ANIMAL BEHAVIOUR, 2006, 72, 1025e1034doi:10.1016/j.anbehav.2006.02.017

Predator foraging strategy influences prey population dynamics:

arthropods predating a gregarious leaf beetle

PETER DALIN* , OSKAR KINDVALL† & CHRISTER BJORKMAN*

*Department of Entomology and

ySwedish Species Information Centre, Swedish University of Agricultural Sciences

(Received 19 October 2005; initial acceptance 8 December 2005;

final acceptance 14 February 2006; published online 22 September 2006; MS. number: 8709)

We examined whether behavioural variation within an enemy complex attacking the willow leaf beetle,Phratora vulgatissima, influences the population dynamics of this gregarious prey. The most common en-emies are three species of heteropteran arthropods: the two mirids Orthotylus marginalis and Closterotomusfulvomaculatus and the anthocorid Anthocoris nemorum. When attacking egg clusters on plants in the lab-oratory, the two mirids consumed a greater proportion of eggs within egg clusters than the anthocorid. Theanthocorid visited and ate eggs from more egg clusters than both the mirids. The two foraging strategieshave been characterized as ‘find and stay’ for the mirids and ‘run and eat’ for the anthocorid. By using a sto-chastic exponential growth model we showed that model prey experienced different temporal dynamicswhen exposed to predators that differ in the probabilities of finding prey aggregations and of consumingprey within aggregations. Model prey exposed to the find and stay type of predator was less likely to be-come established and to increase in abundance than model prey exposed to the run and eat type. In a fieldstudy, we found a correspondence between high abundance of find and stay mirids and low densities ofleaf beetles. The results suggest that, even when average predation rate is constant, the foraging strategyof the predator can have population level consequences for the prey. The consumption of prey in densepatches seems to be important in the control of gregarious prey, especially in the early phase of prey pop-ulation establishment.

� 2006 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

The importance of behaviour in predatoreprey dynamicshas been emphasized for decades (Holling 1961; Van Drie-sche & Bellows 1996; Venzon et al. 2000). Prey is oftenpatchily distributed in space, implying that many preda-tors need to search actively to find food. Accordingly,high search efficiency is considered to be an important be-havioural attribute of predators to control prey popula-tions (Van Driesche & Bellows 1996). The predator’sability to stay and consume prey in dense prey patchesmight also be important, especially in systems where theprey occurs in dense aggregations (Kareiva & Odell1987). The foraging behaviour of a predator, such as its

Correspondence and present address: P. Dalin, Marine Science Institute,University of California at Santa Barbara, CA 93106-6150, U.S.A.(email: dalin@msi.ucsb.edu). O. Kindvall is at the Swedish Species In-formation Centre, Swedish University of Agricultural Sciences, P.O. Box7007, SE-750 07 Uppsala, Sweden. C. Bjorkman is at the Departmentof Entomology, Swedish University of Agricultural Sciences, P.O. Box7044, SE-750 07 Uppsala, Sweden.

10003e3472/06/$30.00/0 � 2006 The Association for the

search intensity, is often related to the type of food eaten(Huey & Pianka 1981). For example, broad diet predators(generalists) are considered to search less frequently fora given prey type than specialists because generalists canfeed on a wide range of other food items that are encoun-tered (Westoby 1978; Coll & Guershon 2002). Besides en-counter frequencies, foraging behaviour is also influencedby factors such as predation risk, prey behaviour andnutritional requirements (Sih 1993; Biesinger & Haefner2005). This often results in a large variation in foragingstrategies within predator complexes where species orage classes of predators differ in, for example, the area ofsearch and how they respond to dense patches (Wiskerke& Vet 1994; McCauley et al. 1996; Cisneros & Rosenheim1998). Few researchers, however, have investigatedwhether such behavioural variations within enemy com-plexes influence the population dynamics of the prey.

Primary consumers, such as herbivorous insects, areoften attacked by a diverse complex of natural enemies(Polis 1991). The insect order Heteroptera (true bugs) con-tains a large number of generalist predator species with

025Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

ANIMAL BEHAVIOUR, 72, 51026

different foraging strategies, ranging from ‘widely forag-ing’ to ‘sit and wait’ predators (Rosenheim et al. 1993). An-thocorids (Heteroptera: Anthocoridae) often have activesearching behaviours (Bjorkman et al. 2003; Montserratet al. 2004), and their foraging seems to be related to thewidely foraging strategy described by Pianka (1966). Thewidely foraging predators are often efficient at findingprey patches but they leave dense patches before all preyare consumed (Caraco & Gillespie 1986). The foraging be-haviour of the anthocorid Anthocoris nemorum L. has alsobeen described as a ‘run and eat’ strategy (Bjorkmanet al. 2003). In comparison with the active anthocoridbugs, several species of assassin bugs (Heteroptera, Redu-viidae) have sedentary behaviours and ambush mobileprey, using their raptorial anterior legs to capture it (Miller1978; Kevan & Greco 2001). The sit and wait and thewidely foraging strategies can be seen as two extrememodes of foraging, where some species actively searchfor prey whereas others wait to capture mobile prey(Huey & Pianka 1981). In Bjorkman et al.’s (2003) study,two species of mirids (Heteroptera, Miridae) seemed tohave a foraging strategy that was intermediate to the sitand wait and the widely foraging strategies (Rosenheimet al. 1993). The mirids, which are primarily plant feeders(Wheeler 2001), search for prey actively but are sedentaryfor much of the time. Although other mirids may havemore active searching behaviours (Montserrat et al.2004), the two mirid species studied by Bjorkman et al.(2003) were less efficient at finding prey patches thanthe anthocorid A. nemorum. However, once prey wasfound, both mirid species tended to stay longer in eachpatch to consume many prey. Because of their relativelyhigh efficiency at consuming prey in aggregations, the for-aging behaviour of the two mirids has been described as‘find and stay’ (Bjorkman et al. 2003). A somewhat similarrange of behaviours has been described among lizards, in-cluding widely foraging, sit and wait and intermediatestrategies (Huey & Pianka 1981; Perry 1999).

An interesting ecological question is to what extent preypopulation dynamics is influenced by different foragingstrategies of predators. Rosenheim & Corbett (2003) usedan individual-based model to study the effects of a sitand wait and a widely foraging predator. The model pre-dicted the widely foraging strategy to be more efficientat suppressing prey populations than the sit and waitstrategy. The sit and wait strategy was not efficient becauseboth the predator and the prey had sedentary behavioursand, thus, were unlikely to meet in the model. In the pred-atoreprey system studied by our research group, the leafbeetle Phratora vulgatissima (L.) (Coleoptera: Chrysomeli-dae) is attacked by three species of heteropterans: one an-thocorid, Anthocoris nemorum, and two mirids, Orthotylusmarginalis Reut and Closterotomus fulvomaculatus De Geer(Bjorkman et al. 2003). The leaf beetle lays eggs in clustersand the larvae feed gregariously throughout the first andsecond instars.

Our aim in the present study was to investigate whetherthe population dynamics of P. vulgatissima would be dif-ferently affected if the beetle were exposed to predatorswith the two foraging strategies find and stay and runand eat, as described by Bjorkman et al. (2003). For this

purpose we used a relatively simple simulation modelbased on stochastic exponential growth. In the model,two predator types were characterized with respect tothe proportion of egg clusters found in a prey population,and with respect to the proportion of eggs eaten withinclusters. Although the two predators were expected tohave similar consumption rates in the model, sedentarypredators often cause more variation in prey mortalityamong prey patches than active predators (Caraco & Gil-lespie 1986). This difference between predators was ex-pressed in our model by the find and stay predatorhaving a lower probability of finding egg clusters but con-suming more eggs within each cluster. We also made a pre-liminary validation of the model outputs by studyingpatterns of leaf beetle and predator abundance in the field.The model was therefore adjusted to population data ofP. vulgatissima collected from the field. Based on the modelresults, we predicted that lower densities of leaf beetleswould be found in willow stands dominated by the pred-ator type that was most efficient at reducing or preventingincreases in leaf beetle numbers in the model. To illustratethe behavioural difference between predator types, we firstpresent results from a laboratory experiment in which wecompared how the three species of heteropteran predatorsdispersed their feeding among egg clusters on plants.

METHODS

Study Species

The leaf beetle P. vulgatissima is univoltine in Sweden. Itoverwinters as an adult and starts to feed on willow plants(Salix spp.: Salicaceae) at the beginning of May. The egg-laying period in Sweden extends from late May to the mid-dle of June and the eggs are laid on willow leaves in clustersof 10e50 eggs. One female can lay several hundreds of eggsduring a season and the eggs hatch after 15e20 days(Kendall & Wiltshire 1998). After passing through three in-stars, the larvae pupate in the soil and the next generationof adult beetles emerges in August. This beetle is a majorinsect pest in plantations of the willow Salix viminalisL. (short-rotation forests) and outbreaks are frequentlyreported (Sage & Tucker 1998; Bjorkman et al. 2004a).

The most common enemies attacking eggs and larvae ofP. vulgatissima are three species of heteropteran generalistpredators (Bjorkman et al. 2003). Anthocoris nemorum hi-bernates as an adult and both adults and newly hatchednymphs can be found in the field during the egg develop-mental period of P. vulgatissima. Orthotylus marginalis isthe most common predator of the eggs and larvae (Bjork-man et al. 2003). Closterotomus fulvomaculatus is the least(or sometimes the second most) abundant of the threeheteropterans and had the highest consumption rate ofeggs in a laboratory experiment (Bjorkman et al. 2003,2004b). The mirids overwinter as eggs and it is mainlytheir nymphal stages that can be found feeding on leafbeetle eggs in the field. Detailed descriptions of the biol-ogy of the heteropterans can be found in Kullenberg(1944) and Southwood & Leston (1959), and for themirids in Wheeler (2001).

