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Predation and Parasitism
Predation and Parasitism THQ Powell and KM Prior, University of Florida, Gainesville, FL, USA r 2016 Elsevier Inc. All rights reserved.
Introduction Predator–prey and parasite–host interactions are nearly ubiquitous in ecological communities. These two interaction types comprise a subset of the broader victim–exploiter interaction in which one consumer species benefits at the cost of its partner through a direct trophic (consumptive) interaction. Predation and parasitism differ from one another in the lethality of the interaction for the victim species and the number of individuals involved on either side of the interaction. In a predatory interaction, the consumer species kills individuals of the prey species. Typically, this involves an individual predator consuming multiple prey individuals over the course of its life cycle. In a parasitic interaction, the parasite’s consumption of the host is not necessarily lethal and often involves a reversal of the relative number of individuals participating on either side of the interaction: many parasites consuming a single host. A single individual parasite may interact with a single host individual, while hosts are likely to interact with many individual parasites. A third class of consumers, parasitoids, shares a mix of traits between predators and parasites. Parasitoids function like parasites in that they usually interact with a single victim over the course of their lives. But like predators, the parasitoid’s victim dies as a result of the interaction. Parasitoid–host systems can often be extremely specialized. Here, we will treat parasitoid–host interactions as a particularly intimate form of predator–prey interactions. Some of the traits involved in these systems, such as manipulation of host gene expression by parasitoids and the host’s immune response are certainly more reminiscent of a gut parasite’s interaction with its host than a lion killing an impala. However, the lethality that defines parasitoid life histories is an important distinction (Figure 1). The outcomes of either predation or parasitism can have crucial fitness consequences for both interacting species. Natural selection is expected to act on variation in the ability of predators and parasites to efficiently consume their victims as well as on variation in the ability of victim species to either avoid or fend off aggressors. The intrinsic differences between predation and parasitism lead to different predictions regarding coevolutionary dynamics in these systems. However, the central premise is similar for both types of interactions. A simple Lotka–Volterra model of predator–prey dynamics is useful for illustrating the general premise of predator–prey coevolution (Abrams, 2001). This model predicts rates of change in a prey population of size V and a predator population of size P over a period of time t, and may be written as: dV ¼ Vðr cPÞ dt dP ¼ PðbcV dÞ dt
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where r is the intrinsic growth rate of the prey population, d is the mortality rate of the predator population, c is the capture rate for the average predator, and b is the conversion rate of captured victims into predator offspring. Although this is a somewhat simplistic model, more complex extrapolations that incorporate density-dependence, more realistic functional responses, and discrete generation time still incorporate the basic components of the Lotka–Volterra framework involved in coevolution. The value of c (capture rate) is determined by traits in both predator and prey populations, and highlights how trait evolution in one species can have an immediate effect on the fitness landscape of the other species. Given intraspecific genetic variation, prey species are expected to evolve trait values which decrease the magnitude of c, while natural selection should favor predator traits that increase c (Abrams, 2001). The strength of this antagonistic coevolution around c Predator / prey
(a)
Parasitoid / host
(b)
Parasite / host
(c)
Figure 1 Diagram of basic demographic and lethality relationships for three types of exploiter/victim ecological relationships: (a) a single predator killing and consuming multiple prey individuals over its lifetime, (b) a single parasitoid killing and consuming a single host individual over its lifetime, and (c) many parasite individuals consuming (but not killing) a single host individual.
Encyclopedia of Evolutionary Biology, Volume 3
doi:10.1016/B978-0-12-800049-6.00188-8
Predation and Parasitism
is necessarily limited by the tradeoffs evolving traits may impose on other components of fitness. For instance, a defensive trait that may reduce c for a prey species may be energetically costly, decreasing r (fecundity). Similarly, in parasite–host systems natural selection should act on traits of both species affecting the rate of transmission of parasites between hosts, the parasite’s ability to draw resources from the host, and the host’s resistance to the parasite. Footprints of coevolutionary dynamics in predator–prey and parasite–host systems may be seen in two different patterns in nature: coevolutionary arms races and codiversification. A third pattern restricted to parasite–host coevolution is the mitigation of virulence. Each of these is discussed in the following sections.
Coevolutionary Arms Races Alongside tightly specialized mutualisms, evolutionary arms races are probably the phenomena most commonly associated with the term coevolution. The concept of two species locked in a never-ending struggle to gain the evolutionary upper hand is a powerful one, and it fits well with the widely held notion of nature as ‘red in tooth and claw.’ This scenario, in which an evolutionary advantage gained in one species is met with a compensatory change in the other, is both straightforward and plausible. This sort of constant coevolutionary struggle has even been implicated as a major reason behind the advantage of sex. However, empirical evidence for arms races can be difficult to find in nature, given that our view of current ecological communities is often limited to only their present state, revealing only a single time point in a dynamic process. The best evidence for on-going arms races comes from predator– prey or parasite–host populations whose traits differ in a correlated manner over geographic space (Thompson, 2005). The geographic mosaic theory of coevolution predicts variation in the strength and specifics of the coevolutionary process among different local populations of interacting species. Thus, predator or parasite populations that are well matched to the traits of their local victim populations, and vice versa, provide strong evidence for on-going coevolutionary arms races. Perhaps the best studied example of this is the classic case of rough-skinned newts and garter snakes in the western United States (Brodie, 2011). In the 1960s, otherwise harmless rough-skinned newts (Taricha granulosa) in Pacific Northwest were found to be highly toxic. The newts produce a compound called tetrodotoxin, which binds to and blocks sodium channels in neurons. The level of toxicity produced by these animals was surprising; with individual newts weighing only a few grams producing doses capable of killing 25 000 mice. Moreover, at the time there were few known predators of these newts, and in particular no large vertebrate predators that would require such a formidable defense. Further ecological surveys of the newts identified a reason for the toxicity: high levels of predation by the common garter snake (Thamnophis sirtalis), which is resistant to the newt’s toxins. Decades of work in this system, led by Edmund Brodie Jr. and Edmund Brodie III, has succeeded in painting a clear picture of the coevolutionary arms race between newts and garter snakes.
TTX (mg)
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TTX (mg)
>2 1–2 0.5 – 1.0 0.3 – 0.5 0.1 – 0.3 0.01 – 0.1 < 0.01
>5 2–3 0.7 – 1.5 0.4 – 0.7 0.2 – 0.4 0.13 – 0.2 < 0.13
Newt toxicity
Garter snake TTX resistance
Figure 2 Depiction of the geographic mosaic in the newt/garter snake coevolutionary arms race. The map on the left shows how newt toxicity (amount of TTX produced) varies over space. The map on the right shows the geographic variation in snake resistance (dose of TTX needed to hinder snake performance). The broad correspondence of geographic variation in the traits of these two species are highlighted with the red (high toxicity and resistance) and blue-green (low toxicity and resistance) arrows. Adapted from Hanifin, C.T., Brodie Jr., E.D., Brodie III, E.D., 2008. Phenotypic mismatches reveal escape from arms-race coevolution. PLoS Biology 6, 0471–0482. Originally published under the Creative Commons Attribution license.
