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The healthy herds hypothesis proposes that predators can reduce parasite prevalence and thereby increase the density of their prey. However, evidence for such predator-driven reductions in the prevalence of prey remains mixed. Furthermore, even less evidence supports increases in prey density during epidemics. Here, we used a planktonic predator-prey-parasite system to experimentally test the healthy herds hypothesis. We manipulated density of a predator (the phantom midge, Chaoborus punctipennis) and parasitism (the virulent fungus Metschnikowia bicuspidata) in experimental assemblages. Because we know natural populations of the prey (Daphnia dentifera) vary in susceptibility to both predator and parasite, we stocked experimental populations with nine genotypes spanning a broad range of susceptibility to both enemies. Predation significantly reduced infection prevalence, eliminating infection at the highest predation level. However, lower parasitism did not increase densities of prey; instead, prey density decreased substantially at the highest predation levels (a major density cost of healthy herds predation). This density result was predicted by a model parameterized for this system. The model specifies three conditions for predation to increase prey density during epidemics: (i) predators selectively feed on infected prey, (ii) consumed infected prey release fewer infectious propagules than unconsumed prey, and (iii) sufficiently low infection prevalence. While the system satisfied the first two conditions, prevalence remained too high to see an increase in prey density with predation. Low prey densities caused by high predation drove increases in algal resources of the prey, fueling greater reproduction, indicating that consumer-resource interactions can complicate predator-prey-parasite dynamics. Overall, in our experiment, predation reduced the prevalence of a virulent parasite but, at the highest levels, also reduced prey density. Hence, while healthy herds predation is possible under some conditions, our empirical results make it clear that the manipulation of predators to reduce parasite prevalence may harm prey density., (© 2023 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

We use global sensitivity analysis (specifically, Partial Rank Correlation Coefficients) to explore the roles of ecological and epidemiological processes in shaping the temporal dynamics of a parameterized SIR-type model of two host species and an environmentally transmitted pathogen. We compute the sensitivities of disease prevalence in each host species to model parameters. Sensitivity rankings are calculated, interpreted biologically, and contrasted for cases where the pathogen is introduced into a disease-free community and cases where a second host species is introduced into an endemic single-host community. In some cases the magnitudes and dynamics of the sensitivities can be predicted only by knowing the host species' characteristics (i.e., their competitive abilities and disease competence) whereas in other cases they can be predicted by factors independent of the species' characteristics (specifically, intraspecific versus interspecific processes or a species' roles of invader versus resident). For example, when a pathogen is initially introduced into a disease-free community, disease prevalence in both hosts is more sensitive to the burst size of the first host than the second host. In comparison, disease prevalence in each host is more sensitive to its own infection rate than the infection rate of the other host species. In total, this study illustrates that global sensitivity analysis can provide useful insight into how ecological and epidemiological processes shape disease dynamics and how those effects vary across time and system conditions. Our results show that sensitivity analysis can provide quantification and direction when exploring biological hypotheses., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

AbstractIn multihost-multipathogen communities, a focal host's risk of being infected by a particular pathogen can be influenced by the presence of other host and pathogen species. We explore how indirect interactions between pathogens at the within-host level (through coinfecting the same individual) and the between-host level (through altered susceptible host densities) affect the focal host's risk of infection. We use an SI-type epidemiological model of two host species and two environmentally transmitted pathogens where one pathogen is a specialist on the focal host and the other pathogen is a generalist. We show that monotonic, unimodal, and U-shaped relationships between the specialist and generalist infectious propagule densities (proxies of the focal host's risk of infection) are driven by the way within-host priority effects alter the production of specialist infectious propagules by infected focal host individuals. Interestingly, within-host priority effects can also lead to overcompensation in density wherein increased infected host mortality results in greater specialist infectious propagule density. We interpret these results in terms of how the focal host's risk of being infected by a specialist pathogen is affected by the presence of a generalist pathogen, its alternative host, and within-host priority effects.