DALIN ET AL.: PREDATOR FORAGING STRATEGIES 1027

Predation of Egg Clusters

To illustrate the behavioural differences between thethree predator types, we studied how they dispersed theirfeeding among three egg clusters laid by P. vulgatissimaon plants in the laboratory. Bjorkman et al. (2003) dida similar experiment with two egg clusters per shoot.The main reason for replicating the experiment withthree egg clusters was that a relatively high proportionof the mirids did not find any eggs in the previous exper-iment (Bjorkman et al. 2003). We therefore expected toreduce the variation in consumption rate among predatorspecies by increasing the number of egg clusters perplant. Although the density of egg clusters was increasedin the present study, it remained within the range of thatoften found under natural conditions in the field (Ken-dall & Wiltshire 1998; C. Bjorkman, K. Eklund & P. Dalin,unpublished data).

The predators were collected from the field and releasedsingly on potted saplings of S. viminalis inside plastic cyl-inders (70 cm high � 25 cm in diameter). The experimentwas conducted in late May and at the beginning of June2001 in an environmentally controlled room (tempera-ture: 20�C; humidity: 80%; 20:4 h light:dark regime). Weused adults of A. nemorum and late instars of the mirids(Instars IIIeIV) in the experiment. These life stages ofpredators were used because they occur in the field atthe same time as eggs of P. vulgatissima are present. Theyalso had similar consumption rates of eggs when studiedin petri dishes (Bjorkman et al. 2003). We kept the preda-tors without access to eggs on the plants for 24 h beforethe experiment, to starve them and to allow them to ad-just to the environment. Three excised leaves, containingone egg cluster on each leaf, were then pinned on to theplants (one at the top, one in the middle and one at thebase of the plants) and the predators were left for 48 h.The egg clusters used in the experiment were laid by fe-male leaf beetles on plants inside cages and consisted of,on average, 13 eggs per cluster (N ¼ 222 egg clusters, range8e24 eggs per cluster). In a previous study, P. vulgatissimalaid, on average, 19 eggs per cluster (P. Dalin, unpublisheddata). Thus, the beetles used in the present study laid rel-atively small egg clusters, perhaps because they were keptat high densities inside the cages and therefore mighthave been competing for suitable places to lay theireggs. The egg clusters used in the experiment were, there-fore, on average smaller than the egg cluster size used inthe model simulations (see below).

After 48 h we counted the eggs eaten and searched theplants for remaining skins left by moulting nymphal mir-ids. We excluded from the analyses data from predatorsthat had been moulting because most insects empty theirgut before each moult and predators that had beenmoulting during the experiment might have been lessmotivated to feed (Waldbauer 1968). We also excludeddata from those replicates where we did not find thepredator when the experiment was terminated. We classi-fied the number of egg clusters visited by an individualpredator as either 0e1 or 2e3, to reach high enough ex-pected numbers to test for differences between predatorspecies with chi-square tests. Consumption rates (i.e.

number of eggs consumed/h) were analysed with a Krus-kaleWallis test with Tukey type Nemenyi tests for preda-tor species comparisons (Zar 1999). Owing to lowexpected frequencies, we used Fisher’s exact tests to testfor differences in the proportion of eggs consumedwithin egg clusters.

Field Densities of Beetles and Predators

We estimated densities of P. vulgatissima and the hetero-pteran predators in 21 stands of S. cinerea in 2000e2002.The size of the stands ranged between 10 and 50 m2.Twelve of the willow stands were located in forest habitats(i.e. surrounded by mixed forests dominated by conifers)and nine were in farmland (i.e. in open, agricultural land-scapes). These two habitats were chosen as comparisonbecause previous studies showed that forest and farmlandS. cinerea differ in predator species composition, but not inhost plant quality for leaf beetles or climatic factors suchas temperature (Dalin 2004). We measured densities byknockdown sampling conducted in late May and earlyJune, when the adult leaf beetles have emerged from win-ter hibernation and start to mate and lay eggs. Sampleswere evenly distributed among willow bushes withinstands and at least 30 samples per stand and year weretaken (mean ¼ 60, range 30e95, samples per stand andyear). Because some stands were rather small, the spatialdensity of samples was higher in small than in largestands. The sampling was done by knocking off all insectsfrom 35-cm sections of willow branches, containing cur-rent-year shoots, inside a plastic cylinder. Leaf beetlesand heteropteran predators were classified to species inthe field and released again at the base of the willowbushes (see also Bjorkman et al. 2004a).

We used nonparametric two-tailed ManneWhitneyU tests to investigate whether densities differed betweenthe forest and the farmland habitats. In the statisticalanalyses, we used mean densities calculated over the 3years for each stand as independent observations. Weused nonparametric tests because the data did not fulfilthe requirements for parametric analyses. The averagerate of population growth between years (Nt þ 1/Nt) andthe average variation in leaf beetle density (CV; the stan-dard deviation of density divided by the mean density)were calculated for P. vulgatissima to be used for adjustingthe simulation model (see below).

