A simple iterative model accurately captures complex trapline formation by bumblebees across spatial scales and flower arrangements

Choosing the best way: how wild common marmosets travel to efficiently exploit resources

While foraging, animals have to find potential food sites, remember these sites, and plan the best navigation route. To deal with problems associated with foraging for multiple and patchy resources, primates may employ heuristic strategies to improve foraging success. Until now, no study has attempted to investigate experimentally the use of such strategies by a primate in a context involving foraging in large-scale space. Thus, we carried out an experimental field study that aimed to test if wild common marmosets (Callithrix jacchus) employ heuristic strategies to efficiently navigate through multiple feeding sites distributed in a large-scale space. In our experiment, we arranged four feeding platforms in a trapezoid configuration with up to 60 possible routes and observe marmosets' decisions under two experimental conditions. In experimental condition I, all platforms contained the same amount of food; in experimental condition II, the platforms had different amounts of food. According to the number and arrangement of the platforms, we tested two heuristic strategies: the Nearest Neighbor Rule and the Gravity Rule. Our results revealed that wild common marmosets prefer to use routes consistent with a heuristic strategy more than expected by chance, regardless of food distribution. The findings also demonstrate that common marmosets seem to integrate different factors such as distance and quantity of food across multiple sites distributed over a large-scale space, employing a combination of heuristic strategies to select the most efficient routes available. In summary, our findings confirm our expectations and provide important insights into the spatial cognition of these small neotropical primates.

Bee species perform distinct foraging behaviors that are best described by different movement models

In insect-pollinated plants, the foraging behavior of pollinators affects their pattern of movement. If distinct bee species vary in their foraging behaviors, different models may best describe their movement. In this study, we quantified and compared the fine scale movement of three bee species foraging on patches of Medicago sativa. Bee movement was described using distances and directions traveled between consecutive racemes. Bumble bees and honey bees traveled shorter distances after visiting many flowers on a raceme, while the distance traveled by leafcutting bees was independent of flower number. Transition matrices and vectors were calculated for bumble bees and honey bees to reflect their directionality of movement within foraging bouts; leafcutting bees were as likely to move in any direction. Bee species varied in their foraging behaviors, and for each bee species, we tested four movement models that differed in how distances and directions were selected, and identified the model that best explained the movement data. The fine-scale, within-patch movement of bees could not always be explained by a random movement model, and a general model of movement could not be applied to all bee species.

Mild movement sequence repetition in five primate species and evidence for a taxonomic divide in cognitive mechanisms

When animals forage, they face complex multi-destination routing problems. Traplining behaviour-the repeated use of the same route-can be used to study how spatial memory might evolve to cope with complex routing problems in ecologically distinct taxa. We analyzed experimental data from multi-destination foraging arrays for five species, two cercopithecine monkeys (vervets, Chlorocebus pygerythrus, and Japanese macaques, Macaca fuscata) and three strepsirrhines (fat-tailed dwarf lemurs, Cheirogaleus medius, grey mouse lemurs, Microcebus murinus, and aye-ayes, Daubentonia madagascariensis). These species all developed relatively efficient route formations within the arrays but appeared to rely on variable cognitive mechanisms. We found a strong reliance on heuristics in cercopithecoid species, with initial routes that began near optimal and did not improve with experience. In strepsirrhines, we found greater support for reinforcement learning of location-based decisions, such that routes improved with experience. Further, we found evidence of repeated sequences of site visitation in all species, supporting previous suggestions that primates form traplines. However, the recursive use of routes was weak, differing from the strategies seen in well-known traplining animals. Differences between strepsirrhine and cercopithecine strategies may be the result of either ecological or phylogenetic trends, and we discuss future possibilities for disentangling the two.

A Quantitative Framework for Identifying Patterns of Route-Use in Animal Movement Data

Animal movement along repeatedly used, “habitual” routes could emerge from a variety of cognitive mechanisms, as well as in response to a diverse set of environmental features. Because of the high conservation value of identifying wildlife movement corridors, there has been extensive work focusing on environmental factors that contribute to the emergence of habitual routes between protected habitats. In parallel, significant work has focused on disentangling the cognitive mechanisms underlying animal route use, as such movement patterns are of fundamental interest to the study of decision making and navigation. We reviewed the types of processes that can generate routine patterns of animal movement, suggested a new methodological workflow for classifying one of these patterns—high fidelity path reuse—in animal tracking data, and compared the prevalence of this pattern across four sympatric species of frugivorous mammals in Panama. We found the highest prevalence of route-use in kinkajous, the only nocturnal species in our study, and propose that further development of this method could help to distinguish the processes underlying the presence of specific routes in animal movement data.

