PARTITIONING COMPONENTS OF RISK REDUCTION IN A DRAGONFLY–FISH INTRAGUILD PREDATION SYSTEM

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Ecology, 84(6), 2003, pp. 1588–1597q 2003 by the Ecological Society of America

PARTITIONING COMPONENTS OF RISK REDUCTION IN ADRAGONFLY–FISH INTRAGUILD PREDATION SYSTEM

PATRICK W. CRUMRINE1 AND PHILIP H. CROWLEY

Department of Biology and Center for Ecology, Evolution and Behavior, University of Kentucky,Lexington, Kentucky 40506-0225 USA

Abstract. Risk to prey imposed by intraguild predation (IGP) can be influenced by anumber of factors, yet to date, few studies have measured the contributions of these factorsto overall risk. A three-species IGP system with larvae of the dragonfly Anax junius as IG(top) predators, larvae of the dragonfly Plathemis lydia as IG prey (intermediate predators),and fathead minnow hatchlings (Pimephales promelas) as shared prey was used to estimatethe contribution of the following three factors to shared-prey mortality rate in combinedpredator treatments: (1) the trophic effect of the IG predator on IG prey density; (2) theeffect of reduced shared prey consumption by the IG prey in the presence of the IG predator;and (3) the effect of alternative prey for the IG predator. These factors were integrated intoa model of multiple predator effects. To quantify minnow mortality, P. promelas wereexposed to A. junius only, P. lydia only, A. junius and P. lydia, or neither in a two-by-twofactorial design. Additional treatments, in which one or both predators were unable to feed,were used to isolate behavioral (activity level) changes in dragonfly larvae.

When predators preyed in combination on P. promelas their impact was less than thatof the summed effects of the two predators, each in the absence of the other—a resulttermed risk reduction. A. junius consumed a significant number of P. lydia when they werepresent (i.e., IGP), and behavioral interactions between A. junius and P. lydia were asym-metric. The presence of A. junius caused P. lydia to become less active, while the presenceof P. lydia elicited a diet shift in A. junius to include some P. lydia. Interactions betweenpredator species, specifically IGP, influenced prey survival. Trophic and behavioral effectsof IGP were similar in magnitude. These results highlight the importance of trophic andbehavioral interactions in predator–prey systems and also suggest that effects of multiplepredators may not be predictable based on the sum of individual effects. Determining theeffects of multiple predators requires the identification of mechanisms that contribute tononadditive prey responses.

Key words: alternative prey; Anax; antipredator behavior; dragonflies; emergent effects; intra-guild predation; multiple predators; Plathemis; predator–prey interactions; risk reduction.

INTRODUCTION

Food web studies have shown that prey species arealmost always subject to predation from multiple pred-ators (Schoener 1989, Polis 1991, Polis and Strong1996). A key issue, then, is whether multiple predatorshave effects on shared prey that differ from expecta-tions based on independent effects of predators on prey(Soluk and Collins 1988, Sih et al. 1998). Observedpredation rates less than and greater than those pre-dicted by a null model are termed risk reduction andrisk enhancement, respectively. A recent review ofmultiple predator effects on prey found that both riskreduction and risk enhancement are common (Sih etal. 1998).

Most multiple-predator studies (Soluk and Collins1988, Soluk 1993, Crowder et al. 1997, Gonzalez andTessier 1997, Sih et al. 1998, Swisher et al. 1998) at-tempt to elucidate the effects of two or more predator

Manuscript received 1 July 2002; revised 7 October 2002;accepted 8 October 2002. Corresponding Editor: O. J. Schmitz.

1 E-mail: [email protected]

species on a specific prey response variable (typicallyprey survival, mortality rate or growth rate) based onthe independent effects of the predators on the prey.Results from these types of experiments suggest thatrisk reduction and risk enhancement are often not pre-dictable based on independent effects of predators onprey. Few studies rigorously address how the interplaybetween trophic and behavioral interactions influencesrisk reduction and risk enhancement. Factors determin-ing the magnitude and direction of multiple predatoreffects on prey, and thus the overall reduction or en-hancement of risk for shared prey, include physical andsocial characteristics of the environment, associated be-havioral interactions between predators and prey, amongpredators, or among the prey and intraguild predation(IGP; Soluk 1993, Sih et al. 1998; Fig. 1).

