Divergence in threat sensitivity among aquatic larvae of cryptic mosquito species

Divergence in threat sensitivity among aquatic larvae

of cryptic mosquito species

Olivier Roux1,2*, Abdoulaye Diabate2 and Frederic Simard1

1Institut de Recherche pour le D�eveloppement, UMR IRD224-CNRS5290-UM1-UM2 MiVEGEC (Infectious Diseases

and Vectors: Ecology, Genetics, Evolution, and Control), 911 Avenue Agropolis, BP 64501, 34394 Montpellier,

France; and 2Institut de Recherche en Sciences de la Sant�e (IRSS), Direction R�egionale de l’Ouest (DRO), BP 390,

Bobo Dioulasso, Burkina Faso

Summary

1. Predation is a major evolutionary force driving speciation. The threat-sensitive response

hypothesis predicts that prey adjust and balance the time spent on a costly antipredator

response with other activities that enhance their fitness. Thus, prey able to develop an antipre-

dator response proportional to risk intensity should have a selective advantage.

2. Knowledge on how evolution has shaped threat sensitivity among closely related species

exposed to different predation pressures is scarce, prompting investigations to better predict

and explain its effect on communities.

3. We explored and compared the antipredator response of aquatic mosquito larvae in three

sibling species of the Anopheles gambiae complex, with contrasting larval biologies in Burkina

Faso. Anopheles arabiensis and An. gambiae sensu stricto breed in temporary water collections

where predator densities are low, whereas Anopheles coluzzii is able to thrive in permanent

pools where the predation pressure is much higher. We hypothesized that the increase and

decline of behavioural antipredator responses might differ between the three species over time.

To test this hypothesis, progenies of field-collected mosquitoes were experimentally exposed

to a range of soluble predation cues and their response was monitored for up to 48 h.

4. The three species were all threat sensitive but their reaction norms differed. For the range of

concentrations tested, An. coluzzii larvae gradually increased in antipredator response, whereas

An. gambiae larvae readily displayed antipredator behaviour at low concentrations leading to a

saturation of the response for high cue concentrations. An. arabiensis displayed a narrower

reaction norm with low response intensity. Larval instars did not differ in their threat sensitiv-

ity. The antipredator behaviour of the three species waned after about 1 h of exposure. Early

instars tended to express antipredation behaviour for longer than did older instars.

5. This study provides information on how aquatic prey species with an aerial adult stage

manage larval predation risk over time according to cue concentrations and suggests that dif-

ferent predation pressures might play a role as a disruptive selective force fostering habitat

segregation and speciation within the An. gambiae complex. The evolution of phenotypic

plasticity is further discussed in the light of divergent predation pressures.

Key-words: chemical ecology, cue degradation, dose response, ecological divergence, incipi-

ent species, malaria vectors, phenotypic plasticity, predation cues, predator–prey relationship,

speciation

Introduction

Predation is a major evolutionary force driving commu-

nity structure and species diversification (Nosil & Crespi

2006). In turn, plastic antipredator behavioural responses

allow prey to cope with variable predation risks (West-

Eberhard 1989; Agrawal 2001). The threat-sensitive

response hypothesis predicts that prey adjust the time

spent on a costly antipredator response according to the

threat level to allow as much time as possible for foraging

and development (Helfman 1989). Behavioural responses*Correspondence author. E-mail: [email protected]

© 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society

Journal of Animal Ecology 2014, 83, 702–711 doi: 10.1111/1365-2656.12163

to a predation risk can take on different shapes, from a

relative indifference wherein prey are unreceptive or

poorly receptive to the threat to a hypersensitive response

in which prey develop a high level of antipredator

response for low threat levels. Intermediate plastic

responses whereby prey adjust their antipredator behav-

iour proportionately to the threat intensity are believed to

be more adaptive (Mathis & Vincent 2000; Mirza &

Chivers 2003; Brown, Poirier & Adrian 2004; Brown et al.

2006; Ferrari et al. 2009). Hence, prey might fine-tune

their antipredator response by adjusting the amount of

time allocated to that response through trade-offs with

other activities affecting its fitness, such as foraging and

mating, minimizing costs (Lima & Dill 1990). Thus, prey

able to develop an antipredator response as a function of

risk intensity should be at a selective advantage (Helfman

1989; Mirza & Chivers 2003).

In aquatic systems, predation risk information is gener-

ally chemically mediated (Ferrari, Wisenden & Chivers

2010; but see Roberts 2012). Chemical cues can be related

to different threat levels ranging from the perceived pres-

ence of a resting predator to realized predation acts (i.e.

prey consumption or digestion). Cue concentrations may

provide information on the amount of time that has

elapsed since the last predation event and the distance

and/or number and identity of the predator(s) and prey.

Because higher cue concentrations are related to acute

predation risk, prey should perceive greater risk with

increasing cue concentrations (Chivers & Smith 1998;

Kesavaraju, Damal & Juliano 2007; Fraker 2008; Ferrari

et al. 2009). Cue concentrations may vary in time due to

dilution or degradation (Sih, Ziemba & Harding 2000;

Peacor 2006; Ferrari, Messier & Chivers 2008). The prey

itself can be a source of variability in the interpretation of

chemical information. For example, continuous exposure

to high cue concentrations may induce a long period of

food deprivation incompatible with prey fitness. Hence, in

such a situation, prey might actively decrease their level

of antipredator behaviour and redirect their efforts

towards foraging and resource harvesting in order to sur-

vive and develop. This process requires prey to be able to

adequately gauge predation risk, something that may

involve a complex cognitive process in which they balance

risks and benefits (Ferrari et al. 2010). The waning of

antipredator behaviour can also be due to sensory habitu-

ation linked to an uncontrollable decrease in the sensitiv-

ity of the chemical receptors whereby prey passively lower

their level of antipredator behaviour because of a physio-

logical incapacity to assess risk (Ferrari et al. 2010).

