Optimal Foraging Behaviour Research Articles

Foraging behaviour and patch size distribution jointly determine population dynamics in fragmented landscapes.

Increased fragmentation caused by habitat loss represents a major threat to the persistence of animal populations. How fragmentation affects populations depends on the rate at which individuals move between spatially separated patches. Whereas negative effects of habitat loss on biodiversity are well known, the effects of fragmentation per se on population dynamics and ecosystem stability remain less well understood. Here, we use a spatially explicit predator-prey model to investigate how the interplay between fragmentation and optimal foraging behaviour affects predator-prey interactions and, subsequently, ecosystem stability. We study systems wherein prey occupies isolated patches and are consumed by predators that disperse following Lévy random walks. Our results show that the Lévy exponent and the degree of fragmentation jointly determine coexistence probabilities. In highly fragmented landscapes, Brownian and ballistic predators go extinct and only scale-free predators can coexist with prey. Furthermore, our results confirm that predation causes irreversible habitat loss in fragmented landscapes owing to overexploitation of smaller patches of prey. Moreover, we show that predator dispersal can reduce, but not prevent or minimize, the amount of lost habitat. Our results suggest that integrating optimal foraging theory into population and landscape ecology is crucial to assessing the impact of fragmentation on biodiversity and ecosystem stability.

Limited-Distance Pollen Dispersal and Low Paternal Diversity in a Bird-Pollinated Self-Incompatible Tree.

Bird pollination in Asia is regarded as an uncommon phenomenon and, therefore, only a few investigations on mating pattern and paternity in fruits of Asian bird-pollinated plants have been conducted. Here, we examined spatial genetic structure, pollen dispersal, and multiple paternity in a natural population of Bombax ceiba (B. ceiba) (Malvaceae) in Hainan Island, South China, using simple sequence repeat (SSR) markers. A low genetic diversity (He = 0.351 ± 0.0341 and 0.389 ± 0.043, respectively, for adults and offspring) and bottleneck effects were observed. Genetic kinship was significant within 400 m or in 1,800–3,800 m. Both the mating pattern and paternity analysis confirmed obligate xenogamy and a low multiple paternity in B. ceiba. There was a strongly negative relationship between the frequency of matings and the distance between mating pairs. The average pollen dispersal distance was 202.89 ± 41.01 m (mean ± SE) and the farthest distance of > 1 km was recorded. Realized mating events showed an extremely leptokurtic distribution within 1,200 m, suggesting that the pollen dispersal distance was consistent with the optimal foraging theory of generalist birds such as Zosterops spp. and Pycnonotus spp. Paternity per tree ranged from two to six and the average effective number of pollen donors per maternal plant was 3.773, suggesting a low level of paternity diversity as compared to other bird-pollinated plants. We concluded that optimal foraging behavior by generalist birds could explain the leptokurtic pollen dispersal distribution and predominantly near-neighbor matings in B. ceiba. The limited pollen dispersal distance and low multiple paternity were consistent with low fruit setting rate (3.27 ± 0.93%) in this self-incompatible tree, which was caused mainly by the restricted flight distance of birds and human disturbances. Low genetic diversity and significant spatial genetic structure might have largely resulted from logging and human collection of fruits.

A model of naturalistic decision making in preference tests

Decisions as to whether to continue with an ongoing activity or to switch to an alternative are a constant in an animal's natural world, and in particular underlie foraging behavior and performance in food preference tests. Stimuli experienced by the animal both impact the choice and are themselves impacted by the choice, in a dynamic back and forth. Here, we present model neural circuits, based on spiking neurons, in which the choice to switch away from ongoing behavior instantiates this back and forth, arising as a state transition in neural activity. We analyze two classes of circuit, which differ in whether state transitions result from a loss of hedonic input from the stimulus (an "entice to stay" model) or from aversive stimulus-input (a "repel to leave" model). In both classes of model, we find that the mean time spent sampling a stimulus decreases with increasing value of the alternative stimulus, a fact that we linked to the inclusion of depressing synapses in our model. The competitive interaction is much greater in "entice to stay" model networks, which has qualitative features of the marginal value theorem, and thereby provides a framework for optimal foraging behavior. We offer suggestions as to how our models could be discriminatively tested through the analysis of electrophysiological and behavioral data.

Perch time allocation and feeding efficiency of flycatching Rhinolophus formosae: an optimal foraging behavior?