Population Model

We modelled prey population dynamics by usinga stochastic exponential growth model with a ceiling (K )restricting the number of individuals to a specific thresh-old determined by the total amount of available resources.In the model, we applied a ceiling value on the number ofreproducing individuals (Nt) instead of on the resulting to-tal population size (Nt þ 1), which is the conventionamong population ecologists (Foley 1994; Middletonet al. 1995). This modification enables the prey populationsize to overshoot the ceiling occasionally and therebyfluctuate realistically close to the ceiling level, which is

ANIMAL BEHAVIOUR, 72, 51028

otherwise not the case. Thus, we used the followingequation:

Ntþ1 ¼ lt �min½Nt ;K�: ð1Þ

The parameter lt is the population rate of increase, whichis realized at each discrete generation (t). The value of thistemporally varying parameter determines how much thenumber of individuals (N ) changes between successivetime steps. To enable investigations on the effects of pred-ator foraging strategies, we split lt into its two basic com-ponents, fecundity (Ft) and survival (St):

lt ¼ Ft � St : ð2Þ

Ft is the average number of eggs produced per prey individ-ual at time step (t). In the simulations, Ft values were gener-ated from a log-normal distribution specified by the long-term average fecundity (F ) and its temporal standard devia-tion (s). This procedure introduces environmental stochas-ticity into the dynamics. The total number of eggs (ntot) laidin any time step was then calculated as the product of Ft andthe current number of reproducing adults.

To simulate the prey laying their eggs in a number ofseparate egg clusters, as is common among many herbiv-orous insects, we calculated the average fecundity (F ) asa product of two separate components, fc and fe:

Ft ¼ fc � fe: ð3Þ

The parameter fc is the average number of egg clusters pro-duced per individual and fe is the average number of eggslaid in each cluster. Based on the value for the total num-ber of eggs laid in each time step (ntot), the number of eggclusters was determined according to the following simplealgorithm. If ntot was smaller than the value for fe, the to-tal number of egg clusters (nc) was set to one, otherwise nc

was set to the integer closest to ntot divided by fe. Thereaf-ter, the number of eggs per cluster (ne) was determined asthe integer closest to ntot divided by nc.

Predation on eggs is expected to contribute onlypartially to the total survival (St). Therefore, we split St

into two sequential components: s1 and s2. The formercomponent is the fraction of eggs that survives the focalegg predator and the latter component is the fraction ofthe remaining eggs (s1 � ntot) that survive all developmen-tal stages to reproducing individuals in the next time step.Thus, the relation between these components and theoverall survival (St) is:

St ¼ s1 � s2: ð4Þ

The impact of an egg predator on the prey population canbe characterized by the following two parameters: (1) theaverage proportion of available egg clusters in the preypopulation found by the predator (pc), and (2) the averageproportion of the eggs consumed within an egg cluster(pe). If the values of these two parameters are known itis possible to calculate the average mortality rate (m) ofthe prey species caused by the focal predator, i.e. 1 � s1:

m¼ pc � pe: ð5Þ

In this study, we assumed that different predators differonly in the values of pe and pc, because of different

foraging strategies, and that their expected average con-sumption rate (s1) is the same. Thereby, for a given valueof pe it was possible to calculate pc as

pc ¼1� s1

pe

: ð6Þ

After having calculated the time step-specific values of nc

and ne, we continued the simulation by stochastically de-termining the total number of eggs (np) that is eaten bythe focal predator. This was done in two steps. First, thenumber of egg clusters preyed upon was determined bygenerating a random value from a binomial distributionspecified by the probability of an egg cluster being foundby the predator (pc) and the current number of egg clus-ters (nc). Thereafter, the number of predated eggs was de-termined for each egg cluster by generating randomvalues from a binomial distribution specified by the prob-ability pe and the current number of eggs in a cluster (ne).

The number of prey individuals in the next generation(Nt þ 1) was finally obtained by simply multiplying thenumbers of surviving eggs (ntot � np) by s2. The adult pop-ulation size (Nt) was tracked through the simulation as realnumbers. If the population size was equal to or smallerthan one individual (Nt � 1), the population was consid-ered to be extinct.

Parameter Values

One of our aims was to try to evaluate the modelresults by comparing model outputs with field densitiesof leaf beetles and heteropteran predators. Egg and larvalmortality caused by heteropteran predators is often highfor P. vulgatissima (Bjorkman et al. 2003, 2004a), andmore than 90% egg mortality from predation is not un-common in stands of S. cinerea (Dalin 2004). We there-fore made simulations for both moderate (0.5) and low(0.1) values of egg survival (s1) in the model. For thefind and stay predator, the value of pc was set to 0.5 or0.9 and the value of pe was set to 1, to generate the aver-age mortality (m) of 0.5 or 0.9. This implies that the findand stay predator will consume all eggs within those eggclusters that are found. For the run and eat predator, pc

was set to 1 and pe was set to 0.5 or 0.9, implying thatthe run and eat predators will find every egg cluster inthe prey population but consume fewer eggs within clus-ters than the find and stay predator.

