Distributing Defenses: How Resource Defendability Shapes the Optimal Response to Risk.

AbstractMany organisms divide limited defenses among heterogeneous assets. Plants allocate defensive chemicals among tissues differing in value, cost of defense, and risk of herbivory. Some ant colonies allocate specialized defenders among multiple nests differing in volume, entrance size, and risk of attack. We develop a general mathematical model to determine the optimal strategy for dividing defenses among assets depending on their value, defendability, and risk of attack. We build on plant defense theory by focusing on defendability, which we define as the functional relationship between defensive investment and successful defense. We show that if hard-to-defend assets cost more to defend, as assumed in resource defense theory, the optimal strategy allocates more defenses to those assets, regardless of risk. Inspired by cavity-nesting ants, we also consider the possibility that hard-to-defend assets have a lower chance to be successfully defended, even when defensive investment is high. Under this assumption, the optimal response to elevated risk is to reduce defensive allocation to hard-to-defend assets, a conservative strategy previously observed in turtle ants (Cephalotes). This new perspective on defendability suggests that in systems where assets differ in the chance of successful defense, defensive strategies may evolve to be sensitive to risk in surprising ways.

Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems.

Adaptive collective systems are common in biology and beyond. Typically, such systems require a task allocation algorithm: a mechanism or rule-set by which individuals select particular roles. Here we study the performance of such task allocation mechanisms measured in terms of the time for individuals to allocate to tasks. We ask: (1) Is task allocation fundamentally difficult, and thus costly? (2) Does the performance of task allocation mechanisms depend on the number of individuals? And (3) what other parameters may affect their efficiency? We use techniques from distributed computing theory to develop a model of a social insect colony, where workers have to be allocated to a set of tasks; however, our model is generalizable to other systems. We show, first, that the ability of workers to quickly assess demand for work in tasks they are not currently engaged in crucially affects whether task allocation is quickly achieved or not. This indicates that in social insect tasks such as thermoregulation, where temperature may provide a global and near instantaneous stimulus to measure the need for cooling, for example, it should be easy to match the number of workers to the need for work. In other tasks, such as nest repair, it may be impossible for workers not directly at the work site to know that this task needs more workers. We argue that this affects whether task allocation mechanisms are under strong selection. Second, we show that colony size does not affect task allocation performance under our assumptions. This implies that when effects of colony size are found, they are not inherent in the process of task allocation itself, but due to processes not modeled here, such as higher variation in task demand for smaller colonies, benefits of specialized workers, or constant overhead costs. Third, we show that the ratio of the number of available workers to the workload crucially affects performance. Thus, workers in excess of those needed to complete all tasks improve task allocation performance. This provides a potential explanation for the phenomenon that social insect colonies commonly contain inactive workers: these may be a 'surplus' set of workers that improves colony function by speeding up optimal allocation of workers to tasks. Overall our study shows how limitations at the individual level can affect group level outcomes, and suggests new hypotheses that can be explored empirically.

Task-switching costs promote the evolution of division of labor and shifts in individuality.

From microbes to humans, the success of many organisms is achieved by dividing tasks among specialized group members. The evolution of such division of labor strategies is an important aspect of the major transitions in evolution. As such, identifying specific evolutionary pressures that give rise to group-level division of labor has become a topic of major interest among biologists. To overcome the challenges associated with studying this topic in natural systems, we use actively evolving populations of digital organisms, which provide a unique perspective on the de novo evolution of division of labor in an open-ended system. We provide experimental results that address a fundamental question regarding these selective pressures: Does the ability to improve group efficiency through the reduction of task-switching costs promote the evolution of division of labor? Our results demonstrate that as task-switching costs rise, groups increasingly evolve division of labor strategies. We analyze the mechanisms by which organisms coordinate their roles and discover strategies with striking biological parallels, including communication, spatial patterning, and task-partitioning behaviors. In many cases, under high task-switching costs, individuals cease to be able to perform tasks in isolation, instead requiring the context of other group members. The simultaneous loss of functionality at a lower level and emergence of new functionality at a higher level indicates that task-switching costs may drive both the evolution of division of labor and also the loss of lower-level autonomy, which are both key components of major transitions in evolution.