Considerable variation exists in both newt toxicity and snake resistance in different geographic locations. Congruent with the geographic mosaic model of coevolution, there is also strong geographic correlation in trait values of newt and snake populations, with more toxic newts generally found within areas with more resistant snakes (Figure 2; Brodie et al., 2002; Hanifin et al., 2008). The molecular basis for both newt toxin production and snake resistance is also now well understood. Newts increase production of tetrodotoxin, while resistant garter snakes possess mutations which change the conformation of sodium channel proteins, which decreases the binding affinity between the toxin and the channels (Geffeney et al., 2002). Experiments have also demonstrated a clear fitness tradeoff in resistance for the snakes. The sodium channel mutations that reduce the toxicity of tetrodotoxin on the snakes also have a negative effect on snake locomotor capacity. Resistant snakes are slower and clumsier than nonresistant snakes (Brodie and Brodie, 1999). This helps explain why the highly resistant alleles have not spread through all the snake populations; the locomotor costs are not worth the benefit when the local newts are less poisonous. This classic garter snake/newt system represents an elegant case study highlighting the potential power of coevolutionary arms races in predator–prey systems in driving trait evolution. In addition to directional escalation of trait values, frequency dependent selection dynamics during coevolutionary arms races may lead to long-term maintenance of genetic diversity in populations. Selection should favor parasite phenotypes that are best suited to attacking the most common phenotype in the host population. As those parasite phenotypes
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increase in number, the fitness of the most common host phenotype will decline, and fitness increases for previously rare host phenotypes that can avoid or fend off the nowcommon parasite phenotypes. The outcome of these dynamics may be to favor host populations that are heterogeneous with respect to defensive traits. In our own immune systems, the tremendous diversity of our MHC genes may partly be explained by our coevolutionary history with parasites.
Codiversification Another potential outcome of coevolution in predator or parasite systems is codiversification. Instead of the back-andforth struggle of trait evolution in an arms race, reciprocal selection pressures imposed by predators or parasites and their prey or hosts may lead to reciprocal diversification in both trophic levels. One method of reducing predation or parasitism pressure may be for a prey or host species to escape from their enemies by adopting new habitats. Divergent adaptation to novel habitats or niches is the basic premise underlying ecological speciation. The relatively enemy-free habitat of the derived population may not last long, however, as new enemies may move in to take advantage of the flourishing new resource. These new enemies may be derived from the previous enemy population, now undergoing divergent adaptation in lock-step with its old coevolutionary partner or an entirely new set of enemies may move in. Just as selection may favor shifts of prey species into new habitats, selection may favor predators and parasites that can find new victims. If a prey species gains a strong upper hand in defense, there may not be sufficient genetic variation in the predator population for an adequate coevolutionary counter move. The resulting fitness landscape may favor predator populations improving their capture rate (parameter c in the model above) by exploiting different, more susceptible prey species. In systems involving a high degree of specialization, like parasitoid insects, these shifts may also trigger ecological speciation events. Lock-step codiversification is expected to produce matching phylogenies in the species of both trophic levels. However, more complex patterns of host shifting may result in discordant phylogenetic patterns that are nonetheless driven by coevolution. For example, even if a novel enemy species came from outside the ancestral system, evolutionary changes in one species are still having a direct effect on the fitness landscape of the other. One prime example of codiversification in action is the case of the apple maggot fly, Rhagoletis pomonella, and the specialist parasitoid wasps that attack it. The apple maggot fly was originally a specialist attacking the fruit of hawthorn trees (Crataegus sp.) throughout much of North America. Domestic apples were introduced to North America from Eurasia in the seventeenth century. About 150 years after this introduction, a population of these flies shifted and began attacking apples instead of hawthorn fruit (Bush, 1969). Genetic and phenotypic evidence has confirmed that these two populations are now strongly reproductively isolated and are on the path to becoming separate species. The apple and hawthorn flies differ in their chemosensory response to host fruit volatiles and in their life history timing (coinciding with differences in the
timing of fruit ripening of their respective hosts). Four parasitoid wasp species specialize in attacking the apple maggot fly, and predation by these wasps may have been a key factor in the selective advantage of the shift to apples. Parasitoid rates in the hawthorn race can be quite high (sometimes in excess of 50%). Apples are considerably larger than hawthorns, with much more room for fly larvae to hide from the ovipositors of wasps on the fruit surface. This enemy-free space is thought to be a major reason behind the shift to apples (Feder, 1995). However, the apple-infesting populations of R. pomonella are not entirely free of parasitoid enemies. The incipient speciation of the apple flies has led to incipient speciation in the wasps as well. The most prevalent of the four parasitoids, Diachasma alloeum, shows strikingly similar patterns of ecological divergence and reproductive isolation (Forbes et al., 2009). These wasps lay eggs into late instar fly larvae tunneling through the fruit. The wasps infesting different races of flies have differentiated in the same key ecological traits that separate the flies: response to fruit olfactory cues, the first crucial step in finding their larval quarry and life history timing specifically in synch with the life cycle of apple flies. Interestingly, genetic evidence suggests that this is not a simple case of lockstep codiversification. Rather, the proximate ancestor of the apple fly-infesting wasps appears to be D. alloeum populations specialized to attacking the blueberry maggot fly, Rhagoletis mendax. Thus, the coevolutionary consequences of divergent adaptation in one species are not restricted to the original interaction partner but can ripple further out into the ecological community.
