Incorporating effects of age on energy dynamics predicts nonlinear maternal allocation patterns in iteroparous animals.

Iteroparous parents face a trade-off between allocating current resources to reproduction versus maximizing survival to produce further offspring. Parental allocation varies across age and follows a hump-shaped pattern across diverse taxa, including mammals, birds and invertebrates. This nonlinear allocation pattern lacks a general theoretical explanation, potentially because most studies focus on offspring number rather than quality and do not incorporate uncertainty or age-dependence in energy intake or costs. Here, we develop a life-history model of maternal allocation in iteroparous animals. We identify the optimal allocation strategy in response to stochasticity when energetic costs, feeding success, energy intake and environmentally driven mortality risk are age-dependent. As a case study, we use tsetse, a viviparous insect that produces one offspring per reproductive attempt and relies on an uncertain food supply of vertebrate blood. Diverse scenarios generate a hump-shaped allocation when energetic costs and energy intake increase with age and also when energy intake decreases and energetic costs increase or decrease. Feeding success and environmentally driven mortality risk have little influence on age-dependence in allocation. We conclude that ubiquitous evidence for age-dependence in these influential traits can explain the prevalence of nonlinear maternal allocation across diverse taxonomic groups.

Incorporating thermodynamics in predator-prey games predicts the diel foraging patterns of poikilothermic predators.

Models of foraging behaviour typically assume that prey do not adapt to temporal variation in predation risk, such as by avoiding foraging at certain times of the day. When this behavioural plasticity is considered-such as in predator-prey games-the role of abiotic factors is usually ignored. An abiotic factor that exerts strong influence on the physiology and behaviour of many animals is ambient temperature, although it is often ignored from game models as it is implicitly assumed that both predators and prey are homothermic. However, poikilotherms' performance may be reduced in cold conditions due to reduced muscle function, limiting the prey-capture ability of predators and the predator-avoidance and foraging abilities of prey. Here, we use a game-theoretic predator-prey model in which diel temperature changes influence foraging gains and costs to predict the evolutionarily stable diel activity of predators. Our model predicts the range of patterns observed in nature, including nocturnal, diurnal, crepuscular and a previously unexplained post-sunset crepuscular pattern observed in some sharks. In general, smaller predators are predicted to be more diurnal than larger ones. The safety of prey when not foraging is critical, explaining why predators in coral reef systems (with safe refuges) may often have different foraging patterns to pelagic predators. We make a range of testable predictions that will enable the further evaluation of this theoretical framework for understanding diel foraging patterns in poikilotherms.

Altruism in a volatile world.

The evolution of altruism-costly self-sacrifice in the service of others-has puzzled biologists since The Origin of Species. For half a century, attempts to understand altruism have developed around the concept that altruists may help relatives to have extra offspring in order to spread shared genes. This theory-known as inclusive fitness-is founded on a simple inequality termed Hamilton's rule. However, explanations of altruism have typically not considered the stochasticity of natural environments, which will not necessarily favour genotypes that produce the greatest average reproductive success. Moreover, empirical data across many taxa reveal associations between altruism and environmental stochasticity, a pattern not predicted by standard interpretations of Hamilton's rule. Here we derive Hamilton's rule with explicit stochasticity, leading to new predictions about the evolution of altruism. We show that altruists can increase the long-term success of their genotype by reducing the temporal variability in the number of offspring produced by their relatives. Consequently, costly altruism can evolve even if it has a net negative effect on the average reproductive success of related recipients. The selective pressure on volatility-suppressing altruism is proportional to the coefficient of variation in population fitness, and is therefore diminished by its own success. Our results formalize the hitherto elusive link between bet-hedging and altruism, and reveal missing fitness effects in the evolution of animal societies.

Trust your gut: using physiological states as a source of information is almost as effective as optimal Bayesian learning.

Approaches to understanding adaptive behaviour often assume that animals have perfect information about environmental conditions or are capable of sophisticated learning. If such learning abilities are costly, however, natural selection will favour simpler mechanisms for controlling behaviour when faced with uncertain conditions. Here, we show that, in a foraging context, a strategy based only on current energy reserves often performs almost as well as a Bayesian learning strategy that integrates all previous experiences to form an optimal estimate of environmental conditions. We find that Bayesian learning gives a strong advantage only if fluctuations in the food supply are very strong and reasonably frequent. The performance of both the Bayesian and the reserve-based strategy are more robust to inaccurate knowledge of the temporal pattern of environmental conditions than a strategy that has perfect knowledge about current conditions. Studies assuming Bayesian learning are often accused of being unrealistic; our results suggest that animals can achieve a similar level of performance to Bayesians using much simpler mechanisms based on their physiological state. More broadly, our work suggests that the ability to use internal states as a source of information about recent environmental conditions will have weakened selection for sophisticated learning and decision-making systems.

