Effect of temperature and search area on the functional response of Anisops sardea (Hemiptera: Notonectidae) against Anopheles stephensi in laboratory bioassay

Accepted Manuscript Title: Effect of temperature and search area on the functional response of Anisops sardea (Hemiptera: Notonectidae) against Anopheles stephensi in laboratory bioassay Author: Rajendra Prasad Mondal Goutam Chandra Subhasis Bandyopadhyay Anupam Ghosh PII: DOI: Reference:

S0001-706X(16)30720-3 http://dx.doi.org/doi:10.1016/j.actatropica.2016.11.034 ACTROP 4127

To appear in:

Acta Tropica

Received date: Revised date: Accepted date:

19-9-2016 18-11-2016 27-11-2016

Please cite this article as: Mondal, Rajendra Prasad, Chandra, Goutam, Bandyopadhyay, Subhasis, Ghosh, Anupam, Effect of temperature and search area on the functional response of Anisops sardea (Hemiptera: Notonectidae) against Anopheles stephensi in laboratory bioassay.Acta Tropica http://dx.doi.org/10.1016/j.actatropica.2016.11.034 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

1 RESEARCH PAPER

Effect of temperature and search area on the functional response of Anisops sardea (Hemiptera: Notonectidae) against Anopheles stephensi in laboratory bioassay

Short Title:Effect of temperature and search area on the functional response of

Anisops sardea……….

Rajendra Prasad Mondal1, Goutam Chandra2, Subhasis Bandyopadhyay3 and Anupam Ghosh4

1

Department of Zoology, Bankura Sammilani College, West Bengal, India

2

Mosquito and Microbiology Research Units, The University of Burdwan, West Bengal, India

3

Department of Mathematics, Bankura Christian College, West Bengal, India

4

Department of Zoology, Bankura Christian College, West Bengal, India

Author for correspondence: Dr. AnupamGhosh, Ph. D, Asstt.Professor, Department of Zoology Bankura Christian College Bankura West Bengal, India-722101 Mail: [email protected] Phone: +91- 9474492745

Abstract Present study was carried out to establish the influence of abiotic factors on foraging activities of a predatory hemipteran insect Anisops sardea against Anopheles stephensi larvae. The functional response of A. sardea was evaluated in variable density of prey items with variation in search area (100, 250, 500 and 1000 ml water volume) and temperatures (20, 25 and 30°C). The results of

2 laboratory bioassay revealed that prey consumption rate of predator species was positively related with increasing temperature and inversely related with increasing search area. Polynomial logistic regression equations and associated parameters showed that A. sardea exhibited a type II functional response in variable search area and type-III response at variable temperatures. Related response specific attack rates and handling times were also evaluated in presence of specific abiotic factors.

Key words: Anisop sardea, Attack rate, Anopheles stephensi, Handling time, Functional response, Search area, Temperature.

Introduction Mosquitoes are vectors of many human diseases like malaria, filaria, dengue etc. that cause serious problems to human health as well as affect economic health of modern civilization. Female Anopheles stephensi is the principal vector of Plasmodium spp., which spread the noxious disease malaria throughout the world especially in tropical countries. WHO has reported a global 219 million malarial cases with 1.2 million deaths in 2010 (Nayyar et al., 2012). India contributes to 61% of global malaria cases and 41%of malaria deaths in SEAR (South East Asia Region) countries (Sharma et al., 2015). Emergence of insecticide resistance in vector population in a large scale and the appearance of pesticide pollulation due to over use of synthetic insecticides necessitated the application of biocontrol agents in vector control programme. Many bio control agents mainly larvivorous fishes (Chandra et al., 2008) and aquatic insect predators (Mandal et al., 2008;Kumar and Hwang, 2005) were investigated for their effective mosquito control efficacy in laboratory and field conditions. But, before recommending the use of a specific natural enemy in a biological control programme, detailed quantitative and qualitative understanding of the interactions of the predator and prey in variable environmental conditions are necessary. One important method for assessing the efficacy of natural enemies in quantitative term is the analysis of functional response. It refers to the number of prey attacked by an individual natural enemy/predator in relation to variable prey densities over a given time interval (Solomon, 1949) and represents an increasing linear relationship (Type I), a decelerating curve (Type II), or a sigmoidal relationship (Type III). Type II response is characterized by an increase in the number of prey attacked over the lower prey densities that reach an upper

