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Published in final edited form as: Ecology. 2024 Apr 28;105(6):e4315. doi: 10.1002/ecy.4315

Effects of predation risk on parasite-host interactions and wildlife diseases

David W Thieltges 1,2, Pieter T J Johnson 3, Anieke van Leeuwen 1, Janet Koprivnikar 4
PMCID: PMC11147705  NIHMSID: NIHMS1985991  PMID: 38679953

Abstract

Landscapes of fear can determine the dynamics of entire ecosystems. In response to perceived predation risk, prey can show physiological, behavioral or morphological trait changes to avoid predation. This, in turn, can indirectly affect other species by modifying species interactions (e.g., altered feeding), with knock-on effects such as trophic cascades on the wider ecosystem. While such indirect effects stemming from the fear of predation have received extensive attention for herbivore-plant and predator-prey interactions, much less is known about how they alter parasite-host interactions and wildlife diseases. In this synthesis, we present a conceptual framework for how predation risk – as perceived by organisms that serve as hosts – can affect parasite-host interactions, with implications for infectious disease dynamics. By basing our approach on recent conceptual advances with respect to predation risk effects, we aim to expand this general framework to include parasite-host interactions and diseases. We further identify pathways through which parasite-host interactions can be affected, e.g., through altered parasite avoidance behavior or tolerance of hosts to infections, and discuss the wider relevance of predation risk for parasite and host populations, including heuristic projections to population-level dynamics. Finally, we highlight the current unknowns, specifically the quantitative links from individual-level processes to population dynamics and community structure, and emphasize approaches to address these knowledge gaps.

Keywords: Predation risk, ecology of fear, non-consumptive effects, trait-mediated indirect effects, parasitism

INTRODUCTION

Anyone who has seen movies such as Jaws, Lake Placid, Piranha or Anaconda knows about the visceral fear that voracious predators can induce in their potential victims. While this might seem like an unpleasant but harmless experience, science has increasingly realized that the fear of predators can have significant consequences not only for scared prey, but also for the wider community around them. In response to perceived risk of predation, prey of many species can undergo physiological, behavioral or morphological trait changes that reduce their predation risk (Lima, 1998; Werner & Peacor, 2003; Sheriff & Thaler, 2014). These energetically costly defenses by fearful prey can, in turn, negatively affect their fitness and abundance (Werner & Peacor, 2003; Peacor et al., 2020).

The resulting changes in prey traits can also indirectly affect other species via species-interactions, with secondary knock-on effects for the community and the wider ecosystem, e.g., through trophic cascades (Peacor et al., 2020). Such wide-ranging effects through a phenomenon coined the ‘ecology of fear’ first gained attention following the re-introduction of wolves to Yellowstone National Park (Ripple & Beschta, 2004; Wirsing & Ripple, 2011). In response to wolf presence, large grazing ungulates adjusted their habitat use and foraging patterns, which led to reduced grazing pressure and subsequent increases in the recruitment of woody plants, particularly along riverbanks. This, in turn, led to the recovery of riparian functions and recolonization of beavers (Ripple & Beschta, 2004; but see Kauffman et al. 2013). These complex, knock-on effects stemming from perceptions of predation risk, yet extending to species interactions, are not unique to terrestrial predator-herbivore-plant systems, and have also been documented in aquatic systems, e.g., in sharks that prey on herbivore dugongs in marine waters, which may in turn affect seagrass meadows through altered dugong foraging (Wirsing & Ripple, 2011).

These manifold indirect effects of perceived predation risk on herbivore-plant and predator-prey interactions have received extensive attention (e.g., see reviews by Lima, 1998; Werner & Peacor, 2003; Sheriff & Thaler, 2014; Peacor et al., 2020). In contrast, much less is known about how the fear of predation can indirectly affect another common type of species interaction, namely, that between parasites and hosts. All animal species serve as hosts to parasites, ranging from microparasites such as viruses and bacteria to macroparasites such as helminths and arthropods (Goater et al., 2013). Hence, predator-induced changes in prey traits may also be relevant for their function as hosts to parasites. Specifically, some trait changes, such as altered behavior or physiology, may affect the various defense mechanisms that hosts have evolved to either avoid becoming infected, or to deal with infections by resistance or tolerance mechanisms (Buck et al., 2018; Råberg et al., 2009) and this, in turn, may decrease or increase disease risk.

Hosts that change their behavior as a response to perceived predation risk by moving to different habitats, or changing their feeding rates or activity levels, may generally be exposed to different species or numbers of parasites (Hoverman & Searle, 2016; Binning et al., 2017; Shaw & Civitello, 2021). As a case in point, tadpoles increase their swimming activity in the presence of trematode (flukes) cercariae to avoid infections; however, when predation risk cues are present, the tadpoles reduce this activity to avoid predation, which consequently results in increased infections (Thiemann & Wassersug, 2000; Koprivnikar & Urichuk, 2017). Physiological changes such as increased stress levels of hosts in response to perceived predation risk may further increase their susceptibility to infections or affect their post-infection defenses due to immunosuppression (Shaw & Civitello, 2021; Sheldon & Verhulst, 1996).

Predation-risk induced trait changes in prey thus have the potential to trigger manifold indirect effects on parasite-host interactions. These are part of a wider range of predator effects on parasite-host interactions, including selective predation on infected hosts and free-living infective stages (Lopez & Duffy, 2021). Predator effects on parasite-host interactions resulting from actual predation (consumption) of hosts or parasites, i.e. density-mediated indirect effects (Fig. 1a) have been comprehensively covered in recent reviews (Johnson et al.; 2010; Shaw & Civitello, 2021; Lopez & Duffy, 2021; Koprivnikar et al., 2023). In contrast, non-consumptive effects of predators that lead to trait-mediated indirect effects on parasite-host interactions (Fig. 1b) have received relatively little attention.

FIGURE 1.

FIGURE 1

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Scope and concepts of current synthesis in the context of related topics and previous reviews. While consumptive effects of predators on parasite-host interactions have been covered by several previous reviews (a), a comprehensive synthesis of non-consumptive effects of predators on parasite-host interactions is missing to date (b). Similar to predators, parasites can also exert consumptive (c) and non-consumptive (d) effects on hosts, with repercussions for parasite-host interactions. Boxes include examples of trait- and density-mediated effects via the different mechanisms covered by previous in-depth reviews and references therein.

