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SHORT RESEARCH COMMUNICATION
Year : 2017  |  Volume : 54  |  Issue : 4  |  Page : 366-368

Functional response and density dependent feeding interaction of Oreochromis niloticus against immatures of Culex quinquefasciatus


1 Department of Zoology, Bankura Christian College, Bankura, India
2 Mosquito, Microbiology and Nanotechnology Research Units, Department of Zoology, The University of Burdwan, Bardhaman, India

Date of Submission03-May-2017
Date of Acceptance08-Nov-2017
Date of Web Publication19-Feb-2018

Correspondence Address:
Anupam Ghosh
Assistant Professor in Zoology, Bankura Christian College, Bankura–722 101, West Bengal
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-9062.225843

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  Abstract 


Keywords: Biological control; Culex quinquefasciatus; feeding interaction; functional response; Oreochromis niloticus; predator


How to cite this article:
Ghosh A, Chandra G. Functional response and density dependent feeding interaction of Oreochromis niloticus against immatures of Culex quinquefasciatus. J Vector Borne Dis 2017;54:366-8

How to cite this URL:
Ghosh A, Chandra G. Functional response and density dependent feeding interaction of Oreochromis niloticus against immatures of Culex quinquefasciatus. J Vector Borne Dis [serial online] 2017 [cited 2018 May 21];54:366-8. Available from: http://www.jvbd.org/text.asp?2017/54/4/366/225843



In tropical and sub-tropical countries particularly in India, mosquito-borne protozoans, nematodes and viral diseases are responsible for high mortality and morbidity. Mosquito-borne diseases such as malaria, filariasis and dengue cause huge medical, financial and social burden in developing and under-developed countries. Increase in the incidence of mosquito-borne diseases mainly occur due to rapid and unplanned urbanization, poor sanitation, widely available temporary and permanent breeding grounds of mosquitoes, development of insecticide resistance in vector species due to wide and injudicious application of chemical insecticides and poor prophylactic and therapeutic measures.

Lymphatic filariasis is mainly caused by the nematode Wuchereria bancrofti. The disease is transmitted primarily by the mosquito Culex quinquefasciatus; however, Mansonia annulifera and Ma. uniformis also act as a vector, where the causative organism is the nematode Brugia malayi. The National Vector Borne Disease Control Programme, Govt. of India has estimated that filariasis is endemic in 255 districts in 21 states and Union Territories. The population of about 650 million in these districts is at risk of lymphatic filariasis. This situation demands the implementation of effective vector control strategy to reduce the higher incidence of mosquito-borne diseases.

Being a holo-metabolous insect, mosquito undergoes four stages in their life cycle, viz. egg, larva, pupa and adult. Due to the restricted aquatic habitat, larval stage is the most important target of many effective vector control operations. Development of insecticide resistance in vector population and degradation of environmental health and undesirable effect on non-target population demands the application of biological control methods in vector control operations[1]. Biological vector control means the use of natural enemies/predators to reduce vector population in their natural habitat using trophic level relationship, i.e. the predators present in higher trophic level are used to feed on organisms at lower trophic level. For example, Gambusia affinis (Mosquito fish), a natural mosquito predator can consume mosquito larvae as their prey.

The Nile Tilapia (Oreochromis niloticus) is a cichlid fish endemic to Africa and Middle East Asia. It is a voracious omnivorous feeder having distinctive, regular, vertical stripes throughout their body up to the edge of caudal fin. This exotic fish species was introduced in India during late 1987. Earlier studies have reported the larvivorous potentiality of O. niloticus in laboratory and field conditions against the mosquito larvae[2]. The present investigation was carried out to establish the feeding interaction of O. niloticus and mosquito larvae in laboratory bioassay. A detailed numerical analysis was also carried out to establish the particular type of functional response of the predatory fish against the larval forms of common filarial vector, Cx. quinquefasciatus.

In the present investigation, larvae of mosquito Cx. quinquefasciatus were collected from cemented drains and temporary aquatic bodies surrounding Bankura Christian College campus, West Bengal (India) during July–August 2016 and brought to the Department of Zoology. They were transferred in a plastic tray and reared in the departmental laboratory with artificial food. Predatory fishes, i.e. O. niloticus were collected from irrigation canals of Bankura and transferred in a glass aquarium maintained in the laboratory. Some aquatic weeds were placed in the aquarium to simulate natural conditions.

After acclimatization for three days in the laboratory, with mosquito larvae as natural food, III instar larvae of Cx. quinquefasciatus were separated from the mixed population of collected larvae and transferred in a glass beaker. A single O. niloticus was allowed for predation with various prey densities (20, 30, 40, 50, 60 and 70 larvae/ day) of Cx. quinquefasciatus larvae for a bioassay period of 24 h. The aquarium was placed within a BOD incubator (Eastern Instrument, Kolkata; 180 ft[3]) and maintained at 28–30°C, humidity of 65–71%, and photo period of 14 h L: 10 h D. After 24 h, the number of consumed larvae for each of the prey density was counted. The experiment was replicated three times at each prey density in accordance with procedure recommended by the Institutional Ethical Committee of the Burdwan University.

Functional response of O. niloticus was analyzed against variable densities of mosquito larvae. The response type was established by non-linear polynomial logistic regression equations of the proportion of prey eaten function of initial prey density (Na /N0) as described by Juliano[3] (random attack equation):



Where, Na is the number of prey eaten, N0 is the initial prey density; P1, P2 and P3 are the intercept, linear, quadratic and cubic coefficients, respectively. Maximum likelihood estimates of parameters P0 to P3 were calculated by logistic regression to a binomial variable that equaled 0 for surviving preys and 1 for consumed preys. As the functional response represents Type-II, the associated parameters, i.e. attack rate and handling time were calculated using Holling’s[4] Disc equation as follows:



Where, a = The attack rate constant; Th = Handling time per prey; and T = Total time available (here, 24 h). The attack rate estimates the rate of prey consumption as a function of variable prey densities and handling time estimates the time required to attack and consume a prey item. In the equation, N0 is independent variable and Na/N0 is outcome variable. For the statistical analysis “MS Excel 2007” and “R” statistical software was used.