3 limit (asymptote) at higher prey densities and thereafter almost remains unchanged due to satiation (Jalali et al., 2010).Shape of Type III functional response curve is almost similar to type II response; but here, ratio of prey consumed and given prey density is a more than linearly increasing function.In any bioassay experiment the resultant functional response is always expressed by two essential parameters viz. attack rate and handling time. Attack rate estimates the steepness of the increase in consumption rate as a function of increasing prey densities and handling time estimate the time required to attack and consume a prey item. A review of available literatures suggest that generally insect predators exhibit a type-II functional response which may be influenced by presence of abiotic factors like temperature and search area (Menon et al.,2002; Timms et al., 2008; Singh et al., 2008;Ghosh and Chandra , 2011). Anisops sardea Herrich-Schaeffer (Hemiptera: Notonectidae)is a predatory back swimmer belongs to family Notonectidae. It has cosmopolitan distribution and abundant in late-season temporary pools (Lahr et al., 1999), as well as in permanent pools (Barry, 1997).The results of laboratory bioassay indicated that A. sardea has a high consumption rate against larvae of Culex mosquitoes (Tawfiket al., 1986;Sridharan et al., 2000).The sizeselective prey preference of A. sardea against Daphnia sp was reported by Lindholm and Hessen, 2007. It was also found that presence of this backswimmer in aquatic pools has a significant effect on oviposition habitat selection of mosquitoes and other dipterans and on community structure in experimental aquatic pools (Eitam et al., 2002).The functional responses of A.sardea against larvae of Cx. Quinquefasciatus was also studiedby Mondal et al .,2014. But no studied have been carried out so far on the analysis of influence of abiotic factors on functional responses of this predatory species against An. stephensi, the most common malarial vector in the South East Asia. The objective of the current study is to investigate the effects of temperature and search area on the functional response of A. sardea to different densities of An. stephensi. A detailed quantitative assay on one type of predator–prey interactions between these two species may be helpful to optimize the augmentative release of this predator species in biological control programme against the vector mosquitoes.

Materials and methods Collection of A. sardea and mosquito larvae

4 Adults of A. sardea were collected from the different temporary and permanent aquatic pools of Bankura, West Bengal, India during the month of June- July 2015. The surface of the pools were sieved by an insect net having 200-µm mesh size. After collection the predators were maintained within glass aquaria (30×20×20 inches) containing pond water (10 liter) and a few aquatic weeds (Pistiasp, Hydrillasp etc.) in laboratory. Five adults were identified upto species level from the Zoological Survey of India. The insects were acclimatized with An.stephensi larvae and artificial food for 10 days in laboratory. The average body lengths of the A. sardea used in the experiments was 5 - 7 mm. Mosquito larvae were collected from clean and stagnant water of rice fields and grassy ditches of the same area and maintained in laboratory in plastic trays containing the water collected from the same habitat for 3 days with a diet containing powder of Brewer yeast, dog biscuits and algae mixture in 3:1:1 ratio(Kamaraj et al., 2011). The third instar larvae of An.stephensi were carefully separated according to their length and maturity and kept in a separate enamel trays in the laboratory for further bioassay experiments. The laboratory bioassay was carried out with relative humidity of 55% and 12 h light/dark cycle within a BOD incubator.

Functional response analysis To determine the type of predator specific functional response, each of the adult specimens of A. sardea was supplied with III rd instar larvae of An. stephensiat variable densities in separate glass beakers containing pond water and was allowed to predate for 24 h. The functional responses were analyzed in two different combinations: a) Functional responses at various prey densities (10, 20, 30, 40, 50, 60, 70, 80 and 90 larvae per 400 ml of pond water) were assessed in three different water temperatures, viz. 20, 25, and 30°C in a temperature controlled BOD incubator. The selected temperatures reflect thermal conditions frequently experienced by the predator in aquatic ecosystem of the study area. b) Functional responses was analyzed at almost similar prey densities (10, 20, 30, 40, 50, 60 and 70, larvae) in three different water volumes viz. 100ml, 250 ml, 500ml and 1 liter of pond water respectively. The water pH ranged from 7.8-8.3 and water temperature ranged from 21°C to 24°C.