Relationships between host species richness and levels of disease in a focal host are likely to be context-dependent, depending on the characteristics of which particular host species are present in a community. I use a multi-host epidemiological model with environmental transmission to explore how the characteristics of the host species (e.g., competence and competitive ability), host density, and the pathogen transmission mechanism affect the proportion of infected individuals (i.e., infection prevalence) in a focal host. My sensitivity-based approach identifies the indirect pathways through which specific ecological and epidemiological processes affect focal host infection prevalence. This in turn yields predictions about the context-dependent rules governing whether increased host species richness increases (amplifies) or decreases (dilutes) infection prevalence in a focal host. For example, in many cases, amplification and dilution are predicted to occur when added host species are sources or sinks of infectious propagules, respectively. However, if the added host species have strong and asymmetric competitive effects on resident host species, then amplification and dilution are predicted to occur when the added host species have stronger competitive effects on resident host species that are sources or sinks of infectious propagules, respectively. My results also predict that greater dilution and less amplification is more likely to occur under frequency-dependent direct transmission than density-dependent direct transmission when (i) the added hosts have lower competence than resident host species and (ii) interspecific competition between the added host species and resident host species is lower; the opposite conditions promote greater amplification and less dilution under frequency-dependent direct transmission. This work helps identify and explain the mechanisms shaping the context-dependent relationships between host species richness and disease in multi-host communities., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The likelihood an individual becomes infected depends on the community in which it is embedded. For environmentally transmitted parasites, host community composition can alter host density, the density of parasites that hosts encounter in the environment, and the dose to which hosts are subsequently exposed. While some multi-host theory incorporates some of these factors (e.g., competition among hosts), it does not currently consider the nonlinear relationships between parasite exposure dose and per-propagule infectivity (dose-infectivity relationships), between exposure dose and infected host mortality (dose-mortality relationships), and between exposure dose and parasite propagule excretion (dose-excretion relationships). This makes it difficult to predict the impact of host species on one another's likelihood of infection. To understand the implications of these nonlinear dose relationships for multi-host communities, we first performed a meta-analysis on published dose-infectivity experiments to quantify the proportion of accelerating, linear, or decelerating dose-infectivity relationships; we found that most experiments demonstrated decelerating dose-infectivity relationships. We then explored how dose-infectivity, dose-mortality, and dose-excretion relationships might alter the impact of heterospecific host density on infectious propagule density, infection prevalence, and density of a focal host using two-host, one-parasite models. We found that dose relationships either decreased the magnitude of the impact of heterospecific host density on propagule density and infection prevalence via negative feedback loops (decelerating dose-infectivity relationships, positive dose-mortality relationships, and negative dose-excretion relationships), or increased the magnitude of the impact of heterospecific host density on infection prevalence via positive feedback loops (accelerating dose-infectivity relationships and positive dose-excretion relationships). Further, positive dose-mortality relationships resulted in hosts that traditionally decrease disease (e.g., low competence, strong competitors) increasing infection prevalence, and vice versa. Finally, we found that dose relationships can create positive feedback loops that facilitate friendly competition (i.e., increased heterospecific density has a positive effect on focal host density because the reduction in disease outweighs the negative effects of interspecific competition). This suggests that without taking dose relationships into account, we may incorrectly predict the effect of heterospecific host interactions, and thus host community composition, on environmentally transmitted parasites., (© 2021 by the Ecological Society of America.)

AbstractBiodiversity in communities is changing globally, including the gain and loss of host species in host-pathogen communities. Increased host diversity can cause infection prevalence in a focal host to increase (amplification) or decrease (dilution). However, it is unclear what general rules govern the context-dependent effects, in part because theories for pathogens with different transmission modes have developed largely independently. Using a two-host model, we explore how the pathogen transmission mode and characteristics of a second host (disease competence and competitive ability) influence disease prevalence in a focal host. Our work shows how the theories for pathogens with environmental transmission, density-dependent direct transmission, and frequency-dependent direct transmission can be unified. Our work also identifies general rules about how host and pathogen characteristics affect amplification/dilution. For example, higher-competence hosts promote amplification, unless they are strong interspecific competitors; strong interspecific competitors promote dilution, unless they are large sources of new infections; and dilution occurs under frequency-dependent direct transmission more than density-dependent direct transmission, unless interspecific host competition is sufficiently strong. Our work helps explain how the characteristics of the pathogen and a second host affect disease prevalence in a focal host.

