State-dependent mortality can enhance behavioral unpredictability.

BACKGROUND: Although behavioral unpredictability is widely described within-individual variability in behavior, its adaptive significance is little understood. Using a dynamic state variable model, this study investigated the conditions under which behavioral unpredictability (a component of within-individual variability) in foraging behavior is advantageous. The model considers a situation in which a forager forages for a fixed period, represented by discrete time steps. The outcome of foraging may change the level of a state (e.g., size and fat storage) of the forager at each time step, and variability in the foraging outcome is assumed to be positively correlated with behavioral unpredictability. The probability of death at each time step is influenced by the state at the same time step. Reproduction occurs after all the foraging steps and is influenced by the state level of a forager at the time of reproduction. According to the expected utility hypothesis, the relationship (e.g., curvature) between the state and fitness will determine the role of behavioral unpredictability. In the model, the relationship was obtained by using the backward iteration method for each foraging time step. RESULTS: State-dependent mortality adds curvature to the relationship between the state and fitness, which makes the effect of behavioral unpredictability on fitness either positive or negative. This conclusion holds for any state-dependent mortality (i.e., as long as mortality is not independent of the state factor). Given that state-dependent mortality is commonly described, conditions that benefit behavioral unpredictability are likely also common. CONCLUSIONS: When mortality depends on a state that is influenced by behavior, conditions that favor behavioral unpredictability may become common. How behavioral unpredictability influences the variability of behavioral outcomes is as important as how it influences the expectation of behavioral outcomes when studying the adaptive significance of behavioral unpredictability.

Demographic stochasticity alters the outcome of exploitation competition.

Temporal variability in resource density is one of the mechanisms that facilitate coexistence between competitors. This study examines whether demographic stochasticity as a source of resource fluctuation can facilitate coexistence. The dynamics of a deterministic model (without demographic stochasticity) and a stochastic individual-based model (with demographic stochasticity) are compared. The deterministic model is an exploitation competition module consisting of two consumer species and one resource. The Gillespie algorithm is used to simulate demographic stochasticity in the corresponding individual-based model. The parameters of the models are chosen to represent cases where the deterministic model shows competitive exclusion according to the R(⁎) rule and exhibits only stable equilibrium dynamics based on any combinations of the species. The analysis of the individual-based model shows that demographic stochasticity induces persistent population cycles between a consumer and the resource (i.e., when one of the consumers is absent), and this resource fluctuation allows the two consumers to coexist. Coexistence becomes possible through emerging tradeoffs that allow an inferior species (predicted by the deterministic model) to become competitively dominant (e.g., deviation of the R(⁎) rule). These tradeoffs are useful for interpreting apparently contradicting empirical observations.

Flexible components of functional responses.

1. The functional response of predators describes the rate at which a predator consumes prey and is an important determinant of community dynamics. Despite the importance, most empirical studies have considered a limited number of models of functional response. In addition, the models often make strong assumptions about the pattern of predation processes, even though functional responses can potentially exhibit a wide variety of patterns. 2. In addition to the limited model consideration, model selections of functional response models cannot tease apart the components of predation (i.e. capture rate and handling time) when flexible traits are considered because it is always possible that many different combinations of the capture rate and handling time can lead to the same predation rate. 3. This study directly examined the capture rate and handling time of functional response in a mite community. To avoid the model selection problem, the searching and handling behaviour data were collected. The model selection was applied directly to these two components of predation data. Commonly used functional response models and models that allow for more flexible patterns were compared. 4. The results indicated that assumptions of the commonly used models were not supported by the data, and a flexible model was selected as the best model. These results suggest the need to consider a wider variety of predation patterns when characterizing a functional response. Without making a strong assumption (e.g. static handling time), model selections on functional response models cannot be used to make reliable inferences on the predation mechanisms.

Adaptive and variable intraguild predators facilitate local coexistence in an intraguild predation module.

