Asexual reproduction changes predator population dynamics in a life predator–prey system

Many organisms display oscillations in population size. Theory predicts that these fluctuations can be generated by predator–prey interactions, and empirical studies using life model systems, such as a rotifer-algae community consisting of Brachionus calyciflorus as predator and Chlorella vulgaris as prey, have been successfully used for studying such dynamics. B. calyciflorus is a cyclical parthenogen (CP) and clones often differ in their sexual propensity, that is, the degree to which they engage into sexual or asexual (clonal) reproduction. Since sexual propensities can affect growth rates and population sizes, we hypothesized that this might also affect population oscillations. Here, we studied the dynamical behaviour of B. calyciflorus clones representing either CPs (regularly inducing sex) or obligate parthenogens (OPs). We found that the amplitudes of population cycles to be increased in OPs at low nutrient levels. Several other population dynamic parameters seemed unaffected. This suggests that reproductive mode might be an important additional variable to be considered in future studies of population oscillations.     

What is an apex predator?

Large ‘apex’ predators influence ecosystems in profound ways, by limiting the density of their prey and controlling smaller ‘mesopredators’. The loss of apex predators from much of their range has lead to a global outbreak of mesopredators, a process known as ‘mesopredator release’ that increases predation pressure and diminishes biodiversity. While the classifications apex‐ and meso‐predator are fundamental to current ecological thinking, their definition has remained ambiguous. Trophic cascades theory has shown the importance of predation as a limit to population size for a variety of taxa (top–down control). The largest of predators however are unlikely to be limited in this fashion, and their densities are commonly assumed to be determined by the availability of their prey (bottom–up control). However, bottom–up regulation of apex predators is contradicted by many studies, particularly of non‐hunted populations. We offer an alternative view that apex predators are distinguishable by a capacity to limit their own population densities (self‐regulation). We tested this idea using a set of life‐history traits that could contribute to self‐regulation in the Carnivora, and found that an upper limit body mass of 34 kg (corresponding with an average mass of 13–16 kg) marks a transition between extrinsically‐ and self‐regulated carnivores. Small carnivores share fast reproductive rates and development and higher densities. Large carnivores share slow reproductive rates and development, extended parental care, sparsely populated territories, and a propensity towards infanticide, reproductive suppression, alloparental care and cooperative hunting. We discuss how the expression of traits that contribute to self‐regulation (e.g. reproductive suppression) depends on social stability, and highlight the importance of studying predator–prey dynamics in the absence of predator persecution. Self‐regulation in large carnivores may ensure that the largest and the fiercest do not overexploit their resources.     

Effects of the probability of a predator catching prey on predator–prey system stability

To understand the effect of the probability of a predator catching prey, P_catch, on the stability of the predator–prey system, a spatially explicit lattice model consisting of predators, prey, and grass was constructed. The predators and prey randomly move on the lattice space, and the grass grows according to its growth probability. When a predator encounters prey, the predator eats the prey in accordance with the probability P_catch. When a prey encounters grass, the prey eats the grass. The predator and prey give birth to offspring according to a birth probability after eating prey or grass, respectively. When a predator or prey is initially introduced or newly born, its health state is set at a high given value. This health state decreases by one with every time step. When the state of an animal decreases to less than zero, the individual dies and is removed from the system. Population densities for predator and prey fluctuated significantly according to P_catch. System stability was characterized by the standard deviation ? of the fluctuation. The simulation results showed that ? for predators increased with an increase of P_catch; ? for prey reached a maximum at P_catch = 0.4; and ? for grass fluctuated little regardless of P_catch. These results were due to the tradeoff between P_catch and the predator–prey encounter rate, which represents the degree of interaction between predator and prey and the average population density, respectively.     

Geometric optimization for prey–predator strategies

This paper investigates several strategies for prey and predator in both bounded and unbounded domains, assuming they have the same speed. The work describes how the prey should move to escape from the predator and how predator should move to catch the prey. The approach is agent-based and explicitly tracks movement of individuals as prey and predator. We show that the prey escapes one or two competing predators, while might be caught in the case of three predators. The paper also describes a strategy for finding a well camouflaged static prey which emits signals.     