AbstractEvolution and plasticity can drive population-level phenotypic change (e.g., changes in the mean phenotype) on timescales comparable to changes in population densities. However, it is unclear whether phenotypic change has the potential to be just as fast as changes in densities or whether comparable rates of change occur only when densities are changing slow enough for phenotypes to keep pace. Moreover, it is unclear whether this depends on the mode of adaptation. Using scaling theory and fast-slow dynamical systems theory, we develop a method for comparing maximum rates of density and phenotypic change estimated from population-level time-series data. We apply our method to 30 published empirical studies where changes in morphological traits are caused by evolution, plasticity, or an unknown combination. For every study, the maximum rate of phenotypic change was between 0.5 and 2.5 times faster than the maximum rate of change in density. Moreover, there were no systematic differences between systems with different modes of adaptation. Our results show that plasticity and evolution can drive phenotypic change just as fast as changes in densities. We discuss the implications of our results in terms of the strengths of feedbacks between population densities and traits.

AbstractIn multipredator and multipathogen systems, exploiters interact indirectly via shared victim species. Interspecific prey competition and the degree of predator specialization are known to influence whether predators have competitive (i.e., (-,-)) or noncompetitive (i.e., (-,+) or (+,+)) indirect interactions. Much less is known about the population-level indirect interactions between pathogens that infect the same populations of host species. In this study, we use two-predator-two-prey and two-host-two-pathogen models to compare the indirect effects between predators with the indirect effects between pathogens. We focus on how the indirect interactions between pathogens are affected by the competitive abilities of susceptible and infected hosts, whether the pathogens are specialists or generalists, and the transmission pathway (direct vs. environmental transmission). In many cases, indirect effects between pathogens and predators follow similar patterns, for example, more positive indirect effects with increased interspecific competition between victim species. However, the indirect effects between pathogens can qualitatively differ, for example, more negative indirect effects with increased interspecific host competition. These contrasting patterns show that an important mechanistic difference between predatory and parasitic interactions (specifically, whether interactions are immediately lethal) can have important population-level effects on the indirect interactions between exploiters.

Bacterial viruses, that is 'bacteriophage' or 'phage', can infect and lyse their bacterial hosts, releasing new viral progeny. In addition to the lytic pathway, certain bacteriophage (i.e. 'temperate' bacteriophage) can also initiate lysogeny, a latent mode of infection in which the viral genome is integrated into and replicated with the bacterial chromosome. Subsequently, the integrated viral genome, that is the 'prophage', can induce and restart the lytic pathway. Here, we explore the relationship among infection mode, ecological context, and viral fitness, in essence asking: when should viruses be temperate? To do so, we use network loop analysis to quantify fitness in terms of network paths through the life history of an infectious pathogen that start and end with infected cells. This analysis reveals that temperate strategies, particularly those with direct benefits to cellular fitness, should be favored at low host abundances. This finding applies to a spectrum of mechanistic models of phage-bacteria dynamics spanning both explicit and implicit representations of intra-cellular infection dynamics. However, the same analysis reveals that temperate strategies, in and of themselves, do not provide an advantage when infection imposes a cost to cellular fitness. Hence, we use evolutionary invasion analysis to explore when temperate phage can invade microbial communities with circulating lytic phage. We find that lytic phage can drive down niche competition amongst microbial cells, facilitating the subsequent invasion of latent strategies that increase cellular resistance and/or immunity to infection by lytic viruses-notably this finding holds even when the prophage comes at a direct fitness cost to cellular reproduction. Altogether, our analysis identifies broad ecological conditions that favor latency and provide a principled framework for exploring the impacts of ecological context on both the short- and long-term benefits of being temperate., (© The Author(s) 2020. Published by Oxford University Press.)

We develop a method to identify how ecological, evolutionary, and eco-evolutionary feedbacks influence system stability. We apply our method to nine empirically parametrized eco-evolutionary models of exploiter-victim systems from the literature and identify which particular feedbacks cause some systems to converge to a steady state or to exhibit sustained oscillations. We find that ecological feedbacks involving the interactions between all species and evolutionary and eco-evolutionary feedbacks involving only the interactions between exploiter species (predators or pathogens) are typically stabilizing. In contrast, evolutionary and eco-evolutionary feedbacks involving the interactions between victim species (prey or hosts) are destabilizing more often than not. We also find that while eco-evolutionary feedbacks rarely altered system stability from what would be predicted from just ecological and evolutionary feedbacks, eco-evolutionary feedbacks have the potential to alter system stability at faster or slower speeds of evolution. As the number of empirical studies demonstrating eco-evolutionary feedbacks increases, we can continue to apply these methods to determine whether the patterns we observe are common in other empirical communities.