BACKGROUND: Intraguild predation (IGP) is common in nature, but its ecological role is still illusive. A number of studies have investigated a three species IGP module that consists of an intraguild predator, intraguild prey, and resource species in which the intraguild predator and the intraguild prey exploitatively compete for the resource while the intraguild predator also consumes the intraguild prey. A common prediction of models of the IGP module is that the coexistence of the species is difficult, which is considered inconsistent to the ubiquity of IGP in nature. This study revisits the IGP module and provides an alternative coexistence mechanism by focusing on a commonly used analysis method (i.e., invasion analysis) in light of individual variation in adaptive behavior. RESULTS: Invasion analysis underestimates the possibility of coexistence regardless of the presence or absence of adaptive behavior. Coexistence is possible even when invasion analysis predicts otherwise. The underestimation by invasion analysis is pronounced when the intraguild predator forages adaptively, which is even further pronounced when the expression of foraging behavior is variable among intraguild predators. CONCLUSIONS: The possibility of coexistence in the IGP module is greater than previously thought, which may have been partly due to how models were analyzed. Inconsistent conclusions may result from the same model depending on how the model is analyzed. Individual variation in adaptive behavior can be an important factor promoting the coexistence of species in IGP modules.

Predator-prey population dynamics may induce the evolutionary dynamics of behavioral unpredictability.

Behavioral unpredictability (within-individual behavioral variability that cannot be explained by extrinsic and intrinsic factors) has been observed in a wide variety of species, but its adaptive significance is not well understood. This study examines the possibility that behavioral unpredictability is maintained through predator-prey population dynamics. An individual-based model was constructed to track the status of individual predators. The handling time of a predator is characterized by its expected value and unpredictability, which are heritable, and each predator features a unique combination of these characteristics. A discrete generation model in which one prey species and one predator species interact was constructed. The model showed that the evolutionarily stable strategy (ESS) of handling time is associated with no behavioral unpredictability and that the ESS handling time depends on the densities of the prey and predators. When populations exhibit cyclic dynamics, the ESS also changes along with the population dynamics, thereby creating mismatches between the traits of predators and the ESS because the dynamics of the ESS and population are faster than the evolution of the handling time traits. This mismatch can generate conditions in which individuals with behavioral unpredictability are at least transiently selected because of the topology of the fitness landscape. However, the model also showed that the selection strength of behavioral unpredictability is weak and can be overruled by inherent stochastic processes.

Searching of Underground Host Patches by a Pupal Parasitoid.

When hosts are distributed in discrete patches, ways in which parasitoids search and move between patches affect variability in parasitism risk among hosts and host-parasitoid population dynamics. This study examined the patch searching behavior of the solitary pupal parasitoid Dirhinus giffardii (Silvestri) (Hymenoptera: Chalcididae) on its host Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) which pupates underground. In a series of two laboratory experiments, host patches were created by burying pupae in peat moss, and the foraging behavior of the parasitoid was recorded. If D. giffardii can detect underground patches, the parasitoid would preferentially exploit high quality patches where the quality of a patch is represented by the number of unparasitized hosts in the patch. The first experiment investigated the effect of patch size (i.e., number of hosts) and host status (whether hosts are parasitized or unparasitized) on patch searching behavior. Results showed parasitoids were more likely to exploit a large patch than a small patch regardless of host status. The second experiment examined the effect of relative locations of patches by establishing three patches (one large patch and two small patches with unequal inter-patch distances from the large patch). The probability of parasitism was lower for the small patch close to the large patch than the small patch far from the large patch. The parasitism patterns described in the experiments have important implications on the distribution of parasitism risk among hosts and population dynamics.

Uncertainty in foraging success and its consequences on fitness.

Optimal foraging models are commonly used to determine the strategy maximizing the proxies for fitness, such as foraging success. The strategies maximizing the proxy for fitness and fitness are assumed to be the same. However, this study shows that this assumption can be invalid when the relationship between the proxy for fitness and fitness is nonlinear and the foraging success is uncertain. A well-known prey choice model that uses long-term energy intake rate as the proxy for fitness was used as an example. This model considers a situation where predators predate on two types of prey that differ in quality, that is, one (primary prey) has higher quality than the other (alternative prey). A strategy can be represented by the probability of attacking alternative prey upon encounter while always attacking primary prey. The probability of attacking alternative prey that maximizes the expected rate of energy intake is either 0 or 1 depending on the density of primary prey (known as the zero-one rule). Meanwhile, the density of alternative prey has no influence on the optimal strategy. A simulation model was used to characterize the stochastic outcomes in the rate of energy intake in a finite foraging duration. The results revealed that foraging strategy influences the expected rate of energy intake and the uncertainty around the expectation. Consequently, the strategies maximizing the rate of energy intake and fitness may not be the same when the relationship between the rate of energy intake and fitness is nonlinear due to Jensen's inequality. Previous results such as the zero-one rule and the independence of the optimal strategy on the availability of alternative prey are no longer valid when fitness, rather than the proxy for fitness, is explicitly considered in a finite foraging duration.