Conflict over non-partitioned resources may explain between-species differences in declines: the anthropogenic competition hypothesis.

ABSTRACT: Human alterations of habitats are causing declines in many species worldwide. The extent of declines varies greatly among closely related species, for often unknown reasons that must be understood in order to maintain biodiversity. An overlooked factor is that seasonally breeding species compete for nest sites, which are increasingly limited in many anthropogenically degraded environments. I used evolutionary game theory to predict the outcome of competition between individuals that differ in their competitive ability and timing of nesting. A range of species following evolutionarily stable strategies can co-exist when there are sufficient nest sites, but my model predicts that a reduction in nest site availability has greater impacts on late-nesting species, especially the stronger competitors, whereas early-nesting, stronger species decline only slightly. These predictions are supported by data on 221 bird and 43 bumblebee species worldwide. Restoration and provision of nest sites should be an urgent priority in conservation efforts. More broadly, these results indicate a new ecological principle of potentially widespread importance: rapid reductions in the abundance of resources for which species' preferences have not diversified will result in unprecedented conflicts that reduce the potential for species co-existence. SIGNIFICANCE STATEMENT: Understanding the causes of species declines is crucial to preventing the losses. Whilst much work on species vulnerability shows broad scale effects, an enduring mystery is the variation in population trends between closely related species. I combined evolutionary modelling with three global-scale long-term data sets to reveal that competition for scarce nest sites causes variation in declines. The impact of the loss of nest sites on differential declines among closely related species from very different taxa indicates a new ecological principle of widespread importance: the effect of habitat degradation on competition among species. A lack of differentiation of nest site preferences means that-now nest sites are more limited-some species may be driving others to extinction. This phenomenon is likely to occur for any other non-partitioned resources that rapidly, on an evolutionary timescale, are now limiting population sizes.

Adaptive and non-adaptive models of depression: A comparison using register data on antidepressant medication during divorce.

Divorce is associated with an increased probability of a depressive episode, but the causation of events remains unclear. Adaptive models of depression propose that depression is a social strategy in part, whereas non-adaptive models tend to propose a diathesis-stress mechanism. We compare an adaptive evolutionary model of depression to three alternative non-adaptive models with respect to their ability to explain the temporal pattern of depression around the time of divorce. Register-based data (304,112 individuals drawn from a random sample of 11% of Finnish people) on antidepressant purchases is used as a proxy for depression. This proxy affords an unprecedented temporal resolution (a 3-monthly prevalence estimates over 10 years) without any bias from non-compliance, and it can be linked with underlying episodes via a statistical model. The evolutionary-adaptation model (all time periods with risk of divorce are depressogenic) was the best quantitative description of the data. The non-adaptive stress-relief model (period before divorce is depressogenic and period afterwards is not) provided the second best quantitative description of the data. The peak-stress model (periods before and after divorce can be depressogenic) fit the data less well, and the stress-induction model (period following divorce is depressogenic and the preceding period is not) did not fit the data at all. The evolutionary model was the most detailed mechanistic description of the divorce-depression link among the models, and the best fit in terms of predicted curvature; thus, it offers most rigorous hypotheses for further study. The stress-relief model also fit very well and was the best model in a sensitivity analysis, encouraging development of more mechanistic models for that hypothesis.

The Impact of Detoxification Costs and Predation Risk on Foraging: Implications for Mimicry Dynamics.

Prey often evolve defences to deter predators, such as noxious chemicals including toxins. Toxic species often advertise their defence to potential predators by distinctive sensory signals. Predators learn to associate toxicity with the signals of these so-called aposematic prey, and may avoid them in future. In turn, this selects for mildly toxic prey to mimic the appearance of more toxic prey. Empirical evidence shows that mimicry could be either beneficial ('Mullerian') or detrimental ('quasi-Batesian') to the highly toxic prey, but the factors determining which are unknown. Here, we use state-dependent models to explore how tri-trophic interactions could influence the evolution of prey defences. We consider how predation risk affects predators' optimal foraging strategies on aposematic prey, and explore the resultant impact this has on mimicry dynamics between unequally defended species. In addition, we also investigate how the potential energetic cost of metabolising a toxin can alter the benefits to eating toxic prey and thus impact on predators' foraging decisions. Our model predicts that both how predators perceive their own predation risk, and the cost of detoxification, can have significant, sometimes counterintuitive, effects on the foraging decisions of predators. For example, in some conditions predators should: (i) avoid prey they know to be undefended, (ii) eat more mildly toxic prey as detoxification costs increase, (iii) increase their intake of highly toxic prey as the abundance of undefended prey increases. These effects mean that the relationship between a mimic and its model can qualitatively depend on the density of alternative prey and the cost of metabolising toxins. In addition, these effects are mediated by the predators' own predation risk, which demonstrates that, higher trophic levels than previously considered can have fundamental impacts on interactions among aposematic prey species.