Collective search in ants: Movement determines footprints, and footprints influence movement.

Collectively searching animals might be expected to coordinate with their groupmates to cover ground more evenly or efficiently than uncoordinated groups. Communication can lead to coordination in many ways. Previous work in ants suggests that chemical 'footprints', left behind by individuals as they walk, might serve this function by modulating the movement patterns of following ants. Here, we test this hypothesis by considering the two predictions that, first, ants may turn away from sites with higher footprint concentrations (klinotaxis), or, second, that they may change their turning patterns depending on the presence of footprints (klinokinesis). We tracked 5 whole colonies of Temnothorax rugatulus ants in a large arena over 5h. We approximated the footprint concentration by summing ant visitations for each point in the arena and calculated the speed and local path straightness for each point of the ant trajectories. We counterintuitively find that ants walk slightly faster and straighter in areas with fewer footprints. This is partially explained by the effect that ants who start out from the nest walking straighter move on average further away from the nest, where there are naturally fewer footprints, leading to an apparent relationship between footprint density and straightness However, ants walk slightly faster and straighter off footprints even when controlling for this effect. We tested for klinotaxis by calculating the footprint concentrations perceived by the left and right antennae of ants and found no evidence for a turning-away (nor turning-towards) behavior. Instead, we found noticeable effects of environmental idiosyncrasies on the behavior of ants which are likely to overpower any reactions to pheromones. Our results indicate that search density around an ant colony is affected by several independent processes, including individual differences in movement pattern, local spatial heterogeneities, and ants' reactions to chemical footprints. The multitude of effects illustrates that non-communicative coordination, individual biases and interactions with the environment might have a greater impact on group search efficiency and exploratory movements than pheromone communication.

Group size and its effects on collective organization.

Many insects and arthropods live in colonies or aggregations of varying size. Group size may affect collective organization either because the same individual behavior has different consequences when displayed in a larger group or because larger groups are subject to different constraints and selection pressures than smaller groups. In eusocial colonies, group size may have similar effects on colony traits as body size has on organismal traits. Social insects may, therefore, be useful to test theories about general principles of scaling, as they constitute a distinct level of organization. However, there is a surprising lack of data on group sizes in social insects and other group-living arthropods, and multiple confounding factors have to be controlled to detect effects of group size. If such rigorous studies are performed, group size may become as important to understanding collective organization as is body size in explaining behavior and life history of individual organisms.

Ants combine systematic meandering and correlated random walks when searching for unknown resources.

Animal search movements are typically assumed to be mostly random walks, although non-random elements may be widespread. We tracked ants (Temnothorax rugatulus) in a large empty arena, resulting in almost 5 km of trajectories. We tested for meandering by comparing the turn autocorrelations for empirical ant tracks and simulated, realistic Correlated Random Walks. We found that 78% of ants show significant negative autocorrelation around 10 mm (3 body lengths). This means that turns in one direction are likely followed by turns in the opposite direction after this distance. This meandering likely makes the search more efficient, as it allows ants to avoid crossing their own paths while staying close to the nest, avoiding return-travel time. Combining systematic search with stochastic elements may make the strategy less vulnerable to directional inaccuracies. This study is the first to find evidence for efficient search by regular meandering in a freely searching animal.

Injected serotonin decreases foraging aggression in black widow spiders (Latrodectus hesperus), but dopamine has no effect.

