Biological Control 35 (2005) 288–298 www.elsevier.com/locate/ybcon

Indirect nontarget eVects of host-speciWc biological control agents: Implications for biological control

Dean E. Pearson a,b,¤, Ragan M. Callaway b

a Rocky Mountain Research Station, USDA Forest Service, Missoula, MT 59807, USA b Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA

Received 31 July 2004; accepted 20 May 2005 Available online 15 July 2005

Abstract

Classical biological control of weeds currently operates under the assumption that biological control agents are safe (i.e., low risk) if they do not directly attack nontarget species. However, recent studies indicate that even highly host-speciWc biological control agents can impact nontarget species through indirect eVects. This Wnding has profound implications for biological control. To better understand the causes of these interactions and their implications, we evaluate recent case studies of indirect nontarget eVects of bio- logical control agents in the context of theoretical work in community ecology. We Wnd that although particular indirect nontarget eVects are extremely diYcult to predict, all indirect nontarget eVects of host speciWc biological control agents derive from the nature and strength of the interaction between the biological control agent and the pest. Additionally, recent theoretical work suggests that the degree of impact of a biological control agent on nontarget species is proportional to the agent’s abundance, which will be high- est for moderately successful control agents. Therefore, the key to safeguarding against indirect nontarget eVects of host-speciWc bio- logical control agents is to ensure the biological control agents are not only host speciWc, but also eYcacious. Biological control agents that greatly reduce their target species while remaining host-speciWc will reduce their own populations through density-depen- dent feedbacks that minimize risks to nontarget species. Published by Elsevier Inc.

Keywords: Biological control; Nontarget eVects; Host speciWcity; Indirect eVects; EYcacy; Natural enemies; Multiple release approach; Lottery approach; Peromyscus maniculatus; Centaurea maculosa; Agapeta zoegana

1. Introduction classical biological control for over 100 years and it con- tinues to be today (Hajek, 2004; Van Driesche and Classical biological control is based on the enemy Bellows, 1996). Although a variety of natural enemies release hypothesis. This hypothesis states that exotic spe- may help control a pest in its native range, not all poten- cies become pests in new environments by escaping the tially eVective natural enemies will serve as safe biologi- inXuence of those natural enemies that suppressed their cal control agents in a pest’s new environment. In populations in their native range (Crawley, 1997; Keane particular, natural enemies with broad host ranges are and Crawley, 2002). Thus, the strategy behind classical unlikely to provide the surgical precision we desire in biological control is to reestablish top-down control by biological control, because they may attack important reintroducing the natural enemies of the pest into its new nontarget organisms in the new environment and range. This has been the conceptual underpinning of become exotic pests in their own right (Follett and Duan, 2000; Harris, 1990; Howarth, 1991; Louda et al., V * Corresponding author. Fax: +1 406 543 2663. 1997; Simberlo and Stiling, 1996; Wajnberg et al., E-mail address: [email protected] (D.E. Pearson). 2001). As a result, biological control programs

1049-9644/$ - see front matter. Published by Elsevier Inc. doi:10.1016/j.biocontrol.2005.05.011 D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 289 emphasize host speciWcity in selecting agents for intro- Myers, 1985; Myers et al., 1989; Sheppard, 2003; Strong duction to avoid these undesirable nontarget eVects. The and Pemberton, 2000). The result of multiple-release outcome has been that biological control operates under strategies in general and the lottery approach in particu- the assumption that nontarget eVects arise only when lar is that exotic organisms intentionally introduced for biological control agents directly attack nontarget spe- classical biological control exceed the number of exotic cies, or conversely that host-speciWc biological control pests targeted for control (Hokkanen and Pimentel, agents are safe (we deWne safe as low risk or safe enough 1984; McEvoy and Coombs, 1999; Myers, 1985). for introduction). Although the introduction of any individual agent will Although the importance of host speciWcity for the present some risk to nontarget species, the degree of risk safety of biological control should not be understated will increase with increasing numbers of agents. If host (e.g., Louda et al., 1997), perhaps it has been overstated speciWcity does not suYciently ensure the safety of bio- (e.g., Hoddle, 2004a). The emphasis on host speciWcity logical control agents, multiple-release strategies like has diverted attention from other potential sources of the lottery approach that emphasize numbers of agents risk to nontarget species that has contributed, at least in over agent eYcacy may present undue risks toward part, to certain biocontrol strategies like the “lottery nontarget species. Here, we apply recent advances in approach” (Myers, 1985) which may unnecessarily ele- community ecology theory to two recent case studies of vate nontarget risk, especially