If threat-sensitive responses have frequently been stud-

ied for a range of cue concentrations, their expression in

their simplest form over time has rarely been investigated,

making it difficult to generalize (but see Peacor 2006;

Ferrari, Messier & Chivers 2008). In addition, knowledge

on how evolution has shaped threat-sensitive responses by

species exposed to different predation pressures is scarce,

prompting investigations to find the best way to better

predict and explain their effect on communities. Here, we

investigated the ability of mosquito larvae within the

Anopheles gambiae species complex to adjust their antipre-

dator behavioural responses according to the threat level

over time, both in their intensity and sensitivity.

The An. gambiae complex is particularly well suited to

investigations on local adaptations and the evolution of

antipredator behaviours because cryptic species within the

complex are exposed to different predation pressures at

the larval stage. The complex consists of seven closely

related species that are reproductively isolated and geneti-

cally and eco-ethologically different, albeit morphologi-

cally indistinguishable (White, Collins & Besansky 2011).

Anopheles gambiae s.s. and Anopheles arabiensis are the

most widespread throughout sub-Saharan Africa, populat-

ing highly diverse environments and frequently sharing

larval as well as adult habitats. Extensive genome scans

have further uncovered an additional lineage split within

the nominal species of the complex, An. gambiae s.s.,

leading to the description of the M and S ‘molecular

forms’ (della Torre et al. 2001; White, Collins & Besansky

2011). Most recently, the taxonomic status of the M form

was elevated to species level with the name Anopheles col-

uzzii, while the S form retains the original name An. gam-

biae (Coetzee et al. 2013). These two cryptic species are

now widely recognized as biologically relevant, assorta-

tively mating reproductive units (Lehmann & Diabat�e

2008; White, Collins & Besansky 2011). Speciation and

further radiation within the An. gambiae complex are

believed to be the products of a process of ecological spe-

ciation putatively triggered by divergent selection at the

larval stage (Coluzzi et al. 2002; Costantini et al. 2009).

The system therefore provides excellent opportunities for

improving our understanding of the process of divergent

selection and the dynamics of ecological speciation

(Costantini et al. 2009; White, Collins & Besansky 2011).

The current hypothesis is that man-made hydrological

schemes such as agricultural irrigation ditches and dams

have created new ecological larval niches and thus new

opportunities for specialization and expansion into mar-

ginal habitats (Ayala & Coluzzi 2005; Costantini et al.

2009).

Anopheles gambiae, the ancestral species, is widely distrib-

uted across sub-Saharan Africa, whereas the derived species

An. coluzzii is found only in West and Central Africa (della

Torre, Tu & Petrarca 2005; Lehmann & Diabat�e 2008).

However, although the adults are commonly found in symp-

atry, larvae might use diverse habitats. The two species are

able to develop in temporary waters (e.g. puddles, quarries,

ruts) during the rainy season where they frequently coexist

with An. arabiensis larvae (Edillo et al. 2002; Gimonneau

et al. 2012a). However, only An. coluzzii tends to exploit

more permanent freshwater habitats (e.g. irrigated fields

such as rice paddies, urban reservoirs) that persist across sea-

sons (Gimonneau et al. 2012a; Kamdem et al. 2012). Hence,

An. coluzzii is able to breed and transmit Plasmodium, which

causes malaria, all year long in areas where permanent

© 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society, Journal of Animal Ecology, 83, 702–711

Threat sensitivity in cryptic species 703

breeding opportunities exist, whereas An. gambiae and

An. arabiensis typically die out at the onset of the dry season

(Simard et al. 2000; Baldet, Diabat�e &Guiguemde 2003).

In western Burkina Faso, the ecological segregation of

larvae is strong with the total dominance of An. coluzzii

that breeds in rice paddies, whereas An. gambiae and

An. arabiensis predominate in the temporary waters in the

surrounding savannas (Gimonneau et al. 2012a). In spite of

recent studies showing that the temporal nature of the

water habitat (i.e. temporary vs. permanent), predation and

interspecific competition possibly contributed to this eco-

logical divergence (Diabat�e et al. 2005, 2008; Gimonneau

et al. 2010), the way in which these selective forces interact

and operate remains poorly understood. It has been shown,

both in the field and through laboratory experiments, that

An. coluzzii larvae from Burkina Faso are more capable

of surviving an acute predation risk than An. gambiae

(Diabat�e et al. 2008; Gimonneau et al. 2010).