BackgroundFlycatching bats are species-rare and comprise predominantly horseshoe bats (Rhinolophidae). Their hang-and-wait foraging mode and long constant-frequency echolocation calls offer advantages in energetics and prey detection, and may enable them apt to foraging optimally, yet not much is known about the foraging behavior of flycatching bats. Thus we assessed the perch use and foraging performance in the field by one of the largest horseshoe bats, Rhinolophus formosae, and offered insights on their perch time allocation.ResultsThe perching-foraging behaviors of the bats did not differ significantly between forest settings, but the residence and giving-up time, mean attack, and attack rate were higher in the late spring-early summer, whereas the mean capture, capture rate, and attack efficiency were lower in the late summer when volant juveniles joined the nocturnal activity. The bats maintained flycatching and exhibited largely similar attack rates through the night with peak residence time around the midnight, but the capture rate and attack efficiency both reduced toward midnight and then increased toward the hours right before dawn. The attack rate was negatively correlated to the number of perches used and perch switch; by contrast, the capture rate was positively correlated with both factors. The total residence time at a site increased but mean residence time per perch decreased as the number of perches used and perch-switch increased. The giving-up time was inversely correlated to the attack rate and attack efficiency, and decreased with an increasing capture rate.ConclusionsThe bats increased perch switch at lower attack rates in early spring, but switched less frequently in late spring and prime summer months when insect abundance is higher. By scanning through a broad angular range for prey detection, and switching more frequently among perches, R. formosae foraged with an increased capture rate, and were able to remain at the site longer by slightly reducing their mean residence time per perch. Our results concur with the predictions of optimal foraging theory for patch selection and offer implications for further exploration of the foraging behavior of flycatching horseshoe bats.

Oceans of stimuli: an individual-based model to assess the role of olfactory cues and local enhancement in seabirds' foraging behaviour.

Oceans are extremely dynamic environments, which poses challenges for top-predators such as seabirds to find food resources. Yet, seabirds evolved sensorial abilities (olfactory senses) along with complex behaviours (social information transfer through local enhancement) to improve foraging efficiency. Using the Cory's shearwater (Calonectris borealis) as a model species, we developed an individual-based model to explore the complementary role of different searching mechanisms (olfactory foraging and local enhancement) for the optimal foraging behaviour of pelagic seabirds during 1-day foraging trips around breeding colonies. Model outputs were compared with observed patterns of Cory's shearwaters distribution during local foraging trips. Also, the foraging efficiency of virtual individuals was analysed considering hypothetical scenarios of foraging conditions and densities of foraging individuals around breeding colonies. The results support the use of a combination of searching strategies by Cory's shearwaters, which produced representative patterns of space use from tracked individuals, including spatial foraging segregation of neighbouring sub-colonies. Furthermore, while the mechanisms underpinning local enhancement played a key role in mitigating sub-optimal foraging conditions, the use of olfactory senses conferred great adaptive foraging advantages over a wide range of environmental conditions. Our results also indicate a synergistic effect between the two strategies, which suggests that a multimodal foraging strategy is useful to forage in extremely dynamic environments. The developed model provides a basis for further investigation regarding the role of foraging mechanisms in the population dynamics of colonial animals, including the adaptive foraging behaviour of marine top predators to dynamic environmental conditions.

Optimal foraging and the information theory of gambling.

At a macroscopic level, part of the ant colony life cycle is simple: a colony collects resources; these resources are converted into more ants, and these ants in turn collect more resources. Because more ants collect more resources, this is a multiplicative process, and the expected logarithm of the amount of resources determines how successful the colony will be in the long run. Over 60 years ago, Kelly showed, using information theoretic techniques, that the rate of growth of resources for such a situation is optimized by a strategy of betting in proportion to the probability of pay-off. Thus, in the case of ants, the fraction of the colony foraging at a given location should be proportional to the probability that resources will be found there, a result widely applied in the mathematics of gambling. This theoretical optimum leads to predictions as to which collective ant movement strategies might have evolved. Here, we show how colony-level optimal foraging behaviour can be achieved by mapping movement to Markov chain Monte Carlo (MCMC) methods, specifically Hamiltonian Monte Carlo (HMC). This can be done by the ants following a (noisy) local measurement of the (logarithm of) resource probability gradient (possibly supplemented with momentum, i.e. a propensity to move in the same direction). This maps the problem of foraging (via the information theory of gambling, stochastic dynamics and techniques employed within Bayesian statistics to efficiently sample from probability distributions) to simple models of ant foraging behaviour. This identification has broad applicability, facilitates the application of information theory approaches to understand movement ecology and unifies insights from existing biomechanical, cognitive, random and optimality movement paradigms. At the cost of requiring ants to obtain (noisy) resource gradient information, we show that this model is both efficient and matches a number of characteristics of real ant exploration.