A heuristic underlies the search for relief in Drosophila melanogaster

Humans rely on multiple types of sensory information to make decisions, and strategies that shorten decision‐making time by taking into account fewer but essential elements of information are preferred to strategies that require complex analyses. Such shortcuts to decision making are known as heuristics. The identification of heuristic principles in species phylogenetically distant to humans would shed light on the evolutionary origin of speed–accuracy trade‐offs and offer the possibility for investigating the brain representations of such trade‐offs, urgency and uncertainty. By performing experiments on spatial learning in the invertebrate Drosophila melanogaster, we show that the fly's search strategies conform to a spatial heuristic—the nearest neighbor rule—to avoid bitter taste (a negative stimulation). That is, Drosophila visits a salient location closest to its current position to stop the negative stimulation; only if this strategy proves unsuccessful does the fly use other learned associations to avoid bitter taste. Characterizing a heuristic in D. melanogaster supports the view that invertebrates can, when making choices, operate on economic principles, as well as the conclusion that heuristic decision making dates to at least 600 million years ago.

Hummingbirds modify their routes to avoid a poor location

Traplining, when animals repeat the order in which they visit a number of locations, is taxonomically widespread, but little is known about which factors influence the routes that animals follow. For example, as the quality of rewarding locations changes over time, foragers are expected to update their traplines, either to prioritize locations where the reward increases or to avoid locations that have ceased to be profitable. Here, we tested how traplining wild hummingbirds responded to increases or to decreases in the sucrose concentration of one of the flowers on their trapline. Hummingbirds did not change their trapline to visit the flower with the increased reward first, but by changing the order in which they visited flowers, they avoided a flower that contained a decreased reward. Depending on where along the trapline the reduced-content flower occurred, hummingbirds either changed the origin of their trapline or changed the direction in which they flew around their trapline. It may be that this asymmetric modification of foraging traplines is especially noticeable in risk-averse foragers, such as these territorial hummingbirds.

A model of resource partitioning between foraging bees based on learning

Central place foraging pollinators tend to develop multi-destination routes (traplines) to exploit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in detail, how populations of foragers use resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, the addition of a negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structures, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging. Our study fills a major gap in modelling pollinator behaviour and constitutes a unique tool to guide future experimental programs.

Patch selection by bumble bees navigating discontinuous landscapes

Pollen and nectar resources are unevenly distributed over space and bees must make routing decisions when navigating patchy resources. Determining the patch selection process used by bees is crucial to understanding bee foraging over discontinuous landscapes. To elucidate this process, we developed four distinct probability models of bee movement where the size and the distance to the patch determined the attractiveness of a patch. A field experiment with a center patch and four peripheral patches of two distinct sizes and distances from the center was set up in two configurations. Empirical transition probabilities from the center to each peripheral patch were obtained at two sites and two years. The best model was identified by comparing observed and predicted transition probabilities, where predicted values were obtained by incorporating the spatial dimensions of the field experiment into each model's mathematical expression. Bumble bees used both patch size and isolation distance when selecting a patch and could assess the total amount of resources available in a patch. Bumble bees prefer large, nearby patches. This information will facilitate the development of a predictive framework to the study of bee movement and of models that predict the movement of genetically engineered pollen in bee-pollinated crops.

New Caledonian crows' basic tool procurement is guided by heuristics, not matching or tracking probe site characteristics

Contrasting findings made it unclear what cognitive processes New Caledonian crows use to procure suitable tools to solve tool tasks. Most previous studies suggested that their tool procurement is achieved by either trial and error or a simple heuristic. The latter provides a fast and cognitively efficient method for stable, routinized behaviour based on past experience with little or no deliberate decision-making. However, early papers by Chappell and Kacelnik reported that two New Caledonian crows procured tools after closely assessing the tool characteristics required for the task, thus using deliberate decision-making, or a 'customized strategy'. Here, I tested eight New Caledonian crows to determine their default behaviour in basic tool procurement tasks as a check on whether or not they use customized strategies. I used two rigorous experiments closely based on Chappell and Kacelnik's experiments. The crows did not use a customized strategy in either experiment, but their behaviour was clearly consistent with tool procurement predominantly guided by a familiarity heuristic. I discuss potential methodological issues that may have led to different conclusions in Chappell and Kacelnik's studies. Heuristic-guided, routinized behaviour in tool procurement has potential implications for understanding how standardization occurs in the early evolution of complex tool manufacture, both in New Caledonian crows and early humans.