Intraguild predators, competitors that consume eachother, are found in numerous taxonomic groups in na-ture (Polis et al. 1989, Polis and Holt 1992). IGP maystrongly influence prey survival and community struc-ture (Polis et al. 1989, Polis and Holt 1992, Holt andPolis 1997, Morin 1999, Diehl and Feissel 2000, Na-

June 2003 1589INTRAGUILD PREDATION AND RISK REDUCTION

FIG. 1. Conceptual overview of the effects of two pred-ators on shared prey survival. Predators 1 and 2 both havean independent effect on prey survival when alone (dashedlines). When both predators are present (solid lines), the effectmay depend on the interaction between predators. Whetherrisk reduction or enhancement occurs may depend on theoccurrence and magnitude of factors such as IGP and behav-ioral shifts made under the threat of IGP by IG prey. Preydefenses can promote survival but may conflict with multiplepredators and decrease survival.

varrete et al. 2000). Asymmetric IGP occurs when atop predator (an IG predator using the terminology ofHolt and Polis [1997]) consumes an intermediate pred-ator (IG prey) and shared prey. In these asymmetricsystems, the IG predator can consume both the IG preyand the shared prey, but the IG prey can only consumethe shared prey. The predators are themselves engagedin a predator–prey relationship in addition to competingfor the shared prey species. Asymmetric IGP oftenleads to risk reduction when prey face multiple pred-ators (Rosenheim et al. 1993, Wissinger and McGrady1993). Risk reduction is often observed in asymmetricIGP systems because IG predators can consume IG prey(perhaps instead of shared prey) and reduce the densityof IG prey in the system. Thus, the amount of shared-prey mortality due to consumption by IG predators andpossible by IG prey is diminished. This effect may bestrengthened if mutual predation occurs between pred-ators.

Many IGP and multiple-predator studies approachIGP by addressing how IG prey and shared prey sur-vival is affected by IG predators, but IGP can contributeto risk reduction both through trophic interactions be-tween the three species as described above and throughbehavioral modifications made by IG prey and sharedprey while attempting to avoid predation by IG pred-ators. Behavioral modifications made by IG prey in

response to the presence of IG predators can lead torisk reduction if IG prey reduce their consumption ofshared prey when IG predators are present (Huang andSih 1991, Wissinger and McGrady 1993, Relyea andYurewicz 2002). IG prey may decrease their consump-tion of shared prey by reducing overall foraging effort,spending more time in refuge or reducing their activitylevel (Lima and Dill 1990). In addition, risk reductionresulting when IG predators alter their diets to includeIG prey and limit their consumption of shared prey istermed an alternative prey effect. It is becoming in-creasingly apparent that behavioral modifications ofpredators and prey, trophic effects of IGP on IG preydensity and alternative prey effects all play importantroles in determining the survival of shared prey speciesin the presence of two predators.

IGP is quite common among larval odonates and cansignificantly impact larval odonate populations and thepopulations of their prey (Johnson 1991). We designedand experiment to address the relative contributions torisk reduction made by of the trophic effect of IG pred-ators on IG prey density, behavioral shifts made by IGprey in the presence of IG predators, and the presenceof alternative prey for IG predators. This study wasconducted in a three-species system with larvae of thedragonfly Anax junius as the IG predator, larvae of thedragonfly Plathemis lydia as the IG prey, and juvenilefathead minnows (Pimephales promelas) as the sharedprey. Our hypotheses were that (1) prey mortality ratewould be greater when exposed to the dragonfly pred-ators A. junius and P. lydia relative to nonpredatorcontrols; (2) prey mortality rate in the presence of bothpredators would be less than that expected by a nulladditive model, suggesting an interaction betweenpredators; (3) shared prey mortality rate due to con-sumption by P. lydia and activity levels of P. lydiawould decrease in the presence of A. junius; and (4)IGP and behavioral shifts in the predators and preywould lead to risk reduction. Previous work bySchmoetzer-Whitt (1990) in this system suggested thatthe effect of both predators in combination on preysurvival would be less than that predicted by an ad-ditive model of predator effects. In addition, Wissingerand McGrady (1993) have shown that direct trophicIGP of IG prey by IG predators can lead to risk re-duction in odonate systems, but IGP alone does notaccount for observed levels of prey survival.

The focus of this paper is to identify and partitionimportant factors contributing to non-additive prey re-sponses to multiple predators. A modified version of arisk model developed by Soluk and Collins (1988) wasused to partition the trophic effect of the intraguildpredator on intraguild prey density, behavioral shiftsby IG prey, and the effect of alternative prey (in theform of IG prey) consumption by the IG predator onrisk reduction in a dragonfly–fish predator prey system.We begin by introducing the study system and dis-cussing how multiple predator effects were identified.

1590 PATRICK W. CRUMRINE AND PHILIP H. CROWLEY Ecology, Vol. 84, No. 6

We then describe how the use of trophically manipu-lated predator treatments were used to isolate trophicand behavioral components of IGP and how those com-ponents were integrated into a model of multiple pred-ator effects on prey. Results are then presented anddiscussed in the context of the literature.

METHODS

Study organisms

A. junius are relatively large (;4.5 cm body lengthin the final instar), active, dragonfly larvae mainlyfound in association with aquatic macrophytes in pondsand lakes throughout much of North America (Corbet1999). A. junius are most commonly found in bodiesof water lacking insectivorous fish, where they use theirlarge size and visual acuity to assume the role of toppredator (Johnson 1991, McPeek 1998, Corbet 1999).P. lydia larvae are smaller (;2.5 cm body length inthe final instar) and less active than A. junius. P. lydiaare benthic sprawlers (Dunkle 1989) inhabiting pondsand lakes throughout much of North America. By theninth of 13 total instars, A. junius larvae are of greaterlength and possess head widths of significantly largersize than all larval instars of P. lydia These two odonatespecies and fathead minnows are all commonly foundin small ponds lacking insectivorous fish, and A. juniuscan be significant predators of small hatchling fish(Wright 1946, Schmoetzer-Whitt 1990). P. lydia andA. junius readily consume fathead minnow hatchlings,and A. junius also prey on P. lydia in laboratory en-closures (Schmoetzer-Whitt 1990).