Based on the field data for leaf beetles, we calculated theaverage population growth rate of P. vulgatissima (Nt þ 1/Nt) to be 1.37 and the CV to be 0.60. By using l ¼ 1.37in the model, we simulated prey over three generationsand varied s (i.e. the degree of environmental stochastic-ity) until a CV value of 0.60 was generated. The value ofs that caused populations to fluctuate in a manner similarto what was found in the field was 60. In a previous study,average lifetime fecundity of female P. vulgatissima was226 eggs and they laid on average 19 eggs per cluster(P. Dalin, unpublished data). Since the model assumesthat all individuals produce eggs, the average long-termfecundity (F ) was set to 113. Because the number of eggsper cluster ( fe) was 19, the corresponding value for the

DALIN ET AL.: PREDATOR FORAGING STRATEGIES 1029

number of egg clusters laid per individual adult ( fc) was setto 5.9 (i.e. F/fe).

Using the model, we studied (1) the probability of preyincreasing 10-fold in abundance, (2) the probability ofprey failing to become established, (3) the variability inprey abundance (CV), and (4) the probability of preyabundance decreasing by 90%. The simulations were runfor 30 time steps (i.e. beetle generations) and eachparameter combination was replicated 1000 times.

To compare probabilities of prey increasing in abun-dance and of prey failing to become established, wesimulated different initial prey population sizes (N0 ¼ 2,5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 160). These valueswere chosen arbitrarily to simulate different initial leafbeetle population sizes colonizing a newly established wil-low stand. Specifically, for each predator and initial preypopulation size, we measured the proportion of 1000prey populations that had increased from N0 toNt � N0 � 10, at some time point during 30 time steps.To study failures of establishment, we measured the pro-portion of populations that had gone extinct (N � 1)during 30 time steps and we set the ceiling (K ) to 3000for all N0 values.

To study variability in prey abundance, we let preyfluctuate at different ceilings (K ). The values of the ceiling(K ) were chosen arbitrarily to simulate prey fluctuating atmaximum population levels in willow stands varying inthe total amount of resources. The CV was used as a mea-sure of population variability. We also measured the pro-portion of prey populations that had decreased fromK (N0) to Nt � K � 0.10, at some time point during 30time steps. We started by simulating prey fluctuating atvery low values of K, e.g. K ¼ 10, 20, 40, 80. Since wefound differences in prey dynamics only for K < 500, inthe Results we present data for prey fluctuating at K valuesbetween 10 and 1280.

To test the robustness of the model results, we also ransimulations for higher and lower values for both thestandard deviation of fecundity (s ¼ 180, s ¼ 20) andthe average rate of prey population increase (l ¼ 1.00,l ¼ 2.00). Table 1 lists the parameters and variables.

RESULTS

Predation of Egg Clusters

The anthocorid visited (i.e. ate eggs from) more egg clustersthan the two mirids, that is, a higher proportion of individualsvisited2e3than0e1eggclusters (chi-square tests:A.nemorumversus O. marginalis: c2

1 ¼ 6:6, P ¼ 0.010; A. nemorum versusC. fulvomaculatus: c2

1 ¼ 5:0, P ¼ 0.026; Fig. 1). The two miridsdid not differ significantly with respect to the number of indi-viduals that visited 0e1 or 2e3 egg clusters (c2

1 ¼ 2:7,P¼ 0.100). The mirid C. fulvomaculatus had the highest con-sumption rate ðX � SE ¼ 0:40� 0:08 eggs consumed=hÞ.The anthocorid had an intermediate consumption (0.19 �0.04 eggs/h) and the mirid O. marginalis had the lowest con-sumption rate (0.09� 0.03 eggs/h). A significant differencewas found between C. fulvomaculatus and O. marginalis(KruskaleWallis, Nemenyi test: Q0.05,N,3 ¼ 3.45, P < 0.05),

whereas no other significant differences in consumption rateswere found. Agreater proportion of the mirid O. marginalis didnot consume any eggs at all compared to the anthocorid (chi-square test: c2

1 ¼ 6:6, P¼ 0.010).Among those egg clusters that were preyed upon,

A. nemorum left a greater proportion of eggs uneatenthan the mirids (Fig. 1), and differed significantly fromO. marginalis (Fisher’s exact test: P ¼ 0.036) and C. fulvo-maculatus (P < 0.001). In addition, C. fulvomaculatus con-sumed a significantly greater proportion of eggs than O.marginalis (P < 0.001).