Parasite Transmission and the Attenuation of Virulence In many parasite–host systems, effective transmission of parasite offspring to new hosts is a critical component of parasite success. It is likely that tradeoffs between efficient use of host resources (conferring greater fitness costs to the host) and transmission among hosts are common. Parasite transmission may require close contact between host individuals. Parasites that grow and reproduce quickly by efficiently pillaging the host’s body may render their hosts too ill to pass their progeny on to new hosts. An aggressive parasite could make a host too weak to move widely and interact with conspecifics, or could kill the host before any opportunity for transmission. One solution to this dilemma is for parasites to alter their host’s phenotypes specifically to maximize transmission. This has important consequences for human disease. Many of the symptoms induced by parasites directly impact the success of parasite transmission. It is likely no coincidence that the main symptoms of infections by waterborne parasites such as Vibrio cholera (the pathogen responsible for cholera) or Giardia lamblia involve severe digestive distress, a surefire way to quickly reinfest water used by hosts. Similarly, the violent behavioral symptoms of rabies infections maximize the transmission of the rabies virus through saliva. Instead of entirely hijacking host phenotypes, some parasites may increase transmission success by minimizing the costs imposed on their hosts. Healthier hosts may live longer,
Predation and Parasitism
move further, and interact with more conspecifics, ultimately leading to greater transmission and dispersal for the parasite. Thus, in situations where transmission is limiting, natural selection may favor reduced virulence in the parasite populations. A famous example of this phenomenon occurred during an attempt at biocontrol of invasive rabbits in Australia (Fenner, 1983). European rabbits (Oryctolagus cuniculus) were introduced to Australia during the mid-nineteenth century. The combination of their rapid reproduction rate and a relatively depauperate predator community in Australia led to an explosion of the rabbit population, causing widespread environmental and economic damage. A solution to the rabbit invasion appeared when an extremely virulent Myxoma virus was discovered in a population of captive rabbits in South America. The virus was intentionally introduced to the Australian rabbit population in 1950. The plan appeared to be a great success in the first couple of years. The virus was nearly always lethal, and the rabbit population declined by more than 75%. However, as the density of the rabbit population plummeted, transmission became an important selective force for the virus. Aggressively virulent strains of the virus caused rabbits (and the viruses they harbored) to die before they were likely to come into contact with other rabbits, while less virulent strains were more likely to be transmitted and survive. By 1952, less virulent strains of the virus began to proliferate and the rabbit population rebounded. The coevolutionary combination of attenuated virulence by the virus and genetic resistance to infection by the rabbits has led to the long-term persistence of Myxoma-infected rabbit populations in Australia. The above example illustrated how parasitic interactions may evolve to become less costly to host species. The difference between parasitism, commensalism, and mutualism is determined by the net result of the costs and benefits to the symbiont partners. Thus, a sufficient decrease in virulence could tip the entire balance of the interaction into a commensal or even mutualistic relationship. Such shifts in the net result of species interactions may occur in both directions. In a mutualism, if one species starts to cheat by failing to provide a benefit to its partner, the interaction may immediately become parasitic in nature. Similarly, if selection on transmission success by parasites leads to minimizing fitness costs for hosts, it is not difficult to imagine a scenario where the net fitness costs to the host are minimized by the parasite providing some offsetting benefit, which could tip the balance into mutualist territory. A striking example of this phenomenon occurred serendipitously in the laboratory of Dr. Kwang Jeon of the University of Tennessee (Figure 3; Jeon, 1972). Jeon was conducting cyto-nuclear transplant experiments with lab lines of the amoeba Amoeba discoides. In 1966, some of the amoeba cultures became infected with very high numbers of an intracellular bacterial parasite. The bacteria appeared to be highly virulent; most newly infected cells died. Those that survived showed markedly slower generation time, smaller size, and greater susceptibility to starvation and mechanical stress. Because of the amount of work that had gone into this project, the amoeba lines were kept alive and nursed along for 5 years. During that time, the infection persisted, but the negative effects completely disappeared. But this was not a straightforward case of attenuation of virulence. In that 5-year span,
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Jeon’s amoebae not only became resistant to the effects of the bacteria but they also became dependent on them. Nuclei from the now resistant infected lines performed very poorly when transferred to cells from uninfected lines. These infectedinto-uninfected transfers resulted in a greater than 10-fold reduction in survivorship compared to transfers within infected or uninfected cells. Similarly, the bacteria could not be cultured outside of the amoebae, indicating that like many endoparasites, they were obligatorily dependent on their hosts. Thus, in only 5 years (B1000 amoeba generations) a clearly parasitic interaction evolved toward a nearly obligatory mutualism.
Coevolution and Ecological Dynamics Coevolutionary responses have important implications for community dynamics in predator–prey and parasite–host systems. Population dynamics and evolutionary change act at the same time scale: generational time. It was once common for biologists to make a clear distinction between biological processes operating in ‘ecological time’ or ‘evolutionary time.’ However, this old dichotomy is neither correct nor useful. Both population demographics and evolutionary change constantly inform and affect one another. The fitness effects of particular alleles depend on the specific ecological and demographic contexts of the population. Likewise, shifts in allele frequencies between generations can alter the outcome of ecological interactions. In the simple Lotka–Volterra model presented above, selective deaths of both predator and prey species may instantaneously change the trait values that control the capture rate parameter (c). Explicity considering this additional dimension of change in models of species interactions demonstrates that on-going coevolution may strongly affect the overall dynamics of predator–prey systems (Abrams, 2001). Interestingly, coevolutionary responses have the potential to stabilize otherwise unstable systems or destabilize otherwise stable systems (Abrams, 2001). One of the important determinants of this appears to be whether the traits involved in prey defense are limited in the potential directionality of their evolutionary response (Abrams and Matsuda, 1997; Gavrilets, 1997). That is, are prey traits likely to evolve in a single direction or can advantageous mismatches be achieved by moving bidirectionally along the trait axis? Unidirectional defensive trait evolution tends to make systems more stable, while bidirectional defensive trait evolution tends to induce cycles in previously stable systems or increase the amplitude of existing cycles. Coevolution may alter population dynamics, but population dynamics may also influence the outcome of coevolution. Whether arms races continue to escalate may be determined by the particular mathematical relationship between predator and prey populations. For instance, the functional response of predators to greater prey population densities is a key consideration (Abrams, 1986). Stronger prey defense may result in a lower capture rate (c) for predators, but the resulting higher prey densities may compensate for this change. This suggests that selection imposed by prey defensive traits on predator traits may generally be weaker than the
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1. Lines of Amoeba discoides strain ‘D’ used in cyto/nuclear transplant experiments 2. Amoebae become infected by bacterium, 60 000−150 000 per cell, causing slower growth rates, decreased stress tolerance, and death 3. Surviving infected lines nursed along in the lab while uninfected strain ‘D’ lines are brought back into the lab from the original source 4. Amoebae lines grown in the lab for 5 years (~1000 generations) during which time, survivorship, growth rate, and stress tolerance of infected lines return to normal, despite presistant infection 5. Microsurgical experiments performed, transplanting nuclei from infected lines into uninfected cytoplasm as well as transplants among infected and uninfected lines
6. Extremely low viability for infected strain nuclei placed in uninfected cytoplasm
92.3%
6.9%
81.6%
Figure 3 Schematic of coevolutionary shift from parasitism to mutualism between Amoeba discoides and a bacterial endosymbiont in the lab of Dr. Kwang Jeon at the University of Tennessee in the late 1960s. Diagram based on description of events, methods, and results by Jeon, K., 1972. Development of cellular dependence on infective organisms: Micurgical studies in amoebas. Science 176, 1122–1123.
reverse, with stronger predator attack traits resulting in both higher per capita capture rates and higher predator densities. This reciprocal feedback between coevolution and community demographic dynamics in predation and parasitism systems calls attention to the continued need for greater integration between evolutionary biology and ecology.