Recent reviews have also considered that parasites themselves are capable of inducing indirect effects, either through consumption, i.e., infection (Fig. 1c; Hatcher & Dunn, 2011; Buck 2019), or via non-consumptive effects if a perceived threat of infection causes changes in host traits that have repercussions for parasite-host interactions (Fig. 1d; Buck & Ripple, 2017; Weinstein et al., 2018; Buck et al., 2018; Buck, 2019; Daversa et al., 2021; Koprivnikar et al., 2021). However, there remains a knowledge gap with regard to potential non-consumptive effects of predators on parasite-host interactions (Fig. 1b). In fact, one of the outstanding questions by Lopez & Duffy (2021) asked by what other mechanisms could predators mediate host–parasite interactions in their prey. Consequently, a comprehensive synthesis of non-consumptive effects of predators on parasite-host interactions would serve to highlight this critical component of general predator influences and spark more studies into this direction.

In this synthesis, we present a conceptual framework of how predation risk perceived by wildlife hosts can affect parasite-host interactions through various pathways, with implications for infectious disease dynamics. We base our approach on recent conceptual advances regarding predation-risk effects (Peacor et al. 2020) with the aim to expand this general framework to include parasite-host interactions and diseases. By synthesizing key findings from the available literature, we identify critical pathways by which parasite-host interactions could be altered by predation-risk effects and discuss their wider relevance for parasite and host populations, as well as areas in need of further research. Throughout this synthesis, we use the term parasite in an ecological sense, i.e., denoting a species interaction between two organisms in which the parasite gains energy and habitat at the expense of the host (Combes, 2001), including classical parasitic groups such as helminths, but also microparasites such as viruses and bacteria that are often categorized as pathogens. By definition, parasites always have negative effects on their host, but not all parasites necessarily cause disease in the form of organismal malfunctioning with veterinary or conservation relevance. However, also in these latter cases, any changes in parasite-host interactions can be expected to potentially affect the disease risk of hosts that are scared by predators.

PREDATION RISK-INDUCED CHANGES IN PREY TRAITS

Organisms can respond to a perceived risk of predation with a diversity of trait changes intended to reduce the threat of injury or death (Fig. 2; for reviews see Lima, 1998; Werner & Peacor, 2003; Sheriff & Thaler, 2014). These changes can include behavioral, morphological, physiological, or life history traits that are phenotypically flexible within individual organisms (Fig. 2). Trait changes in response to predation risk can occur on different time scales, ranging from short-term responses such as moving away from predator cues to long-term responses, such as increasing body size or maturing earlier. For example, mollusks can quickly react to predator cues by closing their valves, retracting into their shells, (Smee & Weissburg, 2006; Kulakovskii & Lezin, 2002; Naddafi et al., 2007), or by escaping into more sheltered microhabitats (Jacobsen & Stabell, 1999; Kobak & Kakareko, 2009; Eschweiler & Christensen, 2011). On longer time scales, in turn, they can grow thicker shells (Freeman & Byers, 2006). There are also many physiological trait responses that can be induced by predation risk in a broad array of organisms, e.g., in the form of increased respiration or elevated glucocorticosteroid levels to support greater vigilance and escape behaviors (Hawlena & Schmitz, 2010). Finally, predation-risk responses can also include life history shifts. For example, larval stages of amphibians and insects can escape predation in their juvenile environment by metamorphosing sooner and at smaller body sizes (Bernard, 2004; Hite et al., 2018).

FIGURE 2.

FIGURE 2

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Different types of trait changes in prey in response to perceived predation risk by predators and host defenses against parasite infections. For details see text.

From these trait changes of prey in response to predation risk, a variety of indirect effects can arise (Fig. 3). Based on the conceptual framework and standardized terminology proposed by Peacor et al. (2020), all such predation-risk effects are based on two fundamental factors. First, the threat of predation usually varies, both in space and time, and many organisms can detect the presence of predators via visual or olfactory cues (Fig. 3a); and second, a perceived risk of predation can trigger a variety of trait changes in prey as they endeavor to avoid harm or death as discussed above (Fig. 3b). It is important to note that these changes result from traits being flexible rather than fixed, i.e., the trait changes in question are phenotypically plastic within an individual and they are not mean trait changes in a population (i.e., resulting from natural selection – Peacor et al., 2020).

FIGURE 3.

FIGURE 3

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Conceptual framework of how the perception of predation risk by prey that serve as hosts to parasites can alter parasite-host interactions and have knock-on effects on the wider community (based on Peacor et al., 2020). All effects resulting from predation risk-induced trait change responses of prey (b) constitute trait-mediated indirect effects of predators. Potential changes in prey fitness (d) are considered to be non-consumptive predator effects on prey (orange) in the strict sense (sensu Peacor et al., 2020). Note that all pathways shown act on individual prey/hosts. Population-level effects, both for parasites and hosts, may result from some of these pathways but are treated in a separate section.

PREDATION-RISK EFFECTS ON PARASITE-HOST INTERACTIONS

When prey that respond to predation risk also serve as hosts to parasites, we advance that this can alter parasite-host/prey interactions and wildlife diseases through pathways similar to those observed for predator-prey and herbivore-plant interactions (Fig. 3c–f). This is partly because the anti-parasite defenses usually exhibited by hosts may be affected by trait changes stemming from their perceived predation risk (Fig. 2). Due to the typically negative fitness consequences of infections, many organisms have evolved a wide array of defenses against parasites, including pre-infection and post-infection mechanisms. Pre-infection mechanisms include avoidance behaviors that lower exposure to infections, and can involve evasive or reduced movements to avoid encounter, spatiotemporal dodging through habitat choice and selective foraging, diel and seasonal migrations, and social behaviors such as aggregation and mate choice (see reviews by Thieltges & Poulin, 2008; Buck et al., 2018; Behringer et al., 2018; Koprivnikar et al., 2021).

