Optimal prey selection: Why do great tits show partial preferences?

Energetic consequences of prey type in little penguins (Eudyptula minor)

Investigation of foraging decisions can help understand how animals efficiently gather and exploit food. Prey chase and handling times are important aspects of foraging efficiency, influencing the net energy gain derived from a prey item. However, these metrics are often overlooked in studies of foraging behaviour due to the difficulty in observing them. The present study used animal-borne cameras to investigate the type, duration and energetic consequences of predator-prey interactions in little penguins (Eudyptula minor) (n = 32) from two colonies in Bass Strait, south-eastern Australia. A total of seven main prey items were observed and consumed by little penguins. Penguins were observed to consume prey types and use strategies that have not been previously documented. These included consumption of bellowsfish (Macroramphosus scolopax) and other fish species captured sheltering around jellyfish or extracted dead from the tentacles. Chase and handling time varied with prey type and lasted approximately 2 s for most prey. Profitability varied among prey types, with a greater amount of low profitable prey being consumed, suggesting a trade-off between minimizing energetic costs, and increasing capture rates. These results highlight the use of animal-borne video data loggers to further understand the foraging adaptations of important predators in the marine environment.

Strategy maps: Generalised giving-up densities for optimal foraging

Finding a common currency for benefits and hazards is a major challenge in optimal foraging theory, often requiring complex computational methods. We present a new analytic approach that builds on the Marginal Value Theorem and giving-up densities while incorporating the nonlinear effect of predation risk. We map the space of all possible environments into strategy regions, each corresponding to a discrete optimal strategy. This provides a generalised quantitative measure of the trade-off between foraging rewards and hazards. This extends a classic optimal diet choice rule-of-thumb to incorporate the hazard of waiting for better resources to appear. We compare the dynamics of optimal decision-making for three foraging life-history strategies: One in which fitness accrues instantly, and two with delays before fitness benefit is accrued. Foragers with delayed-benefit strategies are more sensitive to predation risk than resource quality, as they stand to lose more fitness from a predation event than instant-accrual foragers.

The Cognitive Ecology of Stimulus Ambiguity: A Predator-Prey Perspective

Organisms face the cognitive challenge of making decisions based on imperfect information. Predators and prey, in particular, are confronted with ambiguous stimuli when foraging and avoiding attacks. These challenges are accentuated by variation imposed by environmental, physiological, and cognitive factors. While the cognitive factors influencing perceived ambiguity are often assumed to be fixed, contemporary findings reveal that perceived ambiguity is instead the dynamic outcome of interactive cognitive processes. Here, we present a framework that integrates recent advances in neurophysiology and sensory ecology with a classic decision-making model, signal detection theory (SDT), to understand the cognitive mechanisms that shape perceived stimulus ambiguity in predators and prey. Since stimulus ambiguity is pervasive, the framework discussed here provides insights that extend into nonforaging contexts.

The erroneous signals of detection theory

Signal detection theory has influenced the behavioural sciences for over 50 years. The theory provides a simple equation that indicates numerous 'intuitive' results; e.g. prey should be more prone to take evasive action (in response to an ambiguous cue) if predators are more common. Here, we use analytical and computational models to show that, in numerous biological scenarios, the standard results of signal detection theory do not apply; more predators can result in prey being less responsive to such cues. The standard results need not apply when the probability of danger pertains not just to the present, but also to future decisions. We identify how responses to risk should depend on background mortality and autocorrelation, and that predictions in relation to animal welfare can also be reversed from the standard theory.