Novel location data reveal spatiotemporal strategies used by a central-place forager

Central-place foragers in risky landscapes experience conflicting behavioral demands that they must balance by appropriately adjusting how they move throughout their home ranges. We used novel mini-GPS technology and time local convex hull analyses to determine how golden-mantled ground squirrels (Callospermophilus lateralis) use a spatiotemporal strategy to optimize foraging early in the year when individuals are in an energy deficit. By using serial correlation from GPS data, we could better understand how individuals use a time management strategy influenced by distance traveled from the burrow, location of food patches, location of refuge patches, and vegetative cover type. Individuals maximized time spent in food patches rather than in travel corridors or at the burrow, suggesting the need to forage was prioritized. Individuals spent more time at patches farther from the burrow relative to nearer patches, potentially as a function of intermittent antipredator vigilance activity and energy optimization. Individuals also had high rates of revisitation, but low visit duration, in risky canopy cover types, suggesting that individuals used areas of low vegetative understory cover to travel efficiently between high-value food patches. Increased predation risk incurred while traveling in these open areas was possibly offset by use of refuges. Understanding these spatiotemporal movement patterns and how they relate to dynamic intrinsic and extrinsic demands has the potential to redefine optimal foraging behavior and better inform management and conservation practices.

Paternity analysis reveals wide pollen dispersal and high multiple paternity in a small isolated population of the bird-pollinated Eucalyptus caesia (Myrtaceae)

Optimal foraging behaviour by nectavores is expected to result in a leptokurtic pollen dispersal distribution and predominantly near-neighbour mating. However, complex social interactions among nectarivorous birds may result in different mating patterns to those typically observed in insect-pollinated plants. Mating system, realised pollen dispersal and spatial genetic structure were examined in the bird-pollinated Eucalyptus caesia, a species characterised by small, geographically disjunct populations. Nine microsatellite markers were used to genotype an entire adult stand and 181 seeds from 28 capsules collected from 6 trees. Mating system analysis using MLTR revealed moderate to high outcrossing (tm=0.479-0.806) and low estimates of correlated paternity (rp=0.136±s.e. 0.048). Paternity analysis revealed high outcrossing rates (mean=0.72) and high multiple paternity, with 64 different sires identified for 181 seeds. There was a significant negative relationship between the frequency of outcross mating and distance between mating pairs. Realised mating events were more frequent than expected with random mating for plants <40 m apart. The overall distribution of pollen dispersal distances was platykurtic. Despite extensive pollen dispersal within the stand, three genetic clusters were detected by STRUCTURE analysis. These genetic clusters were strongly differentiated yet geographically interspersed, hypothesised to be a consequence of rare recruitment events coupled with extreme longevity. We suggest that extensive polyandry and pollen dispersal is a consequence of pollination by highly mobile honeyeaters and may buffer E. caesia against the loss of genetic diversity predicted for small and genetically isolated populations.

Multifractal anisotropic swimming: the optimal foraging behaviour of grouper larvae.

It was hypothesized that the Malabar grouper Ephinephelus malabaricus larvae have developed search patterns adapted to the distribution of their prey to maximise their net energy intake per unit time. Analysis of the swimming behaviour of E. malabaricus larvae in both the presence and absence of Artemia sp. nauplii is presented to test this hypothesis. A method derived from turbulence studies (the moment function of the displacements) was used to characterize the behaviour. The results revealed that larval swimming pattern was multifractal (intermittent and long-range-correlated) and isotropic (i.e. uniform in all directions) in the presence of prey, but multifractal and anisotropic (i.e. more frequent long displacement on the vertical axis) in the absence of prey. It is suggested that the search behaviour observed in the absence of prey is an adaptive response to prey distribution pattern, which is often characterised by multifractality and anisotropy (i.e. larger patches on the horizontal axes). In the presence of prey, E. malabaricus shifted to intensive search behaviour. Other possible contributors to the observed patterns are discussed. It is concluded that multifractality and anisotropy of swimming patterns observed in the experiment are mainly explained in an optimal foraging theory framework.