Spatio-temporal dynamics of landscape use by the bumblebee Bombus pauloensis (Hymenoptera: Apidae) and its relationship with pollen provisioning

Understanding how bees use resources at a landscape scale is essential for developing meaningful management plans that sustain populations and the pollination services they provide. Bumblebees are important pollinators for many wild and cultivated plants, and have experienced steep population declines worldwide. Bee foraging behavior can be influenced by resource availability and bees’ lifecycle stage. To better understand these relationships, we studied the habitat selection of Bombus pauloensis by tracking 17 queen bumblebees with radio telemetry in blueberry fields in Entre Ríos province, Argentina. To evaluate land use and floral resources used by bumblebees, we tracked bees before and after nest establishment and estimated home ranges using minimum convex polygons and kernel density methods. We also classified the pollen on their bodies to identify the floral resources they used from the floral species available at that time. We characterized land use for each bee as the relative proportion of GPS points inside of each land use. Bumblebees differed markedly in their movement behavior in relation to pre and post nest establishment. Bees moved over larger areas, and mostly within blueberry fields, before nest establishment. In contrast, after establishing the nest, the bees preferred the edges near forest plantations and they changed the nutritional resources to prefer wild floral species. Our study is the first to track queen bumblebee movements in an agricultural setting and relate movement changes across time and space with pollen resource availability. This study provides insight into the way bumblebee queens use different habitat elements at crucial periods in their lifecycle, showing the importance of mass flowering crops like blueberry in the first stages of queen’s lifecycle, and how diversified landscapes help support bee populations as their needs changes during different phases of their lifecycle.

Bumblebees learn foraging routes through exploitation-exploration cycles

How animals explore and acquire knowledge from the environment is a key question in movement ecology. For pollinators that feed on multiple small replenishing nectar resources, the challenge is to learn efficient foraging routes while dynamically acquiring spatial information about new resource locations. Here, we use the behavioural mapping t-Stochastic Neighbouring Embedding algorithm and Shannon entropy to statistically analyse previously published sampling patterns of bumblebees feeding on artificial flowers in the field. We show that bumblebees modulate foraging excursions into distinctive behavioural strategies, characterizing the trade-off dynamics between (i) visiting and exploiting flowers close to the nest, (ii) searching for new routes and resources, and (iii) exploiting learned flower visitation sequences. Experienced bees combine these behavioural strategies even after they find an optimal route minimizing travel distances between flowers. This behavioural variability may help balancing energy costs-benefits and facilitate rapid adaptation to changing environments and the integration of more profitable resources in their routes.

The Central Complex as a Potential Substrate for Vector Based Navigation

Insects use path integration (PI) to maintain a home vector, but can also store and recall vector-memories that take them from home to a food location, and even allow them to take novel shortcuts between food locations. The neural circuit of the Central Complex (a brain area that receives compass and optic flow information) forms a plausible substrate for these behaviors. A recent model, grounded in neurophysiological and neuroanatomical data, can account for PI during outbound exploratory routes and the control of steering to return home. Here, we show that minor, hypothetical but neurally plausible, extensions of this model can additionally explain how insects could store and recall PI vectors to follow food-ward paths, take shortcuts, search at the feeder and re-calibrate their vector-memories with experience. In addition, a simple assumption about how one of multiple vector-memories might be chosen at any point in time can produce the development and maintenance of efficient routes between multiple locations, as observed in bees. The central complex circuitry is therefore well-suited to allow for a rich vector-based navigational repertoire.

Navigation strategies in three nocturnal lemur species: diet predicts heuristic use and degree of exploratory behavior

Humans generally solve multi-destination routes with simple rules-of-thumb. Animals may do the same, but strong evidence is limited to a few species. We examined whether strepsirrhines, who diverged from haplorhines more than 58 mya, would demonstrate the use of three heuristics used by humans and supported in vervets, the nearest neighbor rule, the convex hull, and a cluster strategy, when solving a multi-destination route. We hypothesized that the evolution of these strategies may depend on a species' dietary specialization. Three nocturnal lemur species were tested on an experimental array at the Duke Lemur Center. Frugivorous fat-tailed dwarf lemurs (Cheirogaleus medius) were expected to follow paths most consistent with distance-saving navigational heuristics because fruit trees are stationary targets. Gray mouse lemurs (Microcebus murinus) and aye-ayes (Daubentonia madagascariensis), which rely on more mobile and ephemeral foods, were expected to use fewer paths consistent with these heuristics and be more exploratory. Our data supported all of these hypotheses. Dwarf lemurs used paths consistent with all three heuristics, took the shortest paths, and were the least exploratory. Mouse lemurs were quite exploratory but sometimes used paths consistent with heuristics. Aye-ayes showed no evidence of heuristic use and were the most exploratory. Distinguishable patterns of inter- and intra-individual variation in ability to solve the route, speed, and behavior occurred in each species. This research suggests that these simple navigational heuristics are not part of a readily available set of cognitive tools inherited by all primates but instead evolve due to need in each lineage.