Once exposed, hosts can still defend themselves through resistance mechanisms that clear parasites or prevent them from establishing successful infections. This can include behavioral and physiological components, such as grooming to remove parasites, self-medication (e.g., through consumption of medical plants) to treat infections, and the mounting of short- or long-term immune responses. Hosts can also tolerate infections in the form of various coping mechanisms (Sheldon & Verhulst, 1996; Råberg et al., 2009), including “sickness behaviors” such as lethargy that conserve host energy (Adelman & Hawley, 2017) and illness-mediated anorexia (Hite et al. 2020). Importantly, we note that many of these anti-parasite defenses may be affected by general trait changes in response to predation risk. In addition, some of the general trait changes in prey may also affect the general function of prey as a host, e.g., by altering the resources available to parasites after infection. Because trait changes in prey/hosts in response to predation risk may also alter parasite-host interactions and infectious disease dynamics, as well as other species interactions, these must be considered in addition to direct/consumptive effects of predators on host parasitism (reviewed by Shaw & Civitello, 2021; Lopez & Duffy, 2021). We discuss host defenses in more detail below in terms of how these may specifically be affected by trait changes in response to predation risk.

A FRAMEWORK FOR CHARACTERIZING PREDATION-RISK EFFECTS ON PARASITE-HOST INTERACTIONS

Building on the conceptual framework and standardized terminology for predation-risk effects proposed by Peacor et al. (2020), we developed an expanded version that conceptualizes and integrates different mechanisms that may drive predation-risk effects on parasite-host interactions (Fig. 3c–f). These arise when predation risk-induced trait changes in prey also affect their function as a host (interaction modification sensu Peacor et al., 2020); Fig. 3c). This interaction modification can, in turn, affect the fitness of prey, e.g., by lowering or increasing infection burden in a manner that negatively affects their survival and/or reproduction (Fig. 3d). Prey fitness can also be affected by the trait changes resulting from perceived predation risk, e.g., in cases where risk-induced trait responses are energetically costly (Fig. 3b). Both pathways lead to non-consumptive effects in the strict sense (sensu Peacor et al., 2020) of predators on their prey, which are basically indirect effects of predators on their prey compared to their direct consumptive effects (Fig. 3d).

Predation risk-induced changes in parasite-host interactions not only affect prey/hosts, but can also affect the fitness of parasites and their infection intensity in hosts. In other words, they affect a third species (the parasite) in addition to the predator and the prey (Fig. 3e). Those effects can have further consequences for additional species in the community; for instance, when the parasites also infect other host species (Fig. 3e). Such knock-on effects on the wider community may also result from the various predation risk-induced effects on the fitness of prey/hosts (Fig. 3d), especially for species with important ecological functions such as ecosystem engineers (Fig. 3e).

As outlined above, predation risk-induced trait changes in prey that affect their function as a host are at the foundation of the various possible trait-mediated indirect effects of predators on parasites and diseases that we suggest here. In general, there are four crucial steps in the life cycle of parasites by which parasite-host interactions can be affected if prey that also serve as hosts show trait changes in response to the threat of predation (Fig. 4). First, behavioral anti-predator responses of prey, such as avoiding specific habitats or adjusting activity and feeding levels, may alter the frequency with which parasites encounter potential hosts. Second, once a host encounters parasite infective stages, predation risk-induced behavioral, physiological, or morphological trait changes in hosts (e.g., immunosuppression due to enhanced stress levels or reduced grooming) may affect parasite establishment success. Similarly, in the third step, these host trait changes may affect the persistence of infections, as well as parasite virulence and pathogenicity in hosts once infected. Finally, the amount or rate of parasite propagule production may also be affected by the same host trait changes or by life history adjustments, such as host longevity. Any changes in parasite-host interactions at one of these four crucial steps in parasite life cycles due to predation risk-induced trait changes in hosts can thus trigger the diverse indirect effects of predators on parasites, hosts and other species outlined above.

FIGURE 4.

FIGURE 4

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Framework for characterizing predation-risk effects on parasite-host interactions along four crucial steps in the life cycle of parasites where parasite-host interactions can be affected by predation risk-induced changes in traits of prey that also serve as host. For details see text.

Although research on predation-risk effects on parasite-host interactions remains in its relative infancy, the few existing studies that have investigated this suggest not only that such effects exist, but that they may have important repercussions for a wide range of parasites and diseases. In the following subsections, we synthesize key findings from those studies with the aim to characterize the various mechanisms associated with the steps highlighted in Fig. 4.

Host encounter

The first step in which predation risk-induced changes in host traits can affect parasite-host interactions is the initial contact between a parasite and its host. This is a critical phase because parasite avoidance is generally considered less costly than resistance or tolerance (Hart, 1990; Hart & Hart, 2018; Gibson & Amoroso, 2022). Consequently, there are many predator-induced trait changes on the host side that can increase or decrease the likelihood of parasites to encounter potential hosts and thus alter parasite-host interactions. For example, changes in habitat use in response to predation risk can increase host contact with infective stages of parasites. This has been observed in coastal gastropods seeking refuge in the high intertidal from predation pressure by subtidal crab and starfish, but this in turn exposes them to more trematode parasites (Byers et al., 2015). Likewise, while the negatively phototactic behavior of some Daphnia water flea clones in response to the presence of planktonic predators leads to lower predation, this habitat shift also leads to higher exposure to parasite spores from pond sediments, leading to elevated infection levels (Decaestecker et al., 2002).

In addition to habitat shifts, social antipredator responses such as group-forming can also have indirect effects on host encounter rates of parasites. For example, shoaling in guppies reduces predation risk; however, at the same time, group-forming leads to higher exposure of uninfected fish to conspecifics infected with monogeneans (directly-transmitted ectoparasitic flatworms), thereby increasing parasite transmission and infection levels in fish (Stephenson et al., 2015; Walsman et al. 2022). Other common anti-predator responses, such as seeking refuge or reducing activity levels, can also indirectly affect host encounter rates with parasites. For example, lower activity of tadpoles as an anti-predator response when exposed to predator cues leads to higher exposure to trematode parasites (Thieman & Wassersug, 2000; Koprivnikar & Urichuk, 2017). Likewise, the hiding of marine mussels within the matrix of mixed mussel and oyster beds to avoid crab and bird predation can lead to elevated infection levels in mussels with trematode parasites which originate from snail first intermediate hosts living inside the matrix (Goedknegt et al., 2020). At the same time, however, this anti-predator behavior leads to reduced infection levels with endoparasitic copepods in mussels, probably due to oysters diluting infective stages settling from the water column into the beds, indicating that the direction and strength of predation risk effects on host encounter rates depend on the specific parasite-host system (Goedknegt et al., 2020). Finally, morphological trait changes can affect host encounter with parasites, as observed in water fleas that increase their body size in response to predator cues. This leads to elevated feeding rates at larger body size and a higher exposure to parasite spores in the water column (Duffy et al., 2011).