Field Densities of Beetles and Predators

Overall, the find and stay mirids (mainly O. marginalis)were more abundant than the run and eat anthocorid(ManneWhitney U test: U ¼ 642, N1 ¼ N2 ¼ 21, P < 0.001;Fig. 2a). Consequently, no willow stands were found wherethe run and eat predator was more abundant than the findand stay predators. Densities of mirids were higher in standsof S. cinerea growing in farmland habitats than in standsgrowing in forest habitats (U ¼ 101, N1 ¼ 9, N2 ¼ 12,P < 0.001; Fig. 2a). No significant difference betweenhabitats could be found in densities of A. nemorum(U ¼ 80, N1 ¼ 9, N2 ¼ 12, P ¼ 0.070; Fig. 2a).

Table 1. Summary of parameters and variables used to study effectsof predator foraging strategy on prey population dynamics

Symbol Descriptive name Investigated values

N0 Initial population size 2e160K Maximum population

size (i.e. ceiling)10e1280, 3000

l Average populationrate of increase

1.00, 1.37, 2.00

F Average fecundity 113s Standard deviation

of fecundity(i.e. degree of environ

mental stochasticity)

20, 60, 100

fe Average numberof eggs per egg cluster

19

fc Average numberof egg clusterslaid per individual

5.9

S Average survivalrate from eggsto adults

0.0089, 0.0121, 0.0177

s1 Average proportionof eggs survivingpredation from focalpredator

0.1, 0.5

s2 Average proportionof surviving eggsthat result in adultspecimens

0.0889, 0.1210, 0.1770

m Average mortalityrate from focal predator

0.9, 0.5

pe Average proportionof eggs consumedin an egg clusterby the focal predator

Run and eat predator:0.9, 0.5Find and staypredator: 1.0

pc Average proportionof egg clustersfound by the focalpredator

Run and eatpredator: 1.0Find and staypredator: 0.9, 0.5

ANIMAL BEHAVIOUR, 72, 51030

O. marginalis O. marginalis

C. fulvomaculatus C. fulvomaculatus

A. nemorum A. nemorum

25

20

15

10

5

0

25

20

15

10

5

0

25

20

15

10

5

0

1

0.5

0

1

0.5

0

1

0.5

0

Nu

mbe

r of

in

div

idu

als

Number of egg clusters visited Percentage of eggs eaten

Prop

orti

on o

f cl

ust

ers

0–1 2–3 1–33 34–67 68–100

Figure 1. The number of predators visiting 0e1 or 2e3 egg clusters and the proportion of clusters from which 1e33, 34e67 or 68e100% of

eggs were eaten by heteropteran predators attacking eggs of the leaf beetle Phratora vulgatissima on willow plants in the laboratory. N ¼ 15,27, 17 individuals and 29, 20 and 24 egg clusters for Anthocoris nemorum, Orthotylus marginalis and Closterotomus fulvomaculatus, respectively.

: Mirids, which represent find and stay predators; ,: anthocorid, the run and eat predator.

The leaf beetle was more abundant in forest than infarmland willow stands (ManneWhitney U test: U ¼ 83,N1 ¼ 9, N2 ¼ 12, P ¼ 0.047; Fig. 2b). Willow stands infarmland habitats were also more often unoccupied byleaf beetles (i.e. no beetles found during sampling) thanforest willow stands (chi-square test: c2

1 ¼ 8:0, P ¼ 0.005;Fig. 2c).

Simulation Model

When simulating initial prey populations colonizinga willow stand, we found differences between predatortypes mainly when predation rates on eggs were high(Fig. 3b, d). The probability of prey increasing in abun-dance was lower with find and stay predators than withrun and eat predators (Fig. 3b). Differences between pred-ator types were found mainly for the smallest initial pop-ulations simulated (N0 < 70 in Fig. 3b). For N0 < 70, therewas also a higher probability of establishment failure (i.e.

higher probabilities of prey populations becoming extinct,N � 1) with the find and stay predator than with the runand eat predator (Fig. 3d). When we varied the degree ofenvironmental stochasticity (s), or the rate of prey popu-lation increase (l), the difference between predator typesremained. However, when s ¼ 180, differences betweenpredator types were found mainly for the very smallestprey populations simulated (N < 30). When we usedl ¼ 1.00, there were generally low probabilities of preyincreasing in abundance. However, for l ¼ 1.00, the dif-ference in establishment failure also became evident forlarger prey populations simulated. For example, for thelargest initial prey population size simulated (N0 ¼ 160),the probability of establishment failure was 0.53 withthe find and stay predator, and 0.35 with the run andeat predator, when prey rate of increase (l) was set to1.00. However, no major difference between predatortypes was found at moderate levels of egg predation(Fig. 3a, c).