It is widely accepted that permanent water habitats

shelter higher densities of predators than do temporary

water habitats (Sunahara, Ishizaka & Mogi 2002; Diabat�e

et al. 2008). It follows that a better ability to gauge the

predation risk and to produce an adequate antipredator

response to balance other fitness traits should provide

evident benefits in permanent water habitats (Tollrian &

Harvell 1999). Moreover, it is assumed that heterogeneous

and fluctuating environments should favour phenotypic

plasticity with large reaction norms, whereas more stable

environmental conditions should favour a loss of plastic-

ity and produce flat reaction norms through the genetic

assimilation of traits (Sultan & Spencer 2002; Hollander

2008). Furthermore, if species are highly mobile between

heterogeneous environments, the gene flow should favour

plasticity (Crispo 2008). In this context and keeping in

mind the predation heterogeneity between permanent and

temporary freshwater collections, how have Anopheles

larvae evolved an antipredator behaviour across species of

the complex and between freshwater habitats? Compared

to An. gambiae and An. arabiensis, did An. coluzzii evolve

a more plastic response with regard to its ubiquity within

permanent and temporary habitats or did it evolve a

selected narrower reaction norm with regard to the consis-

tently high predation level in permanent habitats?

To address the aspect of these questions, we analysed

the intensity and sensitivity (i.e. the ability of individuals

to detect small differences in threat intensity) of the anti-

predator response of the larvae of An. coluzzii, An. gam-

biae and An. arabiensis from wild populations sampled in

Burkina Faso. Because differences in plasticity between

species are predicted to occur when the heterogeneity of

their environment differs, we expected to observe diver-

gences in cue sensitivity between species naturally exposed

to different predation pressures (Brown et al. 2009). Our

recent work showed that both An. coluzzii and An. gam-

biae were sensitive to chemical cues issuing from preda-

tion acts, while An. arabiensis seemed to respond only to

physical cues betraying the presence of a predator (Roux,

Diabate & Simard 2013). Nevertheless, because we found

the lack of sensitivity to chemical cues in An. arabiensis

surprising, we decided to include this species in the study

to examine its sensitivity to high cue concentrations. Fur-

thermore, extending the analyses to the sympatric sibling

species, the results concerning An. arabiensis allowed us

to further assess and compare the use of predation cues in

mitigating antipredator responses among taxa within the

An. gambiae complex with an increasing level of repro-

ductive isolation (Ayala & Coluzzi 2005; Costantini et al.

2009; Simard et al. 2009).

Overall, we predicted that (i) the larvae would respond

more readily and intensively to higher cue concentrations

in keeping with the threat-sensitive response hypothesis;

and (ii) the intensity of the antipredator behaviour would

decrease over time as a result of stimulus degradation

and/or habituation in the mosquito larvae. More pre-

cisely, we expected that (iii) An. coluzzii would display a

large reaction norm and a proportional response to the

threat reflecting its ability to thrive in both types of habi-

tats and its greater sensitivity in gauging predation risk,

respectively, whereas An. gambiae and An. arabiensis

would express a constrained reaction norm (i.e. threshold-

dependent), being naturally exposed to lower predation

risk in temporary waters. (iv) Predictions about instar sen-

sitivity were based on two mutually exclusive hypotheses.

On the one hand, as prey–predator relationships are gen-

erally size dependant, late instars should be less subject to

predation and so should be less sensitive and raise their

antipredator behaviour faster than early instars. On the

other hand, late instars are less conspicuous than early

instars and thus should be more exposed to predation and

could be more sensitive to chemical cues. Our predictions

are summarized in Table 1.

Materials and methods

insect collections

Mosquitoes

Experiments were conducted with larvae obtained from wild

gravid An. gambiae s.l. females collected while at rest in inhabited

human dwellings in villages in south-western Burkina Faso (West

Africa) during the 2011 rainy season (May–October). The village

of Bama (11°23′14″N, 4°24′42″W), surrounded by 1200 ha of irri-

gated rice fields, predominantly shelters An. coluzzii all year

round. In Soumousso (11°00′46″N, 4°02′45″W), a village in the

humid savanna located 57 km away, An. arabiensis, An. coluzzii

and An. gambiae are sympatric. In Bama, gravid females lay their

eggs in the rice paddies, whereas in Soumousso, females only

have access to temporary, rain-filled puddles and quarries that

permit larvae to develop from June to November. The field-

collected gravid females were placed individually in oviposition

cups containing spring water and maintained under controlled

conditions (28 � 1 °C, 80 � 10% relative humidity, 12 L/12 D).

After oviposition, females were identified to species by routine

PCR-RFLP based on segregating SNP polymorphisms in the


704 O. Roux, A. Diabat�e & F. Simard

X-linked ribosomal DNA intergenic spacer region (Fanello,

Santolamazza & della Torre 2002). The larvae were reared in

spring water exposed to ambient conditions in the insectaries

(28 � 1 °C, 80 � 10% relative humidity, 12 L/12 D) and fed with

Tetramin� Baby Fish Food ad libitum. The three populations used

in our experiments consisted of An. gambiae s.l. females collected

in Bama and all identified An. coluzzii, whereas An. gambiae and

An. arabiensis were all obtained from Soumousso.