Population responses to environmental change depend on both the ecological interactions between species and the evolutionary responses of all species. In this study, we explore how evolution in prey, predators, or both species affect the responses of predator populations to a sustained increase in mortality. We use an eco-evolutionary predator-prey model to explore how evolution alters the predator extinction threshold (defined as the minimum mortality rate that prevents population growth at low predator densities) and predator hydra effects (increased predator abundance in response to increased mortality). Our analysis identifies how evolutionary responses of prey and predators individually affect the predator extinction threshold and hydra effects, and how those effects are altered by interactions between the evolutionary responses. Based on our theoretical results, we predict that it is common in natural systems for evolutionary responses in one or both species to allow predators to persist at higher mortality rates than would be possible in the absence of evolution (i.e., evolution increases the predator mortality extinction threshold). We also predict that evolution-driven hydra effects occur in a minority of natural systems, but are not rare. We revisited published eco-evolutionary models and found that evolution causes hydra effects and increases the predator extinction threshold in many studies, but those effects have been overlooked. We discuss the implications of these results for species conservation, predicting population responses to environmental change, and the possibility of evolutionary rescue., (© 2019 by the Ecological Society of America.)

The prevailing paradigm in ecological studies of viruses and their microbial hosts is that the reproductive success of viruses depends on the proliferation of the 'predator', that is, the virus particle. Yet, viruses are obligate intracellular parasites, and the virus genome-the actual unit of selection-can persist and proliferate from one cell generation to the next without lysis or the production of new virus particles. Here, we propose a theoretical framework to quantify the invasion fitness of viruses using an epidemiological cell-centric metric that focuses on the proliferation of viral genomes inside cells instead of virus particles outside cells. This cell-centric metric enables direct comparison of viral strategies characterized by obligate killing of hosts (e.g. via lysis), persistence of viral genomes inside hosts (e.g. via lysogeny), and strategies along a continuum between these extremes (e.g. via chronic infections). As a result, we can identify environmental drivers, life history traits, and key feedbacks that govern variation in viral propagation in nonlinear population models. For example, we identify threshold conditions given relatively low densities of susceptible cells and relatively high growth rates of infected cells in which lysogenic and other chronic strategies have higher potential viral reproduction than lytic strategies. Altogether, the theoretical framework helps unify the ongoing study of eco-evolutionary drivers of viral strategies in natural environments.

This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator-prey systems. We do this by analyzing a general eco-evolutionary predator-prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator-prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator-prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.

The relationship between environmental productivity and species richness often varies among empirical studies, and despite much research, simple explanations for this phenomenon remain elusive. We investigated how phytoplankton and zooplankton coevolution shapes productivity-richness relationships in both phytoplankton and zooplankton, using a simple nutrient-phytoplankton-zooplankton model that incorporates size-dependent metabolic rates summarized from empirical studies. The model allowed comparisons of evolved species richness across productivity levels and at different evolutionary times. Our results show that disruptive selection leads to evolutionary branching of phytoplankton and zooplankton. Both the time required for evolutionary branching and the number of evolved species in phytoplankton and zooplankton tend to increase with productivity, producing a transient unimodal or positive productivity-richness relationship but followed by a positive productivity-richness relationship for both groups over long enough evolutionary time. Our findings suggest that coevolution between phytoplankton and zooplankton can drive the two common forms (unimodal and positive) of productivity-richness relationships in nature.