indirect nontarget risk. community interactions in biological control to evalu- The lottery approach is a multiple release strategy in ate the implications of indirect nontarget eVects of host- classical biological control that promotes the deploy- speciWc biological control agents for the practice of bio- ment of multiple host-speciWc biological control agents logical control. for each target pest (Hokkanen and Pimentel, 1984; McEvoy and Coombs, 2000; Myers, 1985). This approach places great emphasis on host speciWcity of 2. Theory addressing nontarget eVects of host-speciWc individual agents, but does not weigh eYcacy as heavily biological control agents in this process (McEvoy and Coombs, 2000; Sheppard, 2003). This lack of emphasis on eYcacy derives from the Application of community ecology theory to biologi- assumption that the most eVective agent or combination cal control suggests that there are many ways in which of agents will emerge from the milieu of introductions. biological control agents can indirectly impact nontarget The biological control of spotted knapweed (Centaurea organisms. For example, Holt and Hochberg (2001) maculosa Lam.) provides a classic example of the lottery identiWed Wve general scenarios based on community approach. Thirteen species of biological control agents modules (sets of interactions described by three to six have been introduced for the control of spotted strongly interacting organisms) through which biologi- knapweed (Lang et al., 2000), and the pool of agents that cal control agents could indirectly aVect nontarget spe- are suYciently host speciWc to warrant introduction may cies (Fig. 1). Four of these scenarios involve an indirect be exhausted (Müller-Shärer and Schroeder, 1993). eVect that is mediated through a direct attack by the bio- Thus, the entire suite of host speciWc biological control logical control agent on a nontarget species, i.e., these agents may have been introduced for this weed. scenarios depend on some aspect of host inWdelity by the Although there is currently little indication of successful biological control agent. This is reassuring because, in control of spotted knapweed (Maddox, 1982; Müller- theory, contemporary biological control strategies that Shärer and Schroeder, 1993), in other cases where the ensure a high degree of host speciWcity should safeguard lottery approach has been successful, it is often only one against most of these indirect nontarget eVects (this or two of several released agents that end up ultimately assumes screening is eVective at predicting host range, eVecting control (Denoth et al., 2002; Forno and Julien, but see Louda et al., 2003). However, one scenario (Fig. 2000; McFadyen, 2003; Myers, 1985). For example, in 1E), referred to as “enrichment” by Holt and Hochberg the classical success story of klamath weed (Hypericum (2001), only requires the presence of a generalist natural perforatum L.), three agents were introduced, but success enemy capable of exploiting the biological control agent. was attributed to only one of these (HuVaker and Ken- In this case, the biological control agent can be an nett, 1959). extreme specialist on the target weed and still pro- The lottery approach is only one of several multiple- foundly impact other organisms in the systems where release strategies in biological control (Harris, 1991; they have been introduced. If the biological control Sheppard, 2003), but it is the one that has been most agent becomes suYciently abundant, this interaction can criticized because relative to other multiple-release be strong enough to subsidize populations of generalist approaches it depends the most on chance and the least natural enemies and indirectly aVect other organisms on explicit knowledge of community interactions in the attacked by that natural enemy. We believe that such introduction of multiple biological control agents for indirect nontarget eVects are of particular concern each target weed (McEvoy and Coombs, 1999, 2000; because they are not currently guarded against. This is 290 D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298

responses, and (3) food–web interactions (Fig. 2). This last category equates with the enrichment scenario described by Holt and Hochberg (2001; Fig.1E), but the Pest Nontarget other two categories are not yet recognized by their framework. We brieXy introduce these concepts here B Agent (Fig. 2) and provide examples of compensatory Host infldelity responses and food–web interactions to illustrate the implications of these indirect nontarget eVects for the Pest Nontarget Nontarget practice of biological control. C Agent Specialist consumer 3.1. Ecological replacement

Ecological replacement occurs when an established Pest Nontarget invader replaces displaced native species in such a way that other native species become dependent on the D Agent invader. Nontarget eVects occur when successful control Natural enemy of the invader deleteriously impacts the nontarget native Pest species that have come to depend on it (Fig. 2A). Host specific E Nontarget Agent A Nontarget Agent