Defense by exploitation in Negev gerbils

In this study, we addressed how frequently a non-traplining animal should visit food patches. More specifically, we investigate if non-traplining animals engage in a behavior called "defense by exploitation", which is characterized by an increase in visitation rates with increased intra-specific competition. We ran four tests with two gerbil species in the Negev Desert. Firstly, we measured patch use of Gerbillus pyramidum and Gerbillus andersoni allenbyi. We assumed that activity and competition would decrease through the night and that patch use would decrease with number of visits. Secondly, we measured how the number of visits to resource patches increased with the addition of individuals. Thirdly, we repeated this experiment, but instead removed individuals. Lastly, we conducted a simulation to compare these results against theoretical expectations. In the first test, we found support for defense by exploitation in G. pyramidum. The second and third test found no support. The fourth test found support for this increase visitation, but only if costs of locomotion are relatively small.

Vervet monkey (Chlorocebus pygerythrus) behavior in a multi-destination route: Evidence for planning ahead when heuristics fail

Animal paths are analogous to intractable mathematical problems like the Traveling Salesman Problem (TSP) and the shortest path problem (SPP). Both the TSP and SPP require an individual to find the shortest path through multiple targets but the TSP demands a return to the start, while the SPP does not. Vervet monkeys are very efficient in solving TSPs but this species is a multiple central place forager that does not always return to the same sleeping site and thus theoretically should be selected to find solutions to SPPs rather than TSPs. We examined path choice by wild vervets in an SPP experimental array where the shortest paths usually differed from those consistent with common heuristic strategies, the nearest-neighbor rule (NNR-go to the closest resource that has not been visited), and the convex hull (put a mental loop around sites, adding inner targets in order of distance from the edge)-an efficient strategy for TSPs but not SPPs. In addition, humans solving SPPs use an initial segment strategy (ISS-choose the straightest path at the beginning, only turning when necessary) and we looked at vervet paths consistent with this strategy. In 615 trials by single foragers, paths usually conformed to the NNR and rarely the slightly more efficient convex hull, supporting that vervets may be selected to solve SPPs. Further, like humans solving SPPs, vervets showed a tendency to use the ISS. Paths consistent with heuristics dropped off sharply, and use of the shortest path increased, when heuristics led to longer paths showing trade-offs in efficiency versus cognitive load. Two individuals out of 17, found the shortest path most often, showing inter-individual variation in path planning. Given support for the NNR and the ISS, we propose a new rule-of-thumb termed the "region heuristic" that vervets may apply in multi-destination routes.

Continuous Radar Tracking Illustrates the Development of Multi-destination Routes of Bumblebees

Animals that visit multiple foraging sites face a problem, analogous to the Travelling Salesman Problem, of finding an efficient route. We explored bumblebees' route development on an array of five artificial flowers in which minimising travel distances between individual feeders conflicted with minimising overall distance. No previous study of bee spatial navigation has been able to follow animals' movement during learning; we tracked bumblebee foragers continuously, using harmonic radar, and examined the process of route formation in detail for a small number of selected individuals. On our array, bees did not settle on visit sequences that gave the shortest overall path, but prioritised movements to nearby feeders. Nonetheless, flight distance and duration reduced with experience. This increased efficiency was attributable mainly to experienced bees reducing exploration beyond the feeder array and flights becoming straighter with experience, rather than improvements in the sequence of feeder visits. Flight paths of all legs of a flight stabilised at similar rates, whereas the first few feeder visits became fixed early while bees continued to experiment with the order of later visits. Stabilising early sections of a route and prioritising travel between nearby destinations may reduce the search space, allowing rapid adoption of efficient routes.