Group foraging decisions in nutritionally differentiated environments

Summary Foraging behaviour must be flexible enough to adapt to heterogeneities in the distribution and quality of food resources. Accurate models of optimal foraging behaviour should acknowledge the extent to which animals can detect and regulate their intake of food based on smaller scale differences in food types. In particular, consideration of macro‐nutrient distribution and how animals perceive this is limited in studies of optimal foraging, particularly in vertebrates and for animals that forage in groups. Here, we track shoals of eight mosquitofish as they forage in two environments that contain equal amounts of available energy but differ in their distribution of macro‐nutrients. We provide empirical evidence that fish will distribute themselves within an environment in relation to the distribution of specific macro‐nutrients. Also, fish make foraging decisions based on the macronutrient composition of patches, such that their durations on patches are longer when they have a higher concentration of protein and lower concentration of carbohydrate. The ratio of protein to carbohydrate does not affect the probability of a fish joining a patch, however, with low numbers of fish on the patch the probability of a fish leaving is greater per unit time step in the patches with a low protein to carbohydrate ratio than the patches with a high protein to carbohydrate ratio. This study confirms the importance of considering the macro‐nutrient composition of foods when considering the movement decisions of foraging groups and thus has important consequences for developing more accurate foraging models that take into account the distribution of macro‐nutrients in the environment. The results suggest the spatial distribution of nutrients on a landscape scale could influence grouping patterns and social interactions, thus affecting population dynamics.

Optimal foraging behavior and the thermal neutral zone of Peromyscus leucopus during winter: A test using natural and controlled ambient temperatures

Endotherms foraging at temperatures outside of their thermal neutral zone (TNZ) pay an increased energetic cost. We asked if thermally-induced changes in foraging costs influence quitting harvest rate (QHR) of mice. We predicted that mice foraging during the winter would have a higher QHR in more costly colder conditions. We conducted our study with wild caught Peromyscus leucopus in an enclosure located in West Terre Haute, Indiana. We assayed changes in QHR using the forager's giving up density (GUD), which is the amount of uneaten seeds reaming in a tray after foraging activity. Each night from January 12th to March 13th, we assigned 4 trays as “cold trays” (at ambient temperature), and 4 trays as “hot trays” (trays with a ceramic heat element that increased the temperatures of feeding trays ca. 10–15°C). GUDs (and therfore QHRs) increased as a function of decreasing ambient temperature. Furthermore there was an interaction between tray temperature and ambient temperature; namely, on cool nights mice had lower GUDs in the “hot trays”, but on warm nights mice had lower GUDs in the “cold trays”. The TNZ for P. leucopus actively foraging during winter may be closer to the environmental average temperature than typically measured in the laboratory. Overall, these results support the idea that QHR is related to an animal's foraging in thermally challenged conditions. We present a unique way of measuring an animal's TNZ in the field using behavioral indicators.

Optimal foraging behavior with an explicit consideration of within-individual behavioral variation: an example of predation

Animal behavior is flexible, and the same individual can exhibit variable expressions under the equivalent ecological situations (i.e., within-individual behavioral variation). This study examines the evolution of within-individual behavioral variation using an individual-based model. A common predation scenario is considered where a predator spends a period h to handle and consume a captured prey. The model assumes the handling time of the predator to be a random variable. The average and within-individual variance of handling time are described by $$\mu _h$$ and $$\sigma _h^2$$ , respectively, where each individual has its own unique $$\mu _h$$ and $$\sigma _h^2$$ . Using a genetic algorithm, the evolution of $$\sigma _h^2$$ is traced. The results show that natural selection acts on both $$\mu _h$$ and $$\sigma _h^2$$ , and the optimal behavioral variation depends on the density of prey. In particular, individuals with high behavioral variance $$\sigma _h^2$$ are more likely selected when prey density is low. Individual based modeling can be a useful tool for studying the ultimate significance of within-individual behavioral variation and generating empirically testable predictions. The mechanisms of the evolution of within-individual behavioral variation and their ecological implications are discussed.