Macroevolutionary Patterns The examples above demonstrate the various ways that coevolution affects predator–prey and parasite–host systems. While they may be difficult to study empirically, the fingerprints of coevolution are ubiquitous in ecological communities. But what effect has coevolution between predators and prey and parasites and hosts had on broad scale patterns of biodiversity over geological time? Do we see a clear signature of persistent arms races or codiversification in the fossil record? The answer may be that coevolution does indeed drive macroevolutionary patterns, but perhaps in a diffuse and
limited fashion. It is nearly impossible to study pairwise specialist interactions in the fossil record; organisms rarely leave behind precise records of who they ate and who ate them. However, paleontologists have been able to take the approach of studying patterns within ecological guilds that were likely to be broadly interacting. Paleontologist Robert Bakker analyzed coevolutionary trends in morphology between cursorial (chasing) mammalian predators and their primary prey, ungulates, across the entire history of their shared existence from the beginning of the Cenozoic period until the present day (Bakker, 1983). This is a case where the primary trait affecting the parameter c is basically the same for both predator and prey: speed. With few exceptions, ungulate species rely on speed during the early stages of a chase to escape predators, and it is this fleetness of foot of both predator and prey that determines the outcome of most hunts. The basic expectation of coevolution between these guilds would be increased running speed through time. Directional change in skeletal morphology for both ungulates and predators indicates that both groups have become
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Cursorial predators
Mean metatarsal/femur index Faster
10 20
Spotted hyena Crocuta crocuta
30
Impala Aepyceros melampus
40 50 60
Prey: Ungulates Predators: Mesonychids Creodonts Carnivorans
(a)
Eocene
Millions of years ago
Ungulates
Modern
Slower
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Mesonyx unitensis
Phenacodus primaevus
(b)
Figure 4 (a) Plot of inferred running speed (based on limb ratios) over time for ungulates (red circles), and three lineages of cursorial mammalian carnivores, mesonychids (blue squares), creodonts (green squares), and carnivorans (pink squares). These data highlight the continuous directional evolution of running speed in hoofed mammals, but not their predators, at the macroevolutionary scale. Based on data presented in Bakker, R.T., 1983. The deer flees, the wolf pursues: Incongruencies in predator–prey coevolution. In: Futuyma, D.J., Slatkin, M. (Eds.), Coevolution. Sunderland, MA: Sinauer. (b) Example cursorial predators (left) and ungulates (right) from two time along the graph, the Holocene (modern times) (top) and the late Eocene (B50 million years ago). These examples highlight the greater change in limb morphology for hoofed herbivores vs. running predators over the past 50 million years.
increasingly swifter. Several traits associated with greater speed including less acute limb angles, more constrained movement in ball joints, the reduction of side digits, and shorter phalanges show clear progressions in both groups. However, the pace of speed-related skeletal adaptation in ungulates far outpaces that of predators. Ungulates have consistently been getting faster, while cursorial predators have been unable to keep up (pun intended) (Figure 4). Bakker argues that basic trophic structure may be responsible for the widening gap in this arms race. The necessarily greater population size of the prey species makes them less prone to extinction and more likely to stumble upon evolutionary innovations for speed. Alternatively, this could be a case of stronger tradeoffs for the predator species; many carnivores use their hands and claws for digging, fighting, or manipulating prey, and such diverse functional requirements may prevent carnivores from evolving super-specialized running tools. In either case, the fossil record suggests that predator–prey coevolution can indeed drive important long-term evolutionary trends but that there are likely considerable limits to perpetual escalation in arms races.
See also: Commensalism, Amensalism, and Synnecrosis. Ecological Speciation and Its Consequences Geographic Mosaic of Coevolution. Intraspecific Coevolutionary Arms Races. Secondary Metabolites, the Role in Plant Diversification of
References Abrams, P.A., 1986. Adaptive responses of predators to prey and prey to predators: The failure of the arms race analogy. Evolution 4, 1229–1247.
Abrams, P.A., 2001. The evolution of predator−prey interactions: Theory and evidence. Annual Review of Ecology and Systematics 31, 79–105. Abrams, P.A., Matsuda, H., 1997. Fitness minimization and dynamic instability as a consequence of predator−prey coevolution. Evolutionary Ecology 11, 1–20. Bakker, R.T., 1983. The deer flees, the wolf pursues: Incongruencies in predator− prey coevolution. In: Futuyma, D.J., Slatkin, M. (Eds.), Coevolution. Sunderland, MA: Sinauer. Brodie III, E.D., 2011. Patterns, process, and the parable of the coffeepot incident: Arms races between newts and snakes from landscapes to molecules. In: Losos, J.B. (Ed.), In the Light of Evolution: Essays from the Laboratory and Field. Greenwood Village, CO: Roberts & Co, pp. 93–120. Brodie III, E.D., Brodie Jr., E.D., 1999. The cost of exploiting poisonous prey: Tradeoffs in a predator−prey arms race. Evolution 53, 626–631. Brodie Jr., E.D., Ridenhour, B.J., Brodie III, E.D., 2002. The evolutionary response of predators to dangerous prey: Hotspots and coldspots in the geographic mosaic of coevolution between garter snakes and newts. Evolution 56, 2067–2082. Bush, G.L., 1969. Sympatric host race formation and speciation in frugivorous flies of the genus Rhagoletis (Diptera: Tephritidae). Evolution 23, 237–251. Feder, J.L., 1995. The effects of parasitoids on sympatric host races of Rhagoletis pomonella (Diptera: Tephritidae). Ecology 76, 801–813. Fenner, F., 1983. The Florey lecture 1983: Biological control, as exemplified by smallpox eradication and myxomatosis. Proceedings of the Royal Society of London Series B: Biological Sciences 218, 259–285. Forbes, A.A., Powell, T.H.Q., Stelinski, L.L., Smith, J.J., Feder, J.L., 2009. Sequential sympatric speciation across trophic levels. Science 323, 776–779. Gavrilets, S., 1997. Coevolutionary chase in exploiter−victim systems with polygenic characters. Journal of Theoretical Biology 186, 527–534. Geffeney, S., Brodie Jr., E.D., Ruben, P.C., Brodie III, E.D., 2002. Mechanisms of adaptation in a predator−prety arms race: TTX-resistant sodium channels. Science 297, 1336–1339. Hanifin, C.T., Brodie Jr., E.D., Brodie III, E.D., 2008. Phenotypic mismatches reveal escape from arms-race coevolution. PLoS Biology 6, 0471–0482. Jeon, K., 1972. Development of cellular dependence on infective organisms: Micurgical studies in amoebas. Science 176, 1122–1123. Thompson, J.N., 2005. The Geographic Mosaic of Evolution. Chicago, IL: University of Chicago Press.
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Further Reading Abrams, P.A., 1986. Adaptive responses of predators to prey and prey to predators: The failure of the arms race analogy. Evolution 4, 1229–1247. Brodie III, E.D., 2011. Patterns, process, and the parable of the coffeepot incident: Arms races between newts and snakes from landscapes to molecules. In: Losos, J.B. (Ed.), In the Light of Evolution: Essays from the Laboratory and Field. Greenwood Village, CO: Roberts & Co, pp. 93–120.