Pest Nontarget Nontarget Pest Nontarget Fig. 1. Community modules showing pathways for nontarget eVects of biological control agents (after Holt and Hochberg, 2001). The Wrst B Agent four interactions resulting in nontarget eVects (A–D) involve host inW- delity on the part of the biological control agent, but the last nontarget eVect can occur for even highly host-speciWc biological control agents. Interactions are named as follows (see Holt and Hochberg, 2001): (A) Pest Nontarget shared predation, (B) mixed predation and competition, (C) exploit- ative competition, (D) intraguild predation, and (E) enrichment or C Nontarget food–web interaction. Arrows indicate consumption except in (B) where the double-sided arrow indicates competition. Nontarget Nontarget primarily because indirect nontarget eVects that arise from biological control agents with broad host ranges Agent are well documented (Follett and Duan, 2000; Wajnberg et al., 2001), but only a handful of studies have recently begun to evaluate the potential viability and signiWcance Pest Nontarget of indirect nontarget eVects arising from host-speciWc biological control agents (Pearson and Callaway, 2003). Fig. 2. Community modules depicting pathways for indirect nontarget Though these studies are currently few, they help to eVects of host-speciWc biological control agents. (A) Ecological replacement: agent is host speciWc and strongly suppresses the target illustrate the nature and extent of the problems associ- V W weed thereby releasing suppressed natives, but this also weakens ated with indirect nontarget e ects of host-speci c bio- dependencies that have developed between the weed and other native logical control agents. species thereby negatively impacting these nontarget species. (B) Com- pensatory response: agent is host speciWc and the overall interaction between the biological control agent and the weed is top-down, but the 3. Empirical evidence for indirect nontarget eVects of host- target pest is only weakly impacted, because it displaces the negative W impacts onto nontarget species through compensatory responses. (C) speci c biological control agents Food–web interaction: agent is host-speciWc, but the overall interac- tion between the biological control agent and the pest is strongly bot- We recently examined empirical evidence for indirect tom-up so that the biological control agent becomes superabundant nontarget eVects of host-speciWc biological control and then serves to subsidize other natural enemies in the system. These W agents and identiWed three categories of indirect nontar- natural enemies then translate this subsidy into signi cant interactions V W with other nontarget species. Arrow direction indicates direction of the get e ects that can arise from highly host-speci c control dominant interaction and the weight indicates the strength of the agents (Pearson and Callaway, 2003). These categories interaction. Lines without arrows in (A) simply indicate some sort of include: (1) ecological replacement, (2) compensatory dependence. D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 291

Biological control under conditions of ecological compensatory response to root grazing. Over-compensa- replacement can result in undesirable indirect nontarget tion to clipping was reported for the invasive Centaurea eVects, but this is because the targeted pest has become solstitialis by Gerlach and Rice (2003), suggesting the important or desirable with regard to some aspect of its potential for this weed to increase its negative eVects ecology, not because a biological control agent has mis- under herbivory, and Callaway et al. (unpublished) behaved or otherwise failed. For example, saltcedar showed that clipping C. solstitialis did increase its nega- (Tamarix spp.) is a serious invasive pest in the south- tive impacts on native and naturalized California western United States which has replaced native trees grasses, but acknowledged that clipping diVers from her- and shrubs in many riparian areas (DeLoach et al., bivory in many regards. Callaway et al. (1999) and Ride- 2000). The southwestern willow Xycatcher (Empidonax nour and Callaway (2003) found that application of the traillii extimus [Phillips]), which is an endangered sub- biological control agent Agapeta zoegana L. (Lepidop- species of the willow Xycatcher, normally nests in wil- tera: Tortricidae) to its host plant spotted knapweed did lows (Salix spp.), but in some areas where willows have not reduce biomass or fecundity in spotted knapweed, been replaced by saltcedar, the Xycatcher now nests in but instead caused signiWcant reductions in reproduction the saltcedar (Sogge, 2000). The proposed biological and trends toward reduced biomass in neighboring control program for saltcedar was initially held up due Idaho fescue (Festuca idahoensis Elmer). Thus, the extent to concerns that successful control of the invader would to which compensatory responses might result in indi- leave the Xycatcher without nesting habitat in some rect nontarget eVects of biological control introductions areas (DeLoach et al., 2000). However, this program has is not yet clear given the limited research. However, resumed after careful examination of the risks and given the variability in the nature and strength of com- assessment of potential mitigation on behalf of the pensatory responses of plants to herbivory (Crawley, Xycatcher. Avoiding the unintended indirect nontarget 1989; Trumble et al., 1993), it is likely that indirect eVects eVects associated with ecological replacement involves of biological control agents that do occur through com- careful assessment of the target weed and its community pensatory responses would be highly variable and diY- interactions before introductions are made. We see the cult to predict. issue of ecological replacement as it relates to biological control as more of a policy issue than a problem with the 3.3. Food–web interactions ecological understandings of biological control. We are more concerned here with the ecological aspects of Food–web interactions can arise when generalist con- deploying biological control. sumers or other generalist natural enemies exploit a host-speciWc biological control agent (Figs. 1E and 2C). 