Towards a behavioural ecology of obesity.

Addressing the obesity epidemic depends on a holistic understanding of the reasons that people become and maintain excessive fat. Theories about the causes of obesity usually focus proximately or evoke evolutionary mismatches, with minimal clinical value. There is potential for substantial progress by adapting strategic body mass regulation models from evolutionary ecology to human obesity by assessing the role of information.

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.

The influence of the starvation-predation trade-off on the relationship between ambient temperature and body size among endotherms.

AIM: The tendency for animals at higher latitudes to be larger (Bergmann's rule) is generally explained by recourse to latitudinal effects on ambient temperature and the food supply, but these receive only mixed support and do not explain observations of the inverse to Bergmann's rule. Our aim was to better understand how ecological variables might influence body size and thereby explain this mixed support. LOCATION: World-wide. METHODS: Previous explanations do not allow for the selective pressure exerted by the trade-off between predation and starvation, which we incorporate in a model of optimal body size and energy storage of a generalized homeotherm. In contrast to existing arguments, we concentrate on survival over winter when the food supply is poor and can be interrupted for short periods. RESULTS: We use our model to assess the logical validity of the heat conservation hypothesis and show that it must allow for the roles of both food availability and predation risk. We find that whether the effect of temperature on body size is positive or negative depends on temperature range, predator density, and the likelihood of long interruptions to foraging. Furthermore, changing day length explains differing effects of altitude and latitude on body size, leading to opposite predictions for nocturnal and diurnal endotherms. Food availability and ambient temperature can have counteracting selective pressures on body mass, and can lead to a non-monotonic relationship between latitude and size, as observed in several studies. MAIN CONCLUSIONS: Our work provides a theoretical framework for understanding the relationships between the costs and benefits of large body size and eco-geographical patterns among endotherms world-wide.

Adaptive Use of Information during Growth Can Explain Long-Term Effects of Early Life Experiences.

Development is a continuous process during which individuals gain information about their environment and adjust their phenotype accordingly. In many natural systems, individuals are particularly sensitive to early life experiences, even in the absence of later constraints on plasticity. Recent models have highlighted how the adaptive use of information can explain age-dependent plasticity. These models assume that information gain and phenotypic adjustments either cannot occur simultaneously or are completely independent. This assumption is not valid in the context of growth, where finding food results both in a size increase and learning about food availability. Here, we describe a simple model of growth to provide proof of principle that long-term effects of early life experiences can arise through the coupled dynamics of information acquisition and phenotypic change in the absence of direct constraints on plasticity. The increase in reproductive value from gaining information and sensitivity of behavior to experiences declines across development. Early life experiences have long-term impacts on age of maturity, yet-due to compensatory changes in behavior-our model predicts no substantial effects on reproductive success. We discuss how the evolution of sensitive windows can be explained by experiences having short-term effects on informational and phenotypic states, which generate long-term effects on life-history decisions.

Fatness and fitness: exposing the logic of evolutionary explanations for obesity.

To explore the logic of evolutionary explanations of obesity we modelled food consumption in an animal that minimizes mortality (starvation plus predation) by switching between activities that differ in energy gain and predation. We show that if switching does not incur extra predation risk, the animal should have a single threshold level of reserves above which it performs the safe activity and below which it performs the dangerous activity. The value of the threshold is determined by the environmental conditions, implying that animals should have variable 'set points'. Selection pressure to prevent energy stores exceeding the optimal level is usually weak, suggesting that immediate rewards might easily overcome the controls against becoming overweight. The risk of starvation can have a strong influence on the strategy even when starvation is extremely uncommon, so the incidence of mortality during famine in human history may be unimportant for explanations for obesity. If there is an extra risk of switching between activities, the animal should have two distinct thresholds: one to initiate weight gain and one to initiate weight loss. Contrary to the dual intervention point model, these thresholds will be inter-dependent, such that altering the predation risk alters the location of both thresholds; a result that undermines the evolutionary basis of the drifty genes hypothesis. Our work implies that understanding the causes of obesity can benefit from a better understanding of how evolution shapes the mechanisms that control body weight.

Florivory as an Opportunity Benefit of Aposematism.