Stomach fullness shapes prey choice decisions in crab plovers (Dromas ardeola)

Foragers whose energy intake rate is constrained by search and handling time should, according to the contingency model (CM), select prey items whose profitability exceeds or equals the forager’s long-term average energy intake rate. This rule does not apply when prey items are found and ingested at a higher rate than the digestive system can process them. According to the digestive rate model (DRM), foragers in such situations should prefer prey with the highest digestive quality, instead of the highest profitability. As the digestive system fills up, the limiting constraint switches from ingestion rate to digestion rate, and prey choice is expected to change accordingly for foragers making decisions over a relative short time window. We use these models to understand prey choice in crab plovers (Dromas ardeola), preying on either small burrowing crabs that are swallowed whole (high profitability, but potentially inducing a digestive constraint) or on larger swimming crabs that are opened to consume only the flesh (low profitability, but easier to digest). To parameterize the CM and DRM, we measured energy content, ballast mass and handling times for different sized prey, and the birds’ digestive capacity in three captive individuals. Subsequently, these birds were used in ad libitum experiments to test if they obeyed the rules of the CM or DRM. We found that crab plovers with an empty stomach mainly chose the most profitable prey, matching the CM. When stomach fullness increased, the birds switched their preference from the most profitable prey to the highest-quality prey, matching the predictions of the DRM. This shows that prey choice is context dependent, affected by the stomach fullness of an animal. Our results suggest that prey choice experiments should be carefully interpreted, especially under captive conditions as foragers often ‘fill up’ in the course of feeding trials.

Individual differences in choice of food items by pigeons

Pigeons (Columba livia ) select food items idiosyncratically when feeding on grains (Brown, 1969; Moon & Zeigler, 1979; Giraldeau & Lefebvre, 1985). In three experiments pigeons under various conditions of food restriction were offered artificial "grains", pellets of pigeon food that differed only in size, to see whether individual differences in preference would still be observed. When 300-mg ("large") and 20-mg ("small") pellets were available simultaneously there were still wide individual differences in choice, but when encountering the same items successively pigeons took nearly all the items offered.

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.

Modeling behavioral adaptations

Optimization models have often been useful in attempting to understand the adaptive significance of behavioral traits. Originally such models were applied to isolated aspects of behavior, such as foraging, mating, or parental behavior. In reality, organisms live in complex, ever-changing environments, and are simultaneously concerned with many behavioral choices and their consequences. This target article describes a dynamic modeling technique that can be used to analyze behavior in a unified way. The technique has been widely used in behavioral studies of insects, fish, birds, mammals, and other organisms. The models use biologically meaningful parameters and variables, and lead to testable predictions. Limitations arise because nature's complexity always exceeds our modeling capacity.

Horseshoe bats make adaptive prey-selection decisions, informed by echo cues

Foragers base their prey-selection decisions on the information acquired by the sensory systems. In bats that use echolocation to find prey in darkness, it is not clear whether the specialized diet, as sometimes found by faecal analysis, is a result of active decision-making or rather of biased sensory information. Here, we tested whether greater horseshoe bats decide economically when to attack a particular prey item and when not. This species is known to recognize different insects based on their wing-beat pattern imprinted in the echoes. We built a simulation of the natural foraging process in the laboratory, where the bats scanned for prey from a perch and, upon reaching the decision to attack, intercepted the prey in flight. To fully control echo information available to the bats and assure its unambiguity, we implemented computer-controlled propellers that produced echoes resembling those from natural insects of differing profitability. The bats monitored prey arrivals to sample the supply of prey categories in the environment and to inform foraging decisions. The bats adjusted selectivity for the more profitable prey to its inter-arrival intervals as predicted by foraging theory (an economic strategy known to benefit fitness). Moreover, unlike in previously studied vertebrates, foraging performance of horseshoe bats was not limited by costly rejections of the profitable prey. This calls for further research into the evolutionary selection pressures that sharpened the species's decision-making capacity.

