of Malaysia swamp eel in East and Southeast

Asia inferred from partial 16s mitochondrial DNA.

Bioscience Research, 16: 01-09.
Khaleel A.G., Nasir S.A.M, Norshida I., Ahmad-Syazni K.

(2020). Origin of invasive fish species, peacock bass

Cichla species in Lake Telabak Malaysia revealed by
mitochondrial DNA barcoding. Egyptian Journal of

Aquatic Biology and Fisheries, 24: 311-322.

Kovalenko K.E., Dibble E.D., Agostinho A.A.,

Cantanhêde G., Fugi R. (2009). Direct and indirect

effects of an introduced piscivore, Cichla kelberi and
their modification by aquatic plants. Hydrobiologia,
638: 245-253.

Kovalenko K.E., Dibble E.D., Agostinho A.A., Pelicice

F.M. (2010). Recognition of non-native peacock bass,

Cichla kelberi by native prey: testing the naivete´
hypothesis. Biological Invasions, 12: 3071-3080.

Kumar S., Stecher G., Tamura K. (2016). MEGA7:

Molecular evolutionary genetics analysis version 7.0 for

bigger datasets. Molecular Biology and Evolution, 33:

1870-1874.

Layman C., Allgeier J. (2012). Characterizing trophic

ecology of generalist consumers: a case study of the

invasive lionfish in The Bahamas. Marine Ecology
Progress Series, 448: 131–141.

Leray M., Boehm J.T., Mills S.C., Meyer C.P. (2011).

Moorea BIOCODE barcode library as a tool for

understanding predator–prey interactions: insights into

the diet of common predatory coral reef fishes. Coral
Reefs, 31: 383-388.

Li Q., Deng J., Chen C., Zeng L., Lin X., Cheng Z., Huang

X. (2019). DNA barcoding subtropical aphids and

implications for population differentiation. Insects, 11:

11.

Librado P., Rozas J. (2009). DnaSP v5: a software for

comprehensive analysis of DNA polymorphism data.
Bioinformatics, 25: 1451-1452.

Marques A.C.P.B., Franco A.C.S., Salgueiro F., García-

Berthou E., Santos L.N. (2016). Genetic divergence

among invasive and native populations of the yellow

peacock cichlid Cichla kelberi. Journal of Fish Biology,
89: 2595-2606.

Matsuzaki S.S., Sasaki T., Akasaka M. (2016). Invasion of

exotic piscivorous causes losses of functional diversity

and functionally unique species in Japanese lakes.
Freshwater Biology, 61: 1128-1142.

Mendonça H.S., Santos A.C.A., Martins M.M., Araújo

F.G. (2018). Size-related and seasonal changes in the

diet of the non-native Cichla kelberi Kullander &
Ferreira, 2006 in a lowland reservoir in the South-

eastern Brazil. Biota Neotropica, 18: 1-8.
Menezes R.F., Attayde J.L., Lacerot G., Kosten S., Souza

L.C., Costa L.S., Van Nes E.H., Jeppesen E. (2012).

Lower biodiversity of native fish but only marginally

altered plankton biomass in tropical lakes hosting

introduced piscivorous Cichla cf. ocellaris. Biological
Invasions, 14: 1353-1363.

Molina W.F., Gurgel H.C.B., Vieira L.J.S., Canan B.

(1996). Acao de um predador exogeno sobre um

ecossistema aquatico equilibrado, I Extincoes locais e

medidas de conservacao genetica. UNIMAR, 18: 335-

279

Int. J. Aquat. Biol. (2020) 8(4): 272-280

345.
Moran Z., Orth D.J., Schmitt J.D., Hallerman E.M., Aguilar

R. (2015). Effectiveness of DNA barcoding for

identifying piscine prey items in stomach contents of

piscivorous catfishes. Environmental Biology of Fishes,
99: 161-167.

Morris J.A., Akins J.L. (2009). Feeding ecology of invasive

lionfish (Pterois volitans) in the Bahamian archipelago.
Environmental Biology of Fishes, 86: 389-398.

Mousavi-Sabet H., Eagderi S. (2016). First record of the

convict cichlid, Amatitlania nigrofasciata (Günther,

1867) (Teleostei: Cichlidae) from the Namak Lake

basin, Iran. Iranian Journal of Ichthyology, 3(1): 25-30.

Mzaki F., Manchih K., Idrissi H.F., Boumaaz A.,

Haddouch A.B., Tazi O. (2017). Diet of the common

cuttlefish Sepia officinalis (Linnaeus, 1758)
(Cephalopoda: Sepiidae) in the Southern Moroccan

Atlantic waters, Cap Boujdour, Cap Blanc. AACL

Bioflux, 10: 1692-1710.
Ng C.K.C., Ooi P.A., Wong W., Khoo G. (2018).

Ichthyofauna checklist (Chordata: Actinopterygii) for

indicating water quality in Kampar River catchment,

Malaysia. Biodiversitas, 19: 2252-2274.