3.2. Compensatory responses If the biological control agent is suYciently abundant, this interaction can result in a subsidy that signiWcantly Compensatory responses can cause deleterious indi- elevates the consumer’s populations. Such a subsidy can rect nontarget eVects by host-speciWc biological control translate to indirect eVects on nontarget species through agents when an agent’s attack elicits a response from the food–web interactions via the consumer. target species that actually increases its negative impact For example, the gall Xies (Urophora aYnis (Frauen- on nontarget species or shifts its impact to other nontar- feld) and U. quadrifaciata (Meigen), Lepidoptera: Tor- gets (Fig. 2B). Compensatory eVects may occur when a tricidae) introduced to North America to control damaged plant increases relative growth rates and com- spotted knapweed (Müller-Shärer and Schroeder, 1993) petitive eVects (Ramsell et al., 1993), induces the produc- have become extremely abundant (Harris, 1980) and are tion of chemicals that might harm neighbors (Siemens now exploited by many native consumers (Story et al., et al., 2002), or stimulates the release of root exudates 1995). Earlier studies indicated that exploitation of this (Hamilton and Frank, 2001). Plant compensatory resource by the native deer mouse (Peromyscus manicul- responses to herbivory are quite common (Crawley, atus Wagner) signiWcantly altered deer mouse diets with 1989; Trumble et al., 1993), and there are numerous potential to elevate mouse populations in knapweed- examples of compensatory responses of exotic plants to invaded grasslands (Pearson et al., 2000). This Wnding mechanical clipping (Callaway et al., 2001, unpublished; spawned a recent debate in Conservation Biology about Gerlach and Rice, 2003) and to insects used as biological the suYciency of host speciWcity as a safeguard against control agents (Islam and Crawley, 1983; Julien et al., nontarget eVects (Hoddle, 2004a,b; Louda and Stiling, 1987; Katovich et al., 1999; Müller, 1989; Steinger and 2004). In question, in part, was whether gall Xies simply Müller-Shärer, 1992), but it is not clear how often com- served as an extra food resource for mice or whether gall pensation results in negative eVects on neighbors. Xies actually functioned as a subsidy that elevated mouse Ramsell et al. (1993) showed that Tipula paludosa Mei- populations and with them the potential for indirect gen feeding on Lolium perenne L. actually increased its nontarget eVects. New research that was in press during negative impacts on Rumex obtusifolius L. due to a this debate establishes that Urophora food subsidies 292 D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 actually double or triple mouse populations by increas- introduced range (e.g., Goeden and Louda, 1976; Julien ing overwinter survival of mice in knapweed-invaded and GriYths, 1998; Kluge, 1990; Müller and Goeden, habitats (Ortega et al., 2004). Additional studies have 1990; Nuessly and Goeden, 1984; Pearson et al., 2000; since corroborated this result (Pearson and Callaway, Pratt et al., 2003; Reimer, 1988; Sebolt and Landis, 2004; unpublished; D.E. Pearson unpublished data). This Story et al., 1995), food–web interactions are likely a increase in deer mouse populations is very signiWcant common outcome of the establishment of host-speciWc and signiWcantly increases the potential for gall Xies to biological control agents. For example, Nuessly and indirectly aVect other nontarget species through food– Goeden (1984) documented intensive predation by the web interactions (Pearson and Callaway, 2003). In fact, house mouse (Mus musculus L.) on the stem-boring Pearson and Callaway (unpublished) show that gall Xy moth (Coleophora parthenica Meyrick) introduced for food subsidies to mice have tripled the prevalence of the the biological control of Russian thistle (Salsola australis Sin Nombre virus, a hantavirus that causes hantavirus R. Brown) in California. This system is highly reminis- pulmonary syndrome in humans (Childs et al., 1994). cent of the knapweed-gall Xy-deer mouse system Their study area covered over 1600 km2, but the aVected described above. However, as in virtually all cases of area likely includes a much larger region of knapweed- biotic interference with biological control agents, the infested habitats in several western states and provinces. emphasis of Nuessly and Goeden was on evaluating the Additional research suggests that as spotted knapweed eVect of the mouse on the control agent not the eVect of invades native grasslands, gall Xy subsidies to deer mice the control agent on the mouse and other nontarget indirectly increase deer mouse seed predation and reduce organisms. Biological control agent–food–web interac- recruitment in native plants already directly impacted by tions appear to be widespread, but their implications are spotted knapweed (Pearson, unpublished data). poorly understood largely because their impacts are vir- Native species are not the only nontarget organisms tually