Inconspicuous prey pay a cost of reduced feeding opportunities. Flowers are highly nutritious but are positioned where prey would be apparent to predators and often contain toxins to reduce consumption. However, many herbivores are specialized to subvert these defenses by retaining toxins for their own use. Here, we present a model of the growth and life history of a small herbivore that can feed on leaves or flowers during its development and can change its primary defense against visual predators between crypsis and warning coloration. When herbivores can retain plant toxins, their fitness is greatly increased when they are aposematic and can consume flowers. Thus, toxin sequestration leading to aposematism may enable a significant opportunity benefit for florivory. Florivory by cryptic herbivores is predicted when toxins are very potent but are at high concentration only in flowers and not in leaves. Herbivores should usually switch to eating flowers only when large and in most conditions should switch simultaneously from crypsis to aposematism. Our results suggest that florivory should be widespread in later instars of small aposematic herbivores and should be associated with ontogenic color change. Florivory is likely to play an underappreciated role in herbivorous insect life histories and host plant reproductive success.

Costs of Foraging Predispose Animals to Obesity-Related Mortality when Food Is Constantly Abundant.

Obesity is an important medical problem affecting humans and animals in the developed world, but the evolutionary origins of the behaviours that cause obesity are poorly understood. The potential role of occasional gluts of food in determining fat-storage strategies for avoiding mortality have been overlooked, even though animals experienced such conditions in the recent evolutionary past and may follow the same strategies in the modern environment. Humans, domestic, and captive animals in the developed world are exposed to a surplus of calorie-rich food, conditions characterised as 'constant-glut'. Here, we use a mathematical model to demonstrate that obesity-related mortality from poor health in a constant-glut environment should equal the average mortality rate in the 'pre-modern' environment when predation risk was more closely linked with foraging. It should therefore not be surprising that animals exposed to abundant food often over-eat to the point of ill-health. Our work suggests that individuals tend to defend a given excessive level of reserves because this level was adaptive when gluts were short-lived. The model predicts that mortality rate in constant-glut conditions can increase as the assumed health cost of being overweight decreases, meaning that any adaptation that reduced such health costs would have counter-intuitively led to an increase in mortality in the modern environment. Taken together, these results imply that efforts to reduce the incidence of obesity that are focussed on altering individual behaviour are likely to be ineffective because modern, constant-glut conditions trigger previously adaptive behavioural responses.

Adaptive learning can result in a failure to profit from good conditions: implications for understanding depression.

BACKGROUND AND OBJECTIVES: Depression is a major medical problem diagnosed in an increasing proportion of people and for which commonly prescribed psychoactive drugs are frequently ineffective. Development of treatment options may be facilitated by an evolutionary perspective; several adaptive reasons for proneness to depression have been proposed. A common feature of many explanations is that depressive behaviour is a way to avoid costly effort where benefits are small and/or unlikely. However, this viewpoint fails to explain why low mood persists when the situation improves. We investigate whether a behavioural rule that is adapted to a stochastically changing world can cause inactivity which appears similar to the effect of depression, in that it persists after the situation has improved. METHODOLOGY: We develop an adaptive learning model in which an individual has repeated choices of whether to invest costly effort that may result in a net benefit. Investing effort also provides information about the current conditions and rates of change of the conditions. RESULTS: An individual following the optimal behavioural strategy may sometimes remain inactive when conditions are favourable (i.e. when it would be better to invest effort) when it is poorly informed about the current environmental state. Initially benign conditions can predispose an individual to inactivity after a relatively brief period of negative experiences. CONCLUSIONS AND IMPLICATIONS: Our approach suggests that the antecedent factors causing depressed behaviour could go much further back in an individual s history than is currently appreciated. The insights from our approach have implications for the ongoing debate about best treatment options for patients with depressive symptoms.

The starvation-predation trade-off shapes the strategic use of protein for energy during fasting.

The primary function of lipid storage by animals is as an energy source for surviving periods without food. However, muscle and organ protein can be metabolised for energy, and empirical studies have shown that the onset of protein metabolism begins before the exhaustion of lipid reserves. Since protein tissues are important for reasons other than resisting starvation, the adaptive basis for this early onset is unclear. Here, we report the results of a model of the optimal proportion of energy to obtain from protein catabolism during a period without food of unpredictable duration. We assume either that the animal aims only to maximise the duration of survival or that it also has to take account of its future reproductive success given its state when the food supply recommences. In the latter case we find impressive quantitative agreement with observations on lean and obese penguins and rats. Analysis shows that this agreement breaks down if predation risk is insignificant, protein in the form of muscle is ineffective against predation, or there is no benefit to conserving lipid (e.g. for reproduction). This result implies that animals have not evolved to maximise their starvation resistance because doing so would leave them vulnerable when an interruption ends. Our model allows us to make several specific predictions concerning the relationship between the ecological pressures on animals and their starvation survival strategies.

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.

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.

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.

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.