On 1 June 1999 and 4 June 1999, larval A. juniuswere collected from two fishless ponds in central Ken-tucky: Germany Pond located near Versailles, ScottCounty, Kentucky, and Ecological Research Facility(ERF) Pond #3, northern Fayette County, Kentucky. P.lydia larvae were also collected from ERF Pond #3.Both ponds are roughly circular in shape and borderedby Typha spp. All larvae used in these experimentswere in the penultimate (F-1) instar as determined byhead width and wing pad measurement. After collec-tion, A. junius larvae were housed in groups of two inclear, circular (18 cm diameter), plastic containers andfed two 3-wk-old fathead minnow hatchlings per day.P. lydia were housed in groups of six in similar con-tainers and fed six 3-wk-old minnows per day. Bothspecies were kept at room temperature (25.58C) undera 14:10 light:dark photoperiod. The dragonfly larvaewere kept in these conditions for 4 or 6 d, dependingon collection date, prior to being placed in experimentalarenas. Dragonfly larvae were randomly assigned totreatments.

Experimental design

The experimental trials were set up in plastic tubs(30 3 42 3 16 cm deep) divided into an open watersection (30 3 25 3 16 cm deep) and a vegetated section

(30 3 17 3 16 cm deep), representing 60% and 40%of the total volume, respectively. Vegetation was sim-ulated using 15 cm vertical lengths of nylon rope (1cm diameter) anchored to the bottom of the tubs. Twen-ty-five artificial stems were added to each tub, gener-ating a medium level of habitat complexity equivalentto 490 stems/m2. This level of habitat complexity cor-responds to densities reported for natural macrophytes(Sheldon and Boylen 1977). The bottoms of the tubswere covered with white silica sand to a depth of 0.5cm. Each tub was filled with charcoal-filtered water toa depth of 10 cm. A subset of the larvae used in theexperimental trials were ‘‘de-mented,’’ a procedure inwhich the palpal lobes were removed from the labiumof the dragonfly larva (see Wissinger and McGrady1993 for a more complete description of this proce-dure). This procedure prevented the larvae from feed-ing but allowed interactions with the other organismsin the system. Preliminary observations showed thatthe de-mented larvae attempted to capture prey butwere physically unable to do so.

The design consisted of seven treatments, four ofwhich represented the two-by-two factorial structureoften used in multiple predator studies (no predators[none], two A. junius alone [A], six P. lydia alone [P],and two A. junius and six P. lydia [A 1 P]). Thesetreatments allowed us to address whether the effects ofthe two predators on shared prey mortality rate wereindependent (the null expectation), greater than ex-pected (risk enhancement), or less than expected (riskreduction). A set of three de-mented treatments werealso included. In these treatments, one or both predatorswere de-mented (d; A 1 Pd, Ad 1 P, Ad 1 Pd). Thetreatment with both predators de-mented (Ad 1 Pd)served as a control to determine the efficacy of the de-mentation procedure. The de-mented treatments wereused to isolate behavioral shifts in the predators andtheir contribution to prey survival and risk reduction(Van Buskirk 1989, Wissinger and McGrady 1993).Two A. junius and six P. lydia were used in the ex-periment to reflect relative densities of the larvae inthe field. Thirty 3-wk-old fathead minnow hatchlings(obtained from Environmental Consulting and Testingin Superior, Wisconsin) were introduced to each tub atthe start of the trials (Table 1). Each treatment wasreplicated four times, and the trials ran for five daysbeginning on 3 June and 9 June. The levels of repli-cation and the length of the trials were determinedbased on previous experiments in this system(Schmoetzer-Whitt 1990).

Response variables and data analysis

Each tub was observed for 20 min/d between thehours of 0900 and noon during the 5-d trial. Duringthe observational period, the number of dragonflymovements and the positions of the minnows and thedragonfly larvae in the tubs were recorded. Minnowhabitat-use data were reported as percent in vegetation


TABLE 1. Experimental design to test for main and interactive effects of dragonfly predatorson minnow mortality rate with trophically functional and de-mented (d) dragonfly predators.

TreatmentNo.

A. juniusNo.

P. lydiaNo.

A. junius dNo.

P. lydia dNo.

minnows

Main effect of A. juniusMain effect of P. lydiaCombined predatorControlA. junius with alternative preyP. lydia with IG predatorDe-mentation control

2020200

0660060

0000022

0000606

30303030303030

Note: N 5 4 for each treatment.

and arcsine-square-root transformed before analysis tomeet assumptions of ANOVA (Sokal and Rohlf 1995).Dragonfly movements and minnow habitat use wereanalyzed using one-way ANOVA. Treatment meanswere separated into statistically different subsets usingTukey’s multiple comparison test.