A species exhibits a hydra effect when, counter-intuitively, increased mortality of the species causes an increase in its abundance. Hydra effects have been studied in many continuous time (differential equation) multispecies models, but only rarely have hydra effects been observed in or studied with discrete time (difference equation) multispecies models. In addition most discrete time theory focuses on single-species models. Thus, it is unclear what unifying characteristics determine when hydra effects arise in discrete time models. Here, using discrete time multispecies models (where total abundance is the single variable describing each population), I show that a species exhibits a hydra effect in a stable system only when fixing that species' density at its equilibrium density destabilizes the system. This general characteristic is referred to as subsystem instability. I apply this result to two-species models and identify specific mechanisms that cause hydra effects in stable communities, e.g., in host--parasitoid models, host Allee effects and saturating parasitoid functional responses can cause parasitoid hydra effects. I discuss how the general characteristic can be used to identify mechanisms causing hydra effects in communities with three or more species. I also show that the condition for hydra effects at stable equilibria implies the system is reactive (i.e., density perturbations can grow before ultimately declining). This study extends previous work on conditions for hydra effects in single-species models by identifying necessary conditions for stable systems and sufficient conditions for cyclic systems. In total, these results show that hydra effects can arise in many more communities than previously appreciated and that hydra effects were present, but unrecognized, in previously studied discrete time models., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Generalist parasites can strongly influence interactions between native and invasive species. Host competence can be used to predict how an invasive species will affect community disease dynamics; the addition of a highly competent, invasive host is predicted to increase disease. However, densities of invasive and native species can also influence the impacts of invasive species on community disease dynamics. We examined whether information on host competence alone could be used to accurately predict the effects of an invasive host on disease in native hosts. We first characterized the relative competence of an invasive species and a native host species to a native parasite. Next, we manipulated species composition in mesocosms and found that host competence results did not accurately predict community dynamics. While the invasive host was more competent than the native, the presence of the native (lower competence) host increased disease in the invasive (higher competence) host. To identify potential mechanisms driving these patterns, we analyzed a two-host, one-parasite model parameterized for our system. Our results demonstrate that patterns of disease were primarily driven by relative population densities, mediated by asymmetry in intra- and interspecific competition. Thus, information on host competence alone may not accurately predict how an invasive species will influence disease in native species.

Evolution can alter the stability and dynamics of ecological communities; for example, prey evolution can drive cyclic dynamics in predator-prey systems that are not possible in the absence of evolution. However, it is unclear how the magnitude of additive genetic variation in the evolving species mediates those effects. In this study, I explore how the magnitude of prey additive genetic variation determines what effects prey evolution has on the dynamics and stability of predator-prey systems. I use linear stability analysis to decompose the stability of a general eco-evolutionary predator-prey model into components representing the stabilities of the ecological and evolutionary subsystems as well as the interactions between those subsystems. My results show that with low genetic variation, the cyclic dynamics and stability of the system are determined by the ecological subsystem. With increased genetic variation, disruptive selection always destabilizes stable communities, stabilizing selection can stabilize or destabilize communities, and prey evolution can alter predator-prey phase lags. Stability changes occur approximately when the magnitude of genetic variation balances the (in)stabilities of the ecological and evolutionary subsystems. I discuss the connections between my stability results and prior results from the theory of adaptive dynamics.

A hydra effect occurs when the mean density of a species increases in response to greater mortality. We show that, in a stable multispecies system, a species exhibits a hydra effect only if maintaining that species at its equilibrium density destabilizes the system. The stability of the original system is due to the responses of the hydra-effect species to changes in the other species' densities. If that dynamical feedback is removed by fixing the density of the hydra-effect species, large changes in the community make-up (including the possibility of species extinction) can occur. This general result has several implications: (1) Hydra effects occur in a much wider variety of species and interaction webs than has previously been described, and may occur for multiple species, even in small webs; (2) conditions for hydra effects caused by predators (or diseases) often differ from those caused by other mortality factors; (3) introducing a specialist or a switching predator of a hydra-effect species often causes large changes in the community, which frequently involve extinction of other species; (4) harvest policies that attempt to maintain a constant density of a hydra-effect species may be difficult to implement, and, if successful, are likely to cause large changes in the densities of other species; and (5) trophic cascades and other indirect effects caused by predators of hydra-effect species can exhibit amplification of effects or unexpected directions of change. Although we concentrate on systems that are originally stable and models with no stage-structure or trait variation, the generality of our result suggests that similar responses to mortality will occur in many systems without these simplifying assumptions. In addition, while hydra effects are defined as responses to altered mortality, they also imply counterintuitive responses to changes in immigration and other parameters affecting population growth.