The results of the present study clearly indicated that O. niloticus is a good predator of mosquito larvae in laboratory conditions. From the functional response analysis, it was found that predation rate of O. niloticus increases with an increase in prey density. The predatory fish exhibited a type–II functional response as the logistic regression estimated a significant negative linear parameter (P1< 0.001) and the R2 value (0.989) was very close to 1 that indicates a very good fit for Holling’s Disc equation. Associated intercept, linear, quadratic and cubic coefficients are given in [Table 1]. Type-II nature of the functional curve was further confirmed from [Figure 1], where proportion of prey consumed is plotted against given prey densities. Holling’s Disc equation was used for the estimation of attack parameters, i.e. instantaneous attack rate (a=0.0013) and handling time (Th = 0.5198).
Table 1: Results of predatory potentiality, parameters of logistic regression analysis and functional response estimates of the proportion of Cx. quinquefasciatus (III instar) consumed by O. niloticus on increasing prey density

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Figure 1: Observed proportion of prey eaten (Na/N0) vs initial prey density (N0) [solid line] and a fitted type II functional response curve [dotted line] of O. niloticus.

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Study of prey-predator interaction or feeding interaction is a major thrust area of modern ecological research because it regulates food web and community structure in an ecosystem[5]. The response of prey to the predator species also influences evolution of behavioural and morphological characteristics of prey species[6]. Feeding interaction study are basically of two types, one type is shortterm, laboratory-based and at individual-level; whereas, the second type is food-web studies that are field based, long-term and at population and community level. Generally, the outcomes of laboratory-based studies are used to construct ecological models where as the result of field based studies are useful to produce effective vector control strategy. There are several laboratory based studies carried out to establish the larvivorous potentiality of fishes in mosquito control[7]. But the outcome of those studies very rarely moves up to the field application; since there is a wide deviation of larvivorous potentiality in field conditions in contrast to laboratory outcome due to the lack of detailed numerical analysis.

There are several ecological models that describe the feeding interaction of the predator and prey species. Holling’s type II functional response analysis in laboratory conditions is the most widely applied predator–prey model[8]. Feeding interactions can be mathematically described by functional response models which can date back to the 1940s[9]. Functional response generally quantifies the feeding rates of a predatory species as a function of variable resource densities limited by attack rate and handling time. Functional response models often serve as the connection between short-term laboratories based studies and the long-term, community-level studies[10]. Generally, the functional responses are of three types; Type-I, Type-II and Type-III[11] ; amongst which Type II is most commonly reported. In the present study also, the functional response was Type-II response.

Under the alternative strategy of mosquito control, primary emphasis is given on the application of fishes in vector control operations. In the present study, considering the larvivorous potentiality and estimate of functional response parameters, it was concluded that O. niloticus can be successfully used in vector control operations. However, a detailed field study is essential before the wide application of the predator species in mosquito control programme.

Conflict of interest: None.



 
  References Top

1.
Chandra G, Mondal B, Bandyopadhyay S, Ghosh A. Sex-specific functional responses of dragonfly naiads Rhodothemisrufa on Culex quinquefasciatus larvae in laboratory bioassay. Int J Pest Manag 2016; 62(2): 135-9.  Back to cited text no. 1
    
2.
Ghosh A, Bhattacharjee I, Chandra G. Biocontrol efficacy by Oreochromis niloticus. J Appl Zool Res 2006; 17: 114-6.  Back to cited text no. 2
    
3.
Juliano SA. Non-linear curve fitting: Predation and functional response curves. In: Scheiner SM, Gurevitch J, editors. Design and analysis of ecological experiments. II edn. New York: Chapman and Hall 2001; p. 178-96.  Back to cited text no. 3
[PUBMED]    
4.
Holling CS. The functional response of invertebrate predators to prey density. Mem Entomol Soc Can 1966; 98 (S48): 5-86.  Back to cited text no. 4
    
5.
Weterings R, Umponstira C, Buckley HL. Density-dependent allometric functional response models. Ecol Modell 2015; 303: 12-8.  Back to cited text no. 5
    
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Dawkins R, Krebs JR. Arms races between and within species. Proc R SocLond B Biol Sci 1979; 205(1161): 489-511.  Back to cited text no. 6
    
7.
Chandra G, Bhattacharjee I, Chatterjee SN, Ghosh A. Mosquito control by larvivorous fish. Indian J Med Res 2008; 127(1): 13-27.  Back to cited text no. 7
    
8.
Skalski GT, Gilliam JF. Functional responses with predator interference: Viable alternatives to the Holling type II model. Ecology 2001; 82(11): 3083-92.  Back to cited text no. 8
    
9.
Solomon ME. The natural control of animal populations. J Anim Ecol 1949; 18(1): 1-35.  Back to cited text no. 9
    
10.
Kalinkat G, Schneider FD, Digel C, Guill C, Rall BC, Brose U. Body masses, functional responses and predator-prey stability. Ecol Lett 2013; 16(9): 1126-34.  Back to cited text no. 10
    
11.
Awadallah KT, Tawfik MFS, Abdellah MMH. Suppression effect of the reduviid predator, Allaeocranum biannulipes (Montr. Er. Sign.) on populations of some stored product insect pests. J Appl Entomol 1984; 97: 249-53.  Back to cited text no. 11
    


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