Minnow mortality was determined at the end of the5-d trial. Mortality rates (ki) were determined for eachreplicate of treatment i over the trial duration t fromthe proportion of minnows killed, pi (and thus the pro-portion surviving is 1 2 pi)

2k ti1 2 p 5 ei (1)

which rearranges to

k 5 2ln(1 2 p )/t.i i (2)

If kA is the mortality rate of minnows in the presenceof A. junius alone and kP is the mortality rate in thepresence of P. lydia alone, then the null hypothesis iskA 1 kP 5 kA1P. A significant interaction in the two-way ANOVA of A. junius and P. lydia mortality effectsthen implies either risk reduction (if kA1P , kA 1 kP)or risk enhancement (if kA1P . kA 1 kP).

The interaction effect could be accounted for by in-cluding the de-mented treatments in an expanded anal-ysis. The use of the de-mented treatments allowed usto individually quantify the components leading to riskreduction. Observed shared prey mortality rates in thecombined predator treatments were compared with fiveexpected shared prey mortality rates (EXP, EXPI,EXPB, EXPA, and EXPIBA) generated from the ex-perimental data. Treatment means were separated intostatistically different subsets using Tukey’s multiplecomparison test following a significant one-way AN-OVA for treatment effects. The expected prey mortalityrate assuming no interaction between predators (EXP)was determined as noted above:

k 1 k 5 EXPA P (3)

where kA is the mortality rate in the presence of A.junius and kP is the mortality rate in the presence of P.lydia.

Four EXP values were generated by taking four pos-sible random sums of kA and kP from the replicates ofeach treatment. An analogous approach was used to

generate the three other expected values described be-low. Similar studies using two predators have generatedexpected values by taking pairs of predator predationrates blocked by replicate number (Wissinger andMcGrady 1993). Our experiment was not blocked sothere was no reason to pair specific replicates gener-ating values of kA with specific replicates generatingvalues of kP.

EXPI, the expected mortality rate with both preda-tors, correcting for the trophic effects of IGP, was gen-erated using the following equation:

k 1 0.4975k 5 EXPI.A P (4)

The minnow mortality rate in the presence of P. lydia(kP) was multiplied by 0.4975 to reflect the mean re-duction in the number of P. lydia present in the A 1P trials integrated over the 5-d period due to IGP fromA. junius.

EXPB, the expected mortality rate with both pred-ators, correcting for the reduction in prey consumptiondue to reduced activity levels by the IG prey, P. lydia,was generated using the following equation:

k 1 k 5 EXPBA P1Ad (5)

where kP1Ad is the prey mortality rate due to P. lydiain the presence of de-mented A. junius. This reflectsthe behavioral affect that A. junius had on P. lydia. Itis important to note that although A. junius were presentin this treatment, all of the shared prey (minnow) mor-tality was due to predation from P. lydia.

Alternative prey effects were also factored into thenull model. Alternative prey effects can result when IGpredators reduce their consumption of shared preywhen IG prey are present. To account for this effect inthe null model, the value kA1Pd was substituted for kA.The mortality rate of minnows due to A. junius in thepresence of P. lydia is represented by kA1Pd. In thiscase, the P. lydia were de-mented and unable to feed,so all of the minnow mortality was due to A. junius:

k 1 k 5 EXPA.A1Pd P (6)

Finally, EXPIBA, the expected mortality rate withboth predators present simultaneously correcting forthe trophic effect of the IG predator on IG prey density,the reduction in prey consumption due to reduced ac-


FIG. 2. Shared prey mortality rates in alltreatments. Means were compared using Tu-key’s multiple comparison test following a sig-nificant one-way ANOVA for treatment effects;different letters indicate significant differences.Values reported are mean 6 1 SE. Key to pred-ator treatments: A, two A. junius; P, six P. lydia;d, de-mented. N 5 4 for all treatments.

FIG. 3. Observed and expected prey mortality rates ac-counting for the effects of IGP, behavioral shifts made by IGprey under the threat of predation, and alternative prey ef-fects. Means were separated into statistically different groupsusing Tukey’s multiple comparison test following a significantone-way ANOVA for observed and expected effects; differentletters indicate significant differences. Values reported aremean 6 1 SE. For a description of treatments, see Methods:Response variables and data analysis; A and P are definedas in the legend to Fig. 2. N 5 4 for all treatments.

tivity levels by the IG prey and the alternative preyeffect was generated with the following formula:

k 1 0.4975 k 5 EXPIBA.A1Pd P1Ad (7)

This version of the model provides an estimate of totalrisk reduction for shared prey generated by trophic andbehavioral components of IGP.