DALIN ET AL.: PREDATOR FORAGING STRATEGIES 1031

2000 2001 2002 2000 2001 2002ForestFarmland

0

0.5

1

0

0.25

0.5

0.75

0

0.25

0.5

0.75

Leaf

bee

tle

den

sity

(lo

g[N

+1])

Prop

orti

on o

f w

illo

w s

tan

ds

Pred

ator

den

sity

(lo

g[N

+1])

(a)

(b)

(c)

Figure 2. Box plots showing median densities (log [N þ 1]) of heter-

opteran predators and the leaf beetle Phratora vulgatissima per35-cm sections of plants over 3 years in willow, Salix cinerea, stands

growing in farmland (N ¼ 9) and forest (N¼ 12) habitats. (a) Densities

of find and stay predators ( , the two mirids Orthotylus marginalis

and Closterotomus fulvomaculatus added together) and the run andeat predator Anthocoris nemorum (,). (b) Densities of P. vulgatis-

sima, which is a common prey for all three predators, in the same

willow stands. (c) Proportion of willow stands occupied ( ) or not

(,) (i.e. no beetles found in samples) by P. vulgatissima in thetwo habitats.

When we simulated prey fluctuating at different ceil-ings, no major differences in prey population variability(i.e. the coefficient of variation in prey numbers) werefound between predator types, at either moderate or highpredation rates (Fig. 4a, b). However, the model showeda higher probability of prey abundance decreasing by90% with the find and stay predator than with the runand eat predator when predation rate was high (Fig. 4d).Again, differences between predator types were foundmainly for prey fluctuating at the very lowest ceilingvalues, i.e. K < 160 (Fig. 4d). No difference in prey CV orin the probabilities of decreasing in abundance werefound between predator types for prey fluctuating athigher ceilings when we varied the degree of environmen-tal stochasticity (s), or when we varied population growthrate of prey (l), in the model.

DISCUSSION

The findings of behavioural differences between theheteropteran predator species in Bjorkman et al.’s (2003)study were reinforced by the present study (Fig. 1). Themodel predicted that stands dominated by run and eator find and stay predators should behave differentlywith respect to prey population dynamics, especially atlow prey densities and when predation rate was high(Figs 3, 4). The field data gave support to some of themodel predictions (Fig. 2).

According to our model, the foraging strategy ofpredators can affect several important aspects of preypopulation dynamics. However, the impact depends onthe number of prey and predation pressure. The leaf beetleP. vulgatissima often occurs in rather large populations, es-pecially in those large willow plantations that were estab-lished in the early 1990s for biomass production in south-central Sweden. Today, these willow plantations poten-tially support between 5000 and 85 000 adults/ha (95%confidence interval for the mean 45 000 measured in 32willow plantations; C. Bjorkman & K. Eklund, unpub-lished data). For such large populations, no detectable dif-ferences in prey temporal variability are expected to becaused by predator behaviour. Neither will the predatortype affect the chance of population decline when theprey population is larger than a few hundred individualsor when predation rates are low. However, the probabilityof establishment in a vacant willow stand is expected to bemuch lower with find and stay predators than with runand eat predators when predators are present before leafbeetle establishment. Furthermore, the probability of pop-ulation increase from low initial numbers (i.e. to increasefrom endemic levels) is much lower if the predator be-longs to the find and stay type. Consequently, we predictthat smaller willow stands, such as the natural stands of S.cinerea studied here, where find and stay predators aredominant, will more often be unoccupied by leaf beetlessuch as P. vulgatissima than willow stands less dominatedby find and stay predators. High population densities arealso expected mainly in stands of S. cinerea where findand stay predators are uncommon or absent.

The results from our field study showed that find andstay mirids were, in general, more abundant than the run

ANIMAL BEHAVIOUR, 72, 51032

Initial population size

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Figure 3. Model results in which initial prey population sizes (N0) were exposed to predators with two kinds of foraging strategies: find and stay

and run and eat. (a, b) Probability of prey increasing 10-fold in abundance, from N0 to N ¼ N0 � 10, at some time point during 30 time steps,when average egg mortality from predation, s1, was (a) 0.5 and (b) 0.9. (c, d) Probability of establishment failure, i.e. the probability of prey

going extinct (N � 1), when average egg mortality was (c) 0.5 and (d) 0.9.

and eat anthocorid in the willow stands studied. There-fore, no direct comparison between the responses ofsystems dominated by find and stay or run and eatpredators can be made based on our field data. However,the data show that farmland willow stands containinghigh densities of find and stay mirids were often

unoccupied or contained low densities of leaf beetles(Fig. 2). Although we cannot exclude the possibility thatfactors other than predator behaviour might have beenmore important in causing the observed patterns, thedata indicate that mirids may prevent leaf beetles from be-coming established on farmland willows. Previous studies

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Figure 4. Model results in which prey fluctuated at different ceilings (K ), which restrict the maximum number of individuals to specific thresh-

olds, when exposed to find and stay and run and eat predators. (a, b) Coefficient of variation (CV) in prey population size when egg mortalityfrom predation was (a) 0.5 and (b) 0.9. (c, d) Probability of prey abundance decreasing from K to Nt ¼ K � 0.10, at some time point during 30

prey generations when egg mortality was (c) 0.5 and (d) 0.9.