5 Three replicates for each of the prey densities were carried out to different adults with almost similar body length.

Data analysis In the present study, the data were analyzed for functional responses using R statistical software (© The R Foundation, 2013). The functional response of the predator was analyzed in two steps. In the first step, the type or shape of the functional response curve was determined following

a

polynomial logistic regression model (Eq. 1) by considering the proportion of prey eaten (𝑁𝑎 /𝑁0 )as a function of initial prey density (𝑁0 ) (Juliano, 2001). 𝑁𝑎 exp(𝑃0 + 𝑃1 𝑁0 + 𝑃2 𝑁02 + 𝑃3 𝑁03 ) = 𝑁0 1 + 𝑒𝑥𝑝(𝑃0 + 𝑃1 𝑁0 + 𝑃2 𝑁02 + 𝑃3 𝑁03 )

(1)

In this equation 𝑁𝑎 represents the number of prey consumed by a predator, 𝑁0 is the prey density allowed to feed;𝑃0 , 𝑃1 , 𝑃2 and 𝑃3 are the intercept, linear, quadratic and cubic coefficients respectively. The coefficients of the logistic regression were estimated by using the function “glm” in R software. In the second step the parameters of the type II functional response viz. attack rate and handling time of the predator species were estimated by using Holling Disc equation (Eq. 2) 𝑁𝑎 =

𝑎𝑁0 𝑇 1 + 𝑎𝑁0 𝑇ℎ

(2)

where𝑎 = the attack rate constant, 𝑇ℎ = handling time per prey and 𝑇 = total time available (here, 24h). The parameters 𝑎 and 𝑇ℎ were obtained by using non-linear least square regression with the help of “nls” function of R software. Holling’s equation is used for the present study due to small size of predators, and they do not interfere with one another’s prey capture activities and competition among predators for food (if any) occurs only due to the depletion of prey density. As the functional response curve exhibits a Type –III type in bio assay experiments carried out at variable temperatures, the Holling Disc equation (Eq. 2) was modified by considering the attack rate constant 𝑎 as a function of prey density 𝑁0 (Hassell, 1978)(Eq. 3). The most general form of 𝑎 is 𝑎=

𝑑 + 𝑏𝑁0 1 + 𝑐𝑁0

(3)

where 𝑏, 𝑐, and 𝑑 are constants. This value of 𝑎 when substituted in the Disc equation (Eq. 2), yields (Eq. 4),

𝑑𝑁0 𝑇 + 𝑏𝑁02 𝑇 𝑁𝑎 = 1 + 𝑐𝑁0 + 𝑑𝑁0 𝑇ℎ + 𝑏𝑁02 𝑇ℎ

6 (4)

The parameters 𝑏, 𝑐, 𝑑 and 𝑇ℎ were obtained by using non-linear least square regression with the help of “nls” function of R software.

Result The result of changes in the rate of consumption of A. sardea in relation to variable densities of An. Stephensi larvae in different search area and temperature have been presented in Figure 1 and 2 respectively. It was found that the rate of consumption increased with initial prey density until it reached an upper asymptote and thereafter remains nearly unchanged or showed inverse densitydependence in presence of all abiotic conditions. Prey consumption of A. sardea is affected by the volume of search area as expressed in Figure 1. From the data, it was found that the rate of consumption is inversely proportional with the increase in water volume due to decrease in prey density in higher search areas. From the Figure 2, it has been found that the rate of consumption generally increases with increase in temperature from 20°C to 30° C in similar prey density. The non linear polynomial logistic regression estimated a significant linear parameter (P1 <0) for the functional response analysis at different search areas(Table 1), suggesting a Type II response (Figure 3). Accordingly, the Holling Disc equationwas used for the estimation of instantaneous attack rate (a) and handling time (Th) for each combination (Table 2). The lowest value of attack rate and handling time was noticed when bioassay was conducted in 250 ml of search volume. The respective R2 value were very close to 1, in almost all the cases predicting a good fit of Holling Disc rather than Random predator equation. Analysis of the non linear logistic equation revealed a Type III functional response by a positive P1 parameter and a negative P2 parameter in presence of variable temperatures (except the result of bioassay at 25°C) as presented in Table 3 and Figure 4. The modified Holling Disc equation was used to estimate associated attack rate and handling (Table 4).