To estimate the relative contribution of each indi-vidual factor to risk reduction, we computed the dif-ference in the means between each corrected versionof the model and EXP (i.e., (EXP 2 EXPI), (EXP 2EXPB), (EXP 2 EXPA), and (EXP 2 EXPIBA). Wethen divided each of these values by the differencebetween the mean observed prey mortality rate in thecombined-predator treatment and the mean expectedprey mortality rate assuming no interaction betweenthe two predators (i.e., EXP 2 kA1P). For example,(EXP 2 EXPI)/(EXP 2 kA1P) estimates the proportionof the discrepancy between the observed shared preymortality rate and the expected shared prey mortality

rate explained solely by IGP of IG prey by IG predators.Results of this exercise are reported as the percentageof the discrepancy explained by each individual factor(EXPI, EXPB, EXPA) and all of the factors combined(EXPIBA).

RESULTS

Minnow mortality was significantly affected by treat-ment (ANOVA, F 5 60.61, df 5 6, 21, P , 0.0001;Fig. 2). A two-way ANOVA indicated that both drag-onfly predators had significant effects on minnow mor-tality rate (ANOVA, F 5 4.79, df 5 1, 12, P , 0.05[P. lydia]; ANOVA, F 5 86.93, df 5 1, 12, P , 0.0001[A. junius]). There was a significant interaction be-tween A. junius and P. lydia for minnow mortality rate,indicating nonadditive predator effects on shared prey(ANOVA, F 5 170.83, df 5 1, 12, P , 0.0001). Ob-served and expected minnow mortality rates were an-alyzed with one-way ANOVA. Actual observed preymortality rate in the combined predator treatment wassignificantly lower than that predicted by the null model(kA1P , kA 1 kP, Tukey’s P , 0.0001), consistent withrisk reduction (Fig. 3). Components of risk reductionwere partitioned using the methods described above todetermine the relative contributions of trophic reduc-tions of IG prey density by IG predators, behavioralshifts by IG prey under the threat of IGP and alternativeprey effects on risk reduction.

P. lydia survival was significantly lower in the pres-ence of trophically functional A. junius (Student’s t test,t 512.89, P , 0.0001; Fig. 4). There was no P. lydiamortality in the absence of A. junius. The expectedshared prey mortality rate accounting for the trophiceffect of the IG predator on IG prey density (EXPI)differed significantly from the expected prey mortalityrate assuming no interaction between predators (EXP)and from the observed prey mortality rate in the com-bined predator treatment (Tukey’s P , 0.0001, Fig. 3).The trophic effect of the IG predator on IG prey densityaccounted for 30% of the discrepancy between the ob-served shared prey mortality rate and the expected


FIG. 4. P. lydia survival in the presence and absence ofA. junius; A and P are defined as in the legend to Fig. 2.Means were compared using an unpaired Student’s t test.Values reported are mean 6 1 SE. N 5 4 for all treatments.The two means are different at P , 0.001.

FIG. 5. P. lydia activity level in the presence and absenceof a top predator. Means were compared using Tukey’s mul-tiple comparison test following a significant one-way AN-OVA for treatment effects. Values reported are mean 6 1 SE.Key to predator treatments: A, two A. junius; P, six P. lydia;d, de-mented. N 5 4 for all treatments. A 1 P, A 1 Pd, Ad1 P, and Ad 1 Pd are all significantly different from treatmentP at P , 0.0001.

shared prey mortality rate in the absence of interactionbetwe en predators.

P. lydia activity levels were significantly affected bythe presence of A. junius (ANOVA, F 5 46.08, df 54, 15, P , 0.0001). P. lydia exhibited fewer total move-ments in all treatments where A. junius was present,regardless of trophic status (de-mented vs. un-de-ment-ed; Tukey’s multiple comparison test, P , 0.0001; Fig.5). P. lydia also consumed fewer minnows when non-lethal, de-mented A. junius were present (Tukey’s mul-tiple comparison test, P , 0.0001). The expected preymortality rate accounting for the reduction in minnowconsumption by P. lydia, due to behavioral shifts inthe presence of A. junius (EXPB), was significantlydifferent from the expected prey mortality rate assum-ing no interaction between predators and from the ob-served prey mortality rate in the combined predatortreatment (Tukey’s multiple comparison test, P ,0.0001, Fig. 3). Behavioral shifts by the IG prey ac-counted for 35% of the observed level of risk reduction.

A. junius activity levels were not significantly af-fected by the presence of P. lydia (F 5 1.11, df 5 4,15, P 5 0.3889). Alternative prey effects (i.e., de-creased consumption of minnows by A. junius in thepresence of P. lydia) also contributed to risk reduction.There was a significant difference between minnowmortality rate in the A. junius treatment and minnowmortality rate in the A 1 Pd treatment (Tukey’s mul-tiple comparison test, P , 0.005). The expected preymortality rate accounting for the presence of alternativeprey for A. junius (EXPA) was significantly differentfrom the expected prey mortality rate assuming no in-teraction between predators and from the observed preymortality rate in the combined predator treatment (Tu-key’s multiple comparison test, P , 0.0001, Fig. 3).The presence of alternative prey accounted for 25% ofthe observed level of risk reduction.