A fundamental goal of animal behavior research is to discover the proximate mechanisms driving individual behavioral differences. Biogenic amines are known to mediate various aspects of behavior across many species, including aggression, one of the most commonly measured behavioral traits in animals. Arthropods provide an excellent system to manipulate biogenic amines and quantify subsequent behavioral changes. Here, we investigated the role of dopamine (DA) and serotonin (5-HT) on foraging aggression in western black widow spiders (Latrodectus hesperus), as measured by the number of attacks on a simulated prey animal in the web. We injected spiders with DA or 5-HT and then quantified subsequent changes in behavior over 48 h. Based on previous work on insects and spiders, we hypothesized that increasing DA levels would increase aggression, while increasing 5-HT would decrease aggression. We found that injection of 5-HT did decrease black widow foraging aggression, but DA had no effect. This could indicate that the relationship between DA and aggression is complex, or that DA may not play as important a role in driving aggressive behavior as previously thought, at least in black widow spiders. Aggressive behavior is likely also influenced by other factors, such as inter-individual differences in genetics, metabolic rates, environment, and other neurohormonal controls.

How Can We Fully Realize the Potential of Mathematical and Biological Models to Reintegrate Biology?

Both mathematical models and biological model systems stand as tractable representations of complex biological systems or behaviors. They facilitate research and provide insights, and they can describe general rules. Models that represent biological processes or formalize general hypotheses are essential to any broad understanding. Mathematical or biological models necessarily omit details of the natural systems and thus may ultimately be "incorrect" representations. A key challenge is that tractability requires relatively simple models but simplification can result in models that are incorrect in their qualitative, broad implications if the abstracted details matter. Our paper discusses this tension, and how we can improve our inferences from models. We advocate for further efforts dedicated to model development, improvement, and acceptance by the scientific community, all of which may necessitate a more explicit discussion of the purpose and power of models. We argue that models should play a central role in reintegrating biology as a way to test our integrated understanding of how molecules, cells, organs, organisms, populations, and ecosystems function.

Percent lipid is associated with body size but not task in the bumble bee Bombus impatiens.

In some group-living organisms, labor is divided among individuals. This allocation to particular tasks is frequently stable and predicted by individual physiology. Social insects are excellent model organisms in which to investigate the interplay between physiology and individual behavior, as division of labor is an important feature within colonies, and individual physiology varies among the highly related individuals of the colony. Previous studies have investigated what factors are important in determining how likely an individual is, compared to nestmates, to perform certain tasks. One such task is foraging. Corpulence (i.e., percent lipid) has been shown to determine foraging propensity in honey bees and ants, with leaner individuals being more likely to be foragers. Is this a general trend across all social insects? Here we report data analyzing the individual physiology, specifically the percent lipid, of worker bumble bees (Bombus impatiens) from whom we also analyze behavioral task data. Bumble bees are also unusual among the social bees in that workers may vary widely in size. Surprisingly we find that, unlike other social insects, percent lipid is not associated with task propensity. Rather, body size closely predicts individual relative lipid stores, with smaller worker bees being allometrically fatter than larger worker bees.

Specialization does not predict individual efficiency in an ant.

The ecological success of social insects is often attributed to an increase in efficiency achieved through division of labor between workers in a colony. Much research has therefore focused on the mechanism by which a division of labor is implemented, i.e., on how tasks are allocated to workers. However, the important assumption that specialists are indeed more efficient at their work than generalist individuals--the "Jack-of-all-trades is master of none" hypothesis--has rarely been tested. Here, I quantify worker efficiency, measured as work completed per time, in four different tasks in the ant Temnothorax albipennis: honey and protein foraging, collection of nest-building material, and brood transports in a colony emigration. I show that individual efficiency is not predicted by how specialized workers were on the respective task. Worker efficiency is also not consistently predicted by that worker's overall activity or delay to begin the task. Even when only the worker's rank relative to nestmates in the same colony was used, specialization did not predict efficiency in three out of the four tasks, and more specialized workers actually performed worse than others in the fourth task (collection of sand grains). I also show that the above relationships, as well as median individual efficiency, do not change with colony size. My results demonstrate that in an ant species without morphologically differentiated worker castes, workers may nevertheless differ in their ability to perform different tasks. Surprisingly, this variation is not utilized by the colony--worker allocation to tasks is unrelated to their ability to perform them. What, then, are the adaptive benefits of behavioral specialization, and why do workers choose tasks without regard for whether they can perform them well? We are still far from an understanding of the adaptive benefits of division of labor in social insects.

