Barney Luttbeg

REVISITING THE CLASSICS: CONSIDERING NONCONSUMPTIVE EFFECTS IN TEXTBOOK EXAMPLES OF PREDATOR-PREY INTERACTIONS

Predator effects on prey dynamics are conventionally studied by measuring changes in prey abundance attributed to consumption by predators. We revisit four classic examples of predator-prey systems often cited in textbooks and incorporate subsequent studies of nonconsumptive effects of predators (NCE), defined as changes in prey traits (e.g., behavior, growth, development) measured on an ecological time scale. Our review revealed that NCE were integral to explaining lynx-hare population dynamics in boreal forests, cascading effects of top predators in Wisconsin lakes, and cascading effects of killer whales and sea otters on kelp forests in nearshore marine habitats. The relative roles of consumption and NCE of wolves on moose and consequent indirect effects on plant communities of Isle Royale depended on climate oscillations. Nonconsumptive effects have not been explicitly tested to explain the link between planktonic alewives and the size structure of the zooplankton, nor have they been invoked to attribute keystone predator status in intertidal communities or elsewhere. We argue that both consumption and intimidation contribute to the total effects of keystone predators, and that characteristics of keystone consumers may differ from those of predators having predominantly NCE. Nonconsumptive effects are often considered as an afterthought to explain observations inconsistent with consumption-based theory. Consequently, NCE with the same sign as consumptive effects may be overlooked, even though they can affect the magnitude, rate, or scale of a prey response to predation and can have important management or conservation implications. Nonconsumptive effects may underlie other classic paradigms in ecology, such as delayed density dependence and predator-mediated prey coexistence. Revisiting classic studies enriches our understanding of predator-prey dynamics and provides compelling rationale for ramping up efforts to consider how NCE affect traditional predator-prey models based on consumption, and to compare the relative magnitude of consumptive and NCE of predators.

Environmental tolerance, heterogeneity, and the evolution of reversible plastic responses.

Phenotypic plasticity is a key factor for the success of organisms in heterogeneous environments. Although many forms of phenotypic plasticity can be induced and retracted repeatedly, few extant models have analyzed conditions for the evolution of reversible plasticity. We present a general model of reversible plasticity to examine how plastic shifts in the mode and breadth of environmental tolerance functions (that determine relative fitness) depend on time lags in response to environmental change, the pattern of individual exposure to inducing and noninducing environments, and the quality of available information about the environment. We couched the model in terms of prey‐induced responses to variable predation regimes. With longer response lags relative to the rate of environmental change, the modes of tolerance functions in both the presence or absence of predators converge on a generalist strategy that lies intermediate between the optimal functions for the two environments in the absence of response lags. Incomplete information about the level of predation risk in inducing environments causes prey to have broader tolerance functions even at the cost of reduced maximal fitness. We give a detailed analysis of how these factors and interactions among them select for joint patterns of mode and breadth plasticity.

Predator and Prey Models with Flexible Individual Behavior and Imperfect Information

To begin identifying what behavioral details might be needed to characterize community dynamics and stability, we examined the effect of prey behavioral responses to predation risk on community dynamics and stability. We considered the case of prey altering their foraging effort to trade off energy gain and predation risk. We used state‐dependent dynamic optimization to calculate the optimal trade‐off for four models of prey behaviorally responding to predation risk. We consider a fixed behavior model in which prey use constant levels of foraging effort and three flexible behavior models in which prey change their foraging effort according to their physiological state and their perceived level of predation risk. Flexible behavior was destabilizing at the community level as evidenced by higher predator‐prey oscillations and lower community persistence times. The mechanisms by which prey estimated predation risk also affected community stability. We found that community dynamics resulting from prey with flexible behavior and fixed perception of risk approximated community dynamics resulting from prey with flexible behavior and perfect information about predation risk, however neither approximated the community dynamics resulting from prey with flexible behavior and flexible perception of risk. Thus, whether it might be possible to abstract complex behavior with simpler rules when modeling community dynamics depends on the prey’s behavioral mechanisms, which are empirically poorly known.