The shared-prey mortality rate predicted by the EX-PIBA model, which simultaneously accounted for thethree factors, was significantly different from the ex-pected prey mortality rate assuming no interaction be-

tween predators and from the observed prey mortalityrate in the combined predator treatment (Tukey’s mul-tiple comparison test, P , 0.0001; Fig. 3). The EX-PIBA model accounted for 74% of the observed levelof risk reduction. There were no significant differencesbetween the expected prey mortality rates for the threesingle-factor adjusted versions of the null model, EXPIEXPB and EXPA (Tukey’s multiple comparison test,P . 0.90; Fig. 3).

The presence of dragonfly larvae had a significanteffect on prey spatial distribution (F 5 17.81, df 5 6,21, P , 0.0001). Minnows spent the least amount oftime in the vegetated section of the tubs when bothdragonflies were present (Fig. 6). A. junius were foundperched on the simulated vegetation during the entireobservation period. P. lydia habitat use was unaffectedby treatment (ANOVA, F 5 2.412, df 5 4, 15, P .0.095). A Z test was run to compare the proportion ofP. lydia found in the vegetation across all treatments(77%) to the proportion expected if they were randomlydistributed across the habitat (40%). This test was sig-nificant and indicates that, while P. lydia were not ex-clusively located in the vegetated portion of the tubs,they were found significantly more often in the vege-tated section than in open water across all treatments(Z 5 2.965, P 5 0.003).

DISCUSSION

Intraguild predation may often contribute to risk re-duction, but few studies have identified and quantifiedthe underlying mechanisms leading to nonadditive preyresponses. As predicted, both predators significantlydecreased prey survival relative to controls, and preymortality rates were significantly lower in the com-bined predator treatment than predicted by the nullmodel (i.e., risk reduction). The trophic effect of theIG predator on IG prey density, avoidance of IGP byIG prey, and alternative prey effects explained 30%,


FIG. 6. Prey habitat use in experimentaltreatments. Means were separated into statisti-cally different groups using Tukey’s multiplecomparisons test following a significant one-way ANOVA for treatment effects; different let-ters indicate significantly different means. Val-ues reported are mean 6 1 SE. Key to predatortreatments: A, two A. junius; P, six P. lydia; d,de-mented. N 5 4 for all treatments.

35%, and 25% of the discrepancy between observedand expected shared prey mortality rates, respectively.

While it may seem reasonable to simply sum theseindividual effects, in this IGP system, these mecha-nisms operated simultaneously to reduce overall riskfor shared prey. For example, IG predators consumedIG prey and caused those surviving to reduce theiractivity levels and consumption of shared prey. If thereductions for the trophic effect of the IG predator onIG prey density and the behavioral modification weresummed, then IG prey that were already killed throughIGP would be making an additional contribution to riskreduction through behavioral modification. Since thisreduction assumes that a full complement of IG preyare present in the system, clearly this is an impossi-bility. It would be unlikely for an alternative prey effectto exist without IG predators consuming IG prey, unlessof course IG predators focused all of their attention onIG prey and failed to kill any of them. The occurrenceof IGP on IG prey only translates into an alternativeprey affect if IG predators reduce their consumption ofshared prey.

The EXPIBA model was developed by sequentiallycorrecting for components of risk reduction in this IGPsystem. We initially accounted for the density reductionin the IG prey due to IGP from IG predators by mul-tiplying kP by 0.4975, but the remaining IG prey alsoreduced their consumption of shared prey. To compen-sate for this effect we substituted 0.4975kP1Ad for0.4975kP. As IG predators consumed IG prey, they re-duced their consumption of shared prey, and we re-placed kA with kA1Pd. This approach has the benefit ofnot overestimating the behavioral effect but still hasshortcomings. It is likely that a portion of the risk re-duction in the system was attributable to factors notdirectly related to trophic and behavioral interactionsbetween predators. This remaining portion may reflectbehavioral modifications by the shared prey, and theseeffects may not be adequately captured by this ap-proach.

The behavioral response of the minnows was pred-ator dependent. The avoidance response of minnowswas generally greatest in treatments with A. junius pres-

ent regardless of trophic status (de-mented vs. un-de-mented) or the presence of P. lydia. Minnows displayeda weaker avoidance response to P. lydia than to A.junius. Certainly, avoidance responses of shared preyin the presence of both predators should account for aportion of the lower-than-expected levels of minnowmortality in the A 1 P treatment. As the minnowsavoided the habitat where both predators were present,they were able to increase their survival during theexperiment. Shoaling can also be an effective anti-predator strategy used by fathead minnows (Chivers etal. 1995), and this behavior was observed occasionallyduring the experiment. Fathead minnows have the abil-ity to detect and respond behaviorally to predator chem-ical cues. A number of studies have addressed the im-portance of alarm substance in anti-predator behaviorin fathead minnows (Chivers and Smith 1993, 1994,1995a, b, Mathis and Smith 1993), but the mechanismby which the minnows responded to dragonflies in thisexperiment was not determined.