unexplored. susceptible to impacts of biological control food–web interactions. Biological control agents themselves can also be aVected. Coleomegilla maculata De Geer is an aggres- 4. Safeguarding against indirect nontarget eVects of host- sive predator of Galerucella pusilla Duft. and Galerucella speciWc biological control agents calmariensis L., two biological control agents introduced against purple loosestrife (Lythrum salicaria L.) (Landis et These examples show that host speciWcity alone does al., 2003). Thus, C. maculata is a shared natural enemy not ensure the safety of biological control programs as between these two agents that has the potential to aVect previously argued (Frank, 1998; Hoddle, 2004a). More- their relative abundance through apparent competition— over, they indicate that the nature of indirect nontarget a special case of food–web interactions that arises when eVects that can arise from even highly host-speciWc bio- an organism aVects the abundance of a potential competi- logical control agents are such that they simply cannot tor by subsidizing a shared enemy (Holt, 1977). Although be ignored. This conclusion has serious implications for host speciWcity in weed biological control guards against biological control and raises the crucial question of negative aVects of apparent competition that arise from whether or not indirect nontarget eVects of host speciWc the biological control agent becoming the shared natural biological control agents can be predicted well enough to enemy between a target weed and nontarget plants, it does screen for them or if a better understanding of the types not guard against apparent competition occurring of interactions that result in indirect nontarget eVects through higher trophic interactions involving natural ene- will allow us to avoid deleterious outcomes by designing mies that attack the biological control agent. Recent sur- around them. veys monitoring introductions of G. calmariensis and Predictability has historically been an important ele- G. pusilla indicate that G. calmariensis established success- ment for safeguarding against nontarget eVects. In the fully at 100% of 24 release sites whereas G. pusilla failed to case of weed biological control, knowledge of the host establish at any of these release sites (Landis et al., 2003). range of the natural enemy is utilized to develop screen- Although diVerential establishment of the two conspe- ing tests to determine the degree of host speciWcity of ciWcs could be due to intrinsic diVerences in abiotic inter- biological control agents and identify potentially at-risk actions or direct competition between the two agents, it is nontarget species (Briese, 2003; McEvoy, 1996; Waps- quite possible that apparent competition plays a role. here, 1974). This approach has clearly reduced the risks C. maculata is a strong predator of both species (Sebolt associated with biological control agents introduced for and Landis, 2004). If G. calmariensis is better able to suVer weed control (Pemberton, 2000), but the key to employ- this predation, it may indirectly contribute to the demise ing this technique has been the predictability associated of G. pusilla by subsidizing the C. maculata attack on with host-range expansion that has allowed testing to G. pusilla. focus on a Wnite number of prospective alternative hosts Given the frequency with which biological control without having to test all nontarget species present in the agents are exploited by natural enemies in the new environment (Briese, 2003; Pemberton, 2000). D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 293

Examination of the C. maculosa–Urophora spp. and In this case, the direction of the interaction appears to be C. maculosa–A. zoegana examples suggests that speciWc top-down as intended (Müller-Shärer, 1991), but the indirect nontarget eVects are highly unpredictable. It is weed is able to compensate by displacing the negative extremely unlikely that one would anticipate at the out- impact of the biological control agent, thereby increas- set of these introductions that gall Xies would elevate the ing the negative eVects on the recipient organism. Inter- prevalence of hantavirus via subsidies to deer mouse action strength appears to be key here as well. Although populations or that A. zoegana would increase the nega- C. maculosa seems able to displace the negative impacts tive eVect of C. maculosa on F. idahoensis. In general, of A. zoegana in the current scenario, if the impact of predicting speciWc indirect nontarget eVects seems A. zoegana on C. maculosa could be increased, it seems unlikely. However, understanding the process by which likely that eventually C. maculosa would no longer be these interactions occur may allow us to more eVectively able to compensate and successful control would be guard against the types of pathways that can lead to achieved. In general, if the biological control agent is these indirect nontarget eVects. strong enough (e.g., it kills or nearly kills the plant out- Based on the theoretical and empirical evidence pre- right), it is unlikely that the plant will be able to compen- sented above, there are only two basic pathways cur- sate for the attack. rently recognized by which indirect nontarget eVects can Thus, disregarding issues of ecological replacement as arise from host-speciWc biological control agents, and policy problems, we currently recognize two pathways both are driven by the interaction