Discussion Natural structure and proper functioning of any ecosystem depends upon the complex interactions between biotic factors, such as species assemblage, competition, predation, and

7 parasitism, and its fluctuating abiotic components such as pH, temperature, photo-period and search area. Unless the physiological optimum of a species is known for a particular abiotic factor, it is difficult to predict its optimal biotic interactions. Degree of biotic interaction can be numerically expressed by two basic principles viz. numerical response and functional response. Functional response describes the manner in which the consumption rate of a predator changes with increasing prey density(Solomon, 1949;Holling , 1959). A change in the predation as a function of prey density is a key factor that regulates structure and stabilizes small, temporary, aquatic ecotopes. The functional response curve can predict the prey preference and highest number of prey that can be consumed by a predator in a definite time period at a particular habitat condition. Functional response is a density dependent function of increasing prey density, i.e., predator’s rate of prey consumption increases with an increase in prey density. The basic model to study prey-predator interaction is Holling Disc equation and Lotka- volterra model. However several studies reported that the mathematical form of the functional response can be influenced by the volume of available spaces (Van der Meer and Ens, 1997) nutrient enrichment and the biomass of higher trophic levels (De Angelis et al., 1975) as well as the length of food chains (Schmitz, 1992) and accordingly they have modified the Disc equations. During the present study, the increase in predatory rate as a function of increasing prey density was observed which supports the earlier observations of Awadallah et al.(1984); Ambrose (2003); Claver et al. (2004;Ghosh et al.2011)Present study also revealed that the searching time decreased as the prey density was increased which is found in most heteropteran predators (Cohen and Tong, 1997; Cohen, 2000).It is generally found that most of the single predator-single prey functional response curve using insect predator shows a Type II response (Jalali,2010; Ghosh and Chandra,2011). Present study also indicates that the predator species exhibit a Type II functional response to changes in prey density in presence of variable search area. Present study provided first time result on the effects of temperature and volume of search area on the functional responses of A. sardea on the larval instars of An.stephensi. Abiotic climatic factors such as temperature and search area produce a complex array of effects that may extend to species dependent population or community structure. The results of present bioassay experiments revealed that the functional response and the associated attack rate and handling time are influenced by the amount of water volume used.

8 Estimation of consumption rate with variation of search area is a very important parameter before field application. From the estimation of per dip larval density and the volume of aquatic bodies, the effective number of predators required to achieve good results can be calculated. Considering the volume of water used in the present experiment, the predator species can be effectively used in small aquatic ecosystem such as in tree holes, used containers, pots, tubs having low/moderate larval density etc. The rate of predation was also found to be positively related with the changes in temperature where as inversely proportional with the volume of search area. Thermal conditions and tolerance level are especially important in predator–prey interactions that involve ectothermic organismssuch as insects.Earlier studies shows that rises in temperatures within the tolerance level increase the rate of predation and attack rate and decreases handling time of many aquatic insect predators to overcome increasing metabolic demands(Bailey, 1989;Mohaghegh et al., 2001;Skirvin and Fenlon, 2003; Song and Heong, 1997). Similarly, energetic characteristics of exothermic aquatic insect predators, such as food consumption, assimilation, metabolism, gut clearance and energy production also increase at higher temperatures (Heiman and Knight, 1975; Jayakumar and Mathavan, 1991). The range of temperatures that were included in the study are the water temperature range frequently exhibited in the temporary and permanent aquatic habitats of tropical countries and are suitable for the survival and development of the predator species. In the present study the predator showed a type III response in variable temperatures. This type of response is often justified by learning time, prey switching, or a combination of both phenomena. As in present study single prey-predator model is used the change in response from Type II to Type III occurs due to predators learning time which is defined as the natural improvement of a predator’s searching and attacking efficiency in a given ecotope. However, Hollings (1966)stated that predators showing a type III response are theoretically more capable of suppressing prey populations.

In conclusion, our results suggest that A. sardea has the potential to serve as abiological control agent of An.stephensi at various temperatures, limited search area and at low prey density. Although these controlled laboratory studies provide some insight into the predator-prey

9 interaction further field studies are required for more conclusive estimation of biocontrol potential of the particular predator against the prey species.

Acknowledgements: We want to acknowledge the help received from The Director, Zoological Survey of India, Kolkata, for the proper identification of the predator species.