Diet choice and predator—prey dynamics

Summary We compare the dynamics of predator-prey systems with specialist predators or adaptive generalist predators that base diet choice on energy-maximizing criteria. Adaptive predator behaviour leads to functional responses that are influenced by the relative abundance of alternate prey. This results in the per capita predation risk being positively density-dependent near points of diet expansion. For a small set of parameter values, systems with adaptive predators can be locally stable whereas systems with specialist predators would be unstable. This occurs mainly when alternate prey have low enough profitability that predators cannot sustain themselves indefinitely when feeding on alternate prey. Local stability of systems with adaptive predator behaviour is inversely related to the goodness of fit to optimal diet choice criteria. Hence, typical patterns of partial prey preference are more stabilizing than perfect optimal diet selection. Locally stable systems with adaptive predators are often globally unstable, converging on limit cycles for many initial population densities. The small range of parameter combinations and initial population densities leading to stable equilibria suggest that adaptive diet selection is unlikely to be a ubiquitous stabilizing factor in trophic interactions.     

Fading out of vole and predator cycles?

Northern voles and lemmings are famous for their spectacular multiannual population cycles with high amplitudes. Such cyclic vole populations in Scandinavia have shown an unexpected and marked long-term decline in density since the early 1970s, particularly with a marked shift to lower spring densities in the early 1980s. The vole decline, mainly characterized by a strongly decreased rate of change in numbers over winter, is associated with an increased occurrence of mild and wet winters brought about by a recent change in the North Atlantic Oscillation. This has led to a decrease in winter stability and has shortened the period with protective snow cover, the latter considered as an important prerequisite for the occurrence of multiannual, high-amplitude cycles in vole populations. Although the vole decline is predicted to be negative for predators' reproduction and abundance, empirical data showing this are rare. Here we show that the dynamics of a predator-prey system (Tengmalm's owl, Aegolius funereus, and voles), have in recent years gradually changed from 3-4 yr, high-amplitude cycles towards more or less annual fluctuations only.     

Individual behavioral variation in predator–prey models

The role of individual behavioral variation in community dynamics was studied. Behavioral variation in this study does not refer to differences in average responses (e.g., average response between presence and absence of antipredator behavior). Rather it refers to the variation around the average response that is not explained by trivial experimental treatments. First, the effect of behavioral variation was examined based on Jensen’s inequality. In cases of commonly used modeling framework with type II functional response, neglecting behavioral variation (a component of encounter rate) causes overestimation of predation effects. The effect of this bias on community processes was examined by incorporating the behavioral variation in a commonly used consumer-resource model (Rosenzweig–MacArthur model). How such a consideration affects a model prediction (paradox of enrichment) was examined. The inclusion of behavioral variation can both quantitatively and qualitatively alter the model characteristics. Behavioral variation can substantially increase the stability of the community with respect to enrichment.     

Viable populations in a prey–predator system

 Lotka–Volterra equations are considered a dynamical game, where the phenotypes of the predator and of the prey can vary. This differs from the usual procedure of specifying as a priori laws according to which strategies are supposed to change. The question at stake is the survival of each of the species, instead of the maximization of a given pay-off by each player, as it is commonly discussed in games. The predator needs the prey, while the prey can survive without the predator. These obvious and simplistic constraints are enough to shape the regulation of the system: notably, the largest closed set of initial conditions can be delineated, from which there exists at least one evolutionary path where the population can avoid extinction forever. To these so-called viable trajectories, viable strategies are associated, respectively for the prey or for the predator. A coexistence set can then be defined. Within this set and outside the boundary, strategies can vary arbitrarily within given bounds while remaining viable, whereas on the boundary, only specific strategies can guarantee the viability of the system. Thus, the largest set can be determined, outside of which strategies will never be flexible enough to avoid extinction. Received 2 May 1995; received in revised form 15 August 1995     

Metapopulation dynamics for spatially extended predator–prey interactions

Traditional metapopulation theory classifies a metapopulation as a spatially homogeneous population that persists on neighboring habitat patches. The fate of each population on a habitat patch is a function of a balance between births and deaths via establishment of new populations through migration to neighboring patches. In this study, we expand upon traditional metapopulation models by incorporating spatial heterogeneity into a previously studied two-patch nonlinear ordinary differential equation metapopulation model, in which the growth of a general prey species is logistic and growth of a general predator species displays a Holling type II functional response. The model described in this work assumes that migration by generalist predator and prey populations between habitat patches occurs via a migratory corridor. Thus, persistence of species is a function of local population dynamics and migration between spatially heterogeneous habitat patches. Numerical results generated by our model demonstrate that population densities exhibit periodic plane-wave phenomena, which appear to be functions of differences in migration rates between generalist predator and prey populations. We compare results generated from our model to results generated by similar, but less ecologically realistic work, and to observed population dynamics in natural metapopulations.     

Are multiple predator effects directed by prey availability?