Results were similar to those for an IGP system inwhich Tramea lacerata (IG predator) and Erythemissimplicicolis (IG prey) shared damselfly prey (Wissin-ger and McGrady 1993). In that study, risk reductionwas partially attributed to IGP of Erythemis by Trameaand to other behavioral components. Also, the con-sumption of shared prey by the IG prey decreased inthe presence of nonlethal IG predators, but the mech-anisms by which consumption decreased were not iden-tified. Our results show that a reduction in the activitylevel of IG prey (P. lydia) in the presence of IG pred-ators (A. junius) can contribute to risk reduction. Thisreduced activity level theoretically lowers the numberof encounters between P. lydia and minnows and thusthe number of minnows consumed by P. lydia whenA. junius are present.

Incorporating the effects of predator–predator inter-actions (both trophic and behavioral) into the null mod-el did not fully account for the discrepancy betweenobserved and expected prey mortality rates but did pre-dict a level of prey mortality significantly lower thanwithout incorporating those interactions. The trophiceffect of IGP on prey mortality rate was nearly equiv-


alent to the behavioral effect of IGP. Both mechanismsexplained ;30% of the discrepancy between observedand expected prey mortality rates. Although the trait-mediated positive effect on minnow mortality rate wassimilar to the density-mediated effect, this may not bethe case in all systems. Density-mediated effects canhave a greater effect on shared prey survival than trait-mediated effects when IG prey do not modify theirbehavior in the presence of IG predators. This mayoccur if IG prey are under strong selection for rapiddevelopment and continue to forage in the presence ofIG predators (Wissinger et al. 1999) or if IG prey failto detect or respond to IG predators.

These results and the results of similar studies (Pea-cor and Werner 1997, 2001, Relyea and Yurewicz 2002)demonstrate not only the importance of identifyingtrait-mediated effects of multiple predators on sharedprey but also their impact on interspecific interactionsand community structure. In the present study, the re-duction in numbers of IG prey and the decrease inactivity level and consumption of shared prey by IGprey could have important consequences for competi-tors of IG prey species in nature. Peacor and Werner(2001) demonstrated these density- and trait-mediatedindirect effects in an Anax–bullfrog-tadpole–periphy-ton system. In this system, the nonlethal effect of A.junius on vulnerable small bullfrog tadpoles reducedcompetition between large and small tadpoles by in-creasing the amount of periphyton available to non-vulnerable large tadpoles. Trait-mediated indirect ef-fects also play important roles in structuring terrestrialcommunities. Increased folivory of plants lacking pre-dacious theridiid spiders by formicid ants relative toplants with spiders was attributed to an avoidance re-sponse by ants to spiders, a trait-mediated effect (Gas-treich 1999). Predacious spiders also have positivetrait-mediated indirect effects on perennial grass andherb biomass in old fields via behavioral (diet) modi-fications in their herbivorous grasshopper prey(Schmitz 1998, Schmitz and Suttle 2001).

Although IGP and the threat of IGP do play impor-tant roles in determining mortality rates of shared preywhen exposed to multiple predators, decreased con-sumption of shared prey by IG predators can also beimportant. This decrease in consumption, eitherthrough alternative prey effects (e.g., satiation) oravoidance behavior by shared prey, must be consideredwhen evaluating the effects of multiple predators onprey mortality rates. Avoidance behaviors by sharedprey in the presence of multiple predators are mosteffective when prey responses do not conflict withpredator foraging modes (i.e., the response to one pred-ator does not make prey more vulnerable to attack fromthe other predator). When prey behavioral responsesconflict with multiple predators, risk enhancement of-ten occurs (Soluk and Collins 1988, Losey and Denno1998, 1999, Sih et al. 1998, Eklov and VanKooten2001). Risk enhancement appears to be more common

in systems where multiple predators occupy differenthabitats and do not interfere with each other when for-aging (Losey and Denno 1998, 1999, Eklov andVanKooten 2001) or where predators employ differentforaging strategies to capture prey (Soluk and Collins1988, Eklov and VanKooten 2001). Risk enhancementis also more common when predators do not engage inIGP, although combinations of such predators can stillyield risk reduction if interference between predatorsis high.

Risk reduction and risk enhancement have been doc-umented in numerous studies, but few of those attemptto partition and quantify the relative contributions ofpredator–predator interactions to risk reduction. In thisstudy, three quantifiable components of risk reductionwere identified and models were amended to accountfor their effects. Based on these results and the resultsof previous studies, a general pattern of emergent pred-ator effects on prey survival is beginning to materialize.When predators are not expected to interact and preydefenses do no conflict, an additive model (basicallyequivalent to the multiplicative model of Soluk andCollins [1988]) may be appropriate to predict the ef-fects of two predators together from their independenteffects. When one predator is larger than another andIGP is expected to occur, an additive model with thecorrections outlined above may be appropriate. Thevalues one selects to account for IGP, behavioral shiftsby IG predators under the threat of IGP and alternativeprey effects will depend on a priori knowledge of theparticular system under study. Risk enhancement posesa slightly less straightforward approach. Future studiesneed to develop models to account for the factors thatgenerate risk enhancement. These expectations woulddepend on detailed knowledge of predator foragingstrategy and prey responses to predators. If IGP is ex-pected to occur in an experiment the finding of riskreduction is trivial and should be anticipated. The moreinteresting issue now is the extent to which IGP andother factors contribute to risk reduction.