Predators

The backswimmer, Anisops jaczewskii (Hemiptera: Notonectidae),

is the most abundant and widespread predatory bug in both per-

manent and temporary mosquito larval habitats in our study area

(Diabat�e et al. 2008; Gimonneau et al. 2010). Notonectids have

been shown to be very efficient at reducing larval mosquito popu-

lations, and their impact on aquatic invertebrate communities has

also been demonstrated (Blaustein 1998). Predators were collected

in both locations, pooled (n = 80), fed daily ad libitum with a

combination of the larvae of the three populations of Anopheles

and maintained in the same controlled conditions as the

mosquito larvae.

experimental design

Predation cue preparation

To investigate the effect of cue concentrations on the intensity

and sensitivity of the antipredator behavioural response, we pre-

pared a stock solution that was subsequently diluted to make

concentrations of 100 (no dilution), 75%, 50%, 25%, 10%, 5%,

1% and 0% of the stock solution. The stock solution was pre-

pared with the spring water in which the mosquito larvae had

been reared for 5 days (hereafter ‘rearing water’). Four predators

were kept in 120 mL of rearing water in plastic cups

(Ø = 65 mm; h = 85 mm; hereafter ‘preparation cup’) together

with 30 mosquito larvae offered as prey (a random mix of 2nd to

4th instars). The larvae were counted daily, and any missing larva

was replaced. After 5 days, live larvae and predators were

removed. This stock solution has been demonstrated to trigger an

antipredator behaviour in larvae (Roux, Diabate & Simard 2013).

For each mosquito population, instar and cue concentration

tested, 10 stock solutions were simultaneously used and pooled to

neutralize inter-replicate variation before sequential dilution. The

solutions were diluted with rearing water. For each combination

of population, instar and cue concentration, 20 aliquots of

60 mL were placed into plastic cups (Ø = 55 mm, h = 60 mm;

hereafter ‘test cup’) and one larva was tested in each aliquot (=20

larvae per combination).

Behavioural tests

The larvae were fed 12 h before experimentation and used only

once. The experiments began between 9:00 and 9:30 a.m. and ran

for 48 h under controlled insectary conditions (see above). One

2nd, 3rd or 4th instar larva was gently placed in the middle of each

test cup, and observations started after the larvae were allowed a

5-min period of acclimation. The antipredator behaviour in

An. gambiae s.l. larvae was characterized by the larva positioning

itself on the walls of the container (Gimonneau et al. 2012b; Roux,

Diabate & Simard 2013). Data were therefore recorded as either

‘1’ for location on the walls (safe behaviour) or ‘0’ (larva on the

surface, in the middle of the water column or at the bottom of the

container = risky behaviour). The location of the larva was

recorded after 5, 15, 30 min, 1 h, 1 h 30 min, 2 h, 2 h 30 min,

3 h, 3 h 30 min, 5 h, 6 h, 8 h, 10 h, 24 h, 36 h and 48 h leading

to 320 observations per combination of population (n = 3), instar

(n = 3) and cue concentrations (n = 8; =total of 23 040 observa-

tions of which 1440 were mutually independent because repeated

measurements were taken for each larva over 48 h). For each pop-

ulation, instar and concentration combination, the 20 biological

replicates (i.e. larvae) were tested simultaneously and data record-

ings were separated by c. 5 s between replicates. Three to four

treatment combinations were randomly chosen and run at the

same time, with data recordings being separated by c. 2 min.

statist ical analysis

Pattern of the response to increasing cue concentrations

First, to determine the impact of cue concentrations on the anti-

predator behaviour, the larval location (Binary; wall vs. other) at

t = 5 min was analysed using the generalized linear model

(GLM) procedure with binomial errors and logit link. To test for

the differences between populations and between instars, we con-

sidered populations, instars and the log of cue concentrations

and all their interactions as fixed effects.

Secondly, to determine the pattern of the larval response to

threat intensity (i.e. proportional or not), the larval location at

t = 5 min within species subsets was analysed using the GLM

Table 1. Specific predictions for the dynamics of behavioural antipredator responses in three sympatric species of the Anopheles gambiae

complex in Burkina Faso

Anopheles coluzzii An. gambiae Anopheles arabiensis

Larval ecology

Habitat Permanent (e.g. irrigated fields, dams)

+Temporary (e.g. quarries, puddles)

Temporary (e.g. quarries,

puddles)

Temporary (e.g. quarries,

puddles)

Predation risk Low–high Low Low

Expected antipredator response

Sensitivity High Low Low

Shape Graded

(proportional to cue concentrations)

Non-Graded

(with threshold and/or ceiling)

Non-Graded

(with threshold and/or ceiling)

Width of reaction norm Large Small Small



procedure with binomial errors and logit link. Instars and the log

of cue concentrations and their interactions were used as fixed

effects. To test for linearity between threat intensity and antipre-

dator responses, we included the quadratic term of cue concentra-

tions. Significance of quadratic terms in the minimal model

(P < 0�05) should reveal a curvilinear relationship. When curvilin-

earity was observed, data were additionally analysed with a

nonlinear regression procedure with a four-parameter logistic

S-shaped function (nls function in R with self-starting four-

parameter logistic model function ‘SSfpl’). This procedure should

allow both the upper and lower horizontal asymptotes, indicative

of non-sensitivity or saturation, respectively, to be identified

(Crawley 2007, p 678).

For model selection, we used the stepwise removal of terms,

followed by likelihood ratio tests. Term removals that signifi-

cantly reduced explanatory power (P < 0�05) were retained in the

minimal adequate model (Crawley 2007).

Dose–response analyses

Because previous GLM analyses did not reveal an instar effect

(see Results), data on instars were pooled in the dose–response

analysis. The concentration inducing an antipredator behaviour

in 50% of the larvae tested (Effective Concentration: EC50) dur-

ing the first observation (at t = 5 min) was hence computed at

the population level using the dose.LD50 function in the doBy

package in R. An ANOVA followed by a Tuckey’s post hoc test

was used to compare the EC50 between species.