Pallaoro A., Santic M., Jardas I. (2006). Feeding habits of

the common two-banded sea bream, Diplodus vulgaris
(Sparidae), in the eastern Adriatic Sea. Cybium, 30: 19-
25.

Pelicice F.M., Agostinho A.A. (2008). Fish fauna

destruction after the introduction of a non-native

predator (Cichla kelberi) in a Neotropical reservoir.
Biological Invasions, 11: 1789-1801.

Pereira L.S., Agostinho A.A., Gomes L.C. (2015). Eating

the competitor: a mechanism of invasion.
Hydrobiologia, 746: 223-231.

Peyami F.Y. (2018). Food and feeding habit of a

Teleostean fish Salmostoma bacaila (Ham.) at Partapur
dam, Makhdumpur Jehanabad, Bihar. International

Journal of Fisheries and Aquatic Studies, 6: 388-391.

Phone H., Ohtomi J., Suzuki H. (2005). Reproductive

biology of the freshwater palaemonid prawn,
Macrobrachium lanchesteri (De Man, 1911) from
Myanmar. Crustaceana, 78: 201-213.

Pinto-Coelho R.M., Bezerra-Neto J.F., Miranda F., Mota

T.G., Resck R., Santos A.M. (2008). The inverted

trophic cascade in tropical plankton communities:

Impacts of exotic fish in the Middle Rio Doce Lake

district, Minas Gerais, Brazil. Brazil Journal of Biology,

68: 1025-1037.

Radkhah A., Eagderi S., Mousavi-Sabet H. (2016). First

record of the exotic species Hemiculter leucisculus
(Pisces: Cyprinidae) in southern Iran. Limnetica, 35:

175-178.

Rahim K.A.A., Esa Y., Arshad A. (2013). The influence of

alien fish species on native fish community structure in

Malaysian waters. Kuroshio Science, 7: 81-93.

Ratnasingham S., Hebert P. (2007). BOLD: the barcode of

life data system. Molecular Ecology Notes, 7: 355-364.

Riemann L., Alfredsson H., Hansen M.M., Als T.D.,

Nielsen T.G., Munk P., Castonguay M. (2010).

Qualitative assessment of the diet of European eel

larvae in the Sargasso Sea resolved by DNA barcoding.

Biology Letters, 6: 819-822.

Saat A., Isak N.M., Hamzah Z., Wood A.K. (2014). Study

of radionuclides linkages between fish, water and

sediment in former tin mining lake in Kampung Gajah,

Perak, Malaysia. The Malaysian Journal of Analytical

Sciences, 18: 170-177.

Sahtout F., Boualleg C., Kaouachi N., Khelifi N., Menasria

A., Bensouilah M. (2018). Feeding habits of Cyprinus
carpio in Foum El-Khanga Dam, Souk-Ahras, Algeria.
AACL Bioflux, 11: 554-564.

Šantić M., PAlAdin A., Rađa B. (2011). Feeding habits of

common pandora Pagellus erythrinus (Sparidae) from
eastern central Adriatic Sea. Cybium, 35: 83-90.

Santos L.N., Gonzales A.F., Araujo, F.G. (2001). Dieta do

tucunare´-amarelo Cichla monoculus (Bloch &
Schneider) (Osteichthyes, Cichlidae), no reservato´rio

de Lajes, Rio de Janeiro, Brasil. Revista Brasileira de

Zoologia, 18: 191-204.

Shahabudin M.M., Musa S. (2018). An overview on water

quality trending for lake water classification in

Malaysia. International Journal of Engineering and

Technology, 7: 5-10.

Sley A., Jarboui O., Ghorbel M., Bouain A. (2008). Diet

composition and food habits of Caranx rhonchus
(Carangidae) from the Gulf of Gabes (central

Mediterranean). Journal of the Marine Biological
Association of the UK, 88: 00-00.

Tan K.W., Sze K.Z. (2017). Determination of heavy metal

concentration in fish species in Kampar mining lake,

Perak state of Malaysia. Fresenius Environmental

Bulletin, 26: 4202-4207.

Ward R.D., Zemlak T.S., Innes B.H., Last P.R., Hebert

P.D. (2005). DNA barcoding Australia's fish species.

Philosophical Transactions of the Royal Society of

London B: Biological Sciences, 360: 1847-857.

280

Khaleel et al./ Invasive peacock bass prey identification in Malaysia

Yap S.K., Muneera I., Syakir M.I., Zarul H.H., Widad F.

(2016). Stable isotopes approach to infer the feeding

habit and trophic position of freshwater fishes in

tropical lakes. Iranica Journal of Energy and

Environment, 7: 177-183.

Zaret T.M., Paine R.T. (1973). Species introduction in a

tropical lake. Science, 182: 449–455.

Zhao T., Villéger S., Lek S., Cucherousset J. (2014). High

intraspecific variability in the functional niche of a

predator is associated with ontogenetic shift and

individual specialization. Ecology and Evolution, 4:
4649-4657.