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14 Fig 1. Rate of consumption of A.sardea against variable density of An. stephensi at different search area.

35

Rate of Prey consumption

30

25

20

100 ml 250 ml

15

500 ml 1 lit

10

5

0 0

10

20

30

40 Prey density

50

60

70

80

15 Fig 2. Rate of consumption of A.sardea against variable density of An. stephensi at different temperature

45 40 35 30

Rate of prey consumption

25 20 20°C

15

30°C

10

35°C

5 0 0

20

40

60

80

100

Prey density

Fig 3. Functional response curve of A. sardea against An. stephensi at various search area.

50.00

No. of prey eaten (Na)

40.00 30.00

100 ml 250 ml

20.00

500 ml 1000 ml

10.00 0.00 0

10

20

30

40

50

Prey density N0

60

70

80

16 Fig 4. Functional response curve of A. sardea against An. stephensi at various temperatures.

No. of prey eaten (Na)

50.00 40.00 30.00 20 °C 20.00

25 °C 30 °C

10.00 0.00 0

10

20

30

40

50

60

Prey density N0

70

80

90

100

17 Table 1. Results of logistic regression analysis of the proportion of An. stephensi (3

rd

consumed by A. sardea adults on increasing prey density at different volume of search area.

Search

Area

Parameters

Estimate

SE

t-value

Pr(>|t|)

P0

1.54072

0.31065

4.960

0.000

P1

-0.01002

0.01607

-0.623

0.540

P2

-0.00020

0.00018

-1.078

0.295

P0

1.96713

0.37302

5.274

0.000

P1

-0.08310

0.01974

-4.210

0.000

P2

0.00077

0.00023

3.331

0.003

P0

0.79918

0.22798

3.505

0.002

P1

-0.01929

0.00294

-6.551

0.000

P2

-0.00033

0.00015

-2.172

0.043

P0

0.88970

0.27890

3.190

0.005

P1

-0.02403

0.01564

-1.536

0.142

P2

0.00006

0.00019

0.294

0.772

(ml)

100

250

500

1000

instar)

18 Table 2 Estimates (± SE) instantaneous attack rate and handling time of A. sardea against An. stephensi at variable search area.

Search Area (ml)

100

250

500

1000

Parameters Estimate

SE

t-value

Pr(>|t|)

a

0.04735

0.00560

8.452

<0.001

Th

0.38414

0.05126

7.493

<0.001

a

0.02651

0.00295

8.984

<0.001

Th

0.24140

0.07791

3.099

0.005

a

0.04166

0.00441

9.429

<0.001

Th

0.39006

0.05146

7.579

<0.001

a

0.03417

0.00334

10.229

<0.001

Th

0.48482

0.05797

8.363

<0.001

19 Table 3. Results of logistic regression analysis of the proportion of An. stephensi (3

rd

instar)

consumed by A. sardea adults on increasing prey density at different temperature.

Temp ( oC) Parameters Estimate

SE

t-value

Pr(>|t|)

P0

-0.6683693

0.2076017

-3.219

0.00366

P1

0.0177910

0.0100356

1.773

0.08896

P2

-0.0002526

0.0001059

-2.386

0.02528

P0

4.092e-01

2.228e-01

1.836

0.0793

P1

-3.914e-02

2.046e-02

-1.913

0.0683

P2

8.818e-04

4.995e-04

1.765

0.0908

P0

-1.0259900

0.2919808

-3.514

<0.001

P1

0.0510429

0.0119920

4.256

<0.001

P2

-0.0004917

0.0001147

-4.287

<0.001

20

25

30

Table 4 Estimates (± SE) instantaneous attack rate and handling time of A. sardea against An. stephensi at variable search area.

Temp ( oC)

20

25

30

Parameters Estimate

SE

t-value

Pr(>|t|)

d

0.0291969

0.0071206

4.100

0.000438

b

-0.0014624

0.0004968

-2.944

0.007287

c

-0.0501591

0.0097010

-5.170

3.06e-05

Th

0.2088534

0.0760651

2.746

0.011516

a

0.025989

0.002298

11.308

2.54e-11

Th

0.323379

0.051802

6.243

1.57e-06

b (a=bN0)

0.0011082

0.0001333

8.316

1.15e-08

Th

0.4986664

0.0286212

17.423

1.70e-15

20