Evolution and behavioural responses to human-induced rapid environmental change

Almost all organisms live in environments that have been altered, to some degree, by human activities. Because behaviour mediates interactions between an individual and its environment, the ability of organisms to behave appropriately under these new conditions is crucial for determining their immediate success or failure in these modified environments. While hundreds of species are suffering dramatically from these environmental changes, others, such as urbanized and pest species, are doing better than ever. Our goal is to provide insights into explaining such variation. We first summarize the responses of some species to novel situations, including novel risks and resources, habitat loss/fragmentation, pollutants and climate change. Using a sensory ecology approach, we present a mechanistic framework for predicting variation in behavioural responses to environmental change, drawing from models of decision-making processes and an understanding of the selective background against which they evolved. Where immediate behavioural responses are inadequate, learning or evolutionary adaptation may prove useful, although these mechanisms are also constrained by evolutionary history. Although predicting the responses of species to environmental change is difficult, we highlight the need for a better understanding of the role of evolutionary history in shaping individuals' responses to their environment and provide suggestion for future work.

Research on self-control: An integrating framework

The tendency to choose a larger, more delayed reinforcer over a smaller, less delayed one has frequently been termed “selfcontrol.” Three very different research traditions – two models emphasizing the control of local contingencies of reinforcement (Mischel's social learning theory and Herrnstein's matching law) and molar maximization models (specifically optimal foraging theory) – have all investigated behavior within the self-control paradigm. A framework is proposed to integrate research from all three research areas. This framework consists of three parts: a procedural analysis, a causal analysis, and a theoretical analysis. The procedural analysis provides a common procedural terminology for all three areas. The causal analysis establishes that, in all three research traditions, self-control varies directly with the current physical values of the reinforcers; that is, choices increase with reinforcer amount and decrease with reinforcer delay. But self-control also varies according to past events to which a subject has been exposed, and according to current factors other than the reinforcers. Each of the three models has therefore incorporated these indirect effects on self-control by postulating unobservable mechanisms. In all three cases, these mechanisms represent a subject's behavior as a function of a perceived environment. The theoretical analysis demonstrates that evolutionary theory can encompass the research from all three areas by considering differences in the adaptiveness of self-control in different situations. This integration provides a better and more predictive description of self-control.

A framework for the functional analysis of behaviour

We present a general framework for analyzing the contribution to reproductive success of a behavioural action. An action may make a direct contribution to reproductive success, but even in the absence of a direct contribution it may make an indirect contribution by changing the animal's state. We consider actions over a period of time, and define a reward function that characterizes the relationship between the animal's state at the end of the period and its future reproductive success. Working back from the end of the period using dynamic programming, the optimal action as a function of state and time can be found. The procedure also yields a measure of the cost, in terms of future reproductive success, of a suboptimal action. These costs provide us with a common currency for comparing activities such as eating and drinking, or eating and hiding from predators. The costs also give an indication of the robustness of the conclusions that can be drawn from a model. We review how our framework can be used to analyze optimal foraging decisions in a stochastic environment. We also discuss the modelling of optimal daily routines and provide an illustration based on singing to attract a mate. We use the model to investigate the features that can produce a dawn song burst in birds. State is defined very broadly so that it includes the information an animal has about its environment. Thus, exploration and learning can be included within the framework.

Food choice and intake: towards a unifying framework of learning and feeding motivation

The food choice and intake of animals (including humans) has typically been studied using frameworks of learning and feeding motivation. When used in isolation such frameworks could be criticized because learning paradigms give little consideration to how new food items are included or excluded from an individual's diet, and motivational paradigms do not explain how individuals decide which food to eat when given a choice. Consequently we are posed with the question of whether individuals actively interact with the food items present in their environment to learn about their nutritional properties? The thesis of this review is that individuals are motivated to actively sample food items in order to assess whether they are nutritionally beneficial or harmful. We offer a unifying framework, centred upon the concept of exploratory motivation, which is a synthesis of learning and paradigms of feeding motivation. In this framework information gathering occurs on two levels through exploratory behaviour: (i) the discrimination of food from nonfood items, and (ii) the continued monitoring and storage of information concerning the nutritional properties of these food items. We expect that this framework will advance our understanding of the behavioural control of nutrient intake by explaining how new food items are identified in the environment, and how individuals are able to monitor changes in the nutritional content of their food resource.