Effect of time on the waning of the antipredator

response

The analysis of changes in larval location over time was carried

out using the generalized linear mixed model (GLMM) procedure

with binomial errors and logit link (glmer function in the lme4

package). Populations, instars and length of exposure [log(time)]

and interactions between populations and time as well as between

instars and time were used as fixed effects. Individuals were

assigned as a random effect due to repeated measures, and the

factor ‘time’ was nested in concentration levels.

To test for a curvilinear relationship between time and the anti-

predator response, we included the quadratic term of time. As

the introduction of the quadratic term into the model was highly

significant (G = 67�223; d.f. = 1, P < 0�001), we investigated the

curvilinearity of the relationship within species and instar subsets.

When curvilinearity was observed in the subsets, data were analy-

sed with a curvilinear regression procedure with a four-parameter

logistic S-shaped function (SSfpl) to identify significant asymp-

totes (Crawley 2007, p 678). Models were simplified as described

above. All analyses were conducted using the R statistical pack-

age (version 2�12�1; R Development Core Team 2011).

Results

pattern of the antipredator response toincreasing cue concentrations

The analysis of larval position at t = 5 min showed that

the three species were all sensitive to soluble chemical cues

reflecting a predation threat. The higher the cue

concentrations, the higher the level of antipredator behav-

iour recorded, highlighting threat sensitivity (Fig. 1,

Table 2). There was no significant effect of instars on the

antipredator response to increasing cue concentration.

However, species adjusted their antipredator behaviour

differently as the cue concentration increased (i.e. signifi-

cant interaction effect). Anopheles arabiensis (intercept in

Table 2) increased its antipredator behaviour more slowly

than did An. coluzzii and An. gambiae (Fig. 1, Table 2).

Anopheles coluzzii and An. gambiae did not differ from

each other in the rate at which they increased their anti-

predator response according to cue concentration,

although An. gambiae displayed a significantly higher level

Fig. 1. Proportion of larvae exhibiting antipredator behaviour

after 5 min of exposure to increase cue concentrations. Anopheles

coluzzii: red triangles and red line; Anopheles gambiae: black dia-

monds and black line and; Anopheles arabiensis: blue circles and

blue line. Curves are predicted lines obtained from the GLM.

The curve for An. gambiae is obtained from the model including

the quadratic term of log(concentration).

Table 2. Effect of cue concentrations on larval antipredator

behaviour at t = 5 min

Estimate SE Z-value P

Intercept �0�40 0�16 �2�52 <0�05Anopheles coluzzii 0�15 0�20 0�77 NS

Anopheles gambiae 0�71 0�19 3�65 <0�0013rd instar �0�15 0�14 �1�02 NS

4th instar 0�12 0�15 0�81 NS

Log(concentration) 0�20 0�04 4�70 <0�001An. coluzzii 9 log

(concentration)

0�19 0�06 2�99 <0�01

An. gambiae 9 log

(concentration)

0�25 0�07 3�68 <0�001

Results for the minimal adequate model obtained by a GLM

procedure with binomial errors and a logit link function.



of antipredator behaviour than did An. coluzzii (Tukey’s

post hoc test: z-value = 2�82; P = 0�013, Fig. 1).In analyses by species subsets, we found a significant

effect of the quadratic terms for log(concentration) only

in An. gambiae (Likelihood ratio test: G1 = 4�24;P = 0�039) suggesting a curvilinear relationship between

the anti-predator response and cue concentrations in this

species only (An. arabiensis: v² = 2�23; d.f. = 1; P = 0�13and An. coluzzii: v² = 1�19; d.f. = 1; P = 0�27). The curvi-

linear regression revealed that the antipredator behaviour

levelled off at higher concentrations (upper asymptote:

t-value = 6�812; d.f. = 4; P = 0�002).

larval sensit iv ity to predation cues: a dose–response analysis

A dose–response analysis revealed that the three species

differed in their EC50 (ANOVA: F2,6 = 9�13; P = 0�015 and

Table 3). Anopheles arabiensis was the less sensitive

compared to An. coluzzii (Tukey’s post hoc test:

z-value = 4�51; P = 0�04) and to An. gambiae (Tukey’s

post hoc test: z-value = 5�73; P = 0�01). Anopheles coluzzii

and An. gambiae did not differ from each other (Tukey’s

post hoc test: z-value = 1�21; P = 0�68).

waning of the antipredator response

The results of the GLMM showed that time has a nega-

tive effect on the expression of the antipredator behaviour

as the proportion of larvae on the walls decreased signifi-

cantly over time (Table 4, Figs 2 and 3). Species–time

interactions showed that the different species managed

their antipredator behaviour level differently over time.

Anopheles coluzzii and An. gambiae had similar rates of

decline in their antipredator behaviour (similar interaction

with log time in Table 4). Nevertheless, An. gambiae

expressed a higher level of antipredator behaviour during

the entire waning process (Tukey’s post hoc test;

z-value = 4�87 and P < 0�001, Fig. 2 and Table 4). Anoph-

eles arabiensis decreased its antipredator behaviour more

slowly over time than did the two other species (Fig. 2,

Table 4). The inclusion of the quadratic term of ‘time’

into the minimal model was highly significant

(G1 = 67�223; P < 0�001) as it was in the analysis of the

subsets, revealing that the waning in all species was curvi-

linear (An. coluzzii: G1 = 511�8; P < 0�001; An. gambiae:

G1 = 32�15; P < 0�001; An. arabiensis: G1 = 278�34;P < 0�001). The curvilinear regression obtained with the