Futuyma, D.J., Slatkin, M., 1983. Coevolution. Sunderland, MA: Sinauer Associates. Jeon, K., 1972. Development of cellular dependence on infective organisms: Micrurgical studies in amoebas. Science 176, 1122–1123. Thompson, J.N., 2005. The Geographic Mosaic of Evolution. Chicago, IL: University of Chicago Press.
Introduction Predator–prey and parasite–host interactions are nearly ubiquitous in ecological communities. These two interaction types comprise a subset of the broader victim–exploiter interaction in which one consumer species benefits at the cost of its partner through a direct trophic (consumptive) interaction. Predation and parasitism differ from one another in the lethality of the interaction for the victim species and the number of individuals involved on either side of the interaction. In a predatory interaction, the consumer species kills individuals of the prey species. Typically, this involves an individual predator consuming multiple prey individuals over the course of its life cycle. In a parasitic interaction, the parasite’s consumption of the host is not necessarily lethal and often involves a reversal of the relative number of individuals participating on either side of the interaction: many parasites consuming a single host. A single individual parasite may interact with a single host individual, while hosts are likely to interact with many individual parasites. A third class of consumers, parasitoids, shares a mix of traits between predators and parasites. Parasitoids function like parasites in that they usually interact with a single victim over the course of their lives. But like predators, the parasitoid’s victim dies as a result of the interaction. Parasitoid–host systems can often be extremely specialized. Here, we will treat parasitoid–host interactions as a particularly intimate form of predator–prey interactions. Some of the traits involved in these systems, such as manipulation of host gene expression by parasitoids and the host’s immune response are certainly more reminiscent of a gut parasite’s interaction with its host than a lion killing an impala. However, the lethality that defines parasitoid life histories is an important distinction (Figure 1). The outcomes of either predation or parasitism can have crucial fitness consequences for both interacting species. Natural selection is expected to act on variation in the ability of predators and parasites to efficiently consume their victims as well as on variation in the ability of victim species to either avoid or fend off aggressors. The intrinsic differences between predation and parasitism lead to different predictions regarding coevolutionary dynamics in these systems. However, the central premise is similar for both types of interactions. A simple Lotka–Volterra model of predator–prey dynamics is useful for illustrating the general premise of predator–prey coevolution (Abrams, 2001). This model predicts rates of change in a prey population of size V and a predator population of size P over a period of time t, and may be written as: dV ¼ Vðr cPÞ dt dP ¼ PðbcV dÞ dt
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where r is the intrinsic growth rate of the prey population, d is the mortality rate of the predator population, c is the capture rate for the average predator, and b is the conversion rate of captured victims into predator offspring. Although this is a somewhat simplistic model, more complex extrapolations that incorporate density-dependence, more realistic functional responses, and discrete generation time still incorporate the basic components of the Lotka–Volterra framework involved in coevolution. The value of c (capture rate) is determined by traits in both predator and prey populations, and highlights how trait evolution in one species can have an immediate effect on the fitness landscape of the other species. Given intraspecific genetic variation, prey species are expected to evolve trait values which decrease the magnitude of c, while natural selection should favor predator traits that increase c (Abrams, 2001). The strength of this antagonistic coevolution around c Predator / prey
(a)
Parasitoid / host
(b)
Parasite / host
(c)
Figure 1 Diagram of basic demographic and lethality relationships for three types of exploiter/victim ecological relationships: (a) a single predator killing and consuming multiple prey individuals over its lifetime, (b) a single parasitoid killing and consuming a single host individual over its lifetime, and (c) many parasite individuals consuming (but not killing) a single host individual.
Encyclopedia of Evolutionary Biology, Volume 3
doi:10.1016/B978-0-12-800049-6.00188-8
Predation and Parasitism
is necessarily limited by the tradeoffs evolving traits may impose on other components of fitness. For instance, a defensive trait that may reduce c for a prey species may be energetically costly, decreasing r (fecundity). Similarly, in parasite–host systems natural selection should act on traits of both species affecting the rate of transmission of parasites between hosts, the parasite’s ability to draw resources from the host, and the host’s resistance to the parasite. Footprints of coevolutionary dynamics in predator–prey and parasite–host systems may be seen in two different patterns in nature: coevolutionary arms races and codiversification. A third pattern restricted to parasite–host coevolution is the mitigation of virulence. Each of these is discussed in the following sections.
Coevolutionary Arms Races Alongside tightly specialized mutualisms, evolutionary arms races are probably the phenomena most commonly associated with the term coevolution. The concept of two species locked in a never-ending struggle to gain the evolutionary upper hand is a powerful one, and it fits well with the widely held notion of nature as ‘red in tooth and claw.’ This scenario, in which an evolutionary advantage gained in one species is met with a compensatory change in the other, is both straightforward and plausible. This sort of constant coevolutionary struggle has even been implicated as a major reason behind the advantage of sex. However, empirical evidence for arms races can be difficult to find in nature, given that our view of current ecological communities is often limited to only their present state, revealing only a single time point in a dynamic process. The best evidence for on-going arms races comes from predator– prey or parasite–host populations whose traits differ in a correlated manner over geographic space (Thompson, 2005). The geographic mosaic theory of coevolution predicts variation in the strength and specifics of the coevolutionary process among different local populations of interacting species. Thus, predator or parasite populations that are well matched to the traits of their local victim populations, and vice versa, provide strong evidence for on-going coevolutionary arms races. Perhaps the best studied example of this is the classic case of rough-skinned newts and garter snakes in the western United States (Brodie, 2011). In the 1960s, otherwise harmless rough-skinned newts (Taricha granulosa) in Pacific Northwest were found to be highly toxic. The newts produce a compound called tetrodotoxin, which binds to and blocks sodium channels in neurons. The level of toxicity produced by these animals was surprising; with individual newts weighing only a few grams producing doses capable of killing 25 000 mice. Moreover, at the time there were few known predators of these newts, and in particular no large vertebrate predators that would require such a formidable defense. Further ecological surveys of the newts identified a reason for the toxicity: high levels of predation by the common garter snake (Thamnophis sirtalis), which is resistant to the newt’s toxins. Decades of work in this system, led by Edmund Brodie Jr. and Edmund Brodie III, has succeeded in painting a clear picture of the coevolutionary arms race between newts and garter snakes.
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>2 1–2 0.5 – 1.0 0.3 – 0.5 0.1 – 0.3 0.01 – 0.1 < 0.01
>5 2–3 0.7 – 1.5 0.4 – 0.7 0.2 – 0.4 0.13 – 0.2 < 0.13
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Figure 2 Depiction of the geographic mosaic in the newt/garter snake coevolutionary arms race. The map on the left shows how newt toxicity (amount of TTX produced) varies over space. The map on the right shows the geographic variation in snake resistance (dose of TTX needed to hinder snake performance). The broad correspondence of geographic variation in the traits of these two species are highlighted with the red (high toxicity and resistance) and blue-green (low toxicity and resistance) arrows. Adapted from Hanifin, C.T., Brodie Jr., E.D., Brodie III, E.D., 2008. Phenotypic mismatches reveal escape from arms-race coevolution. PLoS Biology 6, 0471–0482. Originally published under the Creative Commons Attribution license.