Optimal foraging by an aphid parasitoid affects the outcome of apparent competition

Apparent competition is an indirect, negative interaction occurring between two or more host species, mediated by a shared parasitoid. Host species' population growth rates, parasitoid attack rates, and parasitoid population size can mediate the outcomes of apparent competition. It has also been suggested that optimal foraging by a natural enemy can influence the outcome of apparent competition, resulting in increased suppression of the optimal host. While this has been shown in theory, to date no studies have empirically tested the link between parasitoid optimal foraging behaviour and the outcome of apparent competition. The present study examined how optimal foraging behaviour influences the outcome of apparent competition in an aphid banker plant system. First, Aphidius colemani Viereck's preference for Myzus persicae Sulzer or Rhopalosiphum padi L., the non-pest host on the banker plant, was examined, and then the difference in M. persicae suppression in the presence and absence of R. padi was assessed. It was found that optimal foraging behaviour led female A. colemani to prefer M. persicae over R. padi, due to increased offspring survival and female size. Consequently, optimally foraging A. colemani parasitised significantly more M. persicae in the presence of both aphid hosts than in the presence of M. persicae alone. Understanding the interaction between optimal foraging and apparent competition has important implications for biological control of arthropod pests and could help to predict the outcome of biological control programmes.

Game-Theoretic Methods for Functional Response and Optimal Foraging Behavior

We develop a decision tree based game-theoretical approach for constructing functional responses in multi-prey/multi-patch environments and for finding the corresponding optimal foraging strategies. Decision trees provide a way to describe details of predator foraging behavior, based on the predator's sequence of choices at different decision points, that facilitates writing down the corresponding functional response. It is shown that the optimal foraging behavior that maximizes predator energy intake per unit time is a Nash equilibrium of the underlying optimal foraging game. We apply these game-theoretical methods to three scenarios: the classical diet choice model with two types of prey and sequential prey encounters, the diet choice model with simultaneous prey encounters, and a model in which the predator requires a positive recognition time to identify the type of prey encountered. For both diet choice models, it is shown that every Nash equilibrium yields optimal foraging behavior. Although suboptimal Nash equilibrium outcomes may exist when prey recognition time is included, only optimal foraging behavior is stable under evolutionary learning processes.

Foraging currencies, metabolism and behavioural routines

A fundamental issue in foraging theory is whether it is possible to find a simple currency that characterizes foraging behaviour. If such a currency exists, then it is tempting to argue that the selective forces that have shaped the evolution of foraging behaviour have been understood. We review previous work on currencies for the foraging behaviour of an animal that maximizes total energy gained. In many circumstances, it is optimal to maximize a suitably modified form of efficiency. We show how energy gain, predation and damage can be combined in a single currency based on reproductive value. We draw attention to the idea that hard work may have an adverse effect on an animal's condition. We develop a model of optimal foraging over a day when a forager's state consists of its energy reserves and its condition. Optimal foraging behaviour in our model depends on energy reserves, condition and time of day. The pattern of optimal behaviour depends strongly on assumptions about the probability that the forager is killed by a predator. If condition is important, no simple currency characterizes foraging behaviour, but behaviour can be understood in terms of the maximization of reproductive value. It may be optimal to adopt a foraging option that results in a rate of energy expenditure that is less than the rate associated with maximizing efficiency.

To eat and not be eaten: optimal foraging behaviour in suspension feeding copepods

Zooplankton feed on microscopic prey that they either entrain in a feeding current or encounter as they cruise through the water. They generate fluid disturbances as they feed and move, thus elevating their risk of being detected and encountered by predators. Different feeding modes generate different hydrodynamic signals to predators and different predator encounter speeds but may also differ in their efficiency; the optimal behaviour is that which maximizes the net energy gain over the predation risk. Here, we show by means of flow visualization and simple hydrodynamic and optimization models that copepods with a diversity of feeding behaviours converge on optimal, size-independent specific clearance rates that are consistent with observed clearance rates of zooplankton, irrespective of feeding mode, species and size. We also predict magnitudes and size-scaling of swimming speeds that are consistent with observations. The rationalization of the magnitude and scaling of the clearance rates of zooplankton makes it more suitable for development of models of marine ecosystems, and is particularly relevant in predicting the size structure and biomass of pelagic communities.