PREY STATE AND EXPERIMENTAL DESIGN AFFECT RELATIVE SIZE OF TRAIT‐ AND DENSITY‐MEDIATED INDIRECT EFFECTS

Indirect effects, in which one species affects another through an intermediate species, can occur by changes in either the density or the traits of the intermediate species. Ecologists have focused primarily on density-mediated indirect effects, but have become interested in quantifying the relative sizes of trait- and density-mediated indirect effects. We examined how state-dependent prey behavior and experimental protocols affect the sizes of measured trait- and density-mediated indirect effects in a three-species chain (pred- ator, prey, and resource). We found that the size of trait-mediated indirect effects relative to the size of density-mediated indirect effects increases as the level of resources increases. We also found that the relative contributions of trait- and density-mediated indirect effects depend on the timing of manipulations in relation to the state of individuals and their vulnerability to predators. In addition, we found that trait-mediated indirect effects that have been measured during a portion of a season may diminish or disappear when measured across a whole season because of behavioral compensation. These results show that the relative contributions of trait- and density-mediated indirect effects in a system will be variable, and experiments need to be designed to account for dynamic systems.

PREDATOR AND PREY SPACE USE: DRAGONFLIES AND TADPOLES IN AN INTERACTIVE GAME

Predator and prey spatial distributions have important population and community level consequences. However, little is known either theoretically or empirically about behavioral mechanisms that underlie the spatial patterns that emerge when predators and prey freely interact. We examined the joint space use and behavioral rules governing movement of freely interacting groups of odonate (dragonfly) predators and two size classes of anuran (tadpole) prey in arenas containing two patches with different levels of the preys resource. Predator and prey movement and space use was quantified both when they were apart and together. When apart from predators, large tadpoles strongly preferred the high resource patch. When apart from prey, dragonflies weakly preferred the high resource patch. When together, large prey shifted to a uniform distribution, while predators strongly preferred the high resource patch. These patterns qualitatively fit the predictions of several three trophic level, ideal free distribution models. In contrast, the space use of small prey and predators did not deviate from uniform. Three measures of joint space use (spatial correlations, overlap, and co-occurrence) concurred in suggesting that prey avoidance of predators was more important than predator attraction to prey in determining overall spatial patterns. To gain additional insight into behavioral mechanisms, we used a model selection approach to identify behavioral movement rules that can potentially explain the observed, emergent patterns of space use. Prey were more likely to leave patches with more predators and more conspecific competitors; resources had relatively weak effects on prey movements. In contrast, predators were more likely to leave patches with low resources (that they do not consume) and more competing predators; prey had relatively little effect on predator movements. These results highlight the importance of investigating freely interacting predators and prey, the potential for simple game theory models to predict joint spatial distributions, and the utility of using model choice methods to identify potential key factors that govern movement.

Evolution of animal personalities.

Arising from: M. Wolf, G. S. van Doorn, O. Leimar & F. J. Weissing 447, 581–584 (2007)10.1038/nature05835; Wolf et al. replyWolf et al. propose a model to explain the existence of animal personalities, consistent with behavioural differences among individuals in various contexts—their explanation is counter-intuitive and cogent. However, all models have their limits, and the particular life-history requirements of this one may be unclear. Here we analyse their model and clarify its organismal scope.

PREDATOR AND PREY HABITAT SELECTION GAMES: THE EFFECTS OF HOW PREY BALANCE FORAGING AND PREDATION RISK

The spatial distributions of predators and prey can be shaped by both intraand interspecific games. Most predator‐prey studies, however, have ignored the interspecific game by focusing on how either predators or prey distribute themselves while holding the distribution of the other species fixed. We use genetic algorithms to examine how the distributional outcome of the game between predators and prey depends on how prey balance the costs of predation risk and the benefits of foraging success. We construct two prey fitness functions. The first prey fitness function has prey reproducing when they reach a threshold mass, which leads to prey choosing patches by minimizing the ratio of predation and foraging rates (µ/f). The second prey fitness function has prey reproducing at the end of a season with mass-dependent reproductive success, which leads to prey choosing patches by maximizing their increase in reproductive value over time. When prey minimize µ/f, predator and prey distributions are unaffected by the overall level of predation risk. In contrast, when prey maximize their increase in reproductive value, under conditions with low predation risk the distributions of prey and predators are shaped mainly by prey competition and the distribution of resources, and as the overall level of predation risk increases the distribution of prey is increasingly shaped by the distribution of predators. Thus, the dynamics of how predators and prey distribute themselves and interact may depend on factors that affect the overall level of predation risk, such as per predator capture rates, predator densities, and shelter from predation.