Antagonistic/synergistic interactions among predators foraging on the same prey have been assumed to play a major role in shaping community structure. Studies in systems with multiple predator species have shown that the strength of these interactions may not be predictable and is largely dependent on individual behavioural traits, species density and habitat complexity. Although the association of prey consumption and satiation of a foraging predator has long been recognized, there has been relatively little research on how prey availability affects multiple predators’ effects. In this work, we present a framework to investigate the variation in two coexisting/competing predators’ effects on prey risk as affected by the prey availability rate. Functional responses by each predator species were first studied in single-predator treatments. Then, the intra- and inter-specific competition was investigated by employing additive and substitutative experimental designs to highlight the nature of multiple effects. Intra- and interspecific interactions were found to be similar and there was risk reduction, and risk enhancement for the prey at intermediate and high levels, respectively, according to the multiplicative risk model (MRM). The results indicated that when similar predators are concerned, the outcomes of MRM may vary according to the functional response curve of these predators. Thus, studies involving a wide range of prey densities are required to explore the nature of interactions. Moreover, this kind of experimental data can contribute to unravelling complexities in theoretical approaches by earlier studies and ultimately promote understanding the effect of multiple predators on prey population regulation.     

Red queen dynamics in specific predator–prey systems

The dynamics of a predator–prey system are studied, with a comparison of discrete and continuous strategy spaces. For a \(2 \times 2\) system, the average strategies used in the discrete and continuous case are shown to be the same. It is further shown that the inclusion of constant prey switching in the discrete case can have a stabilising effect and reduce the number of available predator types through extinction.     

A nonlocal kinetic model for predator–prey interactions

We extend the aggregation model from Fetecau (2011) by adding a field of vision to individuals and by including a second species. The two species, assumed to have a predator–prey relationship, have dynamics governed by nonlocal kinetic equations that include advection and turning. The latter is the main mechanism for aggregation and orientation, which results from interactions among individuals of the same species as well as predator–prey relationships. We illustrate numerically a diverse set of predator–prey behaviors that can be captured by this model. We show that a prey’s escape outcome depends on the social interactions between its group members, the prey’s field of vision and the sophistication of the predator’s hunting strategies.     

Summer predation rates on ungulate prey by a large keystone predator: how many ungulates does a large predator kill?

Estimates of predation rates by large predators can provide valuable information on their potential impact on their ungulate prey populations. This is especially the case for pumas Puma concolor and its main prey, mule deer Odocoileus hemionus . However, only limited information on predation rates of pumas exist where mule deer are the only ungulate prey available. I used VHF telemetry data collected over 24-h monitoring sessions and once daily over consecutive days to derive two independent estimates of puma predation rates on mule deer where they were the only large prey available. For the 24-h data, I had 48 time blocks on female pumas with kittens, 43 blocks on females without kittens and 30 blocks on males. For the daily consecutive data, the average number of consecutive days followed was 51.5±4.2 days. There were data on five female pumas with kittens, five pregnant females and nine females without kittens. Predation rates over an average month of 30 days from the 24-h monitoring sessions were 2.0 mule deer per puma month for males (15.1 days per kill), 2.1 mule deer per puma month (14.3 days per kill) for females without kittens and 2.5 mule deer per puma month (12.0 days per kill) for pregnant females and females with kittens. For the consecutive daily data, females without kittens had an estimated predation rate of 2.1±0.14 mule deer per puma month (14.9±0.90 days per kill). Pregnant and females with kittens had predation rates of 2.7±0.18 and 2.6±0.21 mule deer per puma month, respectively (11.4±0.72 and 12.0±1.1 days per kill, respectively). Predation rates estimated in this study compared with those estimated by energetic demand for pumas in the study area but were lower than other field derived estimates. These data help increase our understanding of predation impacts of large predators on their prey.     

Chemically mediated learning in juvenile rainbow trout. Does predator odour pH influence intensity and retention of acquired predator recognition?

The prediction that variability in ambient pH will influence the intensity and retention of learned predator recognition in juvenile rainbow trout Oncorhynchus mykiss was tested under laboratory conditions. Juvenile rainbow trout were conditioned to recognize the odour of a novel predator at pH 6·0 or 7·0 and then tested for learned recognition of the predator odour at pH 6·0 or 7·0 at 2 or 7 days post-conditioning. When tested 2 days post-conditioning, rainbow trout exhibited a significant learned antipredator response regardless of predator odour pH. The response was stronger, however, when the test pH matched the conditioning pH. When tested 7 days post-conditioning, rainbow trout only exhibited a learned response when conditioning and testing pH were the same. These results demonstrate that episodic acidification may impair the strength and retention of acquired predator recognition learning. Given the demonstrated survival benefits associated with learned predator recognition in prey fishes, such impairment will probably have considerable negative impacts at both individual and population levels.     