Considerable variation exists in both newt toxicity and snake resistance in different geographic locations. Congruent with the geographic mosaic model of coevolution, there is also strong geographic correlation in trait values of newt and snake populations, with more toxic newts generally found within areas with more resistant snakes (Figure 2; Brodie et al., 2002; Hanifin et al., 2008). The molecular basis for both newt toxin production and snake resistance is also now well understood. Newts increase production of tetrodotoxin, while resistant garter snakes possess mutations which change the conformation of sodium channel proteins, which decreases the binding affinity between the toxin and the channels (Geffeney et al., 2002). Experiments have also demonstrated a clear fitness tradeoff in resistance for the snakes. The sodium channel mutations that reduce the toxicity of tetrodotoxin on the snakes also have a negative effect on snake locomotor capacity. Resistant snakes are slower and clumsier than nonresistant snakes (Brodie and Brodie, 1999). This helps explain why the highly resistant alleles have not spread through all the snake populations; the locomotor costs are not worth the benefit when the local newts are less poisonous. This classic garter snake/newt system represents an elegant case study highlighting the potential power of coevolutionary arms races in predator–prey systems in driving trait evolution. In addition to directional escalation of trait values, frequency dependent selection dynamics during coevolutionary arms races may lead to long-term maintenance of genetic diversity in populations. Selection should favor parasite phenotypes that are best suited to attacking the most common phenotype in the host population. As those parasite phenotypes
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increase in number, the fitness of the most common host phenotype will decline, and fitness increases for previously rare host phenotypes that can avoid or fend off the nowcommon parasite phenotypes. The outcome of these dynamics may be to favor host populations that are heterogeneous with respect to defensive traits. In our own immune systems, the tremendous diversity of our MHC genes may partly be explained by our coevolutionary history with parasites.
Codiversification Another potential outcome of coevolution in predator or parasite systems is codiversification. Instead of the back-andforth struggle of trait evolution in an arms race, reciprocal selection pressures imposed by predators or parasites and their prey or hosts may lead to reciprocal diversification in both trophic levels. One method of reducing predation or parasitism pressure may be for a prey or host species to escape from their enemies by adopting new habitats. Divergent adaptation to novel habitats or niches is the basic premise underlying ecological speciation. The relatively enemy-free habitat of the derived population may not last long, however, as new enemies may move in to take advantage of the flourishing new resource. These new enemies may be derived from the previous enemy population, now undergoing divergent adaptation in lock-step with its old coevolutionary partner or an entirely new set of enemies may move in. Just as selection may favor shifts of prey species into new habitats, selection may favor predators and parasites that can find new victims. If a prey species gains a strong upper hand in defense, there may not be sufficient genetic variation in the predator population for an adequate coevolutionary counter move. The resulting fitness landscape may favor predator populations improving their capture rate (parameter c in the model above) by exploiting different, more susceptible prey species. In systems involving a high degree of specialization, like parasitoid insects, these shifts may also trigger ecological speciation events. Lock-step codiversification is expected to produce matching phylogenies in the species of both trophic levels. However, more complex patterns of host shifting may result in discordant phylogenetic patterns that are nonetheless driven by coevolution. For example, even if a novel enemy species came from outside the ancestral system, evolutionary changes in one species are still having a direct effect on the fitness landscape of the other. One prime example of codiversification in action is the case of the apple maggot fly, Rhagoletis pomonella, and the specialist parasitoid wasps that attack it. The apple maggot fly was originally a specialist attacking the fruit of hawthorn trees (Crataegus sp.) throughout much of North America. Domestic apples were introduced to North America from Eurasia in the seventeenth century. About 150 years after this introduction, a population of these flies shifted and began attacking apples instead of hawthorn fruit (Bush, 1969). Genetic and phenotypic evidence has confirmed that these two populations are now strongly reproductively isolated and are on the path to becoming separate species. The apple and hawthorn flies differ in their chemosensory response to host fruit volatiles and in their life history timing (coinciding with differences in the
timing of fruit ripening of their respective hosts). Four parasitoid wasp species specialize in attacking the apple maggot fly, and predation by these wasps may have been a key factor in the selective advantage of the shift to apples. Parasitoid rates in the hawthorn race can be quite high (sometimes in excess of 50%). Apples are considerably larger than hawthorns, with much more room for fly larvae to hide from the ovipositors of wasps on the fruit surface. This enemy-free space is thought to be a major reason behind the shift to apples (Feder, 1995). However, the apple-infesting populations of R. pomonella are not entirely free of parasitoid enemies. The incipient speciation of the apple flies has led to incipient speciation in the wasps as well. The most prevalent of the four parasitoids, Diachasma alloeum, shows strikingly similar patterns of ecological divergence and reproductive isolation (Forbes et al., 2009). These wasps lay eggs into late instar fly larvae tunneling through the fruit. The wasps infesting different races of flies have differentiated in the same key ecological traits that separate the flies: response to fruit olfactory cues, the first crucial step in finding their larval quarry and life history timing specifically in synch with the life cycle of apple flies. Interestingly, genetic evidence suggests that this is not a simple case of lockstep codiversification. Rather, the proximate ancestor of the apple fly-infesting wasps appears to be D. alloeum populations specialized to attacking the blueberry maggot fly, Rhagoletis mendax. Thus, the coevolutionary consequences of divergent adaptation in one species are not restricted to the original interaction partner but can ripple further out into the ecological community.