SSfpl function revealed that the level of the antipredator

behaviour in the three species stayed constant until it

reached a threshold in time at which it started to decrease

(significant asymptotes for low value of log(time):

An. coluzzii: t = 38�09; d.f. = 12; P < 0�001; An. gambiae:

t = 68�12; d.f. = 12; P < 0�001; An. arabiensis: t = 54�55;d.f. = 12; P < 0�001). This threshold was about 1 h after

the beginning of exposure for all three species. The three

species also had an asymptote for a high value of log

Table 3. Mean EC50 for chemical predation cue concentrations

inducing location on the walls after 5 min of exposure

EC50

95% CI

Lower Upper

Anopheles arabiensis 7�6 a 2�1 27�2Anopheles coluzzii 1�9 b 1�0 3�5Anopheles gambiae* 0�7 b 0�5 1�2

EC50, Mean effective concentration at 50%; CI, Confidence inter-

val. Different letters indicate significant differences at P < 0�05(ANOVA: F2,6 = 9�13; P = 0�015; followed by a Tukey’s post hoc

test for pairwise comparisons).

*Values obtained from the model fitted with quadratic term for

log(concentration).

Table 4. Effect of time on larval antipredator behaviour

Estimate SE Z-value P

Intercept 0�53 0�17 3�01 <0�01Anopheles coluzzii 1�18 0�13 8�92 <0�001Anopheles gambiae 1�82 0�13 13�38 <0�0013rd instar �0�44 0�13 �3�24 <0�014th instar 0�01 0�14 0�07 NS

Log(time) �0�18 0�02 �8�06 <0�001An. coluzzii 9 log(time) �0�18 0�02 �7�88 <0�001An. gambiae 9 log(time) �0�19 0�02 �8�46 <0�0013rd instar 9 log(time) �0�01 0�02 �0�06 NS

4th instar 9 log(time) �0�07 0�02 �3�03 <0�01

Results for the minimal adequate model obtained by a GLMM

procedure with binomial errors and a logit link function.

Fig. 2. Effect of time on the proportion of larvae exhibiting anti-

predator behaviour. Anopheles coluzzii: red triangles and red line;

Anopheles gambiae: black diamonds and black line and; Anophe-

les arabiensis: blue circles and blue line. Curves are predicted lines

obtained from a curvilinear regression with the SSfpl function

in R.



(time) meaning that they reached their baseline behaviour

before the end of the experiment (about 12 h after the

beginning of exposure for An. gambiae and An. arabiensis

and, later, for An. coluzzii, Fig. 2) with significant asymp-

totes for a high value of log(time) (An. coluzzii: t = 6�48;d.f. = 12; P < 0�001; An. gambiae: t = 28�79; d.f. = 12;

P < 0�001; An. arabiensis: t = 28�75; d.f. = 12; P < 0�001).The GLMM also revealed significant interactions

between instars and time (Table 4). The level of the anti-

predator behaviour of 4th instar larvae decreased signifi-

cantly faster than for both 2nd and 3rd instar larvae over

time (Table 4, Fig. 3). The waning rates of the antipreda-

tor responses of 2nd and 3rd instars were similar. All

instars presented a curvilinear waning of their antipreda-

tor behaviour (2nd instars: G1 = 28�79; P < 0�001; 3rd

instars: G1 = 9�12; P = 0�002; 4th instars: G1 = 341�6;P < 0�001). The curvilinear regression revealed that the

level of the antipredator behaviour in the three instars

stayed constant until it reached a threshold in time at

which it started to decrease (significant asymptotes for a

low value of log(time): 2nd instars: t = 93�79; d.f. = 12;

P < 0�001; 3rd instars: t = 39�04; d.f. = 12; P < 0�001; 4thinstars: t = 43�85; d.f. = 12; P < 0�001). This threshold

was about 1 h after the beginning of exposure for 2nd

instar larvae and about 30 min for 3rd and 4th instar lar-

vae. The three instars also have an asymptote for a high

value of log(time) meaning that they reached their base-

line behaviour before the end of the experiment (about

12 h after the beginning of the exposition in all instars,

Fig. 3) with significant asymptotes for a high value of log

(time) (2nd instars: t = 28�86; d.f. = 12; P < 0�001; 3rd

instars: t = 17�28; d.f. = 12; P < 0�001; 4th instars:

t = 16�11; d.f. = 12; P < 0�001).

Discussion

Knowledge of how prey gauge and manage a predation

threat is important to the understanding of how predation

pressures drive species divergence and structure communi-

ties. However, evidence for such mechanisms is scarce

because, from an ecological standpoint, they act over the

long term. Our research on incipient species offers an

opportunity to report the early outcomes of such mecha-

nisms and provides empirical support for the hypothesis

that divergence in predation pressure may drive ecological

divergence in the An. gambiae complex.

The results of this study provide estimation of how

aquatic prey species with an aerial (terrestrial) adult stage

manage larval predation risk both over time and accord-

ing to cue concentrations. We show that An. gambiae s.l.

larvae are threat sensitive, increasing their antipredator

responses as predation cue concentrations increase. The

antipredator behaviour waned over time for all three spe-

cies. However, the different species and instars displayed

different rates and intensities in their antipredation behav-

iour highlighting divergent adaptations to predation risk.

threat sensit iv ity

Anopheles arabiensis larvae were less sensitive than both

An. coluzzii and An. gambiae larvae. This might explain

why in a previous study, where chemical cue concentra-

tions were much lower (about less than the 25% dilution

to the present work, Roux, Diabate & Simard 2013),

An. arabiensis larvae appeared to rely mostly on physical

rather than chemical cues to assess and mount an antipre-

dator response. The response was gradual (proportional

to the threat) but constrained to a narrow reaction norm

because of a low sensitivity to high cue concentrations

(i.e. weak slope in the range of concentrations tested).