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities.

Interspecific competition for resources is generally considered to be the selective force driving ecological character displacement, and displacement is assumed to reduce competition. Skeptics of the prevalence of character displacement often cite lack of evidence of competition. The present article uses a simple model to examine whether competition is needed for character displacement and whether displacement reduces competition. It treats systems with competing resources, and considers cases when only one consumer evolves. It quantifies competition using several different measures. The analysis shows that selection for divergence of consumers occurs regardless of the level of between-resource competition or whether the indirect interaction between the consumers is competition (-,-), mutualism (+,+), or contramensalism (+,-). Also, divergent evolution always decreases the equilibrium population size of the evolving consumer. Whether divergence of one consumer reduces or increases the impact of a subsequent perturbation of the other consumer depends on the parameters and the method chosen for measuring competition. Divergence in mutualistic interactions may reduce beneficial effects of subsequent increases in the other consumer's population. The evolutionary response is driven by an increase in the relative abundance of the resource the consumer catches more rapidly. Such an increase can occur under several types of interaction., (© 2015 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.)

Virophages are viruses that rely on the replication machinery of other viruses to reproduce within eukaryotic hosts. Two different modes of coinfection have been posited based on experimental observation. In one mode, the virophage and the virus enter the host independently. In the other mode, the virophage adheres to the virus so both virophage and virus enter the host together. Here we ask: what are the ecological effects of these different modes of coinfection? In particular, what ecological effects are common to both infection modes, and what are the differences particular to each mode? We develop a pair of biophysically motivated ODE models of viral-host population dynamics, corresponding to dynamics arising from each mode of infection. We find that both modes of coinfection allow for the coexistence of the virophage, virus, and host either at a stable fixed point or through cyclical dynamics. In both models, virophage tends to be the most abundant population and their presence always reduces the viral abundance and increases the host abundance. However, we do find qualitative differences between models. For example, via extensive sampling of biologically relevant parameter space, we only observe bistability when the virophage and the virus enter the host together. We discuss how such differences may be leveraged to help identify modes of infection in natural environments from population level data., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

A hallmark of Lotka-Volterra models, and other ecological models of predator-prey interactions, is that in predator-prey cycles, peaks in prey abundance precede peaks in predator abundance. Such models typically assume that species life history traits are fixed over ecologically relevant time scales. However, the coevolution of predator and prey traits has been shown to alter the community dynamics of natural systems, leading to novel dynamics including antiphase and cryptic cycles. Here, using an eco-coevolutionary model, we show that predator-prey coevolution can also drive population cycles where the opposite of canonical Lotka-Volterra oscillations occurs: predator peaks precede prey peaks. These reversed cycles arise when selection favors extreme phenotypes, predator offense is costly, and prey defense is effective against low-offense predators. We present multiple datasets from phage-cholera, mink-muskrat, and gyrfalcon-rock ptarmigan systems that exhibit reversed-peak ordering. Our results suggest that such cycles are a potential signature of predator-prey coevolution and reveal unique ways in which predator-prey coevolution can shape, and possibly reverse, community dynamics.

Pathogen evolution towards the largest basic reproductive number, R0, has been observed in many theoretical models, but this conclusion does not hold universally. Previous studies of host-pathogen systems have defined general conditions under which R0 maximization occurs in terms of R0 itself. However, it is unclear what constraints these conditions impose on the functional forms of pathogen related processes (e.g. transmission, recover, or mortality) and how those constraints relate to the characteristics of natural systems. Here we focus on well-mixed SIR-type host-pathogen systems and, via a synthesis of results from the literature, we present a set of sufficient mathematical conditions under which evolution maximizes R0. Our conditions are in terms of the functional responses of the system and yield three general biological constraints on when R0 maximization will occur. First, there are no genotype-by-environment interactions. Second, the pathogen utilizes a single transmission pathway (i.e. either horizontal, vertical, or vector transmission). Third, when mortality is density dependent: (i) there is a single infectious class that individuals cannot recover from, (ii) mortality in the infectious class is entirely density dependent, and (iii) the rates of recovery, infection progression, and mortality in the exposed classes are independent of the pathogen trait. We discuss how this approach identifies the biological mechanisms that increase the dimension of the environmental feedback and prevent R0 maximization.