Individual variation in prey choice in a predator-prey community.

One predator-two prey community models are studied with an emphasis on individual variation in predator behavior. The predator behaves according to a well-known prey choice model. The behavioral model predicts that predators should always attack the primary prey (more profitable prey of the two), but only attack the alternative prey (less profitable prey of the two) when the density of the primary prey is below a threshold density. The predator that accepts the alternative prey does not discriminate between the primary and alternative prey (all-or-nothing preference for the alternative prey). However, empirical studies do not result in clear all-or-nothing responses. Previous models examined the relaxation of the all-or-nothing response by assuming partial preference (e.g., predators preferentially forage on the primary prey even when they also attack the alternative prey). In this study, I consider individual variation in two predator traits (prey density perception and handling time) as the sources of the variation in the threshold density, which can make empirical data appear deviated from the expectation. I examine how community models with partial preference and individual variation differ in their dynamics and show that the differences can be substantial. For example, the dynamics of a model based on individual variation can be more stable (e.g., stable in a wider parameter region) than that of a model based on partial preference. As the general statistical property (Jensen's inequality) is a main factor that causes the differences, the results of the study have general implications to the interpretation of models based on average per-capita rates.

Biphasic activity of a jumping spider.

Individual variation is a ubiquitous and important factor that affects ecological dynamics. This study examined individual variation in the nest-use pattern of the jumping spider Phidippus audax. Although the jumping spider is a diurnal species, field observations in this study revealed that the majority of individuals remained in their nests during the day. An accompanying examination of the hunger level of the spiders revealed that spiders that remained in nests were more starved than those observed outside nests. If spiders actively forage when they are starved, as has been suggested by previous studies, one would expect to see the opposite trend (i.e., spiders that remained in nests are more satiated). Thus, the pattern observed in the field contradicts the known behavioral pattern of the spiders. An individual-based model was used to investigate the behavioral mechanism of the spider and the discrepancy found in the observations. A basic assumption of the model is that spiders possess distinct inactive and active phases (biphasic activity pattern), and transitions between the two phases are regulated by the hunger level of the spider. Data from a laboratory experiment were used to examine the assumptions of the model partially. The model was able to capture patterns observed in the data, suggesting that the pattern of transitions in biphasic activity is an important trait of the foraging behavior of the jumping spider.

Fitness costs of an insecticide resistance and their population dynamical consequences in the oriental fruit fly.

Naled is a commonly used insecticide for controlling populations of the oriental fruit fly, Bactrocera dorsalis (Hendel), in Taiwan and other countries. B. dorsalis has developed resistance to the insecticide, and the resistance management is an important issue. Ecological effects (e.g., fitness costs) of the resistance, when fully understood, can be used for the resistance management. This study examined the effects of the insecticide resistance on important life history traits (i.e., survival rates, stage durations, and fecundity) of the oriental fruit fly by comparing the traits of insecticide resistant individuals and susceptible individuals. Population dynamical properties were also examined using a stage-structured matrix model that was parameterized with the empirical data. The results revealed that susceptible individuals had shorter stage durations (e.g., grew faster) and reproduced more than resistant individuals. The average longevity of sexually mature susceptible adults was longer than that of sexually mature resistant adults. The matrix population model predicted that a population of the susceptible individuals would grow faster than a population of the resistant individuals in the absence of the insecticide. The sensitivity analysis of the model suggests that the sexually immature adult stage is a good candidate for controlling B. dorsalis populations.

Intraindividual variability in behavior shapes fitness landscapes.