An. gambiae larvae, which share temporary waters with

An. arabiensis, expressed an antipredator response that

was higher in this range of concentrations. The response

was also gradual but with a stronger slope, leading the

antipredation response level to reach its maximum (i.e.

c. 100% of the larvae on the walls) for moderate to high

cue concentrations (i.e. the upper asymptote was reached

for concentrations above 50%). The antipredator response

of the two species is then limited to a narrow reaction

norm but for two different reasons. In contrast, An. col-

uzzii larvae living in permanent waters gradually engaged

in an antipredator response across the entire range of cue

concentrations tested and never reached a plateau in our

experimental conditions.

The weak sensitivity of An. arabiensis to low cue con-

centrations (this study; see also Roux, Diabate & Simard

2013) may actually not be maladaptive (Brown et al.

2001; Mirza & Chivers 2003). Indeed, Brown et al. (2006)

Fig. 3. Effect of time on the proportion of larvae exhibiting anti-

predator behaviour in the three instars. 2nd instars: circles and

dotted line; 3rd instars: triangles and dashed line and; 4th instars:

diamonds and full line. Curves are predicted lines obtained from

a curvilinear regression with the SSfpl function in R.



showed that cichlids had covert and imperceptible changes

in behaviour when exposed to subthreshold cue concen-

trations. In this situation, the prey waits for complemen-

tary risk indicators such as visual cues or novel predation

cues to mount a complete antipredator response. Such a

threshold, when associated with a subsequent graded

response, could be adaptive and may limit the cost of

antipredator behaviour allowing prey to feed at a normal

or subnormal rate until additional cues confirm the risk.

Weak sensitivity to low cue concentrations might there-

fore provide a selective advantage in temporary waters,

allowing larvae to maintain optimal foraging and growth

and thus escape early from short-lived habitats (Lima &

Dill 1990). In Burkina Faso, An. arabiensis is found in

temporary waters and occurs in higher numbers at the

end of the rainy season when temporary ponds are drying

out (Gimonneau et al. 2012a). However, in East Africa,

An. arabiensis is found in permanent fresh water charac-

terized by high predatory pressure suggesting the existence

of different ecotypes (Coluzzi et al. 2002) or different

local environmental pressures that may or may not allow

permanent habitats to be colonized.

Previous transplantation experiments have shown that

An. coluzzii out-competes An. gambiae in rice paddies in

the presence of predators (Diabat�e et al. 2008). Our

results show that this higher performance by An. coluzzii

could be due to better threat sensitivity to chemical preda-

tion cues. Indeed, our results show that at a high risk

level, such as is found in permanent fresh water (Diabat�e

et al. 2008), An. gambiae mounted a maximal antipreda-

tor response, whereas An. coluzzii displayed a lower and

gradual level of antipredator behaviour and then poten-

tially spent more time feeding. Such differences may

explain the ecological divergence between the two species

in which An. coluzzii takes advantage of permanent fresh

water (Diabat�e et al. 2005, 2008).

waning of antipredator behaviour

Fraker (2008) found that young Rana clamitans tadpoles

exhibited a higher level of antipredator behaviour and

recovered their baseline activity after a longer time-lag

than did their older and bigger counterparts. In our study,

the baseline recovery had the same time-lag in the three

instars but the rate at which the 4th instar larvae resumed

their antipredator behaviour was significantly higher than

the 2nd and 3rd instars. The 2nd instars maintained their

antipredator behaviour for longer than did older instars.

This suggests that early instars (i.e. smaller individuals)

perceive a high risk level for a longer period after their

initial exposure to predation cues than do older (larger)

instars, pointing towards a prey size effect. Notonectids

are known to engage in size-selective predation and to

structure aquatic communities by reducing the density of

larger individuals (Scott & Murdoch 1983; Blaustein

1998). Larger individuals may be preyed upon as a conse-

quence of their shorter period of sensitivity over time

and/or because they are more conspicuous than smaller

prey.

The decrease in a response to predation cues over time

is common to most organisms (Lima & Dill 1990). Several

non-exclusive hypotheses can be suggested to explain the

waning of an antipredator response. First, chemical cues

are not stable over time. Compounds can be quickly

diluted or degraded by micro-organisms and ultraviolet

(UV) radiation. Such a loss of biological activity can

occur from within a few hours to several days (Peacor

2006; Ferrari, Messier & Chivers 2008). Moreover, when

predators move around, low concentrations of predation

cues are less reliable indicators of acute predation risk

than are higher concentrations (Fraker 2008). In our

study, the waning of an antipredator response took about

12 h. However, the cue degradation process is probably

more rapid in natural conditions, whereby biological (i.e.

microbial) and abiotic (e.g. UV radiation, adsorption)

processes contribute to the destruction of cues (Ferrari,

Messier & Chivers 2008).