between the biological by which host-speciWc biological control agents can control agent and the weed (Fig. 2). Better understand- cause indirect impacts on nontarget species: (1) compen- ing of the components of this critical interaction may satory responses (Fig. 2B), which are top-down in nature help improve our ability to avoid indirect nontarget and (2) food–web subsidies (Fig. 2C), which are bottom- eVects while simultaneously increasing the success of up in nature. These examples indicate that the nature of biological control. Food–web interactions are one route the biological control–weed interaction (top-down ver- to indirect nontarget eVects of host-speciWc biological sus bottom-up) and the strength of this interaction are control agents that has been identiWed by both theoreti- both very important aspects determining the potential cal and empirical research (Fig. 2C). As illustrated by the for indirect nontarget eVects of host-speciWc biological C. maculosa–Urophora spp. case study, food–web subsi- control agents. This information is valuable for isolating dies depend on an interaction between the biological the source of indirect nontarget eVects arising from host- control agent and the weed that translates into an over- speciWc biological control agents to identify the species all bottom-up eVect (Pearson and Callaway, 2003). That likely to be at risk, but how do we predict the potential is to say, the eVect of the weed on the biological control degree of impacts expected? agent is stronger than the eVect of the biological control Theoretical work suggests that indirect eVects arising agent on the weed so that the overall outcome is an from biological control agents will be proportional to increase in the biological control agent instead of a the agent’s abundance (Holt and Hochberg, 2001). This decrease in the weed. This situation creates conditions means, indirect nontarget eVects will be closely linked to ripe for subsidies to other food–web elements via gener- the biological control agent’s success. Unsuccessful bio- alist natural enemies that are capable of exploiting both logical control agents that are not eVective at establish- the biological control agent and other organisms in the ing or exploiting their host in the new environment will system because the overall interaction is bottom-up not become suYciently abundant to threaten nontarget rather than top-down as intended. Equally important is species. Highly successful biological control agents will the strength of this interaction. For example, in the over-exploit the target species with a resultant reduction C. maculosa–Urophora spp. case even though the direc- in their own numbers and associated risks to nontarget tion of the interaction is bottom-up, if the interaction species (Holt and Hochberg, 2001). In contrast, biologi- between C. maculosa and Urophora spp. were weak (i.e., cal control agents of intermediate success, that eVectively C. maculosa only very weakly subsidized Urophora spp.) establish and exploit their host without greatly reducing the indirect eVects of gall Xies would rapidly attenuate. its populations, are the agents most likely to reach high Mice would eat gall Xies, but gall Xies would not be suY- equilibrium densities in the introduced range and pres- ciently abundant to subsidize mouse populations and ent the greatest risks to nontarget species (Holt and indirect eVects passing through mice to other species Hochberg, 2001). The implication here is that eYcacy is would be negligible. the key to understanding and predicting indirect nontar- The second route by which indirect nontarget eVects get eVects of host-speciWc biological control agents. can arise from host-speciWc biological control agents is Highly eVective host speciWc biological control agents through compensatory responses (Fig. 2B). This type of will present low risk to nontarget species. So long as the indirect nontarget eVect has not yet been recognized by agents do not host-switch, they will reduce their own theoretical work in biological control, but is illustrated numbers through a density-dependent feedback as they by the empirical example of C. maculosa and A. zoegana. reduce the target species. Even if the biological control 294 D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 agent becomes superabundant in the initial process of 1996; Briese and Zapater, 2002; Briese et al., 2002). establishment, which increases its potential indirect non- Recent Wndings regarding nontarget eVects in biological target impacts, as long as the biological control agent is control (Pearson and Callaway, 2003) argue now more ultimately successful, these indirect nontarget eVects than ever for shifting multiple-release strategies away should be ephemeral (exceptions could include extirpa- from lottery-style approaches toward more deliberate tion of a nontarget species or other permanent impacts community assembly by minimizing agent numbers and during the abundant phase). Classical biological control reducing redundancy while attempting to maximize successes such as klamath weed in California, USA and eYcacy of a few select agents through greater knowledge prickly pear (Opuntia spp.) in Australia and elsewhere of the weed and prospective biocontrol agents. very eVectively illustrate this phenomenon (DeBach et al., 1976; HuVaker and Kennett, 1959). EYcacy there- fore is not only important for biocontrol success, it is 6. Host speciWcity