Parasite Transmission and the Attenuation of Virulence In many parasite–host systems, effective transmission of parasite offspring to new hosts is a critical component of parasite success. It is likely that tradeoffs between efficient use of host resources (conferring greater fitness costs to the host) and transmission among hosts are common. Parasite transmission may require close contact between host individuals. Parasites that grow and reproduce quickly by efficiently pillaging the host’s body may render their hosts too ill to pass their progeny on to new hosts. An aggressive parasite could make a host too weak to move widely and interact with conspecifics, or could kill the host before any opportunity for transmission. One solution to this dilemma is for parasites to alter their host’s phenotypes specifically to maximize transmission. This has important consequences for human disease. Many of the symptoms induced by parasites directly impact the success of parasite transmission. It is likely no coincidence that the main symptoms of infections by waterborne parasites such as Vibrio cholera (the pathogen responsible for cholera) or Giardia lamblia involve severe digestive distress, a surefire way to quickly reinfest water used by hosts. Similarly, the violent behavioral symptoms of rabies infections maximize the transmission of the rabies virus through saliva. Instead of entirely hijacking host phenotypes, some parasites may increase transmission success by minimizing the costs imposed on their hosts. Healthier hosts may live longer,
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move further, and interact with more conspecifics, ultimately leading to greater transmission and dispersal for the parasite. Thus, in situations where transmission is limiting, natural selection may favor reduced virulence in the parasite populations. A famous example of this phenomenon occurred during an attempt at biocontrol of invasive rabbits in Australia (Fenner, 1983). European rabbits (Oryctolagus cuniculus) were introduced to Australia during the mid-nineteenth century. The combination of their rapid reproduction rate and a relatively depauperate predator community in Australia led to an explosion of the rabbit population, causing widespread environmental and economic damage. A solution to the rabbit invasion appeared when an extremely virulent Myxoma virus was discovered in a population of captive rabbits in South America. The virus was intentionally introduced to the Australian rabbit population in 1950. The plan appeared to be a great success in the first couple of years. The virus was nearly always lethal, and the rabbit population declined by more than 75%. However, as the density of the rabbit population plummeted, transmission became an important selective force for the virus. Aggressively virulent strains of the virus caused rabbits (and the viruses they harbored) to die before they were likely to come into contact with other rabbits, while less virulent strains were more likely to be transmitted and survive. By 1952, less virulent strains of the virus began to proliferate and the rabbit population rebounded. The coevolutionary combination of attenuated virulence by the virus and genetic resistance to infection by the rabbits has led to the long-term persistence of Myxoma-infected rabbit populations in Australia. The above example illustrated how parasitic interactions may evolve to become less costly to host species. The difference between parasitism, commensalism, and mutualism is determined by the net result of the costs and benefits to the symbiont partners. Thus, a sufficient decrease in virulence could tip the entire balance of the interaction into a commensal or even mutualistic relationship. Such shifts in the net result of species interactions may occur in both directions. In a mutualism, if one species starts to cheat by failing to provide a benefit to its partner, the interaction may immediately become parasitic in nature. Similarly, if selection on transmission success by parasites leads to minimizing fitness costs for hosts, it is not difficult to imagine a scenario where the net fitness costs to the host are minimized by the parasite providing some offsetting benefit, which could tip the balance into mutualist territory. A striking example of this phenomenon occurred serendipitously in the laboratory of Dr. Kwang Jeon of the University of Tennessee (Figure 3; Jeon, 1972). Jeon was conducting cyto-nuclear transplant experiments with lab lines of the amoeba Amoeba discoides. In 1966, some of the amoeba cultures became infected with very high numbers of an intracellular bacterial parasite. The bacteria appeared to be highly virulent; most newly infected cells died. Those that survived showed markedly slower generation time, smaller size, and greater susceptibility to starvation and mechanical stress. Because of the amount of work that had gone into this project, the amoeba lines were kept alive and nursed along for 5 years. During that time, the infection persisted, but the negative effects completely disappeared. But this was not a straightforward case of attenuation of virulence. In that 5-year span,
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Jeon’s amoebae not only became resistant to the effects of the bacteria but they also became dependent on them. Nuclei from the now resistant infected lines performed very poorly when transferred to cells from uninfected lines. These infectedinto-uninfected transfers resulted in a greater than 10-fold reduction in survivorship compared to transfers within infected or uninfected cells. Similarly, the bacteria could not be cultured outside of the amoebae, indicating that like many endoparasites, they were obligatorily dependent on their hosts. Thus, in only 5 years (B1000 amoeba generations) a clearly parasitic interaction evolved toward a nearly obligatory mutualism.
Coevolution and Ecological Dynamics Coevolutionary responses have important implications for community dynamics in predator–prey and parasite–host systems. Population dynamics and evolutionary change act at the same time scale: generational time. It was once common for biologists to make a clear distinction between biological processes operating in ‘ecological time’ or ‘evolutionary time.’ However, this old dichotomy is neither correct nor useful. Both population demographics and evolutionary change constantly inform and affect one another. The fitness effects of particular alleles depend on the specific ecological and demographic contexts of the population. Likewise, shifts in allele frequencies between generations can alter the outcome of ecological interactions. In the simple Lotka–Volterra model presented above, selective deaths of both predator and prey species may instantaneously change the trait values that control the capture rate parameter (c). Explicity considering this additional dimension of change in models of species interactions demonstrates that on-going coevolution may strongly affect the overall dynamics of predator–prey systems (Abrams, 2001). Interestingly, coevolutionary responses have the potential to stabilize otherwise unstable systems or destabilize otherwise stable systems (Abrams, 2001). One of the important determinants of this appears to be whether the traits involved in prey defense are limited in the potential directionality of their evolutionary response (Abrams and Matsuda, 1997; Gavrilets, 1997). That is, are prey traits likely to evolve in a single direction or can advantageous mismatches be achieved by moving bidirectionally along the trait axis? Unidirectional defensive trait evolution tends to make systems more stable, while bidirectional defensive trait evolution tends to induce cycles in previously stable systems or increase the amplitude of existing cycles. Coevolution may alter population dynamics, but population dynamics may also influence the outcome of coevolution. Whether arms races continue to escalate may be determined by the particular mathematical relationship between predator and prey populations. For instance, the functional response of predators to greater prey population densities is a key consideration (Abrams, 1986). Stronger prey defense may result in a lower capture rate (c) for predators, but the resulting higher prey densities may compensate for this change. This suggests that selection imposed by prey defensive traits on predator traits may generally be weaker than the
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1. Lines of Amoeba discoides strain ‘D’ used in cyto/nuclear transplant experiments 2. Amoebae become infected by bacterium, 60 000−150 000 per cell, causing slower growth rates, decreased stress tolerance, and death 3. Surviving infected lines nursed along in the lab while uninfected strain ‘D’ lines are brought back into the lab from the original source 4. Amoebae lines grown in the lab for 5 years (~1000 generations) during which time, survivorship, growth rate, and stress tolerance of infected lines return to normal, despite presistant infection 5. Microsurgical experiments performed, transplanting nuclei from infected lines into uninfected cytoplasm as well as transplants among infected and uninfected lines
6. Extremely low viability for infected strain nuclei placed in uninfected cytoplasm
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Figure 3 Schematic of coevolutionary shift from parasitism to mutualism between Amoeba discoides and a bacterial endosymbiont in the lab of Dr. Kwang Jeon at the University of Tennessee in the late 1960s. Diagram based on description of events, methods, and results by Jeon, K., 1972. Development of cellular dependence on infective organisms: Micurgical studies in amoebas. Science 176, 1122–1123.
reverse, with stronger predator attack traits resulting in both higher per capita capture rates and higher predator densities. This reciprocal feedback between coevolution and community demographic dynamics in predation and parasitism systems calls attention to the continued need for greater integration between evolutionary biology and ecology.