Inter-individual variability in the foraging behaviour of traplining bumblebees

Workers of social insects, such as bees, ants and wasps, show some degree of inter-individual variability in decision-making, learning and memory. Whether these natural cognitive differences translate into distinct adaptive behavioural strategies is virtually unknown. Here we examined variability in the movement patterns of bumblebee foragers establishing routes between artificial flowers. We recorded all flower visitation sequences performed by 29 bees tested for 20 consecutive foraging bouts in three experimental arrays, each characterised by a unique spatial configuration of artificial flowers and three-dimensional landmarks. All bees started to develop efficient routes as they accumulated foraging experience in each array, and showed consistent inter-individual differences in their levels of route fidelity and foraging performance, as measured by travel speed and the frequency of revisits to flowers. While the tendency of bees to repeat the same route was influenced by their colony origin, foraging performance was correlated to body size. The largest foragers travelled faster and made less revisits to empty flowers. We discuss the possible adaptive value of such inter-individual variability within the forager caste for optimisation of colony-level foraging performances in social pollinators.

Why Bees Are So Vulnerable to Environmental Stressors

Bee populations are declining in the industrialized world, raising concerns for the sustainable pollination of crops. Pesticides, pollutants, parasites, diseases, and malnutrition have all been linked to this problem. We consider here neurobiological, ecological, and evolutionary reasons why bees are particularly vulnerable to these environmental stressors. Central-place foraging on flowers demands advanced capacities of learning, memory, and navigation. However, even at low intensity levels, many stressors damage the bee brain, disrupting key cognitive functions needed for effective foraging, with dramatic consequences for brood development and colony survival. We discuss how understanding the relationships between the actions of stressors on the nervous system, individual cognitive impairments, and colony decline can inform constructive interventions to sustain bee populations.

Signatures of a globally optimal searching strategy in the three-dimensional foraging flights of bumblebees

Simulated annealing is a powerful stochastic search algorithm for locating a global maximum that is hidden among many poorer local maxima in a search space. It is frequently implemented in computers working on complex optimization problems but until now has not been directly observed in nature as a searching strategy adopted by foraging animals. We analysed high-speed video recordings of the three-dimensional searching flights of bumblebees (Bombus terrestris) made in the presence of large or small artificial flowers within a 0.5 m³ enclosed arena. Analyses of the three-dimensional flight patterns in both conditions reveal signatures of simulated annealing searches. After leaving a flower, bees tend to scan back-and forth past that flower before making prospecting flights (loops), whose length increases over time. The search pattern becomes gradually more expansive and culminates when another rewarding flower is found. Bees then scan back and forth in the vicinity of the newly discovered flower and the process repeats. This looping search pattern, in which flight step lengths are typically power-law distributed, provides a relatively simple yet highly efficient strategy for pollinators such as bees to find best quality resources in complex environments made of multiple ephemeral feeding sites with nutritionally variable rewards.

Evidence of trapline foraging in honeybees

Central-place foragers exploiting floral resources often use multi-destination routes (traplines) to maximise their foraging efficiency. Recent studies on bumblebees have showed how solitary foragers can learn traplines, minimising travel costs between multiple replenishing feeding locations. Here we demonstrate a similar routing strategy in the honeybee (Apis mellifera), a major pollinator known to recruit nestmates to discovered food resources. Individual honeybees trained to collect sucrose solution from four artificial flowers arranged within 10 m of the hive location developed repeatable visitation sequences both in the laboratory and in the field. A 10-fold increase of between-flower distances considerably intensified this routing behaviour, with bees establishing more stable and more efficient routes at larger spatial scales. In these advanced social insects, trapline foraging may complement cooperative foraging for exploiting food resources near the hive (where dance recruitment is not used) or when resources are not large enough to sustain multiple foragers at once.

Vervet monkeys use paths consistent with context-specific spatial movement heuristics

Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.

Landscape fragmentation and pollinator movement within agricultural environments: a modelling framework for exploring foraging and movement ecology

Pollinator decline has been linked to landscape change, through both habitat fragmentation and the loss of habitat suitable for the pollinators to live within. One method for exploring why landscape change should affect pollinator populations is to combine individual-level behavioural ecological techniques with larger-scale landscape ecology. A modelling framework is described that uses spatially-explicit individual-based models to explore the effects of individual behavioural rules within a landscape. The technique described gives a simple method for exploring the effects of the removal of wild corridors, and the creation of wild set-aside fields: interventions that are common to many national agricultural policies. The effects of these manipulations on central-place nesting pollinators are varied, and depend upon the behavioural rules that the pollinators are using to move through the environment. The value of this modelling framework is discussed, and future directions for exploration are identified.