Parametric analysis of the ratio-dependent predator–prey model

We present a complete parametric analysis of stability properties and dynamic regimes of an ODE model in which the functional response is a function of the ratio of prey and predator abundances. We show the existence of eight qualitatively different types of system behaviors realized for various parameter values. In particular, there exist areas of coexistence (which may be steady or oscillating), areas in which both populations become extinct, and areas of "conditional coexistence" depending on the initial values. One of the main mathematical features of ratio-dependent models, distinguishing this class from other predator-prey models, is that the Origin is a complicated equilibrium point, whose characteristics crucially determine the main properties of the model. This is the first demonstration of this phenomenon in an ecological model. The model is investigated with methods of the qualitative theory of ODEs and the theory of bifurcations. The biological relevance of the mathematical results is discussed both regarding conservation issues (for which coexistence is desired) and biological control (for which extinction is desired).     

Community-driven dispersal in an individual-based predator–prey model

We present a spatial, individual-based predator–prey model in which dispersal is dependent on the local community. We determine species suitability to the biotic conditions of their local environment through a time and space varying fitness measure. Dispersal of individuals to nearby communities occurs whenever their fitness falls below a predefined tolerance threshold. The spatiotemporal dynamics of the model is described in terms of this threshold. We compare this dynamics with the one obtained through density-independent dispersal and find marked differences. In the community-driven scenario, the spatial correlations in the population density do not vary in a linear fashion as we increase the tolerance threshold. Instead we find the system to cross different dynamical regimes as the threshold is raised. Spatial patterns evolve from disordered, to scale-free complex patterns, to finally becoming well-organized domains. This model therefore predicts that natural populations, the dispersal strategies of which are likely to be influenced by their local environment, might be subject to complex spatiotemporal dynamics.     

Does an opportunistic predator preferentially attack nonvigilant prey?

The dilution effect as an antipredation behaviour is the main theoretical reason for grouping in animals and states that all individuals in a group have an equal risk of being predated if equally spaced from each other and the predator. Stalking predators, however, increase their chance of attack success by preferentially targeting nonvigilant individuals, potentially making relative vigilance rates in a group relatively important in determining predation compared with the dilution effect. Many predators, however, attack opportunistically without stalking, when targeting of nonvigilant individuals may be less likely, so that the dilution effect will then be a relatively more important antipredation reason for grouping. We tested whether an opportunistically hunting predator, the sparrowhawk, Accipiter nisus, preferentially attacked vigilant or feeding prey models presented in pairs. We found that sparrowhawks attacked vigilant and feeding mounts at similar frequencies. Our results suggest that individuals should prioritize maximizing group size or individual vigilance dependent on the type of predator from which they are at risk. When the most likely predator is a stalker, individuals should aim to have the highest vigilance levels in a group, and there may be relatively little selective advantage to being in the largest group. In contrast, if the most likely predator is an opportunist, then individuals should simply aim to be in the largest group and can also spend more time foraging without compromising predation risk. For most natural systems this will mean a trade-off between the two strategies dependent on the frequency of attack of each predator type. Copyright 2003 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.     

Bacterial predator–prey dynamics in microscale patchy landscapes

Soil is a microenvironment with a fragmented (patchy) spatial structure in which many bacterial species interact. Here, we explore the interaction between the predatory bacterium Bdellovibrio bacteriovorus and its prey Escherichia coli in microfabricated landscapes. We ask how fragmentation influences the prey dynamics at the microscale and compare two landscape geometries: a patchy landscape and a continuous landscape. By following the dynamics of prey populations with high spatial and temporal resolution for many generations, we found that the variation in predation rates was twice as large in the patchy landscape and the dynamics was correlated over shorter length scales. We also found that while the prey population in the continuous landscape was almost entirely driven to extinction, a significant part of the prey population in the fragmented landscape persisted over time. We observed significant surface-associated growth, especially in the fragmented landscape and we surmise that this sub-population is more resistant to predation. Our results thus show that microscale fragmentation can significantly influence bacterial interactions.     

Seals and fisheries: A case for predator control?

The impact of seals on fisheries has been a controversial matter. This article examines the degree to which a new Canadian Royal Commission Report has been able to judge between the opposing views of the problem. It also examines the implications of the Commission's results for the more general question of controlling predators for the benefit of prey species, or more accurately, the human harvesters of those species. Finally, it touches very briefly on the possible clash of views between the public at large and those who make their living from the sea.