Bacteria and their viruses (bacteriophages) coexist in natural environments forming complex infection networks. Recent empirical findings suggest that phage-bacteria infection networks often possess a nested structure such that there is a hierarchical relationship among who can infect whom. Here we consider how nested infection networks may affect phage and bacteria dynamics using a multi-type Lotka-Volterra framework with cross-infection. Analysis of similar models has, in the past, assumed simpler interaction structures as a first step towards tractability. We solve the proposed model, finding trade-off conditions on the life-history traits of both bacteria and viruses that allow coexistence in communities with nested infection networks. First, we find that bacterial growth rate should decrease with increasing defense against infection. Second, we find that the efficiency of viral infection should decrease with host range. Next, we establish a relationship between relative densities and the curvature of life history trade-offs. We compare and contrast the current findings to the "Kill-the-Winner" model of multi-species phage-bacteria communities. Finally, we discuss a suite of testable hypotheses stemming from the current model concerning relationships between infection range, life history traits and coexistence in complex phage-bacteria communities., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Pathogen transmission can involve direct and/or indirect pathways. Using theoretical models, in this study we ask, "do directly and indirectly transmitted pathogens yield different population-level epidemiological dynamics?" and "can the transmission pathway be inferred from population-level epidemiological data?" Our approach involves comparing the continuous-time dynamics of a class of compartmental epidemiological models with direct versus environmentally mediated indirect transmission pathways. Combing analytical theory and numerical simulations we show that models with direct and indirect transmission can produce quantitatively similar time series when the pathogen cannot reproduce in the environment, particularly when the environmental pathogen dynamics are fast. We apply these results to a previous study on chronic wasting disease and show that identifying the transmission pathway is more difficult than previously acknowledged. Our analysis and simulations also yield conditions under which numerical differences can potentially identify the transmission route in oscillating endemic systems and systems where the environmental pathogen dynamics are not fast. This work begins to identify how differences in the transmission pathway can result in quantitatively different epidemiological dynamics and how those differences can be used to identify the transmission pathway from population level time series.

Interspecific interactions depend not only on the population densities of the interacting species, but on their phenotypes as well. Phenotypic variation can be plastic or heritable and both mechanisms can drive phenotypic change at rates comparable to or faster than those of ecological dynamics (e.g. changes in population abundances or spatial distributions). In this study, we compare the effects rapidly induced and rapidly evolving defences have on community dynamics by considering the fast phenotypic change limit using fast-slow systems theory. Our approach allows us to study phenotypically plastic and evolving systems with one overarching theory, thus capturing the effects rapidly induced defences have on ecological dynamics and how those effects differ from the effects of evolving defences. Our results show that rapidly induced defences tend to stabilize community dynamics and that some behaviours observed in rapidly evolving systems cannot be produced by phenotypic plasticity., (© 2010 Blackwell Publishing Ltd/CNRS.)

An analysis of the major factors affecting the accuracy of harmonic force field computations of water is presented. By systematically varying the level of approximation in the basis set, treatment of electron correlation, core electron correlation, and relativistic correction, the underlying sources of error in the computation of harmonic vibrational frequencies for water were quantified. The convergence error due to wavefunction description with a cc-pVQZ basis set in the absence of electron correlation was 1.6 cm(-1), as determined from extending the Hartree-Fock computations to larger basis sets. The convergence error due to neglecting higher-order electronic correlation terms than are included at the CCSD(T) level using the cc-pVTZ basis set was estimated to be 4.7 cm(-1), as determined from frequency calculations up to CCSDTQ for water and literature results up to CCSDTQP for diatomic molecules. The convergence error due to omitting higher-order diffuse functions than included in aug-cc-pVQZ was found to be 3.7 cm(-1), as determined by adding more diffuse functions in larger basis sets. The error associated with neglecting core electron correlation effects (i.e., "freezing" core electrons) was 5.0 cm(-1) and with neglecting relativistic effects was 2.2 cm(-1). Due to a cancellation among these various sources of error, the harmonic frequencies for H2O computed using the CCSD(T)/aug-cc-pVQZ model chemistry were on average within 2 cm(-1) of experimentally inferred vibrational frequencies.