Behavioral refuges and predator–prey coexistence

The effects of a behavioral refuge caused either by the predator optimal foraging or prey adaptive antipredator behavior on the Gause predator–prey model are studied. It is shown that both of these mechanisms promote predator–prey coexistence either at an equilibrium, or along a limit cycle. Adaptive prey refuge use leads to hysteresis in prey antipredator behavior which allows predator–prey coexistence along a limit cycle. Similarly, optimal predator foraging leads to sigmoidal functional responses with a potential to stabilize predator–prey population dynamics at an equilibrium, or along a limit cycle.

Effects of food quality and starvation on the optimal foraging behavior of Daphnia magna (Cladocera)

In the present work, we evaluated the feeding selectivity of starved Daphnia magna on two freshwater green algae Chlamydomonas sajao and Chlorella pyrenoidosa. Compared to C. pyrenoidosa, food quality of C. sajao are better in food palatability (cell size and digestibility), but poor in nutritional content (total carbon content). D. magna was starved for 0 and 8 d, and then was allowed to graze on a mixture of C. sajao and C. pyrenoidosa with following proportion: 5 × 10 4: 35 × 10 4 cells ml −1, 20 × 10 4: 20 × 10 4 cells ml −1 and 35 × 10 4: 5 × 10 4 cells ml −1. The results indicated that the ingestion rate and filtration rate of starved D. magna, comparing with satiated groups, on C. pyrenoidosa increased significantly, while, inverse trends was observed in C. sajao. Base on selectivity coefficient of D. magna, we observed that when D. magna was in satiation C. sajao will be preferred, while, C. pyrenoidosa will be selected when D. magna was in starvation, and moreover, these foraging behaviors were not influenced by the relative food abundance of each green alga. Therefore, a tradeoff between food palatability (physical makeup) and food nutritional content (chemical composition) can be hypothesized in the foraging behavior of D. magna, which is modified by the starvation of feeder. High valuable food is always selected by D. magna as predicted by optimal foraging theory. However, when D. magna is in satiation food diets with adequate size and easy digestibility will be preferred, while, those foods with relatively higher lipid or total carbon content will be selected when D. magna is in starvation.

Maladaptive “gambling” by Pigeons

When humans buy a lottery ticket or gamble at a casino they are engaging in an activity that on average leads to a loss of money. Although animals are purported to engage in optimal foraging behavior, similar sub-optimal behavior can be found in pigeons. They show a preference for an alternative that is associated with a low probability of reinforcement (e.g., one that is followed by a red hue on 20% of the trials and then reinforcement or by a green hue on 80% of the trials and then the absence of reinforcement) over an alternative that is associated with a higher probability of reinforcement (e.g., blue or yellow each of which is followed by reinforcement 50% of the time). This effect appears to result from the strong conditioned reinforcement associated with the stimulus that is always followed by reinforcement. Surprisingly, although it is experienced four times as much, the stimulus that is never followed by reinforcement does not appear to result in significant conditioned inhibition (perhaps due to the absence of observing behavior). Similarly, human gamblers tend to overvalue wins and undervalue losses. Thus, this animal model may provide a useful analog to human gambling behavior, one that is free from the influence of human culture, language, social reinforcement, and other experiential biases that may influence human gambling behavior.

Information gleaned and former patch quality determine foraging behavior of parasitic wasps

A good estimate of patch quality is of prime importance for a randomly searching forager with limited longevity or fecundity. The forager can perceive cues related to the presence of resource on arrival in a patch and estimates its quality relatively to previous patches. This prior estimate can then be updated through sampling in the patch. However, these 3 sources of information have never been manipulated independently in the same experiment to quantify the effect of each one on foraging behavior. Here, we report experiments highlighting the mechanism by which the braconid Asobara tabida, a parasitoid wasp laying eggs in Drosophila larvae, uses information both gleaned from the previous patch visited and obtained on arrival in the next one, to estimate the quality of the latter and to behave accordingly. We disentangled the effects of the prior estimate of patch quality made on arrival in the patch and the effect of sampling in the patch on the foraging behavior of the parasitoid. We show that information gleaned by A. tabida from a previously visited patch plays a strong role in the response to both chemical cues and oviposition events by parasitoid when exploiting a patch. The information process highlighted in the present study is consistent with the Bayesian-like decision-making, which is suspected in parasitoids, bumblebees, and humans. Moreover, motivation to stay in the patch is likely to be tuned to the forager’s experience. Key words: Bayesian updating, decision, making, optimal foraging behavior, patch quality estimate. [Behav Ecol]