Predator substitutability is another mechanism thatcan contribute to discrepancies between observed andexpected prey mortality rates in the presence of mul-tiple predators (Sih et al. 1998, Sokol-Hessner andSchmitz 2002). Predators are substitutable when preymortality rate at constant total predator density is in-dependent of the relative abundances of the predators(Sih et al. 1998). If predators have substitutable effectson prey mortality rate, then within and between speciesinterference, if any, should be similar. To test for nu-merical predator substitutability, treatments with eightA. junius and with eight P. lydia could be employedand the prey mortality rates in each compared to themortality rates in the A 1 P treatment. Alternatively,substitutability could be defined based on biomass.

These treatments were not included for several rea-sons. First, the resulting density of A. junius (63 A.junius larvae/m2) greatly exceeds the natural densities


of the source ponds (P. Crumrine, personal observa-tion). Preliminary experiments suggested that suchhigh densities would have depleted the prey populationwell before the experimental trials ended. Previouswork demonstrated that interspecific interference andpredation between A. junius and P. lydia differs greatlyfrom interference and cannibalism within either species(Schmoetzer-Whitt 1990), indicating that these pred-ators are clearly not substitutable.

Risk reduction and IGP theory

Theory on IGP (Polis et al. 1989, Polis and Holt1992, Holt and Polis 1997, Diehl and Feissel 2000)suggests that for stable coexistence to occur betweenpredators, IG predators must be more effective ex-ploitative competitors for the shared prey than IG preyand IG predators must gain significantly from consum-ing IG prey. While the species in this experiment didnot wholly adhere to those criteria, some mathematicalmodels show that the addition of IG predators to com-munities with only IG prey and shared prey at equi-librium levels leads to an increase in shared prey sur-vival and risk reduction (Holt and Polis 1997). In thepresent experiment, minnow survival was greater in thecombined predator treatment than in either of the singlepredator treatments, lending some support to this find-ing. Although shared prey survival increased due toIGP of P. lydia, behavioral interactions also have sig-nificant implications for species coexistence in IGPsystems.

IG prey attempted to avoid detection by A. juniusthrough a reduction in activity level. This can be aneffective antipredator behavior for IG prey, but such aresponse can also have important consequences forshared prey survival and influence the coexistence ofIG predators and IG prey. Such adaptive behavior hasbeen shown empirically to help shape the overall in-fluence of predators or predator combinations on IGprey (Huang and Sih 1991, Peacor and Werner 2001).Although several modeling studies have addressed fac-tors favoring coexistence in IGP systems, such as levelsof resource productivity (Diehl and Feissel 2000, Hei-thaus 2001) presence of stage structure (Mylius et al.2001), foraging effects (Krivan 2000), and availabilityof alternative prey (Heithaus 2001), few models havefocused directly on the role of adaptive behavior. Ourown preliminary modeling results suggest that adaptivebehavior can promote coexistence in IGP systems un-der a broad range of conditions (P. Crumrine, unpub-lished data) but much more empirical and theoreticalwork on these behavioral dynamics are clearly needed.

Nonadditive or emergent effects, in the context ofpredator–prey interactions and other ecologically sig-nificant contexts such as ecosystem function, have re-cently received a significant amount of attention in theliterature (Soluk and Collins 1988, Soluk 1993, Crowd-er et al. 1997, Gonzalez and Tessier 1997, Sih et al.1998, Swisher et al. 1998, Cardinale et al. 2002). Iden-

tifying systems with these properties has proven to bemuch easier than partitioning and quantifying the fac-tors that generate emergent effects. In the present study,IGP behavioral shifts made by IG prey under the threatof predation and alternative prey effects all contributedto the discrepancy between the expected mortality rateassuming no interaction between predators and the ob-served predation rate in the combined predator treat-ment. Further studies addressing the interplay betweenforaging strategies of multiple predators and how be-havioral responses of shared prey to IG predators in-fluence risk reduction and enhancement are needed todevelop a more general understanding of the factorsthat generate emergent effects in predator prey systems.

ACKNOWLEDGMENTS

We thank Andrew Sih for his insights into the effects ofmultiple predators on prey and Melissa Zwick for encour-agement during all phases of this study. Earlier versions ofthis paper benefited greatly from conversations with the Sih/Crowley lab group, specifically Brad Dickey, Tom McCarthy,John Niedzwiecki, Jennifer Rehage and Tim Sparkes. OswaldSchmitz and two anonymous reviewers also provided valu-able suggestions that improved this paper. This work wasfunded by a grant from the Ribble Research Fund at theUniversity of Kentucky.

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PARTITIONING COMPONENTS OF RISK REDUCTION IN A DRAGONFLY–FISH INTRAGUILD PREDATION SYSTEM