Sensory habituation cannot be excluded in explaining

the waning of the antipredator response. However, the

2nd instar larvae seemed to maintain their maximal

response longer than did later instars. In the case of sen-

sory habituation, this would imply that the turnover of

odorant binding proteins and the reactivation of the sen-

sory receptors of 2nd instar larvae are faster than for later

instars allowing 2nd instars to be receptive longer. This

difference between early and late instars allows us to par-

tially exclude the dominant effect of cue degradation in

the waning of antipredator responses.

Finally, according to the risk allocation hypothesis,

prey might actively resume foraging in the face of a pre-

dation threat because long periods of food deprivation

may seriously hamper growth and survival, therefore

speeding up the waning of antipredator responses. It is

therefore possible that prey rely on additional cues to

prompt such behaviour.

Knowing which threat level induces an antipredator

response is good, but, in addition, knowing for how long

and why the response is maintained is better. Most studies,

like this one, dealing with threat-sensitive responses investi-

gated the effect of independent exposure to a range of cue

concentrations. However, few of them attempted to quan-

tify the dynamics of the waning of the behavioural response

over time (but see Peacor 2006; Ferrari, Messier & Chivers

2008). Identifying and quantifying the chemical compounds

involved in an antipredator response as well as their degra-

dation derivatives over time hence presents a challenge for

future research. Indeed, if low cue concentrations are not

informative because it is impossible to distinguish between

a recent small predation event and a larger but past event,

detecting degradation derivates could be a selective advan-

tage. By comparing the concentrations of both the original

predation cue and its derivatives, prey could obtain more

complete information on the temporal risk and then gradu-

ally adjust their antipredator behaviour over time.



evolution of phenotypic plastic ity

Phenotypic plasticity provides a selective advantage in

fluctuating environments. However, the impact on fitness

traits remains to be tested in order to determine which

patterns of response to the threat are the best adapted.

Nevertheless, Diabat�e et al. (2008) have shown that in the

presence of predators, An. coluzzii out-competes An. gam-

biae. Its response is thus probably the closest to the opti-

mal, allowing it to best balance antipredator behaviour

with other fitness traits. Here, phenotypic plasticity was

shown in all species, whatever their habitat of origin, sug-

gesting that in the two habitats, larvae are exposed to

fluctuating levels of predation pressure. Permanent fresh-

water habitats are, by definition, more stable than tempo-

rary ones and thus should favour a loss of plasticity and

generate flat reaction norms (Sultan & Spencer 2002;

Hollander 2008). However, as expected, our results

showed that An. coluzzii displayed a highly plastic

response proportional to the threat level, suggesting an

acute response over a large range of risk. Such a high

phenotypic plasticity could be explained by two non-

exclusive hypotheses. First, An. coluzzii is found in both

temporary and permanent habitats suggesting the poten-

tial exposure of natural mosquito populations to hetero-

geneous environments with a high dispersal rate between

habitats. Secondly, Notonectids are winged aquatic insects

at both the adult and nymphal stages and thus, as preda-

tors move between habitats in search of prey, their densi-

ties can fluctuate over time. Phenotypic plasticity in an

antipredator response might have been acquired and

evolved from the ancestral species, An. gambiae, which

also displays a large reaction norm, with the same slope

as An. coluzzii but with a different intensity. However,

An. gambiae is restricted to temporal habitats and there-

fore experiences lower predation risk; its strong antipreda-

tor behaviour to high concentration cues may prevent it

from developing in permanent habitats due to a poor

match with other traded-off fitness traits.

The reaction norm of An. arabiensis is narrower than

the two other species. As An. arabiensis is mainly found

at the end of the rainy season in our study area (Gimon-

neau et al. 2012a), we hypothesise that its abundance may

be negatively correlated with predator density all year

around, allowing larvae to fully develop only at the end

of the rainy season when temporary ponds are drying up.

Conclusion

It is well known that high levels of predation pressure

over generational time may determine the intensity of

antipredator responses (Giles & Huntingford 1984). How-

ever, little is known about the impact of such pressure on

threat sensitivity. Brown et al. (2009) have shown that

Trinidadian guppy populations exposed to a high level of

predation exhibit a more intense and more proportional

antipredator response than do populations exposed to low

predation pressure. Our results agree with these findings

as An. coluzzii mounts a more proportional antipredator

response than either An. gambiae or An. arabiensis larvae.

Nevertheless, the similarity of the rates at which

An. coluzzii and An. gambiae increased their antipredator

response is consistent with An. gambiae being considered

ancestral to the derived An. coluzzii and is in line with

previous scenarios of ecological speciation within the

An. gambiae complex (Ayala & Coluzzi 2005; Costantini

et al. 2009). Hence, our results provide further evidence

that differences in the predation pressure exerted in per-

manent and temporary fresh water likely contributed to

disruptive selection promoting ecological divergence

between An. coluzzii and An. gambiae and between some

species of the An. gambiae complex (Diabat�e et al. 2008;

Roux, Diabate & Simard 2013).

Acknowledgements

We would like to thank Boubacar Nikiema for the PCR, Thierry

Lef�evre and Carlo Costantini for helpful discussions and Andrea

Yockey-Dejean for proofreading the paper. We also thank two

anonymous Referees and the Associate Editor for valuable com-

ments. Financial support for this study was provided through

IRD/MIVEGEC in-house funding. OR received financial support

through a post-doctoral fellowship from the IRD.

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Received 15 March 2013; accepted 13 October 2013

Handling Editor: Ken Wilson



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Divergence in threat sensitivity among aquatic larvae of cryptic mosquito species