DALIN ET AL.: PREDATOR FORAGING STRATEGIES 1033

have shown no general difference in host plant quality orclimatic factors for leaf beetles between forest and farm-land S. cinerea (Dalin 2004). Further studies are needed,however, to elucidate whether the heteropterans can con-trol beetle abundance and to compare population dynam-ics of leaf beetles in systems dominated by run and eat andfind and stay predators. As predicted by the model, highpopulation densities of leaf beetles were found only in for-est willow stands, which were less dominated by find andstay predators than farmland willows.

The difference in temporal dynamics predicted by themodel can be explained by the difference in predationpatterns caused by the two predator types. In the labora-tory experiment, the two mirids caused a greater variationin predation among egg clusters than the anthocorid. Inthe model, the expected mortality of prey from predationwas rather high, 50 or 90%. The reason behind this wasthat egg and larval predation is often high for P. vulgatis-sima on S. cinerea (Dalin 2004), and not uncommon formany other herbivorous insects (Cornell & Hawkins1995). For the high predation pressure simulated, boththe run and eat and the find and stay predator will finda high proportion of available egg clusters in the preypopulation. At low prey densities, there will be a chancethat the find and stay predator will find all egg clustersand thereby kill most prey. For prey attacked by the runand eat type, some eggs will often survive the attacks sincethese predators leave dense patches before all prey are con-sumed. Thus, for a gregarious prey such as P. vulgatissima,the probability of becoming established and increasing innumbers will be low in stands with high densities of findand stay predators because the predators sometimes findall aggregations and kill most prey.

The mirid O. marginalis occurred at high densities onfarmland willows although leaf beetle abundance waslow. Broad diet predators often show temporal persistencebecause they can feed and survive on many types of preyitems and some, such as mirids, even on plant materials(Wheeler 2001). These generalist predators, therefore,have the potential to be present in good numbers in ad-vance of prey establishment and to prevent increases inprey populations (Ekbom et al. 1992; Ostman et al.2001). Our model shows that behavioural characteristicsof the predators may also influence the probability ofprey establishment. For the relatively high predation pres-sure assumed in the model, the frequency of prey popula-tions escaping control was higher with run and eatpredators than with find and stay predators. From biolog-ical control studies, it is evident that increased predatorabundance does not always result in better control of pests(Symondson et al. 2002). Further studies are, therefore,needed to study the relative importance of enemy behav-iour in the control of prey (Mondor & Roitberg 2000).Hypotheses based on spatial behaviours of both predatorsand prey may reveal important insights. For example, thegreater tendency of gregarious herbivorous insect speciesto outbreak than species that feed or lay eggs solitarily(Larsson et al. 1993; Hunter 1995) indicates that spatialbehaviour influences population dynamic processes(Cappuccino et al. 1995). In addition, behaviours mayinfluence interactions among predators (Sih et al. 1998).

Predators with sedentary behaviours are, for example,less likely to interfere with each other negatively than ac-tive predators (Bjorkman & Liman 2005). Reduced inter-ference may facilitate numerical responses of predators,leading to better control of prey. Although this needsfurther studies, predator behaviour may influence preypopulations directly, as suggested by our model, but alsoindirectly by facilitating increased predator abundance.

Behavioural variation within enemy complexes is nota novel finding, but few researchers, to our knowledge, havestudied the influence of such variation on the populationdynamics of the prey. Our model was adjusted to describethe population dynamics of the willow leaf beetle P. vulga-tissima. We are, however, aware that the field data presentedin this paper may not represent a proper test of the model’spredictions. In addition, the model’s predictions can besensitive to the set of parameters chosen. For example, ifthe impact of environmental stochasticity is higher thanthe initial settings, the difference between predator typesbecomes less clear. Predator behaviour is also, as we havedemonstrated, mainly likely to influence prey populationdynamics at high predation pressures. However, the mod-el’s results appear to be reasonably robust as shown by thefact that the major conclusion that predator behaviourmainly affects small populations is consistent and appearsindependently of the parameter values chosen. Manymore studies are needed on patterns of prey population dy-namics in systems dominated by both run and eat and findand stay predators. We also encourage others to try to iden-tify behavioural differences between enemy species since itseems likely that similar (or other) variations can be discov-ered in other enemy complexes (e.g. Wiskerke & Vet 1994).We believe that a deeper knowledge about behaviouralcharacteristics of both natural enemies and their prey willincrease our understanding of the causes behind observedpatterns of prey abundance in both time and space.

Acknowledgments

We thank Jorge Calvo Carillo and Karin Eklund fortechnical assistance and Barbara Ekbom, Mattias Jonsson,Thomas Ranius and two anonymous referees for construc-tive suggestions on the manuscript. Financial support wasprovided by the Swedish National Energy Administration.

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