Although intraindividual variability (IIV) in behavior is fundamental to ecological dynamics, the factors that contribute to the expression of IIV are poorly understood. Using an individual-based model, this study examined the effects of stochasticity on the evolution of IIV represented by the residual variability of behavior. The model describes a population of prey with nonoverlapping generations, in which prey take refuge upon encountering a predator. The strategy of a prey is characterized by the mean and IIV (i.e., standard deviation) of hiding duration. Prey with no IIV will spend the same duration hiding in a refuge at each predator encounter, while prey with IIV will have variable hiding durations among encounters. For the sources of stochasticity, within-generation stochasticity (represented by random predator encounters) and between-generation stochasticity (represented by random resource availability) were considered. Analysis of the model indicates that individuals with high levels of IIV are maintained in a population in the presence of between-generation stochasticity even though the optimal strategy in each generation is a strategy with no IIV, regardless of the presence or absence of within-generation stochasticity. This contradictory pattern emerges because the mean behavioral trait and IIV do not independently influence fitness (e.g., the sign of the selection gradient with respect to IIV depends on the mean trait). Consequently, even when evolution eventually leads toward a strategy with no IIV (i.e., the optimal strategy), greater IIV may be transiently selected. Between-generation stochasticity consistently imposes such transient selection and maintain high levels of IIV in a population.

Census timing alters stage duration distributions in matrix population models.

Matrix population models are widely used to study the dynamics of stage-structured populations. A census in these models is an event monitoring the number of individuals in each stage and occurs at discrete time intervals. The two most common methods used in building matrix population models are the prebreeding census and postbreeding census. Models using the prebreeding and postbreeding censuses assume that breeding occurs immediately before or immediately after the censuses, respectively. In some models such as age-structured models, the results are identical regardless of the method used, rendering the choice of method a matter of preference. However, in stage-structured models, where the duration of the first stage of life varies among newborns, a choice between the prebreeding and postbreeding censuses may result in different conclusions. This is attributed to the different first-stage duration distributions assumed by the two methods. This study investigated the difference emerging in the structures of these models and its consequence on conclusions of eigenvalue and elasticity analyses using two-stage models. Considerations required in choosing a modeling method are also discussed.

Network structural properties mediate the stability of mutualistic communities.

Key advances are being made on the structures of predator-prey food webs and competitive communities that enhance their stability, but little attention has been given to such complexity-stability relationships for mutualistic communities. We show, by way of theoretical analyses with empirically informed parameters, that structural properties can alter the stability of mutualistic communities characterized by nonlinear functional responses among the interacting species. Specifically, community resilience is enhanced by increasing community size (species diversity) and the number of species interactions (connectivity), and through strong, symmetric interaction strengths of highly nested networks. As a result, mutualistic communities show largely positive complexity-stability relationships, in opposition to the standard paradox. Thus, contrary to the commonly-held belief that mutualism's positive feedback destabilizes food webs, our results suggest that interplay between the structure and function of ecological networks in general, and consideration of mutualistic interactions in particular, may be key to understanding complexity-stability relationships of biological communities as a whole.

Stage duration distributions in matrix population models.

Matrix population models are a standard tool for studying stage-structured populations, but they are not flexible in describing stage duration distributions. This study describes a method for modeling various such distributions in matrix models. The method uses a mixture of two negative binomial distributions (parametrized using a maximum likelihood method) to approximate a target (true) distribution. To examine the performance of the method, populations consisting of two life stages (juvenile and adult) were considered. The juvenile duration distribution followed a gamma distribution, lognormal distribution, or zero-truncated (over-dispersed) Poisson distribution, each of which represents a target distribution to be approximated by a mixture distribution. The true population growth rate based on a target distribution was obtained using an individual-based model, and the extent to which matrix models can approximate the target dynamics was examined. The results show that the method generally works well for the examined target distributions, but is prone to biased predictions under some conditions. In addition, the method works uniformly better than an existing method whose performance was also examined for comparison. Other details regarding parameter estimation and model development are also discussed.

On quantitative measures of indirect interactions.

Indirect effects, whether density-mediated (DMII) or trait-mediated (TMII), have been recognized as potentially important drivers of community dynamics. However, empirical studies that have attempted to detect TMII or to quantify the relative strength of DMII and TMII in short-term studies have used a range of different metrics. We review these studies and assess both the consistency of a variety of different metrics and their robustness to (or ability to detect) ecological phenomena such as the dependence of forager behaviour on conspecific density. Quantifying indirect effects over longer time scales when behaviour and population density vary is more challenging, but also necessary if we really intend to incorporate indirect effects into predictions of long-term community dynamics; we discuss some problems associated with this effort and conclude with general recommendations for quantifying indirect effects.

Variation in foraging success among predators and its implications for population dynamics.