Parasite establishment

Once parasites encounter a host, some of the physiological, behavioral or morphological trait changes in response to predation risk cues may affect the successful establishment of parasites in/on the host. In many prey species, various stressors, including the perception of predation risk, can lead to physiological responses in the form of elevated levels of certain hormones, particularly glucocorticoids such as cortisol and corticosterone (Adamo et al., 2017; MacDougall-Shackleton et al., 2019). Those increased glucocorticoid levels can be associated with immunosuppression (Romero, 2004; Sapolsky et al., 2000), which may affect the establishment of parasites in their hosts (Adamo et al., 2017). For example, larval salamanders that are exposed to predator cues are more susceptible to virus infections, presumably resulting from glucocorticosteroid-mediated immunosuppression (Kerby et al., 2011). Similarly, sparrows exposed to predator clues not only showed lowered T-cell–mediated immune responses, but also increased prevalence and intensity of Haemoproteus blood infections (Navarro et al., 2004), and exposure of Wistar rats to olfactorial predator clues resulted in immune suppression and higher burdens of nematode parasites (Horak et al., 2005).

Parasite establishment in hosts can also be affected by changes in host behaviors in response to predation risk clues. For instance, in bivalves, cues of crab predators lead to closure of the valves and cessation of filtration activity (Cornelius et al., 2023). Because filtration is the main route through which bivalves are exposed to trematode infections, this anti-predator response leads to a concurrent reduction of infection levels (Cornelius et al., 2023).

Infection persistence & pathogenicity

Once infected, trait changes in hosts in response to predation risk may affect the persistence and pathogenicity of infections through host resistance and tolerance mechanisms. Interestingly, responses of prey to predator cues can sometimes increase immune function (Duong & McCauley, 2016; Adamo et al., 2017), with implications for infection resistance. As an example, predation clues from cannibalistic conspecific larval dragonflies cause an increased melanization response to simulated parasites in the form of injected monofilaments (Murray et al., 2020). This indicates that host trait changes in response to predation risk do not always benefit parasites; in fact, in some cases, responses to predators could have a dual benefit to prey as they also defend against parasitism. For example, predator-induced acceleration of development and early metamorphosis such as observed in amphibians (Bernard, 2004; Hite et al., 2018) may also lower their exposure to aquatic parasites.

Predators can also affect host behaviors relevant for parasite persistence. For instance, female impalas decreased the time spent grooming their young when in a state of heightened alertness due to the presence of predators, which likely results in reduced removal of ectoparasites such as ticks from calves (Blanchard et al., 2017). However, in cases where parasites manage to persist, predation risk-induced trait changes in their hosts may also affect the pathogenicity of parasites and the ability of hosts to tolerate infections. For instance, in the case of larval salamanders that are more susceptible to virus infections when exposed to predation risk cues, the same glucocorticosteroid-mediated immunosuppression mechanisms are probably also responsible for a higher mortality of infected hosts when predation risk cues are present (Kerby et al., 2011). In another example, mosquitoes exposed to predator cues as larvae showed reduced survival when infected with a parasitic fungus as adults (Ong’wen et al., 2020). Finally, predation risk-induced effects on the pathogenicity of parasites have been observed as a result of shoaling in guppies where the increased host contact rates due to shoaling lead to an increase in multiple infections with different parasite genotypes. The resulting parasite genotype competition, in turn, selects for higher virulence, thus leading to non-consumptive effects of predation on virulence evolution (Walsman et al, 2022).

Parasite propagule production

Finally, trait changes in hosts in response to predation risk may also affect the production of infective stages; for example, in cases where the stress responses of hosts lower their general condition and the availability of resources necessary for the production of infective stages, thus lowering parasite propagule production. However, it is also possible that host trait changes in response to predation risk lead to elevated parasite propagule production. For example, water fleas show an increase in parasite spore production when exposed to predation risk cues as they increase their body size in response to predation, which leads to more resources available to parasites to produce propagules (Duffy et al., 2011). Parasite propagule production can also be affected by behavioral trait changes of hosts in response to predation risk as exemplified by a higher release of trematode infective stages from infected gastropods when predation risk cues are present. This probably results from a higher activity of snails as an antipredator response, which in turn leads to increased parasite propagule release due to increased metabolic activity (Cornelius et al., 2023).

POPULATION-LEVEL CONSEQUENCES

As noted above, predation-risk effects on parasite-host interactions initially result from trait changes in individual prey that also serve as hosts. However, the resulting indirect effects on parasite-host interactions may also have population-level consequences for hosts and parasites. Although such consequences are theoretically likely, the question is whether these effects really matter, i.e., whether trait-mediated predation risk effects translate into significant numerical responses of host or parasite populations or in substantial changes to their regulation. For predation-risk effects on predator-prey and herbivore-plant interactions, evidence for such non-consumptive effects of predators on their prey in the strict sense (sensu Peacor et al., 2020) is extremely limited (see review by Sheriff et al., 2020). Given the paucity of studies on predation-risk effects on parasite-host interactions, evidence is even poorer for non-consumptive effects of predators on hosts via altered parasite-host interactions.

Whether this lack of information reflects a lack of important effects or just a lack of investigations is unclear. However, it is possible to speculate about situations where predation-risk effects should matter for host population dynamics in the context of parasitism. In general, for predation-risk effects to have population-level consequences for hosts, trait changes in individual prey need to translate into effects on population dynamics. In cases where trait changes are directly linked with the processes of individual growth, survival or fecundity (Sheriff et al., 2020), an upstream impact on population dynamics is more likely than in cases where such links are indirect. Hence, trait changes in prey that reflect energetically-costly defenses against predators (Fig. 3b) are likely to affect the fitness of individuals (Fig. 3d), and this in turn could lead to population-level consequences for the prey. The same holds for trait changes connected to resource use since the altered feedback from prey on their food may have population-level effects. Likewise, trait changes in prey that lead to alterations of parasite-host interactions (Fig. 3c) may in turn have fitness consequences for hosts (Fig. 3d). As parasite infections by definition affect their host individual’s energy budget, and therefore growth, survival and/or fecundity (Combes, 2001), infection is likely to have fitness consequences on individual hosts and could ultimately affect host population dynamics.