Flowers help bees cope with uncertainty: signal detection and the function of floral complexity.

Plants often attract pollinators with floral displays composed of visual, olfactory, tactile and gustatory stimuli. Since pollinators' responses to each of these stimuli are usually studied independently, the question of why plants produce multi-component floral displays remains relatively unexplored. Here we used signal detection theory to test the hypothesis that complex displays reduce a pollinator's uncertainty about the floral signal. Specifically, we asked whether one component of the floral display, scent, improved a bee's certainty about the value of another component, color hue. We first trained two groups of bumble bees (Bombus impatiens Cresson) to discriminate between rewarding and unrewarding artificial flowers of slightly different hues in the presence vs absence of scent. In a test phase, we presented these bees with a gradient of floral hues and assessed their ability to identify the hue rewarded during training. We interpreted the extent to which bees' preferences were biased away from the unrewarding hue ('peak shift') as an indicator of uncertainty in color discrimination. Our data show that the presence of an olfactory signal reduces uncertainty regarding color: not only was color learning facilitated on scented flowers but also bees showed a lower amount of peak shift in the presence of scent. We explore potential mechanisms by which scent might reduce uncertainty about color, and discuss the broader significance of our results for our understanding of signal evolution.

Ontogeny of worker body size distribution in bumble bee (Bombus impatiens) colonies.

Bumble bees exhibit worker size polymorphisms; highly related workers within a colony may vary up to 10-fold in body mass. As size variation is an important life history feature in bumble bees, the distribution of body sizes within the colony and how it fluctuates over the colony cycle were analysed.Ten commercially purchased colonies of Bombus impatiens (Cresson) were reared in ad libitum conditions. The size of all workers present and newly emerging workers (callows) was recorded each week.The average size of bumble bee workers did not change with colony age, but variation in body size tended to decrease over time. The average size of callows did not change with population size, but did tend to decrease with colony age. In all measures, there was considerable variation among colonies.Colonies of B. impatiens usually produced workers with normally distributed body sizes throughout the colony life cycle. Unlike most polymorphic ants, there was no increase in worker body size with colony age or colony size. This provides the first, quantitative data on the ontogeny of bumble bee worker size distribution. The potential adaptive significance of this size variation is discussed.

Location, location, location: larvae position inside the nest is correlated with adult body size in worker bumble-bees (Bombus impatiens).

Social insects display task-related division of labour. In some species, division of labour is related to differences in body size, and worker caste members display morphological adaptations suited for particular tasks. Bumble-bee workers (Bombus spp.) can vary in mass by eight- to tenfold within a single colony, which previous work has linked to division of labour. However, little is known about the proximate mechanism behind the production of this wide range of size variation within the worker caste. Here, we quantify the larval feeding in Bombus impatiens in different nest zones of increasing distance from the centre. There was a significant difference in the number of feedings per larva across zones, with a significant decrease in feeding rates as one moved outwards from the centre of the nest. Likewise, the diameter of the pupae in the peripheral zones was significantly smaller than that of pupae in the centre. Therefore, we conclude that the differential feeding of larvae within a nest, which leads to the size variation within the worker caste, is based on the location of brood clumps. Our work is consistent with the hypothesis that some larvae are 'forgotten', providing a possible first mechanism for the creation of size polymorphism in B. impatiens.

Juvenile social experience generates differences in behavioral variation but not averages.