versus eYcacy also important for ensuring the safety of biological control. Given that host speciWcity and eYcacy are both criti- cal for safe and eVective biological control, it is of inter- est to revisit the question of whether these two goals are 5. Deliberate community assembly biologically at odds with each other. Degree of host speciWcity is seen as an indication of highly coevolved The ultimate intent of biological control is deliberate relationship between natural enemy and host (Allee community assembly (sensu Holt and Hochberg, 2001). et al., 1949) and some have argued that this coevolved Whenever we introduce biological control agents we do process undermines the eYcacy of the natural enemy so with the intent of achieving a speciWc outcome in (Hokkanen and Pimentel, 1984; Pimentel, 1963). If this is terms of community interactions. Although all multiple true, evolution may tend to deny us the best ecological release strategies share this common goal, they diVer in combination for biological control—those organisms their routes to achieving it. Multiple release strategies that serve as both highly host speciWc and highly eYca- represent a continuum in biological control that ranges cious agents. Certainly the huge success of myxoma virus from the lottery approach at one extreme to deliberate in controlling European rabbits illustrates just how eVec- community assembly at the other, with the cumulative tive new natural enemy–host associations can be stress model and others somewhere in between (Harris, (Moore, 1987). However, the risks associated with imple- 1991; Myers, 1985; Sheppard, 2003). Strategies like the menting biological control based on new natural enemy– lottery and cumulative stress models rely on chance and host associations are deemed too great to accept given the assumption that multiple host speciWc biological con- that this practice involves introducing natural enemies trol agents will have additive or synergistic eVects with that are suYciently generalist that they are willing to regard to their overall impact on the weed. However, establish on new host species (Goeden and Kok, 1986). multiple agents are just as likely to increase the chances Moreover, older and more coevolved associations can of antagonistic interactions like competition or intra- also be very successful as noted for Chrysolina control of guild predation among biological control agents (e.g., klamath weed (HuVaker and Kennett, 1959; Syrett et al., Ehler and Hall, 1982; Story et al., 1991; Wang and Mess- 2000). The question then arises, what conditions cause ing, 2003; Woodburn, 1996) that can undermine eVective biological control agents derived from older coevolved control while increasing risk to nontarget species. Delib- associations to at times be so virulent? We need to better erate community assembly requires an understanding of understand how and when mechanisms such as condi- the ecology and biology of the weed as well as the biolog- tions in the new environment or escape from natural ical control agent to select, and introduce the minimal enemies by the biological control agent are likely to number of agents while maximizing control. The impor- facilitate successful control (Colautti et al., 2004; Hinz tance of these understandings are being increasingly rec- and Schwarzlaender, 2005) if we are to use this under- ognized in biological control (Briese, 2004; Hinz and standing to engineer more predictable and successful Schwarzlaender, 2005; Sheppard, 2003), and recent stud- biological control. In particular, better understanding of ies in weed biological control have begun to show how the potential tradeoVs between host speciWcity and knowledge of the relative sensitivities of a weed’s life- eYcacy is critical given the need for maximizing both of cycle transitions can indicate which natural enemy these factors for safe and eVective biological control. attacks are most likely to be eVective (McEvoy and Coo- mbs, 1999, 2000; McEvoy et al., 1993). These studies have begun to pave the way toward deliberate community 7. EYcacy testing assembly as a minimalist multiple release strategy in bio- logical control and recent biological control programs The notion of elevating eYcacy standards for biologi- are increasingly moving in this direction (Blossey et al., cal control introductions to the level of those standards D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 295 currently applied to host-speciWcity testing seems oner- (1996) and Syrett et al. (2000), it is important to appro- ous indeed given the current costs, time, and eVort priately assess costs when evaluating biocontrol success. required for host-speciWcity testing (Van Driesche and If one considers that a partially successful control agent Bellows, 1996). However, recent theoretical work sug- that provides marginal Wnancial or ecological returns gests that by turning this process around, time and costs, from a minor reduction in weed populations may simul- might actually be saved in the testing process over cur- taneously have disproportionately strong impacts and rent approaches. McClay and Balciunas (2005) suggest costs associated with its nontarget eVects, then the that because eYcacy testing can be much simpler than notion of partial success must be reevaluated in this host speciWcity testing (it involves testing only one natu- context. If moderately successful agents hold the great- ral enemy–plant interaction per natural