The effects of the expected predation rate on population dynamics have been studied intensively, but little is known about the effects of predation rate variability (i.e., predator individuals having variable foraging success) on population dynamics. In this study, variation in foraging success among predators was quantified by observing the predation of the wolf spider Pardosa pseudoannulata on the cricket Gryllus bimaculatus in the laboratory. A population model was then developed, and the effect of foraging variability on predator-prey dynamics was examined by incorporating levels of variation comparable to those quantified in the experiment. The variability in the foraging success among spiders was greater than would be expected by chance (i.e., the random allocation of prey to predators). The foraging variation was density-dependent; it became higher as the predator density increased. A population model that incorporates foraging variation shows that the variation influences population dynamics by affecting the numerical response of predators. In particular, the variation induces negative density-dependent effects among predators and stabilizes predator-prey dynamics.

Egg limitation and individual variation in parasitization risk among hosts in host-parasitoid dynamics.

Egg limitation is known to destabilize host-parasitoid dynamics. This study reexamines the effect of egg limitation in light of the individual variation in parasitization risk among hosts (e.g., some hosts are more likely to be parasitized than others). Previous studies have considered egg limitation (predicted as a destabilizing factor) and individual variation among hosts (predicted as a stabilizing factor) in isolation; however, their interaction is not known. An individual-based model was used to examine the effects of each factor and their interaction. The model-based analysis shows a clear interaction between egg limitation and individual variation in risk among hosts. Egg limitation can both stabilize and destabilize host-parasitioid dynamics depending on the presence and absence of the risk variation. The result suggests that the population-dynamic consequences of egg limitation are more complex than previously thought and emphasizes the importance of the simultaneous consideration of multiple ecological factors (with individual-level details) to uncover potential interactions among them.

Consequences of variation in foraging success among predators on numerical response.

The relationship between foraging success and reproduction is commonly assumed to be linear in theoretical investigations. Although the exact relationship (e.g., linear or nonlinear) does not influence qualitative conclusions of models under some assumptions, an inclusion of individual behavioral variation can make it otherwise due to Jensen's inequality. In particular, a mechanism that stabilizes food web dynamics is generated when two conditions are satisfied: (1) the reproduction of predators experiences diminishing returns from foraging success (i.e., concave down relationship between foraging success and reproduction) and (2) foraging success variation among predator individuals increases with the predator density. However, empirical results that confirm these conditions are scarce. This study describes the mechanism as a hypothesis for stability and discusses some important considerations for empirical verifications of the mechanism.

Foraging strategy switching in an antlion larva.

Antlion larvae are typically considered as trap-building predators, but some species of antlions always forage without using pits or only sometimes use pits to capture prey; they can ambush prey without pits. This study examined a species that switches its strategy between pit-trapping and ambushing and asked the mechanism behind the switching behaviour. A dynamic optimization model incorporating tradeoffs between the two strategies was built. The tradeoffs were prey capture success and predation risk (both are higher when pit-trapping). The model predicted that antlions should use the trap-building strategy when their energy status is low and should use the ambush strategy when their energy status is high. These predictions as well as an assumption (i.e., predation risk associated with pit-trapping is higher than that associated with ambushing) of the model were empirically confirmed. The results suggest that antlions flexibly switch between pit-trapping and ambushing to maximize their fitness by balancing the costs and benefits of the two strategies.

Incorporating multiple mixed stocks in mixed stock analysis: 'many-to-many' analyses.

Traditional mixed stock analyses use morphological, chemical, or genetic markers measured in several source populations and in a single mixed population to estimate the proportional contribution of each source to the mixed population. In many systems, however, different individuals from a particular source population may go to a variety of mixed populations. Now that data are becoming available from (meta)populations with multiple mixed stocks, the need arises to estimate contributions in this 'many-to-many' scenario. We suggest a Bayesian hierarchical approach, an extension of previous Bayesian mixed stock analysis algorithms, that can estimate contributions in this case. Applying the method to mitochondrial DNA data from green turtles (Chelonia mydas) in the Atlantic gives results that are largely consistent with previous results but makes some novel points, e.g. that the Florida, Bahamas and Corisco Bay foraging grounds have greater contributions than previously thought from distant foraging grounds. More generally, the 'many-to-many' approach gives a more complete understanding of the spatial ecology of organisms, which is especially important in species such as the green turtle that exhibit weak migratory connectivity (several distinct subpopulations at one end of the migration that mix in unknown ways at the other end).