However, effects at higher levels of organization will likely depend on the pathogenicity of the respective parasite and the strength of intensity-dependent pathology. In the case of virulent parasites with strong intensity-dependent pathology, predation risk-induced changes in host encounter, parasite establishment or infection persistence (Fig. 4) are likely to have strong effects on host populations. In contrast, in the case of relatively benign parasite infections with lesser pathology, predation risk-induced changes in parasite-host interactions may be of little relevance for host population dynamics. However, if long-lived parasites that are more benign keep impacting their hosts’ energy budgets throughout their life, infections could still have strong impacts on host populations by affecting growth, survival and/or fecundity.

Predation risk effects may not only have relevance for host populations, but also for the population dynamics of their parasites (Fig. 3e). Any strong effects on host populations caused by predation risk-induced changes of parasite-host interactions will also have repercussions for parasite populations due to the strong dependence of parasites on their hosts. However, in cases where host populations are not affected by predation risk-induced changes to parasite-host interactions, predation-risk effects may still matter for parasite populations because changes in host encounter, parasite establishment, infection maintenance or propagule production are all likely to affect parasite population dynamics. For example, increased transmission stemming from predation risk-induced trait changes in hosts may significantly boost parasite population growth without significant effects on hosts. One possible scenario for such effects could be cases where prey group together in response to predation risk, which then leads to population growth for directly-transmitted pathogens if these now spread more readily among hosts. In contrast, for parasites with indirect transmission, such a scenario might lead to an encounter-dilution effect for the parasites.

EFFECTS ON OTHER SPECIES

Predation risk-induced changes in parasite-host interactions may also affect other species in the wider community (Fig. 3e). This could happen if the respective parasites also infect other hosts beyond the species showing trait changes due to predation risk. For instance, greater infection in one host species due to predation-risk effects may result in higher infection risk for other competent hosts due to greater general parasite population size and infectious propagule production. Such changes in infection levels may in turn alter interspecific competition between hosts, which often can be modified by differential effects of parasite infections on different species (Hatcher et al., 2006). More alarmingly, such changes in infection level could have severe consequences for zoonotic spillover of parasites, including to humans. As many hosts harbor more than one parasite species, predation risk-induced changes in parasite-host interactions involving a specific parasite species may also affect other parasites. This could have significant consequences for competitive intra-host interactions between parasites. For instance, prior infection by one parasite can increase host susceptibility to other species or strains (e.g., Halliday et al., 2020), and may also affect the composition of parasite communities within hosts, as well as both host and parasite fitness (Johnson et al., 2015; Carpenter et al., 2021).

In addition to effects resulting from changes in parasite populations, knock-on effects on the wider community (Fig. 3e) may also result from the fitness effects of predation risk on individual hosts and its population-level consequences (Fig. 3d). For example, if the respective host is a species with important ecological functions such as an ecosystem engineer, changes in host abundance are likely to have far-reaching effects on the wider community (Poulin et al., 1999; Pascal et al., 2020; Fig. 3e). In addition, changes in host traits in response to predation risk could also affect the ecological functioning of host species in communities, with repercussions for ecosystem properties (Mouritsen & Poulin, 2005; Preston et al., 2016). While it is likely that predation risk-induced changes in parasite-host interactions may also affect other species in the wider community via these different pathways, detailed studies on such knock-on effects are lacking to date.

OUTSTANDING QUESTIONS AND FUTURE RESEARCH

Our synthesis highlights that there are several mechanisms by which predation-risk effects of predators can have consequences for parasite-host interactions. The existing studies suggest that such non-consumptive effects of predators may have important repercussions for a wide range of parasites and diseases. However, the number of studies to date is still very limited and more research into predation-risk effects on parasite-host interactions is needed to evaluate how common and broadly relevant they are (see Outstanding Questions Box 1). We thus call for experimental studies that explore predation-risk effects along the crucial steps in the life cycle of parasites that we present in our framework (Fig. 4). Hosts that show strong predation-risk responses, and that are open to experimental manipulations, will be promising starting points to investigate basic research questions such as whether the known trait changes of hosts in response to predation risk affect one or more of the crucial steps in parasite-host interactions.

BOX 1. OUTSTANDING QUESTIONS.

While our synthesis highlights mechanisms that explain how predation-risk effects can have consequences for parasite-host interactions and disease dynamics, it also identifies a range of outstanding research questions:

  • How common are predation-risk effects on parasite-host interactions?

  • Do predation-risk effects differ among host encounter, parasite establishment, infection persistence/pathogenicity, and parasite propagule production?

  • Is there evidence for population-level consequences of changes in parasite-host interactions in response to predation risk?

  • Can predation-risk effects on parasite-host interactions result in knock-on effects on the wider community?

  • What is the relative importance of non-consumptive effects of predators via predation-risk effects compared to the consumptive effects of predators such as predation on infected hosts and consumption of infective parasite stages?

  • Can trait changes in response to perceived infection risk (‘landscape of fear’) interfere with trait changes in response to predation risk with respect to the consequences for parasite-host interactions?

  • Can parasites be receivers of predation risk effects, i.e. can they perceive predation risks and react with specific trait changes, potentially triggering similar effects as when hosts respond to predation risk cues?

Even bigger research gaps exist in regard to population-level consequences and the effects on other species in the wider community of respective predator-prey/host-parasite systems (see previous two sections), but is consistent with our knowledge deficit when it comes to general predation-risk effects on predator-prey and herbivore-plant interactions (see review by Sheriff et al., 2020). As parasite infections usually affect the energy budget of infected hosts, and therefore their growth, survival and/or fecundity which ultimately determine host fitness, it is quite likely that predation-risk induced alterations of parasite-host interactions can influence host population dynamics. However, this is unexplored territory and future research that integrates predation-risk effects in population models will be necessary to identify whether such population-level consequences exist.