Developmental plasticity is known to influence the mean behavioral phenotype of a population. Yet, studies on how developmental plasticity shapes patterns of variation within populations are comparatively rare and often focus on a subset of developmental cues (e.g., nutrition). One potentially important but understudied developmental experience is social experience, as it is explicitly hypothesized to increase variation among individuals as a way to promote "social niches." To test this, we exposed juvenile black widow spiders (Latrodectus hesperus) to the silk of conspecifics by transplanting them onto conspecific webs for 48 h once a week until adulthood. We also utilized an untouched control group as well as a disturbed group. This latter group was removed from their web at the same time points as the social treatment, but was immediately placed back on their own web. After repeatedly measuring adult behavior and web structure, we found that social rearing drove higher or significant levels of repeatability relative to the other treatments. Repeatability in the social treatment also decreased in some traits, paralleling the decreases observed in the disturbed treatments. Thus, repeated juvenile disturbance may decrease among-individual differences in adult spiders. Yet, social rearing appeared to override the effect of disturbance in some traits, suggesting a prioritization effect. The resulting individual differences were maintained over at least one-third of the adult lifespan and thus appear to represent stable, canalized developmental effects and not temporal state differences. These results provide proximate insight into how a broader range of developmental experiences shape trait variation.

Signal categorization by foraging animals depends on ecological diversity.

Warning signals displayed by defended prey are mimicked by both mutualistic (Müllerian) and parasitic (Batesian) species. Yet mimicry is often imperfect: why does selection not improve mimicry? Predators create selection on warning signals, so predator psychology is crucial to understanding mimicry. We conducted experiments where humans acted as predators in a virtual ecosystem to ask how prey diversity affects the way that predators categorize prey phenotypes as profitable or unprofitable. The phenotypic diversity of prey communities strongly affected predator categorization. Higher diversity increased the likelihood that predators would use a 'key' trait to form broad categories, even if it meant committing errors. Broad categorization favors the evolution of mimicry. Both species richness and evenness contributed significantly to this effect. This lets us view the behavioral and evolutionary processes leading to mimicry in light of classical community ecology. Broad categorization by receivers is also likely to affect other forms of signaling.

Peripheral sensory organs vary among ant workers but variation does not predict division of labor.

The neural mechanisms underlying behavioral variation among individuals are not well understood. Differences among individuals in sensory sensitivity could limit the environmental stimuli to which an individual is capable of responding and have, indeed, been shown to relate to behavioral differences in different species. Here, we show that ant workers in Temnothorax rugatulus differ considerably in the number of antennal sensory structures, or sensilla (by 45% in density and over 100% in estimated total number). A larger quantity of sensilla may reflect a larger quantity of underlying sensory neurons. This would increase the probability that a given set of neurons in the antenna detects an environmental stimulus and becomes excited, thereby eliciting the expression of a behavior downstream at lower stimulus levels than an individual with comparatively fewer sensilla. Individual differences in antennal sensilla density, however, did not predict worker activity level or performance of any task, suggesting either that variation in sensilla density does not, in fact, reflect variation in sensory sensitivity or that individual sensory response thresholds to task-associated stimuli do not determine task allocation as is commonly assumed, at least in this social insect. More broadly, our finding that even closely related individuals can differ strongly in peripheral sensory organ elaboration suggests that such variation in sensory organs could underlie other cases of intraspecific behavioral variation.

Multimodal signals enhance decision making in foraging bumble-bees.

Multimodal signals are common in nature and have recently attracted considerable attention. Despite this interest, their function is not well understood. We test the hypothesis that multimodal signals improve decision making in receivers by influencing the speed and the accuracy of their decisions. We trained bumble-bees (Bombus impatiens) to discriminate between artificial flowers that differed either in one modality, visual (specifically, shape) or olfactory, or in two modalities, visual plus olfactory. Bees trained on multimodal flowers learned the rewarding flowers faster than those trained on flowers that differed only in the visual modality and, in extinction trials, visited the previously rewarded flowers at a higher rate than bees trained on unimodal flowers. Overall, bees showed a speed-accuracy trade-off; bees that made slower decisions achieved higher accuracy levels. Foraging on multimodal flowers did not affect the slope of the speed-accuracy relationship, but resulted in a higher intercept, indicating that multimodal signals were associated with consistently higher accuracy across range of decision speeds. Our results suggest that bees make more effective decisions when flowers signal in more than one modality, and confirm the importance of studying signal components together rather than separately.