Macroevolutionary Patterns The examples above demonstrate the various ways that coevolution affects predator–prey and parasite–host systems. While they may be difficult to study empirically, the fingerprints of coevolution are ubiquitous in ecological communities. But what effect has coevolution between predators and prey and parasites and hosts had on broad scale patterns of biodiversity over geological time? Do we see a clear signature of persistent arms races or codiversification in the fossil record? The answer may be that coevolution does indeed drive macroevolutionary patterns, but perhaps in a diffuse and
limited fashion. It is nearly impossible to study pairwise specialist interactions in the fossil record; organisms rarely leave behind precise records of who they ate and who ate them. However, paleontologists have been able to take the approach of studying patterns within ecological guilds that were likely to be broadly interacting. Paleontologist Robert Bakker analyzed coevolutionary trends in morphology between cursorial (chasing) mammalian predators and their primary prey, ungulates, across the entire history of their shared existence from the beginning of the Cenozoic period until the present day (Bakker, 1983). This is a case where the primary trait affecting the parameter c is basically the same for both predator and prey: speed. With few exceptions, ungulate species rely on speed during the early stages of a chase to escape predators, and it is this fleetness of foot of both predator and prey that determines the outcome of most hunts. The basic expectation of coevolution between these guilds would be increased running speed through time. Directional change in skeletal morphology for both ungulates and predators indicates that both groups have become
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Figure 4 (a) Plot of inferred running speed (based on limb ratios) over time for ungulates (red circles), and three lineages of cursorial mammalian carnivores, mesonychids (blue squares), creodonts (green squares), and carnivorans (pink squares). These data highlight the continuous directional evolution of running speed in hoofed mammals, but not their predators, at the macroevolutionary scale. Based on data presented in Bakker, R.T., 1983. The deer flees, the wolf pursues: Incongruencies in predator–prey coevolution. In: Futuyma, D.J., Slatkin, M. (Eds.), Coevolution. Sunderland, MA: Sinauer. (b) Example cursorial predators (left) and ungulates (right) from two time along the graph, the Holocene (modern times) (top) and the late Eocene (B50 million years ago). These examples highlight the greater change in limb morphology for hoofed herbivores vs. running predators over the past 50 million years.
increasingly swifter. Several traits associated with greater speed including less acute limb angles, more constrained movement in ball joints, the reduction of side digits, and shorter phalanges show clear progressions in both groups. However, the pace of speed-related skeletal adaptation in ungulates far outpaces that of predators. Ungulates have consistently been getting faster, while cursorial predators have been unable to keep up (pun intended) (Figure 4). Bakker argues that basic trophic structure may be responsible for the widening gap in this arms race. The necessarily greater population size of the prey species makes them less prone to extinction and more likely to stumble upon evolutionary innovations for speed. Alternatively, this could be a case of stronger tradeoffs for the predator species; many carnivores use their hands and claws for digging, fighting, or manipulating prey, and such diverse functional requirements may prevent carnivores from evolving super-specialized running tools. In either case, the fossil record suggests that predator–prey coevolution can indeed drive important long-term evolutionary trends but that there are likely considerable limits to perpetual escalation in arms races.
See also: Commensalism, Amensalism, and Synnecrosis. Ecological Speciation and Its Consequences Geographic Mosaic of Coevolution. Intraspecific Coevolutionary Arms Races. Secondary Metabolites, the Role in Plant Diversification of
References Abrams, P.A., 1986. Adaptive responses of predators to prey and prey to predators: The failure of the arms race analogy. Evolution 4, 1229–1247.
Abrams, P.A., 2001. The evolution of predator−prey interactions: Theory and evidence. Annual Review of Ecology and Systematics 31, 79–105. Abrams, P.A., Matsuda, H., 1997. Fitness minimization and dynamic instability as a consequence of predator−prey coevolution. Evolutionary Ecology 11, 1–20. Bakker, R.T., 1983. The deer flees, the wolf pursues: Incongruencies in predator− prey coevolution. In: Futuyma, D.J., Slatkin, M. (Eds.), Coevolution. Sunderland, MA: Sinauer. Brodie III, E.D., 2011. Patterns, process, and the parable of the coffeepot incident: Arms races between newts and snakes from landscapes to molecules. In: Losos, J.B. (Ed.), In the Light of Evolution: Essays from the Laboratory and Field. Greenwood Village, CO: Roberts & Co, pp. 93–120. Brodie III, E.D., Brodie Jr., E.D., 1999. The cost of exploiting poisonous prey: Tradeoffs in a predator−prey arms race. Evolution 53, 626–631. Brodie Jr., E.D., Ridenhour, B.J., Brodie III, E.D., 2002. The evolutionary response of predators to dangerous prey: Hotspots and coldspots in the geographic mosaic of coevolution between garter snakes and newts. Evolution 56, 2067–2082. Bush, G.L., 1969. Sympatric host race formation and speciation in frugivorous flies of the genus Rhagoletis (Diptera: Tephritidae). Evolution 23, 237–251. Feder, J.L., 1995. The effects of parasitoids on sympatric host races of Rhagoletis pomonella (Diptera: Tephritidae). Ecology 76, 801–813. Fenner, F., 1983. The Florey lecture 1983: Biological control, as exemplified by smallpox eradication and myxomatosis. Proceedings of the Royal Society of London Series B: Biological Sciences 218, 259–285. Forbes, A.A., Powell, T.H.Q., Stelinski, L.L., Smith, J.J., Feder, J.L., 2009. Sequential sympatric speciation across trophic levels. Science 323, 776–779. Gavrilets, S., 1997. Coevolutionary chase in exploiter−victim systems with polygenic characters. Journal of Theoretical Biology 186, 527–534. Geffeney, S., Brodie Jr., E.D., Ruben, P.C., Brodie III, E.D., 2002. Mechanisms of adaptation in a predator−prety arms race: TTX-resistant sodium channels. Science 297, 1336–1339. Hanifin, C.T., Brodie Jr., E.D., Brodie III, E.D., 2008. Phenotypic mismatches reveal escape from arms-race coevolution. PLoS Biology 6, 0471–0482. Jeon, K., 1972. Development of cellular dependence on infective organisms: Micurgical studies in amoebas. Science 176, 1122–1123. Thompson, J.N., 2005. The Geographic Mosaic of Evolution. Chicago, IL: University of Chicago Press.
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Further Reading Abrams, P.A., 1986. Adaptive responses of predators to prey and prey to predators: The failure of the arms race analogy. Evolution 4, 1229–1247. Brodie III, E.D., 2011. Patterns, process, and the parable of the coffeepot incident: Arms races between newts and snakes from landscapes to molecules. In: Losos, J.B. (Ed.), In the Light of Evolution: Essays from the Laboratory and Field. Greenwood Village, CO: Roberts & Co, pp. 93–120.
Futuyma, D.J., Slatkin, M., 1983. Coevolution. Sunderland, MA: Sinauer Associates. Jeon, K., 1972. Development of cellular dependence on infective organisms: Micrurgical studies in amoebas. Science 176, 1122–1123. Thompson, J.N., 2005. The Geographic Mosaic of Evolution. Chicago, IL: University of Chicago Press.