Andrew D. Higginson

The evolution of decision rules in complex environments

Models and experiments on adaptive decision-making typically consider highly simplified environments that bear little resemblance to the complex, heterogeneous world in which animals (including humans) have evolved. These studies reveal an array of so-called cognitive biases and puzzling features of behaviour that seem irrational in the specific situation presented to the decision-maker. Here we review an emerging body of work that highlights spatiotemporal heterogeneity and autocorrelation as key properties of most real-world environments that may help us understand why these biases evolved. Ecologically rational decision rules adapted to such environments can lead to apparently maladaptive behaviour in artificial experimental settings. We encourage researchers to consider environments with greater complexity to understand better how evolution has shaped our cognitive systems.

Heavy use of equations impedes communication among biologists

Most research in biology is empirical, yet empirical studies rely fundamentally on theoretical work for generating testable predictions and interpreting observations. Despite this interdependence, many empirical studies build largely on other empirical studies with little direct reference to relevant theory, suggesting a failure of communication that may hinder scientific progress. To investigate the extent of this problem, we analyzed how the use of mathematical equations affects the scientific impact of studies in ecology and evolution. The density of equations in an article has a significant negative impact on citation rates, with papers receiving 28% fewer citations overall for each additional equation per page in the main text. Long, equation-dense papers tend to be more frequently cited by other theoretical papers, but this increase is outweighed by a sharp drop in citations from nontheoretical papers (35% fewer citations for each additional equation per page in the main text). In contrast, equations presented in an accompanying appendix do not lessen a paper’s impact. Our analysis suggests possible strategies for enhancing the presentation of mathematical models to facilitate progress in disciplines that rely on the tight integration of theoretical and empirical work.

Environmental heterogeneity, genotype-by-environment interactions and the reliability of sexual traits as indicators of mate quality.

Exaggerated sexual displays are often supposed to indicate the indirect benefits females may receive from sexual reproduction with displaying males, but empirical evidence for positive relationships between the genetic quality and sexual trait quality is scant. The explanation for this might lie in the fact that mixing of reproductive individuals whose development has been influenced by genotype-by-environment interactions (GEIs) can blur the relationship between the individual male genetic quality and phenotype as perceived by females. Strong GEIs can generate an ecological crossover, where different genotypes are superior in environments that are separated either in space or time. Here, we use a stochastic simulation model to show that even a weak GEI, which does not generate an obvious ecological crossover, can neutralize or even reverse the relationship between genetic quality and sexual trait size in the presence of environmental heterogeneity during development. Our model highlights the importance of developmental selection in evolution of traits and allows us to predict the situations in which sexual displays might not be reliable indicators of genetic quality.

Current incentives for scientists lead to underpowered studies with erroneous conclusions

We can regard the wider incentive structures that operate across science, such as the priority given to novel findings, as an ecosystem within which scientists strive to maximise their fitness (i.e., publication record and career success). Here, we develop an optimality model that predicts the most rational research strategy, in terms of the proportion of research effort spent on seeking novel results rather than on confirmatory studies, and the amount of research effort per exploratory study. We show that, for parameter values derived from the scientific literature, researchers acting to maximise their fitness should spend most of their effort seeking novel results and conduct small studies that have only 10%–40% statistical power. As a result, half of the studies they publish will report erroneous conclusions. Current incentive structures are in conflict with maximising the scientific value of research; we suggest ways that the scientific ecosystem could be improved.

Generalized Optimal Risk Allocation: Foraging and Antipredator Behavior in a Fluctuating Environment

Animals live in complex environments in which predation risk and food availability change over time. To deal with this variability and maximize their survival, animals should take into account how long current conditions may persist and the possible future conditions they may encounter. This should affect their foraging activity, and with it their vulnerability to predation across periods of good and bad conditions. Here we develop a comprehensive theory of optimal risk allocation that allows for environmental persistence and for fluctuations in food availability as well as predation risk. We show that it is the duration of good and bad periods, independent of each other, rather than the overall proportion of time exposed to each that is the most important factor affecting behavior. Risk allocation is most pronounced when conditions change frequently, and optimal foraging activity can either increase or decrease with increasing exposure to bad conditions. When food availability fluctuates rapidly, animals should forage more when food is abundant, whereas when food availability fluctuates slowly, they should forage more when food is scarce. We also show that survival can increase as variability in predation risk increases. Our work reveals that environmental persistence should profoundly influence behavior. Empirical studies of risk allocation should therefore carefully control the duration of both good and bad periods and consider manipulating food availability as well as predation risk.