Beyond the considerable non-consumptive indirect effects discussed here, predators can also have direct consumptive effects on parasites (Fig. 1a; Lopez & Duffy, 2021); for example, when predators preferentially feed on infected hosts, they can affect parasite infection levels in host populations (healthy herd hypothesis; Packer et al., 2003). Predators can also consume free-living infective parasitic stages, which can affect transmission from one host to another (Thieltges et al., 2008; Johnson et al., 2010; Johnson & Thieltges, 2010). Predators thus have complex direct and indirect effects on parasite-host interactions and it will be insightful to study the relative importance of predation risk effects compared to other predator effects on parasitism (Lopez & Duffy, 2021; Shaw & Civitello, 2021).

Interestingly, it is not only predators that exert indirect effects on hosts through fear, but parasites can also induce fear responses in their potential hosts (Fig. 1d). As for predation risk, a perceived threat of infection can lead to trait changes in potential hosts that in turn cause a range of indirect effects (Buck et al., 2018; Buck, 2019; Daversa et al., 2021; Koprivnikar et al., 2021). In some cases, infection risk-induced trait changes may counteract trait changes induced by predation risk. For instance, in the tadpole example discussed above, individuals increase their swimming activity in presence of trematode cercariae to avoid infections but reduce this activity in the presence of predators (Thiemann & Wassersug, 2000; Koprivnikar & Urichuk, 2017). Currently we lack a comprehensive understanding of the relative importance of trait changes in response to both predation and infection risk for parasite-host interactions.

Finally, it is currently not known whether parasites can also be receivers of predation risk effects considering that many free-living infective stages of parasites can be consumed by predators (Thieltges et al., 2008; Johnson et al., 2010; Johnson & Thieltges, 2010). If they can perceive predation risk and react with specific trait changes, it could potentially trigger similar indirect effects as discussed above, especially if some parasites have evolved anti-predator behaviors and this interferes with their transmission success. Since many free-living infective stages of parasites can perceive chemical cues which they use for host-finding and seeking (Haas, 2003; Chaisson & Hallem, 2012), it is possible that certain chemical clues released by predators can be perceived by parasites and trigger specific anti-predator strategies. However, whether such behavioral anti-predator responses in parasites exist remains to be studied.

CONCLUSIONS

Our synthesis indicates that predation risk perceived by organisms that serve as hosts to parasites could have far-reaching indirect effects on parasite-host interactions, with implications for infectious disease dynamics and natural communities as a whole. To date, studies on predation-risk effects have mainly focused on how the threat of predation can affect predator-prey and herbivore-plant interactions – here we extend this general framework by including parasite-host interactions to widen the scope of potential non-consumptive and trait-mediated indirect effects exerted by predators on prey. We look forward to future studies that will help to integrate the full range of predation-risk effects and evaluate their relative relevance compared to direct (consumptive) predator effects.

ACKNOWLEDMENTS

We thank two anonymous reviewers for their constructive comments which have significantly helped to improve the clarity of our manuscript. PTJJ acknowledges support from the National Science Foundation (DEB-1754171), the National Institutes of Health (5R01GM135935), and the David and Lucile Packard Foundation. This work was supported by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada to JK (RGPIN-2020–04622).