How cognitive biases select for imperfect mimicry: a study of asymmetry in learning with bumblebees.

Imperfect mimicry presents a paradox of incomplete adaptation - intuitively, closer resemblance should improve performance. Receiver psychology can often explain why mimetic signals do not always evolve to match those of their models. Here, we explored the influence of a pervasive and powerful cognitive bias where associative learning depends upon an asymmetric interaction between the cue (stimulus) and consequence (reinforcer), such as in rats, which will associate light and tone with shock, and taste with nausea, but not the converse. Can such biases alter selection for mimicry? We designed an artificial mimicry system where bees foraged on artificial flowers, so that colours could be switched between rewarding or aversive. We found that when the colour blue was paired with a sucrose reward, other cues were ignored, but not when blue was paired with aversive compounds. We also tested the hypothesis that costs of errors affect how receivers sample imperfect mimics. However, costs of errors did not affect bee visits to imperfect mimics in our study. We propose a novel hypothesis for imperfect mimicry, in which the pairing between specific cues and reinforcers allows an imperfect mimic to resemble multiple models simultaneously. Generally, our results emphasize the importance of receiver psychology for the evolution of signal complexity and specificity.

Reconnaissance and latent learning in ants.

We show that ants can reconnoitre their surroundings and in effect plan for the future. Temnothorax albipennis colonies use a sophisticated strategy to select a new nest when the need arises. Initially, we presented colonies with a new nest of lower quality than their current one that they could explore for one week without a need to emigrate. We then introduced a second identical low quality new nest and destroyed their old nest so that they had to emigrate. Colonies showed a highly significant preference for the (low quality) novel new nest over the identical but familiar one. In otherwise identical experiments, colonies showed no such discrimination when the choice was between a familiar and an unfamiliar high-quality nest. When, however, either all possible pheromone marks were removed, or landmarks were re-orientated, just before the emigration, the ants chose between identical low-quality new nests at random. These results demonstrate for the first time that ants are capable of assessing and retaining information about the quality of potential new nest sites, probably by using both pheromones and landmark cues, even though this information may only be of strategic value to the colony in the future. They seem capable, therefore, of latent learning and, more explicitly, learning what not to do.

Temnothorax rugatulus ant colonies consistently vary in nest structure across time and context.

A host of animals build architectural constructions. Such constructions frequently vary with environmental and individual/colony conditions, and their architecture directly influences behavior and fitness. The nests of ant colonies drive and enable many of their collective behaviors, and as such are part of their 'extended phenotype'. Since ant colonies have been recently shown to differ in behavior and life history strategy, we ask whether colonies differ in another trait: the architecture of the constructions they create. We allowed Temnothorax rugatulus rock ants, who create nests by building walls within narrow rock gaps, to repeatedly build nest walls in a fixed crevice but under two environmental conditions. We find that colonies consistently differ in their architecture across environments and over nest building events. Colony identity explained 12-40% of the variation in nest architecture, while colony properties and environmental conditions explained 5-20%, as indicated by the condition and marginal R2 values. When their nest boxes were covered, which produced higher humidity and lower airflow, colonies built thicker, longer, and heavier walls. Colonies also built more robust walls when they had more brood, suggesting a protective function of wall thickness. This is, to our knowledge, the first study to explicitly investigate the repeatability of nestbuilding behavior in a controlled environment. Our results suggest that colonies may face tradeoffs, perhaps between factors such as active vs. passive nest defense, and that selection may act on individual construction rules as a mechanisms to mediate colony-level behavior.