The Starvation-Predation Trade-Off Predicts Trends in Body Size, Muscularity, and Adiposity between and within Taxa

The storage of lipids to buffer energy shortage may incur such costs as increased vulnerability to predation, and animals may be more muscular in order to reduce such costs. If muscle and lipid mass interact to determine survival, then both the muscularity and the adiposity of animals will be affected by factors such as predator density and food availability. Here we explore how adiposity and muscularity may depend on such factors. We confirm the expectation that adiposity should decrease with the risk of predation and increase with the frequency of interruptions to the food supply. More surprisingly, the predicted relationships between skeletal size, muscularity, and adiposity qualitatively depended on various factors: for example, adiposity should increase with foraging costs only for small animals and should decrease with total body mass if competition for food is intense. Furthermore, if the locomotive costs of carrying lipids are low, then adiposity should increase with body mass, whereas if such costs are high, then adiposity should decrease with body mass. These predictions are supported by observations of variation between and within species. Our approach demonstrates that broad patterns of body composition can be understood in terms of the fundamental ecological trade-off between starvation and predation.

Growth and reproductive costs of larval defence in the aposematic lepidopteran Pieris brassicae

1. Utilization of plant secondary compounds for antipredator defence is common in immature herbivorous insects. Such defences may incur a cost to the animal, either in terms of survival, growth rate or in the reproductive success. 2. A common defence in lepidopterans is the regurgitation of semi-digested material containing the defensive compounds of the food plant, a defence which has led to gut specialization in this order. Regurgitation is often swift in response to cuticular stimulation and deters predators from consuming or parasitizing the larva. The loss of food and other gut material seems likely to impact on fitness, but evidence is lacking. 3. Here, we raised larvae of the common crop pest Pieris brassicae on commercial cabbage leaves, simulated predator attacks throughout the larval period, and measured life-history responses. 4. We found that the probability of survival to pupation decreased with increasing frequency of attacks, but this was because of regurgitation rather than the stimulation itself. There was a growth cost to the defence such that the more regurgitant that individuals produced over the growth period, the smaller they were at pupation. 5. The number of mature eggs in adult females was positively related to pupal mass, but this relationship was only found when individuals were not subjected to a high frequency of predator simulation. This suggests that there might be cryptic fitness costs to common defensive responses that are paid despite apparent growth rate being maintained. 6. Our results demonstrate a clear life-history cost of an antipredator defence in a model pest species and show that under certain conditions, such as high predation threat, the expected relationship between female body size and potential fecundity can be disrupted.

Adaptive changes in size and age at metamorphosis can qualitatively vary with predator type and available defenses

In many taxa the timing of metamorphosis is plastic in response to predation risk during the pre-metamorphic stage, and trends in both age and body size at metamorphosis have been the subject of much study. The responses to cues of predators are predominantly to be larger or equal-sized at the same age or older at metamorphosis. These observations are in direct contrast with existing theoretical treatments of this plasticity, which mostly predict earlier and smaller metamorphosis and never later and larger metamorphosis without invoking indirect effects on growth rate. Here we resolve the discrepancy between theory and observation using a dynamic state-dependent model that incorporates morphological and behavioral responses to predation risk. We allow prey to choose the optimal activity level and/or investment in defense over the growth period. We show that under certain conditions, metamorphosis at a larger size and later time is likely to be optimal. Our analysis allows us to make testable predictions about the changes in activity level of prey as they grow and how the effect of providing refuges will vary with predator type. Several of these predictions are supported by a meta-analysis of metamorphic responses to caged predators by larval amphibians and insects. Our predictions lead to insights about the feedback effects of antipredator responses on growth and subsequent implications for life history.

Paying for nectar with wingbeats: a new model of honeybee foraging

Honeybees acquire wing damage as they age and older foraging honeybees accept lavender inflorescences with fewer flowers. These indicate the operation of some kind of optimal response, but this cannot be based on energy because energy expenditure does not change as the wings get damaged. However, wingbeat frequency increases with wing damage. A deterministic analytical model was constructed, based on the assumptions that bees have a limited total number of wingbeats that the flight motor can perform and that they maximize lifetime energy profit by conserving the number of wingbeats used in foraging. The optimal response to wing damage is to reduce the threshold number of flowers needed to accept an inflorescence. The predicted optimal gradient between wing damage (wingbeat frequency) and acceptance threshold (number of flowers on an inflorescence) was close to the observed gradient from field data. This model demonstrates that wear and tear is a significant factor in optimal foraging strategies.

Optimal foraging for multiple nutrients in an unpredictable environment.

Foraging theory has typically been concerned with the acquisition of a single resource even though organisms from mammals to protozoa are capable of balancing their requirements for multiple resources. Existing theory concerning multiple nutrients from multiple foods does not predict the sequence of food selection. We constructed an optimisation model of the simplest case of two foods containing differing amounts of two nutrients. We begin with the well-supported assumption that reproductive value declines with the distance from target nutrient intake. We show that nutrient space divides into two distinct areas where the animal should exclusively consume one food or the other. The organism thus initially concentrates on one food type until the border between the areas is reached and then moves as closely as possible along the border to approach the target. This strategy is commonly observed in a range of organisms, suggesting that the assumed fitness function is common.