The effects of variable predation risk on foraging and growth: Less risk is not necessarily better

There is strong evidence that the way prey respond to predation risk can be fundamentally important to the structuring and functioning of natural ecosystems. The majority of work on such nonconsumptive predator effects (NCEs) has examined prey responses under constant risk or constant safety. Hence, the importance of temporal variation in predation risk, which is ubiquitous in natural systems, has received limited empirical attention. In addition, tests of theory (e.g., the risk allocation hypothesis) on how prey allocate risk have relied almost exclusively on the behavioral responses of prey to variation in risk. In this study, we examined how temporal variation in predation risk affected NCEs on prey foraging and growth. We found that high risk, when predictable, was just as energetically favorable to prey as safe environments that are occasionally pulsed by risk. This pattern emerged because even episodic pulses of risk in otherwise safe environments led to strong NCEs on both foraging and growth. However, NCEs more strongly affected growth than foraging, and we suggest that such effects on growth are most important to how prey ultimately allocate risk. Hence, exclusive focus on behavioral responses to risk will likely provide an incomplete understanding of how NCEs shape individual fitness and the dynamics of ecological communities.

Comparing alternative models to empirical data: Cognitive models of western scrub-jay foraging behavior

Animals often select one item from a set of candidates, as when choosing a foraging site or mate, and are expected to possess accurate and efficient rules for acquiring information and making decisions. Little is known, however, about the decision rules animals use. We compare patterns of information sampling by western scrub‐jays (Aphelocoma californica) when choosing a nut with three decision rules: best of n (BN), flexible threshold (FT), and comparative Bayes (CB). First, we use a null hypothesis testing approach and find that the CB decision rule, in which individuals use past experiences to make nonrandom assessment and choice decisions, produces patterns of behavior that more closely correspond to observed patterns of nut sampling in scrub‐jays than the other two rules. This approach does not allow us to quantify how much better CB is at predicting scrub‐jay behavior than the other decision rules. Second, we use a model selection approach that uses Akaike Information Criteria to quantify how well alternative models approximate observed data. We find that the CB rule is much more likely to produce the observed patterns of scrub‐jay behavior than the other rules. This result provides some of the best empirical evidence of the use of Bayesian information updating by a nonhuman animal.

Modeling the behavior of the northern anchovy, Engraulis mordax, as a schooling predator exploiting patchy prey

Abstract Extensive data sets on the bioenergetics of the northern anchovy, Engraulis mordax, and the patchy food distribution in its natural habitat allow its foraging dynamics to be inferred by modeling using techniques from population biology and behavioral ecology. The behavioral model consistently predicts that E. mordax grows much more slowly than would be expected with a pure, net-energy intake rate maximization strategy. The reduced growth rates could result from the fish avoiding zooplankton patches, where they are under increased predation risk, by swimming slowly in the waters between zooplankton patches. The combinations of growth rates and daily instantaneous mortality rates generated by the behavioral model are internally consistent with a Lefkovitch matrix population model, which includes an early juvenile stage of a stable and stationary population. Several novel and testable predictions are made by the behavioral model, including: (1) anchovies swim very slowly between zooplankton patch encounters; (2) within a patch fish swim very rapidly while searching for prey; and (3) fish often leave zooplankton patches before totally filling their stomachs. Given these encouraging initial results, the behavioral modeling approach appears to be a valuable technique for examining how potential habitat changes due to global warming may affect fish behavior and populations. Several such scenarios are proposed and discussed.