Footnotes

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

REFERENCES

  1. Adamo SA, Easy R, Kovalko I, MacDonald J, McKeen A, Swanburg T et al. (2017) Predator stress-induced immunosuppression: trade-off, immune redistribution or immune reconfiguration? Journal of Experimental Biology 220: 868–875 [DOI] [PubMed] [Google Scholar]
  2. Adelman JS, Hawley DM (2017) Tolerance of infection: a role for animal behavior, potential immune mechanisms, and consequences for parasite transmission. Hormones and Behavior 88: 79–86 [DOI] [PubMed] [Google Scholar]
  3. Behringer DC, Karvonen A, Bojko J (2018) Parasite avoidance behaviours in aquatic environments. Philosophical Transactions of the Royal Society B 373: 20170202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Benard MF (2004) Predator-induced phenotypic plasticity in organisms with complex life histories. Annual Review of Ecology and Systematics 35: 651–73 [Google Scholar]
  5. Binning SA, Shaw AK, Roche DG (2017) Parasites and host performance: incorporating infection into our understanding of animal movement. Integrative and Comparative Biology 57: 267–280 [DOI] [PubMed] [Google Scholar]
  6. Blanchard P, Pays O, Fritz H (2017) Ticks or lions: trading between allogrooming and vigilance in maternal care. Animal Behaviour 129: 269–279 [Google Scholar]
  7. Buck JC (2019) Indirect effects explain the role of parasites in ecosystems. Trends in Parasitology 35: 835–847 [DOI] [PubMed] [Google Scholar]
  8. Buck JC, Weinstein SB, Young HS (2018) Ecological and evolutionary consequences of parasite avoidance. Trends in Ecology & Evolution 33: 619–632 [DOI] [PubMed] [Google Scholar]
  9. Buck JC, Ripple WJ (2017) Infectious agents trigger trophic cascades. Trends in Ecology & Evolution 32: 681–694 [DOI] [PubMed] [Google Scholar]
  10. Byers JE, Malek AJ, Quevillon LE, Altman I, Keogh CL (2015) Opposing selective pressures decouple pattern and process of parasitic infection over small spatial scale. Oikos 124: 1511–1519 [Google Scholar]
  11. Carpenter SA, Vannatta JT, Minchella DJ (2021) Host exposure history and priority effects impact the development and reproduction of a dominant parasite. International Journal for Parasitology 51: 935–943 [DOI] [PubMed] [Google Scholar]
  12. Chaisson KE, Hallem EA (2012) Chemosensory behaviors of parasites. Trends in Parasitology 28: 427–436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Combes C (2001) Parasitism: the ecology and evolution of intimate interactions. The University of Chicago Press, Chicago [Google Scholar]
  14. Cornelius A, Buschbaum C, Khosravi M, Waser AM, Wegner KM, Thieltges DW (2023) Predation risk effects on parasite transmission from first to second intermediate trematode hosts. Journal of Animal Ecology 92: 991–1000 [DOI] [PubMed] [Google Scholar]
  15. Daversa DR, Hechinger RF, Madin E, Fenton A, Dell AI, Ritchie EG, Rohr J, Rudolf VHW, Lafferty KD (2021) Broadening the ecology of fear: non-lethal effects arise from diverse responses to predation and parasitism. Proceedings of the Royal Society B 288: 20202966. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Decaestecker E, De Meester L, Ebert D (2002) In deep trouble: Habitat selection constrained by multiple enemies in zooplankton. PNAS 99: 5481–5485 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Duffy MA, Housley JM, Penczykowski RM, Caceres CW, Hall SR (2011) Unhealthy herds: indirect effects of predators enhance two drivers of disease spread. Functional Ecology 25: 945–953 [Google Scholar]
  18. Duong T, McCauley SJ (2016) Predation risk increases immune response in a larval dragonfly (Leucorrhinia intacta). Ecology 97: 1605–1610 [DOI] [PubMed] [Google Scholar]
  19. Eschweiler N & Christensen HT (2011) Trade-off between increased survival and reduced growth for blue mussels living on Pacific oyster reefs. Journal of Experimental Marine Biology and Ecology 403: 90–95 [Google Scholar]
  20. Freeman AS, Byers JE (2006). Divergent induced responses to an invasive predator in marine mussel populations. Science 313: 831–833. [DOI] [PubMed] [Google Scholar]
  21. Gibson AK, Amoroso CR (2022) Evolution and ecology of parasite avoidance. Annual Review of Ecology, Evolution, and Systematics 53: 47–67 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Goater TM, Goater CP, Esch GW (2013) Parasitism: the diversity and ecology of animal parasites. Cambridge University Press [Google Scholar]
  23. Goedknegt MA, Buschbaum C, van der Meer J, Wegner KM, Thieltges DW (2020) Introduced marine ecosystem engineer indirectly affects parasitism in native mussel hosts. Biological Invasions 11: 3223–3237 [Google Scholar]
  24. Haas W (2003) Parasitic worms: strategies of host finding, recognition and invasion. Zoology 106: 349–364 [DOI] [PubMed] [Google Scholar]
  25. Halliday FW, Penczykowski RM, Barrès B, Eck JL, Numminen E, Laine AL (2020) Facilitative priority effects drive parasite assembly under coinfection. Nature Ecology & Evolution 4:1510–1521 [DOI] [PubMed] [Google Scholar]
  26. Hart BL (1990) Behavioral adaptations to pathogens and parasites: five strategies. Neuroscience & Biobehavioral Reviews 14: 273–294 [DOI] [PubMed] [Google Scholar]
  27. Hart BL, Hart LA (2018) How mammals stay healthy in nature: the evolution of behaviours to avoid parasites and pathogens. Philosophical Transactions of the Royal Society B: Biological Sciences 373: 20170205. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hatcher MJ, Dick JTA, Dunn AM (2006) How parasites affect interactions between competitors and predators. Ecology Letters 9:1253–1271 [DOI] [PubMed] [Google Scholar]
  29. Hatcher MJ, Dick JTA, Dunn AM (2012) Diverse effects of parasites in ecosystems: linking interdependent processes. Frontier in Ecology and Environment 10: 186–194 [Google Scholar]
  30. Hatcher MJ, Dunn AM (2011) Parasites in ecological communities: from interactions to ecosystems. Cambridge, UK:Cambridge University Press [Google Scholar]
  31. Hawlena D, Schmitz OJ (2010b) Physiological stress as a fundamental mechanism linking predation to ecosystem functioning. The American Naturalist 176: 537–556 [DOI] [PubMed] [Google Scholar]
  32. Hite JL, Hughey MC, Warkentin KM, Vonesh JR (2018) Cross-ecosystem effects of terrestrial predators link treefrogs, zooplankton, and aquatic primary production. Ecosphere 9:e02377 [Google Scholar]
  33. Hite JL, Pfenning AC, Cressler CE (2020) Starving the enemy? Feeding behavior shapes host-parasite interactions. Trends in Ecology & Evolution 35: 68–80 [DOI] [PubMed] [Google Scholar]
  34. Horak P, Tummeleht L, Talvik H (2006) Predator threat, copulation effort and immunity in male rats (Rattus norvegicus). Journal of Zoology 268: 9–16 [Google Scholar]
  35. Hoverman JT, Searle CL (2016) Behavioural influences on disease risk: implications for conservation and management. Animal Behaviour 120: 263–271 [Google Scholar]
  36. Jacobsen HP, Stabell OB (1999) Predator-induced alarm responses in the common periwinkle, Littorina littorea: dependence on season, light conditions, and chemical labelling of predators. Marine Biology 134: 551–557 [Google Scholar]
  37. Johnson PTJ Dobson A, Lafferty KD, Marcogliese DJ, Memmott J, Orlofske SA, Poulin R, Thieltges DW (2010) When parasites become prey: ecological and epidemiological significance of eating parasites. Trends in Ecology and Evolution 25: 362–371 [DOI] [PubMed] [Google Scholar]