enemy instead of est potential risk to indirect nontarget species (Holt and many), it can actually function as a fast, eVective method Hochberg, 2001), this understanding must be incorpo- for reducing the list of control agents being tested for rated in the evaluation of success to develop more introduction. Even if such a method is only crudely objective standards for quantifying biological control applied, it could provide a more objective means of success. prescreening for eYcacy before host-speciWcity testing that could be systematically applied and formally evalu- ated. Under a deliberate community assembly approach, 9. Future directions agents that test poorly for eYcacy simply would not get evaluated further because they are rejected for release. Additional work is needed to advance our under- Evaluating weed life-cycle transitions (McEvoy and standings of how weed and natural enemy biology and Coombs, 1999; McEvoy et al., 1993) can also reduce the ecology determine not only biological control success, list of species that need to be tested for host speciWcity by but also community-level outcomes of biological con- screening out organisms unlikely to eVect control over trol introductions so that we can begin to more predict- the weed. For example, seedhead Xies may be inappro- ably engineer community outcomes resulting from priate for species that are not seed limited (Myers and these introductions (e.g., McEvoy and Coombs, 1999; Risley, 2000; Stanley, 2005). Although, eYcacy tests in McEvoy et al., 1993). For example, little is known the laboratory and in the Weld in the native range will about compensatory responses of weeds or inverte- never provide a fail-safe predictor for the outcomes of brate pests to biological control agents. More work is complex community interactions in the new environ- needed in the realm of eYcacy testing and evaluation ment, using eYcacy testing to drive biological control of sensitivities of weed life-cycle transitions to deter- agent selection is consistent with a deliberate community mine to what extent such information can serve to bet- assembly approach to biological control that focuses on ter Wlter out weak agents that oVer little chance for fewer more eYcacious control agents that will reduce successful control (McClay and Balciunas, 2005). Bio- risk to nontarget species and increase chances for suc- logical control agents as a whole should be evaluated cessful biological control. with regard to eYcacy versus potential indirect nontar- get risks to determine if certain biological control groups or strategies that have low eYcacy also have 8. DeWning success high potential risks for indirect nontarget eVects. If cer- tain categories of biological control agents have low The conclusion that indirect nontarget eVects arising eYcacy, high potential risks, or both, these groups from host-speciWc biological control agents are linked should be considered for exclusion from future biologi- to biocontrol success has important ramiWcations for cal control programs. Finally, we need to expand on how successful control is deWned. From a theoretical our understanding of potential tradeoVs between host perspective, successful biological control is deWned speciWcity and eYcacy if we are to determine how to based on a threshold of economic or ecological impact best maximize both of these factors in the agents we and therefore is dichotomous (Van den Bosch and Mes- choose. senger, 1973). However, in practice, the deWnition of successful biological control has evolved into a rather continuous concept including diVerent degrees of par- 10. Conclusions tial control being variously identiWed as success (Gurr and Wratten, 2000; McFadyen, 1998). This has resulted The fact that host-speciWc biological control agents in a general lack of agreement on a common deWnition can deleteriously impact nontarget species has profound of successful control that has contributed to the widely implications for biological control and multiple release divergent estimates of biological control success seen in strategies like the lottery approach. The lottery approach the literature (e.g., DeLoach, 1991; McFadyen, 1998; has been challenged on the grounds that (1) it is risky to Williamson, 1996). However, as pointed out by McEvoy introduce more biological control agents than are 296 D.E. Pearson, R.M. Callaway / Biological Control 35 (2005) 288–298 necessary to achieve eVective control and (2) multiple bio- Briese, D.T., Petit, W., Swirepik, A., Walker, A., 2002. A strategy for the logical control agents can just as well negatively aVect the biological control of Onopordum spp. Thistles in south-eastern outcome of biological control as result in additive or syn- Australia. Biocontrol Sci. Tech. 12, 121–137. Callaway, R.M., DeLuca, T.H., Belliveau, W.M., 1999. Biological-con- ergistic interactions as intended (McEvoy and Coombs, trol herbivores increase competitive ability of Centaurea maculosa. 2000; Myers, 1985; Myers et al., 1989; Pearson and Call- Ecology 80, 1196–1201. away, 2003; Strong and Pemberton, 2000). Until now, the Callaway, R.M., Newingham, B., Zabinski, C.A., Mahall, B.E., 2001. assumption that host-speciWc biological control agents Compensatory growth and competitive ability of and invasive weed are safe has helped to sustain multiple release approaches are enhanced by soil fungi and native neighbors. Ecol. Lett. 4, 1–5. 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