  38. Johnson PTJ, de Roode JC, Fenton A (2015) Why infectious disease research needs community ecology. Science 349:1259504. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Johnson PTJ, Thieltges DW (2010) Diversity, decoys and the dilution effect: how ecological communities affect disease risk. Journal of Experimental Biology 213: 961–970 [DOI] [PubMed] [Google Scholar]
  40. Kerby JL, Hart AJ, Storfer A (2011) Combined effects of virus, pesticide, and predator cue on the larval tiger salamander (Ambystoma tigrinum). EcoHealth 8: 46–54. [DOI] [PubMed] [Google Scholar]
  41. Kobak J, Kakareko T (2009) Attachment strength, aggregation and movement of the zebra mussel (Dreissena polymorpha, Bivalvia) in the presence of potential predators. Fundamental and Applied Limnology/Archiv für Hydrobiologie 174: 193–204 [Google Scholar]
  42. Koprivnikar J, Urichuk TMY (2017. ) Time-lagged effect of predators on tadpole behaviour and parasite infection. Biology Letters 13: 20170440. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Koprivnikar J, Rochette A, Forbes MR (2021) Risk-induced trait responses and non-consumptive effects in plants and animals in response to their invertebrate herbivore and parasite natural enemies. Frontiers in Ecology and Evolution 9:667030 [Google Scholar]
  44. Koprivnikar J, Thieltges DW, Johnson PTJ (2023) Consumption of trematode parasite infectious stages: from conceptual synthesis to future research agenda. Journal of Helminthology 97: 1–19 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Kulakovskii EE, Lezin PA (2002) Filtration activity of the blue mussel, Mytilus edulis, under influence of the starfish, Asterias rubens (Forcipulata, Asteriidae). Zoologicheskiy Zhurnal 81: 292–297 [Google Scholar]
  46. Lima SL (1998) Nonlethal effects in the ecology of predator-prey interactions: what are the ecological effects of anti-predator decision-making? BioScience 48: 25–34 [Google Scholar]
  47. Lopez LK, Duffy MA (2021) Mechanisms by which predators mediate host–parasite interactions in aquatic systems. Trends in Parasitology 37: 890–906 [DOI] [PubMed] [Google Scholar]
  48. MacDougall-Shackleton SA, Bonier F, Romero LM, Moore IT (2019) Glucocorticoids and “stress” are not synonymous. Integrative Organismal Biology, 1: obz017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Mouritsen KN, Poulin R (2005) Parasites boost biodiversity and change animal community structure by trait-mediated indirect effects. Oikos 108: 344–350 [Google Scholar]
  50. Murray RL, Tah S, Koprivnikar J, Rowe L, McCauley SJ (2020) Exposure to potentially cannibalistic conspecifics induces an increased immune response. Ecological Entomology 45: 355–363 [Google Scholar]
  51. Naddafi R, Pettersson K, Eklöv P (2007) The effect of seasonal variation in selective feeding by zebra mussels (Dreissena polymorpha) on phytoplankton community composition. Freshwater Biology 52: 823–842 [Google Scholar]
  52. Navarro C, de Lope F, Marzal A, Møller AP (2004) Predation risk, host immune response, and parasitism. Behavioral Ecology 15: 629–635 [Google Scholar]
  53. Ong’wen F, Ogola Onyango P, Bukhari T (2020) Direct and indirect effects of predation and parasitism on the Anopheles gambiae mosquito. Parasites & Vectors 13: 43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Packer C, Holt RD, Hudson PJ, Lafferty KD, Dobson AP (2003) Keeping the herds healthy and alert: implications of predator control for infectious disease. Ecology Letters 6: 797–802 [Google Scholar]
  55. Pascal L, Grémare A, de Montaudouin X, Deflandre B, Romero-Ramirez A, Maire O (2020) Parasitism in ecosystem engineer species: a key factor controlling marine ecosystem functioning. Journal of Animal Ecology 89: 2192–2205 [DOI] [PubMed] [Google Scholar]
  56. Peacor SD, Barton BT, Kimbor DL, Sih A (2020) A framework and standardized terminology to facilitate the study of predation-risk effects. Ecology 101: e03152. [DOI] [PubMed] [Google Scholar]
  57. Poulin R, Thomas F, de Meeûs T, Guégan J-F, Renaud F (1999) Parasites and ecosystem engineering: what roles could they play? Oikos 84: 167–171 [Google Scholar]
  58. Preston DL, Mischler JA, Townsend AR, Johnson PTJ (2016) Disease ecology meet ecosystem science. Ecosystems 19: 737–748 [Google Scholar]
  59. Råberg L, Graham AL, Read AF (2009) Decomposing health: tolerance and resistance to parasites in animals. Philosophical Transactions of the Royal Society B 364: 37–49 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Ripple WJ, Beschta RL (2004) Wolves and the ecology of fear: can predation risk structure ecosystems? BioScience 54:755–766 [Google Scholar]
  61. Romero LM (2004). Physiological stress in ecology: Lessons from biomedical research. Trends in Ecology and Evolution 19: 249–255 [DOI] [PubMed] [Google Scholar]
  62. Sapolsky RM, Romero LM, Munck AU (2000) How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocrine Reviews 21: 55–89 [DOI] [PubMed] [Google Scholar]
  63. Shaw KE, Civitello DJ (2021) Re-emphasizing mechanism in the community ecology of disease. Functional Ecology 35: 2376–2386 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Sheldon BC, Verhulst S (1996). Ecological immunology: costly parasite defenses and trade-offs in evolutionary ecology. Trends in Ecology and Evolution 11: 317–321 [DOI] [PubMed] [Google Scholar]
  65. Sheriff MJ, Peacor SD, Hawlena D, Thaker M (2020) Non-consumptive predator effects on prey population size: a dearth of evidence. Journal of Animal Ecology 89: 1302–1316 [DOI] [PubMed] [Google Scholar]
  66. Sheriff ML, Thaler JS (2014) Ecophysiological effects of predation risk; an integration across disciplines. Oecologia 176: 607–611 [DOI] [PubMed] [Google Scholar]
  67. Smee DL, Weissburg MJ (2006). Hard clams (Mercenaria mercenaria) evaluate pre-dation risk using chemical signals from predators and injured conspecifics. Journal of Chemical Ecology 32: 605–619 [DOI] [PubMed] [Google Scholar]
  68. Stephenson JF, van Oosterhout C, Mohammed RS, Cable J (2015) Parasites of Trinidadian guppies: evidence for sex- and age-specific trait-mediated indirect effects of predators. Ecology 96: 489–498 [DOI] [PubMed] [Google Scholar]
  69. Thieltges DW, Jensen KT, Poulin R (2008) The role of biotic factors in the transmission of free-living endohelminth stages. Parasitology 135: 407–426 [DOI] [PubMed] [Google Scholar]
  70. Thieltges DW, Poulin R (2008) Parasites and pathogens: avoidance. In: Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester [Google Scholar]
  71. Thiemann GW, Wassersug RJ (2000). Patterns and consequences of behavioural re-sponses to predators and parasites in Rana tadpoles. Biological Journal of the Linnean Society 71: 513–528 [Google Scholar]
  72. Walsman JC, Janecka MJ, Clark DR, Kramp RD, Rovenolt F, Patrick R, Mohammed RS, Konczal M, Cressler CE, Stephenson JF (2022) Shoaling guppies evade predation but have deadlier parasites. Nature Ecology & Evolution 6: 945–954 [DOI] [PubMed] [Google Scholar]
  73. Weinstein SB, Buck JC, Young HS (2018) A landscape of disgust. Science 359: 1213–1214 [DOI] [PubMed] [Google Scholar]
  74. Werner EE, Peacor SD (2003) A review of trait-mediated indirect interactions in ecological communities. Ecology 84: 1083–1100 [Google Scholar]
  75. Wirsing AJ, Ripple WJ (2011) A comparison of shark and wolf research reveals similar behavioral responses by prey. Frontiers in Ecology and the Environment 9: 335–341 [Google Scholar]

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